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Scenario

scenario

Author:
(1) David Novoa-Paradela, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain & Corresponding author (Email: david.novoa@udc.es);
(2) Oscar Fontenla-Romero, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: oscar.fontenla@udc.es);
(3) Bertha Guijarro-Berdiñas, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: berta.guijarro@udc.es). Table of Links Abstract and Introduction Related work The proposed pipeline Evaluation Conclusion & Acknowledgements References & Appendix Abstract This paper presents a pipeline to detect and explain anomalous reviews in online platforms. The pipeline is made up of three modules and allows the detection of reviews that do not generate value for users due to either worthless or malicious composition. The classifications are accompanied by a normality score and an explanation that justifies the decision made. The pipeline’s ability to solve the anomaly detection task was evaluated using different datasets created from a large Amazon database. Additionally, a study comparing three explainability techniques involving 241 participants was conducted to assess the explainability module. The study aimed to measure the impact of explanations on the respondents’ ability to reproduce the classification model and their perceived usefulness. This work can be useful to automate tasks in review online platforms, such as those for electronic commerce, and offers inspiration for addressing similar problems in the field of anomaly detection in textual data. We also consider it interesting to have carried out a human evaluation of the capacity of different explainability techniques in a real and infrequent scenario such as the detection of anomalous reviews, as well as to reflect on whether it is possible to explain tasks as humanly subjective as this one. Keywords: Anomaly Detection, Text Reviews, Transformers, Explainability 1. Introduction Nowadays more than ever in history, the user opinions about products and services have a great impact on the future of the company that offers them. In such a globalized and highly competitive world, online review platforms, such as electronic commerce (e-commerce), play a crucial role in the credibility of products and services. These user reviews usually come in the form of text reviews or numerical ratings, accompanied in some cases by images or videos. These reviews provide users with information about the product or service they are considering purchasing, which directly influences the number of sales. Most people make purchase decisions based on ratings and reviews from other users [1]. In the case of many companies, such as Amazon, each product in the store has a list of text reviews published by customers of the platform. Users can access this list of reviews (opinions) to obtain extra information about the product, being able to mark the reviews as useful, which will position those reviews with the most votes at the top of the list. In addition to this, users can report to Amazon if they feel a review is inappropriate, for example, if its content is incorrect. This procedure to rank reviews based on their usefulness and report inappropriate reviews is carried out manually by platform users. As a result, Amazon reported more than 200 million suspected fake reviews in 2020 alone [2]. This problem does not only occur on Amazon, but affects all platforms that allow their users to post reviews. For example, Tripadvisor uses an automatic system capable of distinguishing between normal, suspicious and inappropriate reviews [3]. Inappropriate ones are automatically removed (3.1% of review submissions in 2020), while those classified as suspicious are reviewed again by a human moderator (5.1% of review submissions in 2020). On the other hand, in machine learning (ML), anomaly detection (AD) is the branch that builds models capable of differentiating between normal and abnormal data [4]. At first, anomaly detection might seem like a classification problem with only two classes. However, anomalies tend to occur infrequently or are non-existent, so normal data prevails in these scenarios. Because of this, it is common for models to be trained only with normal data. The goal of these models is to represent the normal class as well as possible in order to classify new data as normal or anomalous. The technological development of recent years has allowed the construction of very powerful models for Natural Language Processing (NLP) [5]. Contrary to other tasks such as Sentiment Analysis [6] or Question Answering [7], the application of anomaly detection on texts is still at an early stage, probably due to its lower demand. For this reason, we present in this article a pipeline that, given text reviews of a product (in this case from Amazon), addresses opinion filtering as an anomaly detection problem where: • Reviews containing representative information about the product are considered as the normal class. • Reviews whose content has nothing to do with the product to be represented are considered as the anomalous class. The proposed pipeline allows us to carry out the following tasks: • Classify reviews as normal or anomalous, allowing us to locate those that do not describe characteristics of the product to which they are associated, and therefore have no value for the users of the platform. • Issue a normality score associated with each review. • Generate an explanation that justifies the classification made for each review by the system. The pipeline’s ability to solve the anomaly detection task was evaluated using different datasets created from a large Amazon database [8]. In addition, to evaluate the explainability module, a study was carried out to compare three explainability techniques in which a total of 241 people had participated. The objective of this study is both to measure the impact of the explanations on the reproducibility of the classification model by the respondents, as well as the usefulness of these explanations. We believe that this work can be useful to automate tasks such as those mentioned in online review platforms, in addition to the existing interest in the application of anomaly detection models on texts, for which it can serve as inspiration to solve similar problems. We also consider it interesting to have carried out a human evaluation of the capacity of different explainability techniques in a real and infrequent scenario such as the detection of anomalous reviews, as well as to reflect on whether it is possible to explain tasks as humanly subjective as this one. This document is structured as follows. Section 2 contains a brief review of the main anomaly detection works in texts and, more specifically, in text reviews. Section 3 describes the proposed pipeline and its operation. Section 4 collects the experimentation carried out and, finally, conclusions are drawn in Section 5. This paper is available on arxiv under CC 4.0 license. Author: (1) David Novoa-Paradela, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain & Corresponding author (Email: david.novoa@udc.es); (2) Oscar Fontenla-Romero, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: oscar.fontenla@udc.es); (3) Bertha Guijarro-Berdiñas, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: berta.guijarro@udc.es). Author: Author: (1) David Novoa-Paradela, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain & Corresponding author (Email: david.novoa@udc.es); (2) Oscar Fontenla-Romero, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: oscar.fontenla@udc.es); (3) Bertha Guijarro-Berdiñas, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: berta.guijarro@udc.es). Table of Links Abstract and Introduction Abstract and Introduction Related work Related work The proposed pipeline The proposed pipeline Evaluation Evaluation Conclusion & Acknowledgements Conclusion & Acknowledgements References & Appendix References & Appendix Abstract This paper presents a pipeline to detect and explain anomalous reviews in online platforms. The pipeline is made up of three modules and allows the detection of reviews that do not generate value for users due to either worthless or malicious composition. The classifications are accompanied by a normality score and an explanation that justifies the decision made. The pipeline’s ability to solve the anomaly detection task was evaluated using different datasets created from a large Amazon database. Additionally, a study comparing three explainability techniques involving 241 participants was conducted to assess the explainability module. The study aimed to measure the impact of explanations on the respondents’ ability to reproduce the classification model and their perceived usefulness. This work can be useful to automate tasks in review online platforms, such as those for electronic commerce, and offers inspiration for addressing similar problems in the field of anomaly detection in textual data. We also consider it interesting to have carried out a human evaluation of the capacity of different explainability techniques in a real and infrequent scenario such as the detection of anomalous reviews, as well as to reflect on whether it is possible to explain tasks as humanly subjective as this one. Keywords: Anomaly Detection, Text Reviews, Transformers, Explainability Keywords: 1. Introduction Nowadays more than ever in history, the user opinions about products and services have a great impact on the future of the company that offers them. In such a globalized and highly competitive world, online review platforms, such as electronic commerce (e-commerce), play a crucial role in the credibility of products and services. These user reviews usually come in the form of text reviews or numerical ratings, accompanied in some cases by images or videos. These reviews provide users with information about the product or service they are considering purchasing, which directly influences the number of sales. Most people make purchase decisions based on ratings and reviews from other users [1]. In the case of many companies, such as Amazon, each product in the store has a list of text reviews published by customers of the platform. Users can access this list of reviews (opinions) to obtain extra information about the product, being able to mark the reviews as useful, which will position those reviews with the most votes at the top of the list. In addition to this, users can report to Amazon if they feel a review is inappropriate, for example, if its content is incorrect. This procedure to rank reviews based on their usefulness and report inappropriate reviews is carried out manually by platform users. As a result, Amazon reported more than 200 million suspected fake reviews in 2020 alone [2]. This problem does not only occur on Amazon, but affects all platforms that allow their users to post reviews. For example, Tripadvisor uses an automatic system capable of distinguishing between normal, suspicious and inappropriate reviews [3]. Inappropriate ones are automatically removed (3.1% of review submissions in 2020), while those classified as suspicious are reviewed again by a human moderator (5.1% of review submissions in 2020). On the other hand, in machine learning (ML), anomaly detection (AD) is the branch that builds models capable of differentiating between normal and abnormal data [4]. At first, anomaly detection might seem like a classification problem with only two classes. However, anomalies tend to occur infrequently or are non-existent, so normal data prevails in these scenarios. Because of this, it is common for models to be trained only with normal data. The goal of these models is to represent the normal class as well as possible in order to classify new data as normal or anomalous. The technological development of recent years has allowed the construction of very powerful models for Natural Language Processing (NLP) [5]. Contrary to other tasks such as Sentiment Analysis [6] or Question Answering [7], the application of anomaly detection on texts is still at an early stage, probably due to its lower demand. For this reason, we present in this article a pipeline that, given text reviews of a product (in this case from Amazon), addresses opinion filtering as an anomaly detection problem where: • Reviews containing representative information about the product are considered as the normal class. • Reviews whose content has nothing to do with the product to be represented are considered as the anomalous class. The proposed pipeline allows us to carry out the following tasks: • Classify reviews as normal or anomalous, allowing us to locate those that do not describe characteristics of the product to which they are associated, and therefore have no value for the users of the platform. • Issue a normality score associated with each review. • Generate an explanation that justifies the classification made for each review by the system. The pipeline’s ability to solve the anomaly detection task was evaluated using different datasets created from a large Amazon database [8]. In addition, to evaluate the explainability module, a study was carried out to compare three explainability techniques in which a total of 241 people had participated. The objective of this study is both to measure the impact of the explanations on the reproducibility of the classification model by the respondents, as well as the usefulness of these explanations. We believe that this work can be useful to automate tasks such as those mentioned in online review platforms, in addition to the existing interest in the application of anomaly detection models on texts, for which it can serve as inspiration to solve similar problems. We also consider it interesting to have carried out a human evaluation of the capacity of different explainability techniques in a real and infrequent scenario such as the detection of anomalous reviews, as well as to reflect on whether it is possible to explain tasks as humanly subjective as this one. This document is structured as follows. Section 2 contains a brief review of the main anomaly detection works in texts and, more specifically, in text reviews. Section 3 describes the proposed pipeline and its operation. Section 4 collects the experimentation carried out and, finally, conclusions are drawn in Section 5. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Explained Anomaly Detection in Text Reviews: Can Subjective Scenarios Be Correctly Evaluated?

Unitarity Bound on Dark Matter in Low-temperature Reheating Scenarios: Acknowledgments and Reference

নিম্ন-তাপমাত্রা পুনঃউষ্ণকরণের পরিস্থিতিতে ডার্ক ম্যাটারে ঐক্যবদ্ধতা: স্বীকৃতি এবং রেফারেন্স

Unitaritätsgrenze für Dunkle Materie in Niedertemperatur-Wiedererwärmungsszenarien: Danksagungen und Referenz

Unitaridad unida a la materia oscura en escenarios de recalentamiento a baja temperatura: reconocimientos y referencias

Unitarité liée à la matière noire dans les scénarios de réchauffage à basse température : remerciements et référence

निम्न-तापमान पुनःतापन परिदृश्यों में डार्क मैटर पर यूनिटैरिटी बाउंड: आभार और संदर्भ

低温再加熱シナリオにおける暗黒物質のユニタリー性限界: 謝辞と参考文献

저온 재가열 시나리오에서 암흑물질에 결합된 단일성: 승인 및 참고자료

Unitariedade vinculada à matéria escura em cenários de reaquecimento de baixa temperatura: reconhecimentos e referências

Унитарность, связанная с темной материей в сценариях низкотемпературного разогрева: благодарности и ссылки

Düşük Sıcaklıkta Yeniden Isıtma Senaryolarında Karanlık Maddeye Bağlı Üniterlik: Teşekkür ve Referans

Tính thống nhất bị ràng buộc đối với Vật chất tối trong các kịch bản hâm nóng ở nhiệt độ thấp: Lời cảm ơn và tài liệu tham khảo

低温再加热场景中暗物质的幺正性界限：致谢和参考文献

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Nicolas Bernal, New York University Abu Dhabi;
(2) Partha Konar, Physical Research Laboratory;
(3) Sudipta Show, Physical Research Laboratory. Table of Links Abstract and Intro
S-matrix: Unitarity and its Consequences
Dark Matter Annihilation and Unitarity Bound
Low-temperature Reheating
Freeze-out with a Low-temperature Reheating
Summary and Conclusion
Acknowledgments and References Abstract Model-independent theoretical upper bound on the thermal dark matter (DM) mass can be derived from the maximum inelastic DM cross-section featuring the whole observed DM abundance. We deploy partial-wave unitarity of the scattering matrix to derive the maximal thermally-averaged cross-section for general number-changing processes r → 2 (with r ≥ 2), which may involve standard model particles or occur solely within the dark sector. The usual upper limit on the DM mass for s-wave annihilation is around 130 TeV (1 GeV) for r = 2 (3), only applies in the case of a freeze out occurring in the standard cosmological scenario. We consider the effects of two nonstandard cosmological evolutions, characterized by low-temperature reheating: i) a kination-like scenario and ii) an early matter-dominated scenario. In the first case, the early freeze-out strengthens the unitarity bound to few TeVs for WIMPs; while in the second case, WIMP DM can be as heavy as ∼ 1010 GeV due to a large entropy dilution. 1. Introduction Consideration of a specific DM production paradigm in the early stage of the universe may further constrain the mass range for a viable DM candidate. For instance, the number-changing pair annihilation of DM to SM particles determines its present mass density, where it maintains the chemical and kinetic equilibrium with the thermal soup in the early universe. Interestingly, the requirement of the unitarity of the S-matrix sets a model-independent upper bound on the DM mass for this scenario [12, 13]. The implication of unitarity offers the maximum inelastic cross-section, which fixes the minimum number density of the frozen-out DM. Using this number density, one can establish the maximum allowed DM mass by fulfilling the observed relic density of it. In the theories of DM with long-range forces, bound states of DM can form and therefore relax the unitarity bound by suppressing the inelastic annihilation rate [14–16]. In addition, dark sectors with particle-antiparticle asymmetry enforce the apprehend of the nonzero equilibrium chemical potential for DM, further constraining the unitarity limits due to the demand for an increased effective DM number density at the time of freeze-out [15, 17]. Furthermore, different indirect searches for DM may put a lower limit on DM mass for some specified scenarios. A strong model-independent lower bound for the thermal DM that is annihilating to visible states through an s-wave process is about 20 GeV [18]. In addition, a more restrictive lower limit has recently been found. It has been shown that the lower bound is 200 GeV, considering H.E.S.S. and other updated observational data [19]. In particular, all the DM scenarios mentioned so far pay attention to the 2 → 2 number-changing process where a DM pair annihilates into a pair of SM particles, that is, the Weakly Interacting Massive Particle (WIMP) paradigm [20–22].[1] Moreover, it is not necessary that the number-changing processes involve SM particles, so they may also occur within the dark sector. The minimalistic realization of this scenario is the 3 → 2 process, where this kind of number-changing reaction involves a single DM species. In general, such processes arise in DM theories with new sizable self-interactions, and in several contexts as self-interacting DM [29–31], the Strongly Interacting Massive Particle (SIMP) paradigm [32–49], or even the ELastically DEcoupling Relic (ELDER) scenario [50, 51]. It is essential to mention that the early history of the universe plays a crucial role in DM genesis, since the decoupling of thermal DM occurred at that time. Generally, the studies of DM consider the standard cosmological picture in which the radiation energy density is assumed to dominate the energy budget before the Big Bang Nucleosynthesis (BBN). However, there is no direct evidence for the energy content at very high temperatures. Therefore, it is vital to look at the effects of modified cosmology on the production of DM. In recent times, the evolution of the DM in the period of non-standard expansion usually triggered by the decay of a long-lived massive particle [48, 52–71] or by Hawking evaporation of primordial black holes [72–95] is receiving increasing attention.[2] All such studies point towards the fact that non-standard cosmology alters the value of the thermally averaged cross section needed to satisfy the observed relic of DM. Such a modification in the thermally averaged cross-section may also change the unitarity mass bound of DM. In a recent article, the authors studied the impact of early matter domination on unitarity limits [112]. This article is decorated as follows. In Sections 2 and 3, we present the detailed derivation of the maximum thermally-averaged cross-section allowed by the unitarity of the Smatrix. We discuss two different non-standard cosmological pictures: kination-like and late-time reheating in Section 4. Section 5 shows the analytical expressions for freeze-out and cross sections for the radiation-dominated universe and the mentioned modified cosmologies, and we also demonstrate our results. Finally, we summarize our findings in Section 6. [1] Alternatively, one can also have in the final state a DM and a SM particle (semi-annihilations) [23–27], or in the initial state a DM and another particle of the dark sector (coannihilations) [28]. [2] For studies on baryogenesis with a low reheating temperature or during an early matter-dominated phase, see Refs. [52, 96–100] and [101–104], respectively. Furthermore, the production of primordial gravitational waves in scenarios with an early matter era has recently received particular attention [105–111]. This paper is available on arxiv under CC 4.0 license. Authors: (1) Nicolas Bernal, New York University Abu Dhabi; (2) Partha Konar, Physical Research Laboratory; (3) Sudipta Show, Physical Research Laboratory. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Nicolas Bernal, New York University Abu Dhabi; (2) Partha Konar, Physical Research Laboratory; (3) Sudipta Show, Physical Research Laboratory. Table of Links Abstract and Intro S-matrix: Unitarity and its Consequences Dark Matter Annihilation and Unitarity Bound Low-temperature Reheating Freeze-out with a Low-temperature Reheating Summary and Conclusion Acknowledgments and References Abstract and Intro Abstract and Intro S-matrix: Unitarity and its Consequences S-matrix: Unitarity and its Consequences Dark Matter Annihilation and Unitarity Bound Dark Matter Annihilation and Unitarity Bound Low-temperature Reheating Low-temperature Reheating Freeze-out with a Low-temperature Reheating Freeze-out with a Low-temperature Reheating Summary and Conclusion Summary and Conclusion Acknowledgments and References Acknowledgments and References Abstract Model-independent theoretical upper bound on the thermal dark matter (DM) mass can be derived from the maximum inelastic DM cross-section featuring the whole observed DM abundance. We deploy partial-wave unitarity of the scattering matrix to derive the maximal thermally-averaged cross-section for general number-changing processes r → 2 (with r ≥ 2), which may involve standard model particles or occur solely within the dark sector. The usual upper limit on the DM mass for s-wave annihilation is around 130 TeV (1 GeV) for r = 2 (3), only applies in the case of a freeze out occurring in the standard cosmological scenario. We consider the effects of two nonstandard cosmological evolutions, characterized by low-temperature reheating: i) a kination-like scenario and ii) an early matter-dominated scenario. In the first case, the early freeze-out strengthens the unitarity bound to few TeVs for WIMPs; while in the second case, WIMP DM can be as heavy as ∼ 1010 GeV due to a large entropy dilution. 1. Introduction Consideration of a specific DM production paradigm in the early stage of the universe may further constrain the mass range for a viable DM candidate. For instance, the number-changing pair annihilation of DM to SM particles determines its present mass density, where it maintains the chemical and kinetic equilibrium with the thermal soup in the early universe. Interestingly, the requirement of the unitarity of the S-matrix sets a model-independent upper bound on the DM mass for this scenario [12, 13]. The implication of unitarity offers the maximum inelastic cross-section, which fixes the minimum number density of the frozen-out DM. Using this number density, one can establish the maximum allowed DM mass by fulfilling the observed relic density of it. In the theories of DM with long-range forces, bound states of DM can form and therefore relax the unitarity bound by suppressing the inelastic annihilation rate [14–16]. In addition, dark sectors with particle-antiparticle asymmetry enforce the apprehend of the nonzero equilibrium chemical potential for DM, further constraining the unitarity limits due to the demand for an increased effective DM number density at the time of freeze-out [15, 17]. Furthermore, different indirect searches for DM may put a lower limit on DM mass for some specified scenarios. A strong model-independent lower bound for the thermal DM that is annihilating to visible states through an s-wave process is about 20 GeV [18]. In addition, a more restrictive lower limit has recently been found. It has been shown that the lower bound is 200 GeV, considering H.E.S.S. and other updated observational data [19]. In particular, all the DM scenarios mentioned so far pay attention to the 2 → 2 number-changing process where a DM pair annihilates into a pair of SM particles, that is, the Weakly Interacting Massive Particle (WIMP) paradigm [20–22].[1] Moreover, it is not necessary that the number-changing processes involve SM particles, so they may also occur within the dark sector. The minimalistic realization of this scenario is the 3 → 2 process, where this kind of number-changing reaction involves a single DM species. In general, such processes arise in DM theories with new sizable self-interactions, and in several contexts as self-interacting DM [29–31], the Strongly Interacting Massive Particle (SIMP) paradigm [32–49], or even the ELastically DEcoupling Relic (ELDER) scenario [50, 51]. It is essential to mention that the early history of the universe plays a crucial role in DM genesis, since the decoupling of thermal DM occurred at that time. Generally, the studies of DM consider the standard cosmological picture in which the radiation energy density is assumed to dominate the energy budget before the Big Bang Nucleosynthesis (BBN). However, there is no direct evidence for the energy content at very high temperatures. Therefore, it is vital to look at the effects of modified cosmology on the production of DM. In recent times, the evolution of the DM in the period of non-standard expansion usually triggered by the decay of a long-lived massive particle [48, 52–71] or by Hawking evaporation of primordial black holes [72–95] is receiving increasing attention.[2] All such studies point towards the fact that non-standard cosmology alters the value of the thermally averaged cross section needed to satisfy the observed relic of DM. Such a modification in the thermally averaged cross-section may also change the unitarity mass bound of DM. In a recent article, the authors studied the impact of early matter domination on unitarity limits [112]. This article is decorated as follows. In Sections 2 and 3, we present the detailed derivation of the maximum thermally-averaged cross-section allowed by the unitarity of the Smatrix. We discuss two different non-standard cosmological pictures: kination-like and late-time reheating in Section 4. Section 5 shows the analytical expressions for freeze-out and cross sections for the radiation-dominated universe and the mentioned modified cosmologies, and we also demonstrate our results. Finally, we summarize our findings in Section 6. [1] Alternatively, one can also have in the final state a DM and a SM particle (semi-annihilations) [23–27], or in the initial state a DM and another particle of the dark sector (coannihilations) [28]. [2] For studies on baryogenesis with a low reheating temperature or during an early matter-dominated phase, see Refs. [52, 96–100] and [101–104], respectively. Furthermore, the production of primordial gravitational waves in scenarios with an early matter era has recently received particular attention [105–111].

Unitarity Bound on Dark Matter in Low-temperature Reheating Scenarios: Abstract and Intro

নিম্ন-তাপমাত্রা পুনঃউষ্ণকরণের দৃশ্যে ডার্ক ম্যাটারে ঐক্যবদ্ধতা: বিমূর্ত এবং ভূমিকা

Unitaritätsgrenze für Dunkle Materie in Niedertemperatur-Wiedererwärmungsszenarien: Zusammenfassung und Einführung

Unitaridad ligada a la materia oscura en escenarios de recalentamiento a baja temperatura: resumen e introducción

Unitarité liée à la matière noire dans des scénarios de réchauffage à basse température : résumé et introduction

निम्न-तापमान पुनःतापन परिदृश्यों में डार्क मैटर पर यूनिटैरिटी बाउंड: सार और परिचय

低温再加熱シナリオにおける暗黒物質のユニタリー性限界：概要と序論

저온 재가열 시나리오에서 암흑물질에 결합된 단일성: 개요 및 소개

Unitariedade vinculada à matéria escura em cenários de reaquecimento em baixa temperatura: resumo e introdução

Унитарность, связанная с темной материей в сценариях низкотемпературного повторного нагрева: Аннотация и введение

Düşük Sıcaklıkta Yeniden Isıtma Senaryolarında Karanlık Maddeye Bağlı Birlik: Özet ve Giriş

Tính đơn nhất bị ràng buộc đối với Vật chất tối trong các kịch bản hâm nóng ở nhiệt độ thấp: Tóm tắt và giới thiệu

低温再加热场景中暗物质的幺正性界限：摘要和简介

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Nicolas Bernal, New York University Abu Dhabi;
(2) Partha Konar, Physical Research Laboratory;
(3) Sudipta Show, Physical Research Laboratory. Table of Links Abstract and Intro
S-matrix: Unitarity and its Consequences
Dark Matter Annihilation and Unitarity Bound
Low-temperature Reheating
Freeze-out with a Low-temperature Reheating
Summary and Conclusion
Acknowledgments and References 6. Summary and Conclusion The requirement of the de Broglie wavelength of dark matter (DM) to hold it inside galaxies and the stability of the stellar galaxy cluster collectively put a broad allowed mass range for DM by providing the lower and upper bound of DM mass, respectively. Specifying some properties of DM can further tighten the mass range. Interestingly, one can put the model-independent upper bound by specifying the thermal production of DM in the early universe. The observed DM abundance and unitarity of partial waves from the scattering matrix jointly place an upper limit on DM mass. Primarily, the upper limits on the inelastic cross section for a general number-changing process 2 → r can be derived with the help of the optical theorem, the matrix elements and the elastic scattering cross section for the process. After that, one can obtain the thermally averaged cross section for the r → 2 process by invoking the principle of detailed balance. Finally, the unitarity bounds on the thermally averaged cross section translate to the upper limits on the DM mass satisfying the relic density constraints. It is known that the maximum allowed DM mass for the 2 → 2 and 3 → 2 DM annihilation processes is around 130 TeV and 1 GeV, respectively. However, these bounds not only depend on the particle physics model, but have a strong dependence on the cosmological evolution of the universe, being valid only if the universe followed the so-called “standard cosmological scenario”. Instead, this article explores the DM mass bound in nonstandard cosmological setups characterized by low-temperature reheating. In particular, we focus on i) kination-like scenarios, where the early universe was dominated by a fluid with an energy density that gets diluted faster than free radiation, and ii) early matter-dominated scenarios, where a component with an energy density that scales as nonrelativistic matter dominates the early universe and eventually decays into SM particles. First, we study the kination-like universe, which demands a larger thermally-averaged annihilation cross section to saturate the observed abundance of DM compared to the standard radiation-dominated picture since, in this case, freeze-out occurs early. As a result, the upper bound on the DM mass becomes more stringent than in the standard case. For example, if the reheating temperature is as low as a few MeVs (corresponding to the start of the Big Bang nucleosynthesis epoch), the usual bound of the DM mass m ≲ 130 TeV can be reduced to a few TeVs for WIMPs. Before closing, we want to emphasize that the evolution of the early universe is largely unknown. The standard assumption of a universe dominated by standard-model radiation from the end of cosmological inflation until matter-radiation equality, together with a transition from an inflaton-dominated to a radiation-dominated universe occurring at a very early time, cannot be taken for granted. Having that in mind, here we have studied the impact of the unitarity bound on DM in the case of low-temperature reheating scenarios. This paper is available on arxiv under CC 4.0 license. Authors: (1) Nicolas Bernal, New York University Abu Dhabi; (2) Partha Konar, Physical Research Laboratory; (3) Sudipta Show, Physical Research Laboratory. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Nicolas Bernal, New York University Abu Dhabi; (2) Partha Konar, Physical Research Laboratory; (3) Sudipta Show, Physical Research Laboratory. Table of Links Abstract and Intro S-matrix: Unitarity and its Consequences Dark Matter Annihilation and Unitarity Bound Low-temperature Reheating Freeze-out with a Low-temperature Reheating Summary and Conclusion Acknowledgments and References Abstract and Intro Abstract and Intro S-matrix: Unitarity and its Consequences S-matrix: Unitarity and its Consequences Dark Matter Annihilation and Unitarity Bound Dark Matter Annihilation and Unitarity Bound Low-temperature Reheating Low-temperature Reheating Freeze-out with a Low-temperature Reheating Freeze-out with a Low-temperature Reheating Summary and Conclusion Summary and Conclusion Acknowledgments and References Acknowledgments and References 6. Summary and Conclusion The requirement of the de Broglie wavelength of dark matter (DM) to hold it inside galaxies and the stability of the stellar galaxy cluster collectively put a broad allowed mass range for DM by providing the lower and upper bound of DM mass, respectively. Specifying some properties of DM can further tighten the mass range. Interestingly, one can put the model-independent upper bound by specifying the thermal production of DM in the early universe. The observed DM abundance and unitarity of partial waves from the scattering matrix jointly place an upper limit on DM mass. Primarily, the upper limits on the inelastic cross section for a general number-changing process 2 → r can be derived with the help of the optical theorem, the matrix elements and the elastic scattering cross section for the process. After that, one can obtain the thermally averaged cross section for the r → 2 process by invoking the principle of detailed balance. Finally, the unitarity bounds on the thermally averaged cross section translate to the upper limits on the DM mass satisfying the relic density constraints. It is known that the maximum allowed DM mass for the 2 → 2 and 3 → 2 DM annihilation processes is around 130 TeV and 1 GeV, respectively. However, these bounds not only depend on the particle physics model, but have a strong dependence on the cosmological evolution of the universe, being valid only if the universe followed the so-called “standard cosmological scenario”. Instead, this article explores the DM mass bound in nonstandard cosmological setups characterized by low-temperature reheating. In particular, we focus on i ) kination-like scenarios, where the early universe was dominated by a fluid with an energy density that gets diluted faster than free radiation, and ii ) early matter-dominated scenarios, where a component with an energy density that scales as nonrelativistic matter dominates the early universe and eventually decays into SM particles. i ii First, we study the kination-like universe, which demands a larger thermally-averaged annihilation cross section to saturate the observed abundance of DM compared to the standard radiation-dominated picture since, in this case, freeze-out occurs early. As a result, the upper bound on the DM mass becomes more stringent than in the standard case. For example, if the reheating temperature is as low as a few MeVs (corresponding to the start of the Big Bang nucleosynthesis epoch), the usual bound of the DM mass m ≲ 130 TeV can be reduced to a few TeVs for WIMPs. Before closing, we want to emphasize that the evolution of the early universe is largely unknown. The standard assumption of a universe dominated by standard-model radiation from the end of cosmological inflation until matter-radiation equality, together with a transition from an inflaton-dominated to a radiation-dominated universe occurring at a very early time, cannot be taken for granted. Having that in mind, here we have studied the impact of the unitarity bound on DM in the case of low-temperature reheating scenarios.

Unitarity Bound on Dark Matter in Low-temperature Reheating Scenarios: Summary and Conclusion

নিম্ন-তাপমাত্রা পুনঃউষ্ণকরণের পরিস্থিতিতে ডার্ক ম্যাটারে একতা আবদ্ধ: সারাংশ এবং উপসংহার

Unitaritätsgrenze für Dunkle Materie in Niedertemperatur-Wiedererwärmungsszenarien: Zusammenfassung und Schlussfolgerung

Unitaridad unida a la materia oscura en escenarios de recalentamiento a baja temperatura: resumen y conclusión

Unitarité liée à la matière noire dans les scénarios de réchauffage à basse température : résumé et conclusion

निम्न-तापमान पुनःतापन परिदृश्यों में डार्क मैटर पर यूनिटैरिटी बाउंड: सारांश और निष्कर्ष

低温再加熱シナリオにおける暗黒物質のユニタリー性限界：要約と結論

저온 재가열 시나리오에서 암흑물질에 결합된 단일성: 요약 및 결론

Limitação de unitaridade na matéria escura em cenários de reaquecimento em baixa temperatura: resumo e conclusão

Унитарность, связанная с темной материей в сценариях низкотемпературного разогрева: итоги и выводы

Düşük Sıcaklıkta Yeniden Isıtma Senaryolarında Karanlık Maddeye Bağlı Üniterlik: Özet ve Sonuç

Tính đơn nhất bị ràng buộc đối với Vật chất tối trong các kịch bản hâm nóng ở nhiệt độ thấp: Tóm tắt và kết luận

低温再加热场景中暗物质的幺正性界限：总结和结论

Testing the Extents of AI Empathy: A Nightmare Scenario

এআই সহানুভূতির পরিধি পরীক্ষা করা: একটি দুঃস্বপ্নের দৃশ্য

Testen des Ausmaßes der KI-Empathie: Ein Albtraumszenario

Probando el alcance de la empatía con la IA: un escenario de pesadilla

Tester l’étendue de l’empathie de l’IA : un scénario de cauchemar

एआई सहानुभूति के विस्तार का परीक्षण: एक दुःस्वप्न परिदृश्य

AI 共感の程度をテストする: 悪夢のシナリオ

AI 공감의 범위 테스트: 악몽 시나리오

Testando a extensão da empatia com IA: um cenário de pesadelo

Проверка степени эмпатии ИИ: кошмарный сценарий

Yapay Zeka Empatisinin Kapsamlarını Test Etmek: Bir Kabus Senaryosu

Kiểm tra mức độ đồng cảm của AI: Kịch bản ác mộng

测试人工智能同理心的程度：噩梦场景

This paper is available on arxiv under CC 4.0 license. Authors: (1) Eleonora Alei, ETH Zurich, Institute for Particle Physics & Astrophysics & National Center of Competence in Research PlanetS; (2) Björn S. Konrad, ETH Zurich, Institute for Particle Physics & Astrophysics & National Center of Competence in Research PlanetS; (3) Daniel Angerhausen, ETH Zurich, Institute for Particle Physics & Astrophysics, National Center of Competence in Research PlanetS & Blue Marble Space Institute of Science; (4) John Lee Grenfell, Department of Extrasolar Planets and Atmospheres (EPA), Institute for Planetary Research (PF), German Aerospace Centre (DLR) (5) Paul Mollière, Max-Planck-Institut für Astronomie; (6) Sascha P. Quanz, ETH Zurich, Institute for Particle Physics & Astrophysics & National Center of Competence in Research PlanetS; (7) Sarah Rugheimer, Department of Physics, University of Oxford; (8) Fabian Wunderlich, Department of Extrasolar Planets and Atmospheres (EPA), Institute for Planetary Research (PF), German Aerospace Centre (DLR); (9) LIFE collaboration, www.life-space-mission.com. Table of Links Abstract & Introduction Methods Results Discussion Conclusions Next Steps & References Appendix A: Scattering of terrestrial exoplanets Appendix B: Corner Plots Appendix C: Bayes’ factor analysis: other epochs Appendix D: Cloudy scenarios: additional figures Appendix D: Cloudy scenarios: additional figures In this section, we provide additional plots for the cloudy scenarios. In Figures D.1 and D.2 we show the retrieved exoplanet parameters and abundances for the different scenarios with varying R and S/N values. Finally, we plot in Figure D.3 the maximum difference ∆ between the cumulative posteriors for the different model parameters, for each combination of the cloudy scenarios and different R-S/N pairs. This paper is available on under CC 4.0 license. arxiv

The Finale of Our Exoplanet LIFE Study: Cloudy Scenarios

https://www.youtube.com/watch?v=JN3KPFbWCy8&embedable=true&transcript=true&long=true

[Transcript] Elon Musk and Lex Fridman on Supreme Beings, Alien Kidnapping Scenarios, and Diablo

This article focuses on extending the property pattern to the next level. Refer prerequisites section for the previous toll fare example used, and the following article extends that example further. Prerequisites Please review the article example below, which calculates a toll fare based on the vehicle type. Advance Property Pattern C# 8.0 The article describes how pattern matching provides an effective way to utilize and process that data in forms that…*medium.com Recap of requirements already covered: If the vehicle is Car => 100 Rs If the vehicle is DeliveryTruck => 200 Rs If the vehicle is Bus => 150 Rs If the vehicle is Taxi => 120 Rs Cars & taxis with “NO” passengers pay an extra 10 Rs. Cars & taxis with two passengers get a 10 Rs discount. Cars & taxis with three or more passengers get a 20 Rs discount. Buses that are less than 50% of passengers pay an extra 30 Rs. Buses with over 90% of passengers get a 40 Rs discount. Trucks over 5000 lbs are charged an extra 100 Rs. Light trucks under 3000 lbs, given a 20 Rs discount. Let’s extend the property pattern. The toll authority wants to add time-sensitive peak pricing for the final feature. Extended Requirements During peak hours, double the price; this rule applies in one direction, i.e., morning into the city and evening out of the city. inbound traffic outbound traffic Late-night & early morning tolls are reduced by 25%. During workday hours, the increasing toll is 50%. During weekends, the toll price is constant concerning time. Reference Table Let’s write some code. Let’s proceed with identifying each column of the reference table above. Identify Day Firstly the program should be aware of whether a particular day is a weekday or weekend. Refer new switch syntax. The above code makes use “ ” enum. System.DaysOfWeek public enum DayOfWeek
{
 Sunday = 0,
 Monday = 1,
 Tuesday = 2,
 Wednesday = 3,
 Thursday = 4,
 Friday = 5,
 Saturday = 6
} Identify Time Firstly, the distinct time slots available. private enum TimeSlots
{
 MorningPeak,
 Daytime,
 EveningPeak,
 Overnight
} Now let’s identify the time slots using switch syntax with time in hours. Identify Direction As there are two possible values of direction, it can directly be used as a boolean flag, i.e., if ‘true’ means inbound and if ‘false’ means outbound. True  => inbound  => Into the city
False => outbound => Out of the city The alternative is to create an enum and add switch syntax, similar to what we have done above. Identify Premium After all table columns are identified, the below switch expression with the tuple pattern calculates the toll premium. Refer to pattern-matching syntax with single & multiple property classes. Link The switch expression. Premium method call var costInbound = PeakPremium.CalculatePeakTimePremium(DateTime.Now, true); var costOutbound = PeakPremium.CalculatePeakTimePremium(DateTime.Now, false); Console.WriteLine("Charges {0} for {1}",costInbound,DateTime.Now); Console.WriteLine("Charges {0} for {1}", costOutbound, DateTime.Now); Output Charges 1.50 for 9/8/2020 12:05:29 PM
Charges 1.50 for 9/8/2020 12:05:29 PM Github Sample ssukhpinder/PropertyPatternExample Thank you for reading. I hope you like the article..!! Also published here.

Pattern Matching in C# for Complex Scenarios: An Extension on Property Patterns

It’s inevitable that at some point the world will end. The only question left is whether it will be in a slow, inexorable heat death of the universe, or something a little more active and exciting. Unsurprisingly most sci fi movies tend to explore the second option (although there are some excellent books and short stories such as Asimov’s which look at the first). The Last Question Since it’s my field, we’re going to look at how cyber security failings could cause these apocalypses (apocalypsi?), and which are most likely. We’ve got the deliberate corruption of global agritech, hijacking of DNA printers, the classic infrastructure hack, and autonomous smart device madness. Those of an anxious or nervous disposition may want to stop reading now. Instead, you can go watch something nice and light. If you’d like a more active distraction, then there’s some great games here to take your mind off the inevitable collapse of, well, everything. Now that we’re left with the incurably curious, lets crack on. Disclaimer: Don’t take these as inspiration. Also, if one of these does happen to be accurate, please note that neither HackerNoon nor I had anything to do with it. 1. Agritech, Agriculture, and Famine Agritech is about technology being applied to farming, especially more advanced and intelligent technology. As agriculture is more and more industrialised, we see traditional farming equipment replaced with advanced gadgetry such as smart tractors, sprinklers, and of course . drones At the 2011 DefCon Chris Roberts and Jesse Diekman demonstrated to the world just how bad cyber security flaws in the ever-expanding world of agritech could be. They’d managed to find a way to access and modify the manufacturer’s software repository, where updates to be pushed out to (in this case) tractors were constructed. The targeted tractor was definitely a labour-saving device, even handling planting of crops at the perfect depth and distance from one another for optimum growth. The software update in question controlled a number of variables, such as the depth and distance for planting. They showed that it could be edited, and staged for update to the full network of tractors. Caption: Not the tractor in question. Instead, an automated harvester for green asparagus developed by Muddy Machines. When dealing with highly industrialised farming measurements are vital. Everything is calculated as perfectly as possible, with very small margins for error. If you’ve gardened at all you’ll know the issues that planting an inch too low can cause. In this case, it could easily have led to grain crop failures across the American Midwest, which may not have been detected until after the planting season when it was too late to correct. There is no doubt difficulties would have quickly followed, especially as one strand of a multi-targeted attack to cause as much damage and disruption as possible. Worryingly, the manufacturers themselves worsen the situation by fighting desperately against the right to repair and trying to force their own central control. If something does go wrong, only the manufacturer can fix by design. Add to this the possibility of of disruption due to other attacks and while it’s a remote possibility, a well-resourced and multi-threaded attack could definitely push into agricultural crisis. Once food is disrupted on a severe enough scale, everything else follows. 2. Pandemics to Order - Bioweapons We’ve now seen what a pandemic can do, at least to some degree. COVID-19 is difficult to judge, but is probably far from in recorded history. Still, at least any attempt to weaponise a virus would surely need highly advanced knowledge and expensive equipment, and any such equipment would never be connected to the internet. the worst pandemic Of course, that ignores desktop DNA synthesisers which come with internet connections. The ones I researched and spoke about in 2021 are, luckily, just used for synthesising base pairs and so couldn’t create an entire custom virus. Still, technology advances, convenience trumps security, and efforts to put protections in place would best be described as struggling. https://www.youtube.com/watch?v=L9vXiqpLkKU?embedable=true While this is unlikely to be how the world ends, the more these technologies advance without putting effective cyber security in place the more likely it becomes. At the very least it would be good to see some sort of fiction about custom-designed killer viruses. Oh, never mind. 3. Out of Power While it’s the most popular option for the average cyber-crisis film about impossible missions, the whole idea of attacking infrastructure isn’t as effective as fiction would lead people to believe. There have been individual incidents of being targeted, more often for ransomware than poisoning, and famously Ukraine’s in 2015, but even in the worst cases these tend to be fairly localised. The good news is, that means even the worst case of a successful attack on national infrastructure is only likely to cause kilodeaths, rather than the megadeaths of something like nuclear warfare. water treatment plants power grid hack The reason for this is that, generally speaking, the people who run national infrastructure have resources, and are very aware of how appealing their systems are for someone wanting to cause harm. There’s also the advantage that different systems are diverse rather than standardised. The time to worry will be if there are significant efforts to standardise and centralise control systems for critical infrastructure - diversity makes systems more resilient, as attacks against one component are less likely to impact others. Frankly, critical national infrastructure failures are more likely to be equipment failures or human error rather than a team of hackers sitting in a room watching green code scroll past. 4. Killer Cars We are a long way from truly self-driving vehicles, despite the hype and enthusiasm we’ve had around them since at least the 1980s. There’s a lot of work before they’re , let alone legal, but it’s one of those things that keeps floating around the collective unconsciousness and popping up as ‘just a few years away’. safe There’s plenty of different models that could be applied to autonomous vehicles, ranging from centralised control to each vehicle making its own decisions. It’s not hard to predict the potential flaws of either model - malicious updates causing cars to become homicidal ala Cory Doctorow’s . We could even see centralised control hijacking as famously shown in . Attack Surface Minority Report That’s only talking about vehicles though, and we already have autonomous drones, including ones which are heavily armed. As with all smart devices, ultimately they do the bidding of whoever controls their software and encryption keys, which puts them as a very definite candidate for at least a local apocalypse. That’s assuming we don’t instead have to battle our own smart homes to the death, becoming more and more popular in film. Or have to deal with our cars locking us in and spontaneously combusting. https://youtu.be/IgZf-auOZxI?embedable=true The Good News In great news, any of these (or other cyber security attack scenarios) are almost certainly not the way the world is going to end. There are plenty of other options out there which are far more likely, and these are largely used as FUD (Fear, Uncertainty, and Doubt) to drum up anxiety rather than anything else - but that doesn’t mean there aren’t serious questions we need to be asking. https://www.youtube.com/watch?v=FcyNNqaXLg8?embedable=true While this is a bit of a light hearted take on things, there are serious conversations we need to have about how we deal with security and how we get from where we are to a place where at least things aren’t getting worse. I’ll just leave you with a little final thought, badly paraphrased from T. S. Elliot’s The Hollow Men. This is the way the world ends This is the way the world ends This is the way the world ends Not with a bang but with a HTTP ERROR 410

How Will The World End? Top 4 Cyber Apocalypse Scenarios

¿Como el mundo terminara? Los 4 mejores escenarios de ciberapocalipsis

Comment le monde finira-t-il ? Top 4 des scénarios de cyber-apocalypse

दुनिया कैसे खत्म होगी? शीर्ष 4 साइबर सर्वनाश परिदृश्य

世界はどのように終わりますか?トップ 4 のサイバー アポカリプス シナリオ

Como o mundo vai acabar? Os 4 principais cenários de apocalipse cibernético

Thế giới sẽ kết thúc như thế nào? 4 kịch bản khải huyền mạng hàng đầu

世界将如何终结？ 4 大网络启示录场景

Every generation has its tech heroes, among other more super (fictional) and less regular (real-life) ones. For the and , that hero is undeniably Elon Musk. For my Gen X, AKA the “forgotten” and/or “lost” generation, that was/is Kim Dotcom. Millennials Gen Zs What could these two distinguished and controversial individuals have in common? Well, to begin with, they’re Twitter buddies. Elon “Lekker” Musk and Kim “Kiwi” Dotcom You can please some of the people all of the time, you can please all of the people some of the time, but you can’t please all of the people all of the time. ― John Lydgate So, one fine day, Kim Dotcom wasn’t feeling fine about Elon’s “sleeping” Starlink satellites. By the way, a great song by Tasmin Archer. Look for it on YouTube. Elon entered into the full “mea culpa” mode with his reply: Then, we had a series of tweets about love, humanity, peace in the world, and other commonplaces every Miss Universe contestant knows by heart. Love is in the air, but at a lower altitude than “kamikaze drones” and the Internet satellites, obviously. What’s fair is fair, Kim Dotcom has a lot on his plate too. The Ukrainians may forgive one day, but , which is more certain than death and taxes. The silver lining for Kim is the fact that he’s living in the in the world. Elon’s peace “suggestion” Hollywood won’t let Kim slip through their copyright fingers doomsday-bunkers-for-billionaires-friendliest country , it’s good to have Kim Dotcom for a friend, even if it’s only on Twitter. In the worst-case scenario of a nuclear apocalypse The basic survival premise is to get to New Zealand’s apocalypse-proof bunkers just in time before, you know what. But, that’s another story. Just before we leave the founder of , not to be confused with MAGA, to enjoy in the company of Peter Jackson’s Hobbits (LOTR and The Hobbit Trilogy filming location), let’s not forget to mention Kim’s political “tryouts” as , again not to be confused with MAGA Movement. Why is that even a thing? Well, big money, big tech, and politics are simply destined or doomed to cross paths, this way or another. MEGA an independent candidate and with the MANA Movement The “Damnation” of the Political “Wrong Turn” Does Elon Musk have to be omnipresent? There’s no other way to put it, and this is a legit question to ask. Whenever there’s an event that captures the entire world’s attention, there’s no high probability, but certainty Elon would be there, involved. I’m not talking about the war in Ukraine. Do you remember the ? There has to be a bitter taste of controversy left behind Elon. It’s just the way it or he is. In his own defense, he has every right to say that the road to bad publicity is paved with good intentions. trapped Thai youth soccer team The cherry on top was delivered by Larry T Bird. The Twitter takeover is a done deal judging by the . So, we’re free to address the Elephant in the room. Elon is to spice Midterms up, that’s the plan. Nah, I don’t think so. Why so serious? I see “Batman Begins” rather than how Twitter ends. locked staff stock accounts bringing back Trump on Twitter and setting some new rules about the pool area… Also, I wouldn’t go that far as judging someone’s character or personality based on tweets. "In addition to being the world’s wealthiest man, Elon Musk also seems to be exhibiting the symptoms of histrionic personality disorder. HPD, as it’s known in the psychiatric sciences, resides in the ‘Cluster B’ garden of personality disorders and is associated with narcissism, attention-seeking behaviors and manipulation. HPDers tend to be charming and lively, often verging into flirtatiousness and excitability," . Politico’s Jack Shafer wrote Why so personal? All I see are Bruce Wayne and Clark Kent in one of the final scenes of “Justice League.” I’m not the first nor the last who has compared Elon Musk with Bruce Wayne, but those who compare Trump with Clark Kent should consult that Politico’s columnist I quoted. What’s wrong with this picture? Nothing. The man who is taking us to Mars has to worry about what he’s going to tweet next because he might get suspended. C’mon! Seriously? But, what’s going to happen with the current Twitter employees? Let’s say, for the sake of this story, that I have a friend who works at Twitter. He’s asking me for a piece of advice on whether or not he should leave or stay. I’d say, if you want to leave only because you don’t like Elon as a person, then you’re about to make a mistake, which you’re very likely to regret. But if you want to leave because you believe that Elon is way over his head with the whole Twitter thing, then you’re right. You work at Twitter; you know the ins and outs of it. In that case, I understand and support you. I have had clients from all over the world. With some of them, I shared the turbulent and brutal history of our nations and countries. But what does that have to do with business? NOTHING! Are you a professional regardless of the circumstances OR an activist regardless of the “agendas?” What you do in your free time; it’s your thing. Your workplace should be sacred. There’s no room for politics, ideologies, bias, and similar at work. Twitter Don’t Cry - Midterms Have A Bigger Fish To Fry Can the richest man in the world decide the outcome of the Midterm Elections in 2022? Nope! By the way, a great movie by Jordan Peele. You’re free to ask Kim Dotcom where you can watch it for free, but I wouldn’t recommend you that. Elon Musk can’t fix inflation and the southern border crisis. He can’t make pro-choice and pro-life activists come up with a win-win scenario, nor make Zelensky and Putin shake hands and smile. However, Elon could get caught in the midterm crossfire. What’s even worse, he could become the very tree distracting us from seeing that the tech forest is on fire. “The Supreme Court will hear two cases that could change Section 230 of the Communications Decency Act. Slate's senior writer Mark Joseph Stern tells "Nightcap's" Jon Sarlin why big tech and social media companies are calling this a "fundamental threat to their existence.” https://edition.cnn.com/videos/business/2022/10/06/nightcap-supreme-court-section-230-clip-orig-nb.cnn?embedable=true When you’re facing an “existential threat,” you aren’t yourself. This means that the big tech could and would become extremely biased. Elon Musk, with or without Twitter, can afford to be “politically neutral,” but YouTube and Facebook can’t. “Especially at a time when to include ham-handed safeguards for political conservatives.” This means that the big tech would have to be even more generous with their donations to the Democrats because “ , so the Court may not, in the long run, have the last say.” many Republicans would like to rewrite Section 230 members of Congress regularly consider legislative changes to Section 230 Plain and simple, while you’re deciding whether or not you should tweet under the “rule” of Elon Musk, you may lose your immunity as a content creator because “Section 230’s protections are essential for to offer user-contributed content and that restrictions on the statute’s historically broad immunity would impede innovation and prove unduly burdensome.” website publishers and app services As you can see not even all the money in the world can’t guarantee that you will have it your way. It’d take one Supreme Court decision to change Section 230 and make Elon’s $44B investment in Twitter - worthless. Elon Musk will be damned whether he turns left or right, does something, or does nothing, but you won’t if you support my nomination for the with your votes at this year’s Noonies that will last longer than midterms. HACKERNOON CONTRIBUTOR OF THE YEAR- ELON-MUSK https://www.noonies.tech/2022/internet-heroes/2022-hackernoon-contributor-of-the-year-elon-musk?embedable=true

Elon Musk and The Worst-Case Scenario of a Nuclear Apocalypse

Elon Musk y el peor de los casos de un apocalipsis nuclear

Elon Musk et le pire scénario d'une apocalypse nucléaire

एलोन मस्क और परमाणु सर्वनाश का सबसे खराब स्थिति परिदृश्य

イーロン・マスクと核の黙示録の最悪のシナリオ

Elon Musk e o pior cenário de um apocalipse nuclear

Elon Musk và tình huống tồi tệ nhất về ngày tận thế hạt nhân

伊隆马斯克和核灾难的最坏情况

In today’s digital world, the threat of cyber-attacks has become a significant challenge for organizations to overcome. While most organizations take significant precautions and implement many cybersecurity measures, that doesn’t always mean that they’re completely safe from the threat of cyberattacks. One type of cyber-attack that organizations fear most is ransomware attacks. Though no organization ever wants to find itself as the victim of a ransomware attack, it’s important to be aware of what to do when that happens. Understanding how to appropriately respond to this type of cyber-attack can make the process of diffusing the situation less challenging and damaging. Here are some things to consider when facing a ransomware scenario. What Is a Ransomware Attack? Before one can be prepared to respond to a ransomware attack effectively, it’s important to have a general understanding of what a ransomware attack is. Ransomware is a form of malware that hackers and cybercriminals use to make files inaccessible to individuals or organizations. They do this by encrypting files, essentially locking individuals and organizations out from accessing their personal databases. The “ransom” in ransomware refers to the practice of cybercriminals demanding a ransom in exchange for access to the affected network. What to Look Out For When it comes to ransomware attacks, there are some common ways that cybercriminals capitalize on weak and vulnerable points in an organization’s cybersecurity measures. Understanding where an organization may be most vulnerable can help them safeguard themselves and their organization from these types of attacks. Here are some things to look out for when it comes to guarding one’s organization against ransomware attacks. Management Software and Managed Service Providers When cybercriminals are looking to breach an organization’s cybersecurity measures, they’ll often look for ways that they can do so undetected. One technique that hackers have capitalized upon in the past is that of utilizing managed service providers and management software as a way to access the networks of many other organizations. When cybercriminals hack into a managed service provider’s network, they can then easily coerce the organizations who use these services and software to unknowingly download malware. Once this happens, hackers can then encrypt the information of an organization and demand a ransom in exchange for renewed access. This type of cybersecurity breach has affected many industries of varying types. One such industry that has keenly experienced these types of breaches is the supply chain industry. Since 2021, have been on the rise, and managed service providers have been hackers’ points of entry for many of them. supply chain attacks What makes this type of breach so effective is the fact that organizations typically place a substantial amount of trust in their managed service providers. This means that there is typically little to no suspicion that managed service providers could potentially be threatening one’s cybersecurity measures. This being the case, it’s important for organizations to be on high alert when it comes to surveying managed service provider updates and downloads in order to steer clear of making oneself vulnerable to becoming the victim of a cyber-attack. Partners and Third-Party Services Organizations of a certain scale and size typically work with a number of other organizations in order to be able to function. While these are often necessary partnerships, they can make one’s organization vulnerable to cyber-attacks. As such, being cautious when it comes to choosing the partners and third-party services that one chooses to work with can be a key cybersecurity measure that helps keep one’s organization safe from being the victim of a cyber-attack. In order to improve one’s organization’s chances of being the victim of a ransomware attack, it can be useful to assess the cybersecurity measures of other organizations before deciding to work with them. If an organization’s partner is hacked, that puts that organization at risk of being hacked as well. This means that vetting and assessing the cybersecurity measures of the organizations that one works with can be paramount to safeguarding oneself from ransomware attacks. How to Respond to a Ransomware Attack While it can be a difficult practice, organizations can benefit from creating a plan of action for the chance that a scenario occurs in which they are the victim of a ransomware attack. Understanding appropriate ways to respond can make the scenario go smoother and cause less damage to one’s organization. One of the main reasons that ransomware attacks have increased in popularity is the fact that more organizations are willing to pay ransoms than ever before. While conceding to cybercriminals can be a difficult pill to swallow, oftentimes, simply paying the ransom is the cheapest and most efficient way to get out of a ransomware attack scenario. Though it can be difficult to think that one’s organization should be ready to pay hackers, it might be the most prudent and rational thing that an organization can do in that scenario. As such, it can be helpful for organizations to decide upon a predetermined amount of money that they would be willing to pay if a severe and effective ransomware attack were to occur. This amount can be based on research about how long it would take and how much money it would cost to try to deal with a ransomware attack in an alternative manner. In addition to being prepared to pay a ransom, it can be useful for one’s organization to have a plan regarding which cybersecurity professionals to assign to remedy and monitor the situation. This is because there is no shortage of cybersecurity jobs today, and many organizations have a variety of cybersecurity professionals working for them. This can make it difficult to know who to call upon in a stressful and chaotic scenario such as a ransomware attack. This being the case, having a game plan about which professionals to tap for assistance in these situations can help organizations be more prepared for cyber-attack scenarios. How to Bolster Cybersecurity Measures and Stay Safe from Ransomware Attacks While all organizations typically have some level of cybersecurity measures in place, there is almost always more that can be done to better protect one’s network and files. Being aware of some practical ways to improve one’s organization’s cybersecurity measures can be helpful for those looking to safeguard themselves against ransomware attacks. Here are some steps to take to bolster cybersecurity measures and stay safe from ransomware attacks. Effective Cybersecurity Training for All Employees For most organizations, cybersecurity training is something that many employees participate in at some point in time. Though this is the case, these cybersecurity training sessions aren’t always effective enough to instill everyone with a working knowledge of proper cybersecurity protocols. By putting more time, energy, and effort into crafting effective cybersecurity training programs for all employees, organizations can significantly improve their chances of being safe from cybercriminals and their efforts to breach networks. It is worth investing money and resources into proper training for your employees as ransomware situations can be incredibly expensive. Dr. Christopher Whyte, assistant professor in the in the Wilder School of Government and Public Affairs at Virginia Commonwealth University elaborates on the potential cost of a ransomware scenario. homeland security and emergency preparedness program “There are generally five main costs to consider. One is the unit cost of building defensive “walls” that will keep attackers out. Another is the cost of maintaining backups. Yet another is the prospective cost of an after-the-fact effort to salvage data and value from the digital debris left by an attack, including potential hardware and infrastructure costs. There is also the cost of disruption from an attack, namely the lost operational capacity for profit. And there is also the prospective profit deficit to accrue from a successful attack, namely coming from a hit to reputation that reduces usership, share prices and so on.” With everything considered, there is still room for debate regarding whether it is worth it to pay or not to pay the ransom. , Assistant Professor of Cybersecurity at Maryville University weighs in on this dilemma: Dr. Brian Gant “In most cases regarding ransomware and whether organizations should pay the ransom, it is recommended that they not for several reasons. The primary one being there is no guarantee that once the ransom is paid that the attackers will provide the decryption tool. They are after all “attackers” exploiting a vulnerability.” Taking Advantage of Honeytokens While preventing cyber-attacks usually consists of bolstering security measures, honeytokens are a way to lure cybercriminals into attacking one’s company in order to gain the upper hand. Put simply, honeytokens are typically bogus data resources that organizations will plant in their network in the hopes of baiting cybercriminals into hacking into them. When cybercriminals attempt to hack into honeytokens, the cybersecurity professionals working within an organization will be alerted, giving them a chance to prepare themselves for an attack on the organization’s actual databases before it happens. This also allows cybersecurity professionals the chance to identify how a particular cybercriminal is plans to hack into their network. By knowing this information, organizations can better defend themselves against cybercriminals and their attempts to perform cyber-attacks. Encrypting Internal Data While it’s not always the most convenient course of action, encrypting internal data can help organizations safeguard themselves from hackers. While encryption adds a layer of protection to an organization’s files, it also deters hackers from even attempting to breach the network in the first place. This is because hacking into networks that aren’t encrypted is much easier while breaching a network with encryption can be challenging and time-consuming for cybercriminals. By encrypting internal data, organizations can make their organization seem like an unattractive target for cyber-attacks. As such, this simple practice can be extremely effective in safeguarding one’s organization from a wide variety of cyber-attacks. Staying Safe in the Face of Ransomware Attacks While organizations may pour a large amount of time and effort into crafting robust cybersecurity measures, this doesn’t always ensure that a cyber-attack won’t happen. In the case that one’s organization is the victim of a ransomware attack, understanding how to respond appropriately can make it easier and less stressful to respond to. This being the case, all organizations can benefit substantially from having a plan in the event of a ransomware attack.

Things to Consider When Facing a Ransomware Scenario

This post analyzes ops & maintenance solutions with experiences taken from real production scenarios for data sharding and other functions provided by ShardingSphere-Proxy Version 5.1.0. Unless otherwise specified, in the following examples, when we say “database” we refer to MySQL. What does ShardingSphere-Proxy do? ShardingSphere-Proxy allows users to use Apache ShardingSphere just as if it were a native database. To gain a better understanding of what’s ShardingSphere-proxy, let’s take a look at its definition provided, by : Apache ShardingSphere’s official website ShardingSphere-Proxy is a transparent database proxy that provide a database server containing database binary protocols designed to support heterogeneous languages. Currently, it supports MySQL and (and PostgreSQL-based databases, such as ) and any related terminals (such as , Workbench, etc.) that are compatible with MySQL or PostgreSQL protocols to operate data. It’s a DBA-friendly tool. PostgreSQL openGauss MySQL Command Client It’s worth noting that ShardingSphere-Proxy is a service process. In terms of client-side program connections, it is similar to a MySQL database. Why you need ShardingSphere-Proxy ShardingSphere-Proxy is a good choice when: sharding rules or other rules are used; because data will be distributed across multiple database instances, inevitably making management inconvenient. non-Java developers need to leverage ShardingSphere capabilities. 1. Application scenarios There are many scenarios where ShardingSphere-JDBC is used for data sharding. If you have a user table and need to perform horizontal scaling with Hash for the User ID property, the way the client connects to the database is like this: Below are three real production scenarios: A testing engineer wants to see the information of user ID 123456 in databases & tables, and you need to tell the engineer which subtable the user is in. You need to find out the total user growth in 2022 and overall user information for drafting a yearly report. Your company is going to hold its 8th-anniversary event and you are required to provide a list of active users who have been registered for over 8 years. Since the data is distributed across database shards and table shards, it is not easy to complete the above-mentioned tasks. If you develop code every time to satisfy these temporary requirements, it’ll be inefficient, to say the least. ShardingSphere-Proxy is perfect for these scenarios. ShardingSphere-Proxy hides the actual backend databases, so the user operates the client-side the same way as a database. For example, is split into several real tables at the database level, that is from to . While operating ShardingSphere-Proxy on the client-side, the user only needs to know one logical table , and routing to the real tables is executed inside ShardingSphere-Proxy. t_user t_user_0 t_user_9 t_user The logical name of the horizontally-scaled databases/tables with the same structure. A logical table is the logical identifier of tables in SQL. For example, user data is sharded into 10 tables according to the significant digits of the primary key, that is, to , and their common logical table is named . 1. Logical table: t_user_0 t_user_9 t_user The physical table actually exists in databases after scale-out, that is, the above-mentioned to . 2. Actual table: t_user_0 t_user_9 2. The differences between ShardingSphere-JDBC and ShardingSphere-Proxy After reading the above description, you probably feel that ShardingSphere-Proxy and ShardingSphere-JDBC are so similar. So what are the differences between the two? Check out more on the differences between the two below: ShardingSphere-JDBC is a package. Its bottom layer completes SQL parsing, routing, rewriting, execution, and other processes by rewriting JDBC components. You should add the configuration files to implement the corresponding functions in the project, making it intrusive to applications. .jar ShardingSphere-Proxy is a process service. In most cases, it is positioned as a productivity tool to assist operations. It disguises itself as a database, making itself non-intrusive to applications. The SQL execution logic in ShardingSphere-Proxy is the same as in ShardingSphere-JDBC because they share the same kernel. Since ShardingSphere-Proxy is non-intrusive to applications, and it shares the same kernel with ShardingSphere-JDBC — so why do we still need ShardingSphere-JDBC? When an application directly operates databases through ShardingSphere-JDBC, there is only one network I/O. However, when the application connects to ShardingSphere-Proxy, one network I/O, and then ShardingSphere-Proxy operates databases, and another network I/O occurs, in total two network I/O requests. There is one more layer of an application called link, which is more likely to cause a data traffic bottleneck and potential risks to the application. In general, it’s suggested that an application should be used together with ShardingSphere-JDBC. Of course, ShardingSphere-JDBC and ShardingSphere-Proxy can be deployed simultaneously with a hybrid architecture. ShardingSphere-JDBC is suitable for high-performance lightweight Online Transaction Processing (OLTP) applications developed in Java, while ShardingSphere-Proxy is perfect for Online Analytical Processing (OLAP) applications and scenarios for managing and operating sharding databases. Quick Start Guide There are three setup methods to install ShardingSphere-Proxy: binary package, Docker, and Helm. Stand-alone deployment and clustered deployment are also provided. Here, we take the standalone binary package as an example: Get the ShardingSphere-Proxy binary installation package ; at this link Decompress it and then modify and files starting with the prefix to configure sharding, read/write splitting and other functions; conf/server.yaml config- If you use Linux as operating system, please run For Windows operating systems, please run to bootup ShardingSphere-Proxy. bin/start.sh. bin/start.bat The file directory looks like this: ├── LICENSE
├── NOTICE
├── README.txt
0009 ─ ─ bin #Start/stop script
0009 ─ ─ conf #service configuration, data sharding, read/write splitting, data encryption, and other function configuration files
├── lib # Jar package
└── licenses Download the ( ) or ( ) into the package. 1. Copy MySQL Java connector to the ext-lib package driver mysql-connector-java-5.1.47.jar Click the link to download mysql-connector-java-8.0.11.jar https://repo1.maven.org/maven2/mysql/mysql-connector-java/8.0.11/mysql-connector-java-8.0.11.jar ext-lib Note: There is no package in the initial directory, so you need to create one yourself. ext-lib For the default operation mode is . Below is how to configure the standalone operation mode. 2. Modify the conf/server.yaml configuration file server.yaml Cluster Mode mode:
Type: Standalone #Standalone mode
repository:
type: File
props:
Path: /Users/xxx/software/apache-shardingsphere-5.1.0-shardingsphere-proxy/file #persistent file paths such as metadata configuration
Overwrite: false #Overwrite the existing metadata？
Rules: #Verification Info
- !AUTHORITY
Users: #Init user
- root@%:root
- sharding@:sharding
provider:
type: ALL_PRIVILEGES_PERMITTED
- !TRANSACTION
defaultType: XA
provider Type: Atomikos
- !SQL_PARSER
sqlCommentParseEnabled: true
sqlStatementCache:
initialCapacity: 2000
maximum Size: 65535
concurrencyLevel: 4
parseTreeCache:
initialCapacity: 128
maximum Size: 1024
concurrencyLevel: 4
Props: #public configuration
max-connections-size-per-query: 1
kernel-executor-size: 16  # Infinite by default.
proxy-frontend-flush-threshold: 128  # The default value is 128.
proxy-opentracing-enabled: false
proxy-hint-enabled: false
sql-show: false
check-table-metadata-enabled: false
show-process-list-enabled: false
# Proxy backend query fetch size. A larger value may increase the memory usage of ShardingSphere Proxy.
# The default value is -1, which means set the minimum value for different JDBC drivers.
proxy-backend-query-fetch-size: -1
check-duplicate-table-enabled: false
proxy-frontend-executor-size: 0 # Proxy frontend executor size. The default value is 0, which means let Netty decide.
# Available options of proxy backend executor suitable: OLAP(default), OLTP. The OLTP option may reduce time cost of writing packets to client, but it may increase the latency of SQL execution
# and block other clients if client connections are more than `proxy-frontend-executor-size`, especially executing slow SQL.
proxy-backend-executor-suitable: OLAP
proxy-frontend-max-connections: 0 # Less than or equal to 0 means no limitation.
sql-federation-enabled: false
# Available proxy backend driver type: JDBC (default), ExperimentalVertx
proxy-backend-driver-type: JDBC Note: if you start a standalone ShardingSphere-Proxy and later need to change Proxy configurations, you need to set to true. By doing so, ShardingSphere-Proxy will reload the metadata after startup. mode.overwrite Execute the bootup command: . The default port , and the port can be replaced by adding parameters to the start script command: . 3. Start ShardingSphere-Proxy sh bin/start.sh is 3307 sh bin/start.sh 3308 To check whether ShardingSphere-Proxy started successfully, execute the check log command: . tail -100f logs/stdout.log The following information placed on the last line means that the startup is successful: [INFO ] xxx-xx-xx xx:xx:xx.xxx [main] o.a.s.p.frontend.ShardingSphereProxy - ShardingSphere-Proxy Standalone mode started successfully Scenarios and applications Based on actual production scenarios, we’d like to show you how you can utilize ShardingSphere-Proxy to meet your expectations. 1. Initialize the database & table # CREATE DATABASE
CREATE DATABASE user_sharding_0;
CREATE DATABASE user_sharding_1;
# CREATE TABLE
use user_sharding_0;
CREATE TABLE `t_user_0` (
`id` bigint (20) NOT NULL,
`user_id` bigint (20) NOT NULL,
`create_date` datetime DEFAULT NULL,
PRIMARY KEY (`id`)) ENGINE = InnoDB DEFAULT CHARSET = latin1;
CREATE TABLE `t_user_1` (
`id` bigint (20) NOT NULL,
`user_id` bigint (20) NOT NULL,
`create_date` datetime DEFAULT NULL,
PRIMARY KEY (`id`)) ENGINE = InnoDB DEFAULT CHARSET = latin1;
use user_sharding_1;
CREATE TABLE `t_user_0` (
`id` bigint (20) NOT NULL,
`user_id` bigint (20) NOT NULL,
`create_date` datetime DEFAULT NULL,
PRIMARY KEY (`id`)) ENGINE = InnoDB DEFAULT CHARSET = latin1;
CREATE TABLE `t_user_1` (
`id` bigint (20) NOT NULL,
`user_id` bigint (20) NOT NULL,
`create_date` datetime DEFAULT NULL,
PRIMARY KEY (`id`)) ENGINE = InnoDB DEFAULT CHARSET = latin1; 2. Initialize sharding configuration in Proxy schemaName: sharding_db
dataSources:
ds_0:
url: jdbc:mysql://127.0.0.1:3306/user_sharding_0?serverTimezone=UTC&useSSL=false
username: root
password: root
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
ds_1:
url: jdbc:mysql://127.0.0.1:3306/user_sharding_1?serverTimezone=UTC&useSSL=false
username: root
password: root
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
rules:
- !SHARDING
tables:
t_user:
actualDataNodes: ds_${0..1}.t_user_${0..1}
tableStrategy:
standard:
shardingColumn: user_id
shardingAlgorithmName: t_user_inline
keyGenerateStrategy:
column: user_id
keyGeneratorName: snowflake
bindingTables:
- t_user
defaultDatabaseStrategy:
standard:
shardingColumn: user_id
shardingAlgorithmName: database_inline
defaultTableStrategy:
none:
shardingAlgorithms:
database_inline:
type: INLINE
props:
algorithm-expression: ds_${user_id % 2}
t_user_inline:
type: INLINE
props:
algorithm-expression: t_user_${user_id % 2}
KeyGenerators:
snowflake:
type: SNOWFLAKE 3. Test sharding configuration Use the MySQL terminal command to connect to the ShardingSphere-Proxy server. If you deploy databases in Docker containers, you need to add native . Because accessing 127.0.0.1 in the container is blocked. -h ip #replace {xx} with actual parameter
mysql -h {ip} -u {username} -p{password} -P 3307
#example command
mysql -h 127.0.0.1 -u root -proot -P 3307 ShardingSphere-Proxy supports , , , , and other database management connectors. Navicat MySQL DataGrip WorkBench TablePlus After confirming the connection is successful, query the databases and make sure they are consistent with those in the configuration file. mysql> show databases;
+-------------+
| schema_name |
+-------------+
| sharding_db |
+-------------+ 1 row in set (0.02 sec) Execute the new statement, insert 6 pieces of user data (3 pieces for 2021, and 3 pieces for 2022). t_user mysql> use sharding_db;
mysql> INSERT INTO t_user (id, user_id, create_date) values(1, 1, '2021-01-01 00:00:00'), (2, 2, '2021-01-01 00:00:00'), (3, 3, '2021-01-01 00:00:00'), (4, 4, '2022-01-01 00:00:00'), (5, 5, '2022-02-01 00:00:00'), (6, 6, '2022-03-01 00:00:00');
Query OK, 6 rows affected (0.16 sec)
mysql> select * from t_user;
+----+---------+---------------------+
| id | user_id | create_date         |
+----+---------+---------------------+
|  2 |       2 | 2021-01-01 00:00:00 |
|  4 |       4 | 2022-01-01 00:00:00 |
|  6 |       6 | 2022-03-01 00:00:00 |
|  1 |       1 | 2021-01-01 00:00:00 |
|  3 |       3 | 2021-01-01 00:00:00 |
|  5 |       5 | 2022-02-01 00:00:00 |
+----+---------+---------------------+ At this time, the data is in the and databases respectively. user_sharding_0 user_sharding_1 Scenario 1: How to locate data information? Since ShardingSphere-Proxy has logically aggregated the tables, you can query them directly. mysql> select * from t_user where user_id = 1;
+----+---------+---------------------+
| id | user_id | create_date         |
+----+---------+---------------------+
|  1 |       1 | 2021-01-01 00:00:00 |
+----+---------+---------------------+
1 row in set (0.01 sec) Scenario 2: How to check user growth in 2022 and user information? mysql> select count(*) from t_user where create_date > '2022-00-00 00:00:00';
+----------+
| count(*) |
+----------+
|        3 |
+----------+
1 row in set (0.10 sec)
mysql> select * from t_user where create_date > '2022-00-00 00:00:00';
+----+---------+---------------------+
| id | user_id | create_date         |
+----+---------+---------------------+
|  4 |       4 | 2022-01-01 00:00:00 |
|  6 |       6 | 2022-01-01 00:00:00 |
|  5 |       5 | 2022-01-01 00:00:00 |
+----+---------+---------------------+
3 rows in set (0.02 sec) Scenario 3: How to get a list of active users who have been registered for over 8 years? Refer to the above code and you will know how to cope with it. Conclusion This post summarizes the basic concepts of ShardingSphere-Proxy based on the actual data sharding production scenarios and demonstrates how ShardingSphere-Proxy faces these scenarios. After reading this article, you should be able to: Understand why ShardingSphere-Proxy is an excellent product to assist developers in DevOps. Know the differences between ShardingSphere-JDBC and ShardingSphere-Proxy, their advantages and disadvantages, and how they are implemented. Since you now have a better understanding of ShardingSphere-Proxy, we believe, it will be easier for you to study its source code. To know more about ShardingSphere, please visit or our community’s previous blogs such as Create a Distributed Database Solution Based on PostgreSQL/openGauss. Apache ShardingSphere's official website Also published . here

A Quick Start Guide to Use ShardingSphere-Proxy in Real Production Scenarios 

In the current scenario, mobile app development is an essential part of an online business. With the fast-growing rate of smartphones and tablets in the market, is gaining popularity with web developers. Android App Development Apps can provide a variety of services including shopping, entertainment, and communication. Mobile apps are transforming the business world, making it easier and more convenient than ever before to shop, bank, book travel, and connect with your favorite brands. Mobile apps are no longer just for entertainment on the go. They have become a necessity in our daily lives, facilitating everything from tracking calorie intake to taking photos. With so many apps out there, only a few can truly be deemed “mobile-friendly” and truly make use of the latest smartphone features. This is why mobile application development is an extremely important skill that both businesses and individuals should have – without it, you could be missing out on an incredible opportunity! Types Of Mobile Apps Mobile apps are like desktop software but are specifically designed for mobile devices. Established operating systems such as iOS, and Android have done a brilliant job of standardizing the types of development available to programmers. However, there is still a wide range of possibilities for mobile app developers. There are some types of mobile app development: Native Apps HTML5 Apps Hybrid Apps Web Apps Native Applications Native apps are added to the app stores directly by developers. The user experience is as simple as one click, and it’s easy for users to install the app. Smartphones and tablets both have app stores that make finding, downloading, and installing these applications easy for consumers. It’s important to note that native apps aren’t cross-platform: They can only be used on Android devices if they are developed in Java, and on iOS devices, if they are developed in Objective-C.  A native app is an application that was developed specifically for a certain operating system in most cases, iOS or Android. This means that developers write the code based on certain specifications and guidelines from that particular platform. HTML5 Applications The best part is that with the Appery.io app development platform, your app will be compatible with many different operating systems and require minimal changes to ensure full functionality on each platform. It's easy to focus on building your app, not maintaining it. HTML5 apps have great cross-platform capability and can be viewed by any device (smartphone, tablet, or desktop) that has a web browser, without requiring an app store download. Web apps are developed using  HTML, CSS, and JavaScript. HTML5 is the most common standard for web apps these days, which allows for richer app-like experiences. Web apps can still send desktop notifications and trigger interactions through email and other avenues. These types of mobile apps tend to be more flexible since they can be accessed from any computer or mobile device with a web browser. Hybrid Applications A hybrid app allows you to take advantage of native features and functionality that are already present on each mobile operating system. Coding is typically done in HTML5, CSS3 and JavaScript. By creating a customized user interface, you can differentiate your application from others with a similar purpose. For example, if you're planning on launching an entertainment-focused app, consider utilizing the Facebook and Twitter buttons already available within iOS apps or add share buttons allowing users to immediately share content on other social media networks. Web Applications There are two types of mobile apps: native and web apps. Native apps integrate more closely with your device, while web apps behave similarly to native apps but are accessed via a web browser on your mobile device. Web apps are simply websites that can be accessed on the go. They’re often stand-alone websites that you visit in your device’s web browser. The difference between a web app and a native app is that you don’t have to download and install an app to your device; it loads like any other webpage. When you come across the option to “install” a web app, it simply saves the website name or URL on your device for quick access later. Progressive web apps (PWAs) are a new type of website that aims to deliver a user experience that is better than the mobile website or app. Web apps are just like websites but on your devices. They're built using HTML5, CSS, and javascript to create the user interface and you can use them anywhere. App Development Process We have outlined the six main steps in the app development process to help you bring your idea to life quickly and efficiently. It's important to remember that you can always change these steps or skip them altogether if you are working with a team of developers who have previous experience developing apps. Starting with an idea and moving it to reality is the first step in developing a successful app. To begin, you must ask yourself what problem your app will solve and who the target audience will be. Once you know these things, you'll need to determine which features are important for your app's success. Lastly, you should investigate if competitors have similar apps. Idea: In the design step, you’ll create a mock-up of the user interface (UI) to navigate the user through your app and make it easy to follow. Design: This is the first of the three stages in app development. It’s during this phase that you’ll start to build your app – you’ll write the code and develop your idea. Development: Testing is a crucial step. It ensures that your app is up to industry standards by testing its quality, any malfunctions, and what you can improve before it’s submitted to the app store. Testing: Once your app is ready to go, publishing it on marketplaces like the Apple App Store and Google Play allows you to make money from your hard work. Launch: The app development process begins with a marketing strategy, where you create a plan to get users to download your app and give you feedback on how to improve. Marketing: Benefits of Mobile Apps Development for Businesses Accessibility from Different Platforms The best thing about for businesses is that it’s accessible on various platforms. Whether you want to reach Apple or Android users, or people who use Blackberry mobiles, there are plenty of options available to make money by developing a mobile app. mobile app development Reach Global Audience Mobile apps provide businesses with the opportunity to reach a global audience by making their content easily accessible on mobile devices. Apps work beautifully for B2C and B2B businesses that want to showcase their products and services and use them as engagement tools. Increase Accessibility Mobile app development is essential for business incorporation. The primary benefit of mobile apps is to improve business accessibility. Getting track of your customers and their needs, can help you develop a good customer base. Promotes Brand Recognition Mobile app development can help promote your brand as soon as it is launched. Bringing your business to mobile customers, who spend more time with their phones than any other device, will enhance your overall brand recognition. Encourage Brand Loyalty Mobile applications help in notifying the administrator about the users’ interest in specific offers and products. User ID and Password to your account. In addition, it also helps in managing committees to plan further for users and personalized brand loyalty programs. Increase Sell-Through Customers are spending more time on mobile apps instead of mobile sites. Mobile application development is the backbone of any business today. It helps in attracting new customers and attaining success.

Why Mobile Application Development Is Important In Current Scenario?

Ah, crypto. The playground of the bulls and bears. Which side do you fall on? Since the start of 2022, bears have dominated the conversation. They promise bitcoin’s price will drop to $30,000 or lower. 2018 all over again. Bear flag target is $21,000. Capitulation imminent. At least two more years before we go back to a new all-time high. What about the bulls? I can’t hear them over all the crickets chirping. The bullish fractals have disappeared. Bear market, recession, US stocks, sovereign debt, there's no way price goes up for a long, long time. Somebody has to fill the void. Why not me? Do you want to know my most bullish scenario for bitcoin (and by extension, the whole crypto market)? Up a little, down a little, forever. Something like this: No FOMO, supercycle, or moonshots. Just aggressive, consistent growth that outpaces every other investment that people like you and I can access. Dream or nightmare? Yes, that’s my dream. You get perfect conditions for growth. Plenty of opportunities for people to enter and exit, enough upward price movement to give new buyers confidence in the market, not enough “zoom!” to make people get too greedy, enough boredom that scammers go back to other things, and enough excitement to motivate investors to learn about what they’re buying. Most importantly, enough liquidity and casual interest that builders and innovators have an audience for their creations. For most people, that’s a nightmare. Six months before the price doubles? Multiple drops of +20% along the way? Nobody wants to wait six months for their Lambo. How long could that trend continue before traders decide it’s no longer a bear flag? And anyway, how do you get a good entry if the price doesn’t break out of the trading pattern? Easy rider While that outcome doesn’t bring a lot of volatility, it’s a much easier ride than massive bull and bear markets. Easier on the mind, body, and portfolio. Would you be upset if the price goes to $80,000 and the value of your investment doubles in one year? And then another 2x next year? And another 2x the year after? *only* *only* What about 50% each year? Would you be sad about a 600% return on investment over five years? That’s probably more sustainable than whatever your data model predicts. While that’d be nice, I’m not betting on it. This market has always moved in extremes. Big moves up and big moves down. Do you see any reason that should change now? Mark Helfman publishes the newsletter. He is also the author of three books and a top bitcoin writer on and . Learn more about him in his . Crypto is Easy Medium Hacker Noon bio Originally published in Cryptowriter .

My Most Bullish Scenario for Bitcoin

As a front-end engineer, Node is an essential development tool for java. Currently, most projects I am in charge of are based on Node 12. But currently, I am designated for a new project that requires building its own blog site based on Javascript; I chose gatsby-starter-blog as the frame to develop, which requires Node 14. The problem is that this version will conflict with other projects that I manage. I started brainstorming and searching for solutions. At this time, I thought of , a cloud collaborative development platform that I used before. It provides some high-performance and lightweight tools. I just thought of their official updates on Facebook, which notifies me that the product Pylon has a new tool called , which seems to have features that could satisfy my demands. TeamCode Pylon CLI I went to its official website and started to check the documents of It is a client tool that controls the Pylon development environment locally. You can build a development environment locally through the Git repository address and manage all locally created development environments. Pylon CLI: Then I started to download and install the CLI according to the guidance and created the latest version of . Node 16 Download ; Node 16 And created gatsby-starter-blog successfully. Open the gatsby-starter-blog with VSCode. In this way, I ran and started gatsby-starter-blog on your computer without worrying about environmental conflicts or coordination issues. For most developers, the local computing power is sufficient, and there is no additional cost to set up a cloud-based development environment. However, there will be some adaptation and compatibility problems in the local development environment. The most obvious issue is that there is no environment isolation, and the versions of dependencies required by different projects are inconsistent, resulting in the failure to run projects. Pylon CLI is designed to solve these problems. It can build and manage multiple local development environments quickly. Different sub-development environments are isolated from each other, meeting the requirements of the operating environment for different projects; that's the reason I chose it.

Application Scenarios of Pylon CLI — A Client Tool that Controls the Dev Environment Locally

The recent days in the cryptocurrency market have inspired great optimism. In 24 hours, the price of bitcoin rose by more than $3,000 and set a new all-time record at around $23,700. This happened even faster than many analysts expected. Now the price of bitcoin has returned to the $23,000 level, and its movement has temporarily stopped. Now it has become much more difficult to predict further changes in the price of the first cryptocurrency than before. The fact is that for the past three years, analysts have relied on existing charts and levels of resistance and support, as well as on proven scenarios. Now when bitcoin is more expensive than ever, analyzing it has become more risky. However, we still have some technical analysis tools, and today we will talk about the most likely scenarios. Now we are witnessing a breakout of the “ascending triangle” pattern, which has already been repeatedly observed on the bitcoin chart. This movement is a very good signal for the market and for the bulls in particular, but big capital does not like many open long positions. In such situations, there is often a "short squeeze" on stop losses and margin calls. “ ”,— believes Alex Lebed, Head of Development at , a blockchain R&D lab launched by , a publicly-traded company (NASDAQ: ZKIN).The company recently announced the launch of a decentralized exchange for trading stablecoins. We can expect several waves of growth, as a result of which the price will reach $25,000 and then collapse to $20,000. This will be a good opportunity to buy an asset, which will be used by those who did not have time to do this before the explosive growth began xSigma DeFi ZK International We are less likely to see the beginning of a correction in the coming days. Then there will be no growth waves mentioned above. Similar scenario happened between 13 and 16 November this year. However, bitcoin looks very good in the long run. First, a lot of capital is invested in the market, and there are no reversal patterns on the chart. Secondly, during price drawdowns, bitcoin is bought very quickly, and in general, price movements downward are similar to speculative manipulations. So, in general, everything looks very optimistic, and now there are no hints of a fall in bitcoin, as it was at the end of 2017.

Market Scenarios: Bitcoin Could Reach $25,000 Soon

Most businesses these days use systems to gain improved performance and security. Redundant Array of Independent Disks (RAID) systems are a configuration of multiple disk drives that can improve storage and computing capabilities. This system comprises multiple hard disks that are connected to a single logical unit to provide more functions. As one single operating system, RAID architecture (RAID level 0, 1, 5, 6, etc.) distributes data over all disks. RAID This system can be configured in many different ways to serve different purposes. Typically, there are seven different RAID levels- RAID 0 to RAID 6. For instance RAID 0 is designed to increase computing speed. This RAID configuration splits the data evenly across multiple disks. However, in this system, if one disk fails then the entire system will fail, leading to data loss. The different RAID-levels have certain protection mechanisms but the technology doesn’t guarantee complete data security. RAID arrays offer stability and reliability, but similar to all mechanical devices, they can and do break down. Due to many reasons, data stored on RAID arrays may become inaccessible, or worse, permanently deleted. This situation becomes more devastating if your data hasn't been properly backed up. So, to avoid data loss, you need to know the most common causes of RAID failures. Understanding the common causes of failure will help in averting data loss due to RAID damage. So, let’s check out some causes of RAID failure and find out what you can do to maximize the chance of recovering your data. Most Common Causes of RAID Failure Most RAID arrays are fault-tolerant but all are still vulnerable to hardware and software failure. The causes of RAID failure can be categorized as- Hardware Failures, Software Failures, Application Failures, and Failures from Human Error. The causes of hardware damage include issues such as hard disk component failure, RAID controller failure, power supply failure, and overheating. Logical or software problems like configuration errors, file corruption, and malware attacks could also lead to data loss. RAID failure due to application errors involves the corruption of the applications and programs installed in the RAID server. The fourth and most common type of failure is human error which includes accidental file deletion and mistakenly reformatting the partitions, drives, or the entire arrays. So, your RAID system may fail due to the following reasons: RAID controller failure due to power surges or other problems Missing RAID Partitions Fault in RAID Volume Rebuild Multiple Disk Failure Server Crash Accidental deletion/reformatting Fire or water damage Virus corruption How to Deal with a RAID Failure Here are some of the dos and don’ts of dealing with a failed RAID system to avoid permanent data loss. 1. Always Keep Backups Offsite No matter what type of storage device you’re using, maintaining a current backup of your data is crucial. Even if RAID systems are known for their reliability, your data can disappear due to several reasons. In an event of RAID failure, up-to-date offsite backup on external hard drives, cloud, and tapes are good solutions. 2. Stop Using RAID System If you notice data loss or any other problem with your RAID, stop using the system immediately. This is the most important step in preventing further damage because continuous system operation will exacerbate the issues and overwrite the data. Installing recovery software is also not recommended because it can overwrite the existing files. 3. Avoid DIY Recovery Often data loss occurs due to multiple drives failure. If you experience a failure on two drives, don’t try to replace one of the failed drives and run a rebuild. A single mistake in rebuilding the RAID after replacing the failed disk with a new one could result in additional damages. Also, unless you’re experienced in DIY recovery, don’t think about replacing a RAID control or circuit boards. Replacing the circuit can be risky because each hard drive has its unique circuit boards. If you open the drives in the array, you’re exposing these drives to an unclean environment that will cause further damage. So, to avoid permanent data loss, it is best to take recourse to expert RAID data recovery service. If you encounter any of the above-mentioned issues, you need to take a few steps to maximize the chances of raid data recovery .

Common RAID Failure Scenarios And How to Deal with Them

Photo Credit: Flickr via The people and government of China should be mostly concerned about Facebook’s intended launch of the Libra. The story didn’t just end there because Facebook said that in addition to Libra, the project will also issue a “ .” Christoph Scholz Compfight cc Libra investment token China’s of the world’s population makes it the largest single most populated country in the world as of August 2019. Facebook recorded by the second quarter of 2019, effectively makes it the biggest social platform globally. 18.41 percent 2.41 billion monthly active users Therefore, any time any of these two sneezes, the world should take note of it. Facebook, however, was able to achieve this mammoth penetration in the world despite being banned from operating in the country by the government of the People’s Republic of China. If you go through the whitepaper on Libra, you will discover that the focus of Libra is to create a currency that empowers billions of people, allowing them to engage in friction-less financial transactions in a simple, secure, and cost-effective manner. The catch here is billions of people and the question, you will want to ask is: Did Facebook take into consideration the Chinese people before coming up with this idea? Why the question seems important is because both Facebook and cryptocurrency are banned in China. China’s government has been trying from all fronts to quash the cryptocurrency market in recent years in order “to prevent financial risks,” according to the . South China Morning Post But all the measures put in place have at stopping all cryptocurrency trade. You must, however, note that all has not been rosy for the yet to launched Libra. often failed Hits have been coming from regulators in . Taking into consideration the recent bipartisan scrutiny from U.S. lawmakers for announcing Libra and the argument by some people that it could be , you’ll realize that Libra still has a long way to go. Washington and Europe Facebook’s downfall Even President Donald Trump added to Libra’s discomfort by saying that cryptocurrencies are “not money” and “based on thin air.” All these aside, Libra is still causing upheavals in China. There is a report that China’s is making serious attempts to evolve a digital currency that will redress whatever problems Facebook’s Libra may possibly pose to China’s financial system, according to the report of July 8. central bank South China Morning Post’s Wang Xin, director of the People’s Bank of (PBoC) research bureau, is of the opinion that “if [Libra] is widely used for payments, cross-border payments, in particular, would it not be able to function as money and accordingly have a large influence on monetary policy, financial stability, and the international monetary system?” China Wang, therefore, said that PBoC decided to create its own digital currency specifically because of the unclear role of the dollar once Libra is issued: “If the digital currency is closely associated with the U.S. dollar, it could create a scenario under which sovereign currencies would coexist with U.S. dollar-centric digital currencies. But there would be in essence one boss, that is the U.S. dollar and the United States. If so, it would bring a series of economic, financial, and even international political consequences.” United States What we see going on in China recently is that PBoC has purportedly been given the nod from the chief Chinese administrative authority, the State Council, to begin work with other market players and bodies to fashion out a central bank digital currency. The academics sector was not left out. They are said to have also launched an intensive initiative on digital finance which includes resources from Peking University, Renmin University, Zhejiang University, and Shanghai Jiao Tong University. , deputy director of the PBOC’s payments department, also lent a voice to the debate. Changchun, reportedly said that Libra “must be put under the oversight of monetary authorities.” Mu Changchun He was of the view that, as a currency that can be freely exchanged into another currency for any purpose, without regulatory restrictions, Libra “will not be sustainable without the support and supervision of central banks,” emphasizing though that, “In the longer term, the yuan will be damaged by Libra if it’s not convertible.” Former People’s Bank of China governor , who a decade ago gave an insight into a global currency based upon the International Monetary Fund’s Special Drawing Rights, was of the opinion that Libra is a potent sign that there could be a new “strong international currency”, which could be exchangeable with existing government-backed currencies and be global in nature Zhou Xiaochuan Zhou observed that the overriding effect of such a currency is that it would challenge cross-border payments and weaken the role of sovereign currencies that do not have a stable value, just as many countries around the world have accepted the US dollar as a means of payment. What China is apprehensive of is that Libra is coming as a financial revolution that will eventually and greatly impact the country and all other traditional cross-border businesses as well as payment systems. Despite the fact that the situation has not yet become a serious source of  concern to China, Zhou, however, noted that Beijing must “make good preparations and make the Chinese yuan a stronger currency.” Going along with Zhou’s observation, you can safely say that inasmuch as the Libra is meant to take care of cross-border payments, it will go a long way to ease the problems developing countries encounter with their payment structures. It’s remarkable to note that in the early days of digital currencies, the PBoC did not outlaw assets such as bitcoin, but rampant speculation and wild price swings led China to impose an outright ban on trading and exchanging as well as any form of initial offerings of cryptocurrencies. The most important thing, however, is that governments must gauge the mood of the people before implementing laws and imposing restrictions.

Facebook's Libra And China: The Real Scenario

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