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biologit

This paper is available on arxiv under CC 4.0 license. Authors: (1) Vianney Brouard, ENS de Lyon, UMPA, CNRS UMR 5669, 46 All´ee d’Italie, 69364 Lyon Cedex 07, France; E-mail: vianney.brouard@ens-lyon.f. Table of Links Abstract & Introduction and presentation of the model Main results and biological interpretation First-order asymptotics of the mutant sub-populations for an infinite mono-directional grap First-order asymptotics of the mutant sub-populations for a general finite trait space (Theorem 2.1) Convergence for the stochastic exponents (Theorem 2.2) Acknowledgements & References 2 Main results and biological interpretation In Subsection 2.1 the first-order asymptotics of the size of all the mutant sub-populations in the timescales (3) and (4) are given under the non-increasing growth rate condition (5). In Subsection 2.2 the asymptotic result on the stochastic exponent of all the mutant sub-populations are given without any assumption on the growth rate function λ. In each subsection, biological interpretations of the results are made. 2.1 First-order asymptotics of the mutant sub-population sizes under nonincreasing growth rate condition In this subsection assume that (V, E, L) satisfies the non-increasing growth rate graph condition of Equation (5). Heuristics: The next definitions, notations and results are first motivated using some heuristics for the simplest graph that one can think of, i.e. a wild-type and a mutant population where only mutations from wild-type to mutant cells are considered. More precisely (V, E, L) = ({0, 1}, {(0, 1)}, {ℓ(0, 1)}) as in Figure 1. Then two scenari are possible: Notations: Now the natural definitions issued from these heuristics are formally made before giving the results. (Deleterious and neutral vertices) Definition 2.1. A vertex v ∈ V satisfying λ(v) = λ(0), respectively λ(v) < λ(0), is called a neutral, respectively deleterious, vertex. Remark 2.1. In the previous definition the neutral or deleterious denomination of a mutation originates from the comparison of its inner growth rate to the growth rate of the wild-type population. But one could imagine a mutation from a vertex v to a vertex u satisfying λ(v) < λ(u) ≤ λ(0). This mutation should theoretically be called selective but in the previous definition it is actually called neutral or deleterious (depending on the value of λ(u) compared to λ(0)). This nomenclature emerges from the fact that under Assumption (5) any mutant population grows exponentially fast at rate λ(0), as seen in the previous heuristics. Hence it legitimates the previous definition. (Path on the graph) Definition 2.2. γ = (v(0), · · · , v(k)) is said to be the path on the graph (V, E) linking v(0) to v(k) by using the edges (v(i), v(i + 1)) if for all 0 ≤ i ≤ k, v(i) ∈ V and ∀0 ≤ i ≤ k − 1,(v(i), v(i + 1)) ∈ E. For a path γ = (v(0), v(1), · · · v(k)) on (V, E, L) define Definition 2.3. (Admissible paths) For all v ∈ V denote by P(v) the set of all paths γ on (V, E) linking the vertex 0 to the vertex v. Define also t(v) := min{t(γ), ∀γ ∈ P(v)}, θ(v) := max {θ(γ), ∀γ ∈ P(v), t(γ) = t(v)} , A(v) := {γ ∈ P(v) : t(γ) = t(v) and θ(γ) = θ(v)}. . Remark 2.3 In the previous definition A(v) is called the set of admissible paths because as seen in the heuristics, only paths belonging to A(v) are contributing to the growth dynamics of the mutant cells of trait v. This is made formal in Theorem 2.1. Definition 2.4. (Weight of a vertex) The weight of a vertex v ∈ V \{0} at time t is defined as Results: Now the more refined result under Assumption (5) can formally be stated. such that for all v ∈ V \{0} we obtain the following results for the different time-scales: Using the mathematical definition of the model given in Section 4, see (78) and (79), the above convergences are obtained in probability in the adequate L∞-spaces. For any other mathematical description, the convergences are at least in distribution in D ([0, T] × [−M, M]) for Equation (11) and in D ([T1, T2] × [−M, M]) for Equations (12), (13) and (14). The proof of Theorem 2.1 is based on a martingale approach using Doob’s and Maximal Inequalities. The first step involves the control of the growth of the lineage of wild-type cells issued from the initial cell both for the deterministic and random time-scales (4) and (3) (Lemma 3.1 and 3.2). Then for any vertex v ∈ V \{0}, potentially many mutational paths on the graph (V, E) can start from 0 and lead to v. The contribution on the first-order asymptotics of the mutant sub-population of trait v for any of these paths needs to be understood. The proof is then done in 2 steps. The first one consists in considering an infinite mono-directional graph under Assumption (5) and in obtaining the result for this particular graph, see Section 3. Doing the first step for an infinite graph allows in particular to deal with the cycles (backward mutations for instance) for a general finite graph. The second step consists in discriminating among all the paths from the initial vertex 0 to v the ones that do not contribute to the first-order asymptotics of the mutant sub-population of trait v, see Section 4. (ii) The random variable W is explicitly defined as the almost sure limit of the natural positive martingale associated to a specific birth and death branching process with rates α(0) and β(0), see (81). The martingale associated to the lineage of wild-type cells issued from the initial cell is shown to behave as the one associated to the latter birth and death branching process (Lemma 4.1). Thus W quantifies the randomness of this lineage over the long time. Due to the power law mutation rates regime mutations arise after a long time such that the stochasticity of this lineage is already given by W. Notice that under Assumption (5) the randomness in the first-order asymptotics of any mutant sub-population is summed up in W. Meaning that the stochasticity of these sub-populations are driven more by the stochasticity in the growth of the wild-type sub-population than by both the randomness in the mutational process and the randomness of any lineages of mutant cells. (iii) It seems more than natural not to obtain such a result when considering selective mutation (λ(v) > λ(0)). Indeed, a selective mutation would mean that any time advantage is an advantage into growth. Thus the stochasticity of the mutational process can not be ignored as well as the one of the lineages of mutant cells. Hence hoping to control the stochasticity of the mutant population controlling only the randomness of the wild-type population and not the randomness of the mutational process as well as the one of the lineages of the mutant cells is vain. Meaning that using a martingale approach to get the first-order asymptotics can not be successful for a selective mutation. Nevertheless looking at the stochastic exponent (6) the martingale approach allows to get convergence results given in Theorem 2.2. (iv) In view of Theorem 2.1, the mathematical definition of neutral mutation λ(v) = λ(0) is well understood instead of the more restrictive but biologically more meaningful condition α(v) = α(0) and β(v) = β(0). Indeed, taking the growth rate λ(v) equal to λ(0) when changing birth and death rates α(v) and β(v) modify the distribution of any lineage of mutant cells. Consequently one could naturally believe that it should impact the stochasticity of the size order of the mutant population. This is not the case, the randomness on the first asymptotic order is fully summed up by W. Hence it is fully consistent with getting for the neutral assumption only a condition on the growth rate function instead of on the birth and death rates. (v) Considering the time-scale t (n) t notice that the result slightly differs depending on whether the vertex is neutral or deleterious. Indeed, when looking at the asymptotic behavior for a deleterious vertex v our result is true strictly after time t(v), whereas in the case of a neutral vertex all the trajectory from the initial time can be dealt with. Mathematically, this difference originates from the supplementary multiplicative log(n) factor in the first asymptotic order when considering a neutral mutation. It allows to control the quadratic variation at time t(v) for the martingale associated to the mutant population. Then exactly three different regimes are obtained, see (10) and (11) : 2.2 Result for a general finite oriented labeled graph This subsection is free from the non-increasing growth rate condition of Equation (5). Without this condition, the martingale approach fails in order to get the first-order asymptotics off all the mutant sub-populations. But, the stochastic exponent, as defined in (6), off all the mutant sub-populations can be uniformly tracked over time. In particular, we show that the limits are positive deterministic non-decreasing piecewise linear continuous functions. Such limits are defined via a recursive algorithm tracking their slopes over time. More precisely, we show that the slopes can only increase and take values on the set of the growth rates. Two different kinds of updates can be made. The first one is when a non-already born trait becomes alive and take the slope which is the maximum between its inner growth rate and the slope of the sub-population that is giving birth to it. The second one is when an already born trait changes it slope to increase it because another born trait among its upcoming neighbors with a higher slope has reached the typical size allowing it to now drive the trait in question, and consequently giving it its slope. This heuristic is made formal in the following theorem. The complexity of such an algorithm comes from the trait structure which is a general finite trait space. On a mono-directional one, this algorithm would be much easier. In particular, at the same time, the two kinds of event can happen. Theorem 2.2. For all v ∈ V define 0 < T1 < T2, Then we have for all Initialisation: Set A0 = {0}, U0 = V \{0} and for all v ∈ V For any other mathematical description as the one given in Section 4, see (78) and (79), the convergences are at least in distribution in D ([T1, T2]). The proof of this theorem is given in Section 5. It is heavily based on the proofs of [13], where we exploit the stochastic construction of such a model, given in the beginning of Section 4, to adapt the proofs of the previous article to the situation of the present work. For that reason, we introduce lemmas and explain in the proofs how the adaptations from the proofs of [13] are made, without reproving them. This theorem is the counterpart of the study made in [8] in the case of branching sub-populations, instead of having competition between sub-populations. One difference is that the power law mutation rates regime is a bit more general in the present work, allowing each mutation probabilities to scale differently. But, the result in [8] can be adapted with this more general regime, as mentioned by the authors.

Main Results and Biological Interpretation

God The Invisible King by H. G. Wells, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . MODERN IDEAS OF SIN AND DAMNATION MODERN IDEAS OF SIN AND DAMNATION 1. THE BIOLOGICAL EQUIVALENT OF SIN If the reader who is unfamiliar with scientific things will obtain and read Metchnikoff’s “Nature of Man,” he will find there an interesting summary of the biological facts that bear upon and destroy the delusion that there is such a thing as individual perfection, that there is even ideal perfection for humanity. With an abundance of convincing instances Professor Metchnikoff demonstrates that life is a system of “disharmonies,” capable of no perfect way, that there is no “perfect” dieting, no “perfect” sexual life, no “perfect” happiness, no “perfect” conduct. He releases one from the arbitrary but all too easy assumption that there is even an ideal “perfection” in organic life. He sweeps out of the mind with all the confidence and conviction of a physiological specialist, any idea that there is a perfect man or a conceivable perfect man. It is in the nature of every man to fall short at every point from perfection. From the biological point of view we are as individuals a series of involuntary “tries” on the part of an imperfect species towards an unknown end. Our spiritual nature follows our bodily as a glove follows a hand. We are disharmonious beings and salvation no more makes an end to the defects of our souls than it makes an end to the decay of our teeth or to those vestigial structures of our body that endanger our physical welfare. Salvation leaves us still disharmonious, and adds not an inch to our spiritual and moral stature. 2. WHAT IS DAMNATION? Let us now take up the question of what is Sin? and what we mean by the term “damnation,” in the light of this view of human reality. Most of the great world religions are as clear as Professor Metchnikoff that life in the world is a tangle of disharmonies, and in most cases they supply a more or less myth-like explanation, they declare that evil is one side of the conflict between Ahriman and Ormazd, or that it is the punishment of an act of disobedience, of the fall of man and world alike from a state of harmony. Their case, like his, is that THIS world is damned. We do not find the belief that superposed upon the miseries of this world there are the still bitterer miseries of punishments after death, so nearly universal. The endless punishments of hell appear to be an exploit of theory; they have a superadded appearance even in the Christian system; the same common tendency to superlatives and absolutes that makes men ashamed to admit that God is finite, makes them seek to enhance the merits of their Saviour by the device of everlasting fire. Conquest over the sorrow of life and the fear of death do not seem to them sufficient for Christ’s glory. Now the turning round of the modern mind from a conception of the universe as something derived deductively from the past to a conception of it as something gathering itself adventurously towards the future, involves a release from the supposed necessity to tell a story and explain why. Instead comes the inquiry, “To what end?” We can say without mental discomfort, these disharmonies are here, this damnation is here—inexplicably. We can, without any distressful inquiry into ultimate origins, bring our minds to the conception of a spontaneous and developing God arising out of those stresses in our hearts and in the universe, and arising to overcome them. Salvation for the individual is escape from the individual distress at disharmony and the individual defeat by death, into the Kingdom of God. And damnation can be nothing more and nothing less than the failure or inability or disinclination to make that escape. Something of that idea of damnation as a lack of the will for salvation has crept at a number of points into contemporary religious thought. It was the fine fancy of Swedenborg that the damned go to their own hells of their own accord. It underlies a queer poem, “Simpson,” by that interesting essayist upon modern Christianity, Mr. Clutton Brock, which I have recently read. Simpson dies and goes to hell—it is rather like the Cromwell Road—and approves of it very highly, and then and then only is he completely damned. Not to realise that one can be damned is certainly to be damned; such is Mr. Brock’s idea. It is his definition of damnation. Satisfaction with existing things is damnation. It is surrender to limitation; it is acquiescence in “disharmony”; it is making peace with that enemy against whom God fights for ever. (But whether there are indeed Simpsons who acquiesce always and for ever remains for me, as I have already confessed in the previous chapter, a quite open question. My Arminian temperament turns me from the Calvinistic conclusion of Mr. Brock’s satire.) 3. SIN IS NOT DAMNATION Now the question of sin will hardly concern those damned and lost by nature, if such there be. Sin is not the same thing as damnation, as we have just defined damnation. Damnation is a state, but sin is an incident. One is an essential and the other an incidental separation from God. It is possible to sin without being damned; and to be damned is to be in a state when sin scarcely matters, like ink upon a blackamoor. You cannot have questions of more or less among absolute things. It is the amazing and distressful discovery of every believer so soon as the first exaltation of belief is past, that one does not remain always in touch with God. At first it seems incredible that one should ever have any motive again that is not also God’s motive. Then one finds oneself caught unawares by a base impulse. We discover that discontinuousness of our apparently homogeneous selves, the unincorporated and warring elements that seemed at first altogether absent from the synthesis of conversion. We are tripped up by forgetfulness, by distraction, by old habits, by tricks of appearance. There come dull patches of existence; those mysterious obliterations of one’s finer sense that are due at times to the little minor poisons one eats or drinks, to phases of fatigue, ill-health and bodily disorder, or one is betrayed by some unanticipated storm of emotion, brewed deep in the animal being and released by any trifling accident, such as personal jealousy or lust, or one is relaxed by contentment into vanity. All these rebel forces of our ill-coordinated selves, all these “disharmonies,” of the inner being, snatch us away from our devotion to God’s service, carry us off to follies, offences, unkindness, waste, and leave us compromised, involved, and regretful, perplexed by a hundred difficulties we have put in our own way back to God. This is the personal problem of Sin. Here prayer avails; here God can help us. From God comes the strength to repent and make such reparation as we can, to begin the battle again further back and lower down. From God comes the power to anticipate the struggle with one’s rebel self, and to resist and prevail over it. 4. THE SINS OF THE INSANE An extreme case is very serviceable in such a discussion as this. It happens that the author carries on a correspondence with several lunatics in asylums. There is a considerable freedom of notepaper in these institutions; the outgoing letters are no doubt censored or selected in some way, but a proportion at any rate are allowed to go out to their addresses. As a journalist who signs his articles and as the author of various books of fiction, as a frequent NAME, that is, to any one much forced back upon reading, the writer is particularly accessible to this type of correspondent. The letters come, some manifesting a hopeless disorder that permits of no reply, but some being the expression of minds overlaid not at all offensively by a web of fantasy, and some (and these are the more touching ones and the ones that most concern us now) as sanely conceived and expressed as any letters could be. They are written by people living lives very like the lives of us who are called “sane,” except that they lift to a higher excitement and fall to a lower depression, and that these extremer phases of mania or melancholia slip the leash of mental consistency altogether and take abnormal forms. They tap deep founts of impulse, such as we of the safer ways of mediocrity do but glimpse under the influence of drugs, or in dreams and rare moments of controllable extravagance. Then the insane become “glorious,” or they become murderous, or they become suicidal. All these letter-writers in confinement have convinced their fellow-creatures by some extravagance that they are a danger to themselves or others. The letters that come from such types written during their sane intervals, are entirely sane. Some, who are probably unaware—I think they should know—of the offences or possibilities that justify their incarceration, write with a certain resentment at their position; others are entirely acquiescent, but one or two complain of the neglect of friends and relations. But all are as manifestly capable of religion and of the religious life as any other intelligent persons during the lucid interludes that make up nine-tenths perhaps of their lives. . . . Suppose now one of these cases, and suppose that the infirmity takes the form of some cruel, disgusting, or destructive disposition that may become at times overwhelming, and you have our universal trouble with sinful tendency, as it were magnified for examination. It is clear that the mania which defines his position must be the primary if not the cardinal business in the life of a lunatic, but his problem with that is different not in kind but merely in degree from the problem of lusts, vanities, and weaknesses in what we call normal lives. It is an unconquered tract, a great rebel province in his being, which refuses to serve God and tries to prevent him serving God, and succeeds at times in wresting his capital out of his control. But his relationship to that is the same relationship as ours to the backward and insubordinate parishes, criminal slums, and disorderly houses in our own private texture. It is clear that the believer who is a lunatic is, as it were, only the better part of himself. He serves God with this unconquered disposition in him, like a man who, whatever else he is and does, is obliged to be the keeper of an untrustworthy and wicked animal. His beast gets loose. His only resort is to warn those about him when he feels that jangling or excitement of the nerves which precedes its escapes, to limit its range, to place weapons beyond its reach. And there are plenty of human beings very much in his case, whose beasts have never got loose or have got caught back before their essential insanity was apparent. And there are those uncertifiable lunatics we call men and women of “impulse” and “strong passions.” If perhaps they have more self-control than the really mad, yet it happens oftener with them that the whole intelligent being falls under the dominion of evil. The passion scarcely less than the obsession may darken the whole moral sky. Repentance and atonement; nothing less will avail them after the storm has passed, and the sedulous preparation of defences and palliatives against the return of the storm. This discussion of the lunatic’s case gives us indeed, usefully coarse and large, the lines for the treatment of every human weakness by the servants of God. A “weakness,” just like the lunatic’s mania, becomes a particular charge under God, a special duty for the person it affects. He has to minimise it, to isolate it, to keep it out of mischief. If he can he must adopt preventive measures. . . . These passions and weaknesses that get control of us hamper our usefulness to God, they are an incessant anxiety and distress to us, they wound our self-respect and make us incomprehensible to many who would trust us, they discredit the faith we profess. If they break through and break through again it is natural and proper that men and women should cease to believe in our faith, cease to work with us or to meet us frankly. . . . Our sins do everything evil to us and through us except separate us from God. Yet let there be no mistake about one thing. Here prayer is a power. Here God can indeed work miracles. A man with the light of God in his heart can defeat vicious habits, rise again combative and undaunted after a hundred falls, escape from the grip of lusts and revenges, make head against despair, thrust back the very onset of madness. He is still the same man he was before he came to God, still with his libidinous, vindictive, boastful, or indolent vein; but now his will to prevail over those qualities can refer to an exterior standard and an external interest, he can draw upon a strength, almost boundless, beyond his own. 5. BELIEVE, AND YOU ARE SAVED But be a sin great or small, it cannot damn a man once he has found God. You may kill and hang for it, you may rob or rape; the moment you truly repent and set yourself to such atonement and reparation as is possible there remains no barrier between you and God. Directly you cease to hide or deny or escape, and turn manfully towards the consequences and the setting of things right, you take hold again of the hand of God. Though you sin seventy times seven times, God will still forgive the poor rest of you. Nothing but utter blindness of the spirit can shut a man off from God. There is nothing one can suffer, no situation so unfortunate, that it can shut off one who has the thought of God, from God. If you but lift up your head for a moment out of a stormy chaos of madness and cry to him, God is there, God will not fail you. A convicted criminal, frankly penitent, and neither obdurate nor abject, whatever the evil of his yesterdays, may still die well and bravely on the gallows to the glory of God. He may step straight from that death into the immortal being of God. This persuasion is the very essence of the religion of the true God. There is no sin, no state that, being regretted and repented of, can stand between God and man. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. H. G. Wells (2016). God The Invisible King. Urbana, Illinois: Project Gutenberg. Retrieved October 2022, from https://www.gutenberg.org/files/1046/1046-h/1046-h.htm This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org, located at https://www.gutenberg.org/policy/license.html.

What is the Biological Equivalent of Sin?

A time is coming when your thoughts will be the only activity you need to get things done. Have you ever been so caught up with work, you don't want to move a muscle? You are not willing to use your voice because you feel the ideas will escape once you do. So, what do you do when you suddenly wish your favorite songs were playing at that moment, but you feel too lazy to pick up your phone or call Siri's attention to turn on your playlist? If only your thoughts could make the orders, right? Here, you are thinking, "Siri, play me 'Easy on Me' by Adele" and seconds later the sound fills your workspace. Then you think, "Nope, too low. Siri, increase the volume to 10", and the volume gets adjusted to suit what’s on your mind perfectly. Your brain alone processes commands without any effort from your mouth. I guess that can be seen as a grand breakthrough in the history of neuroscience—or probably not! Let's find out what this means for the world collectively. What Exactly is Neurocomputing? Neurocomputing is a branch of neuroscience that deals with the examination of brain patterns and activities. It is a subfield of cognitive neuroscience that scientifically studies the biological mechanisms and reactions of the brain to different experiences. The term applies to the process of reading, analyzing, and interpreting brain activities by utilizing brain sensors and an imaging framework to examine how our brain reacts in response to different emotions. This is usually through the use of a Brain-Computer Interface Device. The framework, in this case, is called the "triad,” a 3-step process of emotion-valuation, sensory-motor, and meaning-knowledge evaluation. With the introduction of Al, neuroscientists hit a new milestone with brain activity studies. The Rise of Neurocomputing Would you have ever imagined that one day, the content of your thoughts could be read by devices? Science fiction? Sure! Why not? We see a lot of that. But reality? That's almost impossible (or so we thought). Lie detectors were the most mind readers, but they can never detect what your thoughts are word by word. However, technology always seems to awe us as time progresses because the technology we once thought only existed in movies is right here! The use of brainwave-controlled devices to read minds began with the invention of Electro Encephalogram (EEG) in the 1900s. History has it that the German psychiatrist, Hans Berger, created the in neurosurgery. first EEG brain recording These devices, fitted with sensors, were used mostly to monitor and record a patient's brain activity. When placed on your scalp, the sensors pick up electrical signals produced by the brain, which can be interpreted. Around 2008, consumer-focused EEG became commercialized for public use. and —both tech companies—were among the early players in this scene as they released EEG headsets with the promise to create mind-controlled video games. NeuroSky Emotive Furthermore, it began being tested in other areas besides video games, like how it could be used to control your phone or other activities by companies like and . iBrain Muse Relief from Brain-Computer Interfaces Technology Innovations and advanced companies like Meta and Neuralink notched it up with their research into Brain-Computer Interfaces (BCIs) - a technology that can pick thoughts directly from brain neurons and translate them into words. This technology uses AI algorithms to read brain activity and decode emotions into words. Between 2017 and 2019, Meta began funding . As of March 2022, the funded Nature Neuroscience, UCSF researchers achieved brain-to-text decoding with an average error rate as low as 3% when it was tested with vocabularies of up to 300 words—a huge advancement from previous studies. this technology research into At the same time, Elon Musk's Neuralink is already making a good deal of progress with its flexible ultra-thin threads that can be implanted directly into the brain, enabling the carrier to control their gadgets/devices with their thoughts. This is already being tested on paraplegics. The technology has been very much welcomed by paralytic patients who need to gain a good level of control over their lives again. Neuralink has already begun testing the brain threads on paraplegics. Case Study of Neurocomputing Although this technological concept sounds somewhat new, neurocomputing has been in the research and development stage for years, and test-flight gadgets are already being produced. The possibilities of mind reading and brainwave-controlled gadgets are endless. Scientists continue to look into ways to integrate them into our lives, experimenting across various sectors with the possible use of non-invasive EEG devices and BCIs. Many of these experiments are often procedures aimed at helping the physically and mentally disabled to communicate their needs and gain some control over their lives. The world is not new to cases of patients who can not speak due to sicknesses, paralysis, stroke, or just being born that way. So when, for the first time in history, researchers at the GrapheneX-UTS Human-centric Artificial Intelligence Centre, University of Technology Sydney, invented a portable non-invasive device that could translate thoughts into words, it was seen as a breakthrough in neurocomputing. Breakthrough at the GrapheneX-UTS Human-centric Artificial Intelligence Centre: At the time, though, the accuracy was questionable, but with the initial goal achieved, it would only take more years of developing it to increase its accuracy rating. We already find Meta and Neuralink taking up this task with BCIs and electron threads. Evolving neurocomputing also makes smooth communication possible between humans and machines, be it our gadgets, robots, or prosthetic arms. The history of neurocomputing and brain-controlled devices left a remarkable mark in the FIFA 2014 World Cup when, for the first time, the symbolic kick-off event for the tournament was led and completed by a paraplegic man using an advanced assisted mobility technology—a brain-controlled exoskeleton. The FIFA 2014 World Cup Kick-Off Event: This technology, by , a collaborative invention of over 100 scientists from around the world, made use of a set of non-invasive electrodes to read the brain signals from the paraplegic and transmit them to the lightweight exoskeleton triggering movements that helped the man complete the kick-off successfully. The Walk Again Project In the same year of the FIFA World Cup kick-off event, the director of the Center for Neuromodulation, Ohio State University, Dr. Ali Rezai, performed a on 26-year-old quadriplegic Ian Burkhart. Paralyzed Ian Burkhart Regained Mobility: life-changing surgery The surgery involved implanting a tiny 4 x 4 mm microchip into Burkhart's motor cortex, used alongside an electrical sleeve and purpose-made algorithms. This allowed the sensors to trigger his thoughts to control his hands and fingers while bypassing his damaged spinal cord. It was a success. This is not the only successful brain implant in the history of neurocomputing; a man paralyzed from the shoulders down has also been able to regain control of his paralyzed muscles by bypassing the injured spinal cord with the into his motor cortex. implantation of two aspirin-sized 96-channel electrode arrays EEG devices and BCIs are greatly contributing to improved quality of life for disabled people. Other Notable Strides: But we can't say that brain-controlled and mind-reading devices are only for the sick and disabled. These devices could also be used to carry out other tasks/activities for the good of everyone: BBC and This Place teamed up to create a mind-reading headset to enable its user to control the with their thoughts—goodbye to remote controls. BBC iPlayer A team led by an Associate Professor at the KU-KIST Graduate School of Converging Science and Technology, Korea University, . Suk-Won Hwang, developed E-Glasses This prototype eyeglass is made up of flexible electrode sensors located between the ears and eyes of the wearer. First, the electrodes consist of an EEG to monitor the brain's electrical activity and an ElectroOculogram (EOG) to track eye movements and transmit both from the glasses to a device for processing and interpretation. This glass can be used to monitor the mental health of the wearer, help them control games with their eyes, and turn on and off the sunglasses mode when the wearer needs it. Nissan and NASA are working together to build a self-driving robot car technology called that can read, monitor, and measure a driver's brain activity to know if he/she is alert to drive or not. Mind Sense In an exciting twist of things, in 2013, NASA came up with the crazy idea of using . Together with scientists from the University of Essex, they launched a project to control a virtual spaceship with the mind. BCIs to control planetary rovers A competition was held in 2016 by neuroscientists at the University of Florida, a competition that had pilot flying their drones to the finish line by using their minds. Brain Drone Race And the list goes on and on. But like every other technology and thing that exists, there will always be pros and cons to consider. The Ethical Considerations of Neurocomputing Neurocomputing is a technology that is already transforming lives, especially for paraplegics, who, in many cases, have been able to get robotic body parts that can be controlled with their minds or bypass spinal cord injuries to stimulate their bodies into motion through brain neuron implants. People who couldn't talk can now communicate their feelings and what they want/need and interact through mind-reading gadgets. For everyone else abled people, organizations, and companies that wish to apply these gadgets in their daily lives or their various sectors, it is very much achievable. It can bring "ease" into certain activities and, perhaps, create a more quiet world. However, the implantation of invasive BCIs into the brain involves a surgical procedure that is almost too risky to be considered. The brain is a fragile organ; damage to it can lead to mental abnormalities or even brain death. As such, the risk of brain implants makes this technology far-fetched for fully functional humans. Paraplegics, on the other hand, can wager these procedures because of the quest to have a better quality of life. A delicate situation, but if that is what it takes for them not to be stuck in a static world at the mercy of others, it is worth the risky shot. This is why BCIs by companies like Neuralink and Meta, although envisioned to cater to all and sundry, are more appealing to the paralytic section of the world at the moment. Because of these concerns, scientists are looking back into non-invasive methods of mind reading. Last year, researchers at the , University of Technology Sydney, invented a portable, non-invasive cap-like device that could translate thoughts into words when placed on the head. GrapheneX-UTS Human-centric Artificial Intelligence Centre Additionally, scientists from the University of Texas, Austin, developed to translate the thoughts in one's brain into actual speech by monitoring the brain's activity involving the use of fMRI and Al language models. a non-invasive technique The accuracy of these techniques was average. However, with the intended goal achieved, it would only take more years of development to increase its accuracy. Still, no one wants to walk around carrying a headpiece with cords sticking out, and neither can they carry fMRI machines all day. Hence, there is a need for less obvious, non-intrusive devices or less risky invasive BCIs. While the world can be swamped by Brainwave-controlled devices that read our minds, it poses serious concerns. One day, like every other day, we'll be carrying out activities with silent thoughts all in our heads, but this is the sad part: organizations would be able to read, monitor, store, access, and use these thoughts when needed. As tragic as this sounds, it is already in progress. The thoughts in our brain are currently our only inaccessible assets, our privacy safe, our most intimate thoughts, and our personal identity—no one should be able to access our minds. Data Privacy: But with the recent discoveries and technologies in neuroscience, this intrinsic privacy may be breached sooner than we know, leaving us truly vulnerable to Big Tech companies and organizations. If we lose control of our minds, if any company can spy into our thoughts, what else do we have left of ourselves? Just like we have on the internet, companies would be able to buy and access our brain data for targeted marketing. The first appeal for every product starts with the brain. You may not be able to say it, but you can think it accurately. Imagine advertisers having that exact information just as we feel it; then, they will be able to market their products in a practically irresistible way. Neurocomputing and mind-reading devices would make brain data available on a massive scale, and this is also very detrimental to us. Think about it; aside from compelling advertising, how safe are you? The brain is where all your secrets lie: your passwords, location, investments, amount of money you own, where you saved your assets, etc. A brain data hack would mean a loss too great to bear. The argument of some neuroscientists that the potential for misuse of neurocomputing and mind reading is so great that there needs to be a revamp of the human rights laws to protect us all is valid. Because this technology has what it takes to interfere with our most basic rights, the current laws are not fully equipped to salvage the situation; we need a new "jurisprudence of the mind" for our protection. So, in all, our biggest challenge is privacy and safety! What's the future? A quiet world. Maybe what we need? Or maybe not. Elon Musk and his company, Neuralink, have been at the forefront, pushing the concept of neurocomputing beyond the idea of it being the help for paraplegics only. For Musk, it would take conceptual interactions to a whole new level where words and conversations don't have to be verbalized, just thought. He calls it "consensual telepathy,” a realm where your speech becomes completely unnecessary. You can walk into a room with people conversing but not conversing because their thoughts are flying invisibly between them. Reading that now, it does sound uncanny. What becomes of our speech? Oh! I know what you are thinking, "there would never be a day when our speech isn't needed,” and of course, that's somewhat true. But come to think of it, before the advent of mobile phones, would there have been a day we thought we'd be so glued to these gadgets we'd rarely appreciate physical communication and rather be embedded in virtual conversations? I don't think so. When all you need is your thoughts to perform the most basic activities like ordering a coffee from a cafe, asking your friend to pass you the popcorn at a movie, communicating a proposal to your boss, conversing verbally on a date, etc., you may slowly lose touch of actual words. Almost the same way, we are slowly losing touch with writing on paper because we'd rather type into our computers, tablets, or phones. Well, there's no denying the fact that it sounds pretty interesting, too. You'd never have to say you don't know how to express yourself because your mind will do all the expressing for you where words would have escaped you. The concept of your feelings will flow just as you feel them, and no matter how disgruntled they are, your receiver will get the exact message with the fear, excitement, contempt, and all the fleeting emotions - conveyed just as it is. Also, the advancement of this technology would eliminate the language barrier. Whatever we think can be communicated directly to the recipient in whatever language desired. What neurocomputing proposes for the future is both unsettling and intriguing, but we really can't stop technology from evolving, and neither can we stop the future. We only hope that measures are instituted to mitigate the cons while we hope for the best.

From Science Fiction to Reality: The Promise of Neurocomputing and Brain-Computer Interfaces (BCIs)

কল্পবিজ্ঞান থেকে বাস্তবে: নিউরোকম্পিউটিং এবং ব্রেন-কম্পিউটার ইন্টারফেসের প্রতিশ্রুতি (BCIs)

Von der Science-Fiction zur Realität: Das Versprechen von Neurocomputing und Brain-Computer-Interfaces (BCIs)

De la ciencia ficción a la realidad: la promesa de la neurocomputación y las interfaces cerebro-computadora (BCI)

De la science-fiction à la réalité : la promesse de la neuroinformatique et des interfaces cerveau-ordinateur (BCI)

विज्ञान कथा से वास्तविकता तक: न्यूरोकंप्यूटिंग और मस्तिष्क-कंप्यूटर इंटरफेस (बीसीआई) का वादा

サイエンスフィクションから現実へ: ニューロコンピューティングと脳コンピュータインターフェース (BCI) の可能性

SF에서 현실로: 신경컴퓨팅과 뇌-컴퓨터 인터페이스(BCI)의 전망

Da ficção científica à realidade: a promessa da neurocomputação e das interfaces cérebro-computador (BCIs)

От научной фантастики к реальности: перспективы нейрокомпьютеров и интерфейсов «мозг-компьютер» (BCI)

Bilim Kurgudan Gerçeğe: Nörobilgisayar ve Beyin-Bilgisayar Arayüzlerinin (BCI) Vaadi

Từ khoa học viễn tưởng đến hiện thực: Lời hứa về giao diện máy tính thần kinh và não-máy tính (BCI)

从科幻到现实：神经计算和脑机接口 (BCI) 的前景

Memes and Narrative Strategies in the Russo-Ukrainian War: A Comprehensive Study

রুশো-ইউক্রেনীয় যুদ্ধে মেমস এবং বর্ণনামূলক কৌশল: একটি ব্যাপক অধ্যয়ন

Meme und Erzählstrategien im Russisch-Ukrainischen Krieg: Eine umfassende Studie

Memes y estrategias narrativas en la guerra ruso-ucraniana: un estudio exhaustivo

Mèmes et stratégies narratives dans la guerre russo-ukrainienne : une étude approfondie

रूस-यूक्रेनी युद्ध में मीम्स और कथात्मक रणनीतियाँ: एक व्यापक अध्ययन

ロシア・ウクライナ戦争におけるミームと物語戦略：包括的研究

러시아-우크라이나 전쟁의 밈과 서사 전략: 종합 연구

Memes e estratégias narrativas na guerra russo-ucraniana: um estudo abrangente

Мемы и нарративные стратегии в российско-украинской войне: комплексное исследование

Rus-Ukrayna Savaşında Memler ve Anlatı Stratejileri: Kapsamlı Bir Çalışma

Memes và chiến lược kể chuyện trong Chiến tranh Nga-Ukraina: Một nghiên cứu toàn diện

俄乌战争中的模因与叙事策略：综合研究

Why Humans Are Drawn to Games

কেন মানুষ গেমের প্রতি আকৃষ্ট হয়

Warum Menschen sich zu Spielen hingezogen fühlen

Por qué los humanos se sienten atraídos por los juegos

Pourquoi les humains sont attirés par les jeux

मनुष्य खेलों की ओर क्यों आकर्षित होते हैं?

人間がゲームに惹かれる理由

인간이 게임에 끌리는 이유

Por que os humanos são atraídos pelos jogos

Почему людей привлекают игры

İnsanlar Neden Oyunlara Çekilir?

Tại sao con người bị thu hút bởi trò chơi

人类为何热衷于游戏

Transcendence Book 9: Far-skies

Authors:
(1) Renan F. F. da Silva, Institute of Computing, University of Campinas;
(2) Yulle G. F. Borges, Institute of Computing, University of Campinas;
(3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. 9 Conclusion Our approaches were quite effective, enabling us to find solutions very close to the optimal solution, even in instances with many items. These results are partly due to the excellent quality of the solutions given by Two-by-Two, which efficiently handles color constraints. Another positive factors are our neighborhoods, which are efficient in quality and time complexity. Lastly, Gilmore and Gomory Formulation has a strong relaxation for the BPP, and this property may extend to CBPP. For a strong relaxation, the values for the optimal fractional and integer solutions are very close, so the patterns used by relaxation probably belong to integer solutions of high quality. Therefore, this is an excellent method to find a good set of patterns for the initial build of GRASP. Acknowledgements This project was supported by the S˜ao Paulo Research Foundation (FAPESP) grants #2015/11937-9 and #2020/06511-0; and the Brazilian National Council For Scientific and Technological Development (CNPq) grants #144257/2019-0, #311039/2020-0 and #425340/2016 3. Declarations Conflict of interest All authors declare that they have no conflicts of interest. References [1] Alsarhan H, Chia D, Christman A, et al (2016) A two-pass algorithm for unordered colored bin packing. Proceedings of the 9th International Conference on Discrete Optimization and Operations Research and Scientific School pp 1–10 [2] Balogh J, B´ek´esi J, Dosa G, et al (2013) Black and white bin packing. In: Erlebach T, Persiano G (eds) Approximation and Online Algorithms. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 131–144, https://doi.org/10.1007/978-3-642-38016-7_12 [3] Balogh J, B´ek´esi J, D´osa G, et al (2015) Offline black and white bin packing. Theoretical Computer Science 596:92–101. https://doi.org/10.1016/j.tcs.2015.06.045 [4] Belov G, Scheithauer G (2006) A branch-and-cut-and-price algorithm for one-dimensional stock cutting and two-dimensional two-stage cutting. European Journal of Operational Research 171(1):85–106. https://doi.org/10.1016/j.ejor.2004.08.036 [5] B¨ohm M, Sgall J, Vesel´y P (2015) Online colored bin packing. In: Bampis E, Svensson O (eds) Approximation and Online Algorithms. Springer International Publishing, Cham, pp 35–46, https://doi.org/10.1007/978-3-319-18263-6_4 [6] B¨ohm M, D´osa G, Epstein L, et al (2018) Colored bin packing: Online algorithms and lower bounds. Algorithmica 80(1):155–184. https://doi.org/10.1007/s00453-016-0248-2 [7] Borges Y, Schouery R (2020) Modelos pseudo polinomiais para o problema do empacotamento colorido. In: Anais do V Encontro de Teoria da Computa¸c˜ao, pp 37–40, https://doi.org/ 10.5753/etc.2020.11084, (In Portuguese) [8] Borges YGF, Schouery RCS, Miyazawa FK (2023) Mathematical models and exact algorithms for the colored bin packing problem. 2305.15291 [9] Brand˜ao F, Pedroso JP (2016) Bin packing and related problems: General arc-flow formulation with graph compression. Computers & Operations Research 69:56–67. https://doi.org/10. 1016/j.cor.2015.11.009 [10] Buljubaˇsi´c M, Vasquez M (2016) Consistent neighborhood search for one-dimensional bin packing and two-dimensional vector packing. Computers & Operations Research 76:12–21. https://doi.org/10.1016/j.cor.2016.06.009 [11] Carvalho JMVd (1999) Exact solution of bin-packing problems using column generation and branch-and-bound. Annals of Operations Research 86(0):629–659. https://doi.org/10. 1023/A:1018952112615 [12] Castelli M, Vanneschi L (2014) A hybrid harmony search algorithm with variable neighbourhood search for the bin-packing problem. 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014) pp 1–6. https://doi.org/10.1109/NaBIC.2014. 6921849 [13] Chen J, Han X, Bein W, et al (2015) Black and white bin packing revisited. In: Lu Z, Kim D, Wu W, et al (eds) Combinatorial Optimization and Applications. Springer International Publishing, Cham, pp 45–59, https://doi.org/10.1007/978-3-319-26626-8_4 [14] Delorme M, Iori M (2020) Enhanced pseudo-polynomial formulations for bin packing and cutting stock problems. INFORMS Journal on Computing 32(1):101–119. https://doi.org/ 10.1287/ijoc.2018.0880 [15] Delorme M, Iori M, Martello S (2018) Bpplib: a library for bin packing and cutting stock problems. Optimization Letters 12(2):235–250. https://doi.org/10.1007/s11590-017-1192-z [16] Demˇsar J (2006) Statistical comparisons of classifiers over multiple data sets. The Journal of Machine learning research 7:1–30 [17] D´osa G, Epstein L (2014) Colorful bin packing. In: Ravi R, Gørtz IL (eds) Algorithm Theory – SWAT 2014. Springer International Publishing, Cham, pp 170–181, https://doi.org/10. 1007/978-3-319-08404-6_15 [18] Feo TA, Resende MG (1989) A probabilistic heuristic for a computationally difficult set covering problem. Operations Research Letters 8(2):67–71. https://doi.org/https://doi.org/ 10.1016/0167-6377(89)90002-3 [19] Fleszar K, Hindi KS (2002) New heuristics for one-dimensional bin-packing. Computers & Operations Research 29(7):821–839. https://doi.org/10.1016/S0305-0548(00)00082-4 [20] Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32(200):675–701. https: //doi.org/10.1080/01621459.1937.10503522 [21] Gilmore PC, Gomory RE (1961) A linear programming approach to the cutting-stock problem. Operations Research 9(6):849–859. https://doi.org/10.1287/opre.29.6.1092 [22] Gonz´alez-San-Mart´ın J, Cruz-Reyes L, G´omez-Santill´an C, et al (2023) Comparative Study of Heuristics for the One-Dimensional Bin Packing Problem, Springer Nature Switzerland, Cham, pp 293–305. https://doi.org/10.1007/978-3-031-28999-6_19 [23] Gupta JND, Ho JC (1999) A new heuristic algorithm for the one-dimensional binpacking problem. Production Planning & Control 10(6):598–603. https://doi.org/10.1080/ 095372899232894 [24] Iman RL, Davenport JM (1980) Approximations of the critical region of the fbietkan statistic. Communications in Statistics - Theory and Methods 9(6):571–595. https://doi.org/10. 1080/03610928008827904 [25] Karp RM (1972) Reducibility among Combinatorial Problems, Springer US, Boston, MA, pp 85–103. https://doi.org/10.1007/978-1-4684-2001-2_9 [26] de Lima VL, Iori M, Miyazawa FK (2022) Exact solution of network flow models with strong relaxations. Mathematical Programming pp 1–34. https://doi.org/10.1007/ s10107-022-01785-9 [27] Loh KH, Golden B, Wasil E (2008) Solving the one-dimensional bin packing problem with a weight annealing heuristic. Computers & Operations Research 35(7):2283–2291. https:// doi.org/10.1016/j.cor.2006.10.021 [28] Mladenovi´c N, Hansen P (1997) Variable neighborhood search. Computers & Operations Research 24(11):1097–1100. https://doi.org/10.1016/S0305-0548(97)00031-2 [29] Nemenyi PB (1963) Distribution-free multiple comparisons. PhD thesis, Princeton University [30] Pessoa A, Sadykov R, Uchoa E, et al (2020) A generic exact solver for vehicle routing and related problems. Mathematical Programming 183(1):483–523. https://doi.org/10.1007/ s10107-020-01523-z [31] Vance PH (1998) Branch-and-price algorithms for the one-dimensional cutting stock problem. Computational Optimization and Applications 9(3):211–228. https://doi.org/10.1023/A: 1018346107246 [32] Wei L, Luo Z, Baldacci R, et al (2020) A new branch-and-price-and-cut algorithm for onedimensional bin-packing problems. INFORMS Journal on Computing 32(2):428–443. https://doi.org/10.1287/ijoc.2018.0867 This paper is available on arxiv under CC 4.0 license. Authors: (1) Renan F. F. da Silva, Institute of Computing, University of Campinas; (2) Yulle G. F. Borges, Institute of Computing, University of Campinas; (3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. Authors: (1) Renan F. F. da Silva, Institute of Computing, University of Campinas; (2) Yulle G. F. Borges, Institute of Computing, University of Campinas; (3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. 9 Conclusion Our approaches were quite effective, enabling us to find solutions very close to the optimal solution, even in instances with many items. These results are partly due to the excellent quality of the solutions given by Two-by-Two, which efficiently handles color constraints. Another positive factors are our neighborhoods, which are efficient in quality and time complexity. Lastly, Gilmore and Gomory Formulation has a strong relaxation for the BPP, and this property may extend to CBPP. For a strong relaxation, the values for the optimal fractional and integer solutions are very close, so the patterns used by relaxation probably belong to integer solutions of high quality. Therefore, this is an excellent method to find a good set of patterns for the initial build of GRASP. Acknowledgements This project was supported by the S˜ao Paulo Research Foundation (FAPESP) grants #2015/11937-9 and #2020/06511-0; and the Brazilian National Council For Scientific and Technological Development (CNPq) grants #144257/2019-0, #311039/2020-0 and #425340/2016 3. Acknowledgements Declarations Conflict of interest All authors declare that they have no conflicts of interest. Conflict of interest References [1] Alsarhan H, Chia D, Christman A, et al (2016) A two-pass algorithm for unordered colored bin packing. Proceedings of the 9th International Conference on Discrete Optimization and Operations Research and Scientific School pp 1–10 [2] Balogh J, B´ek´esi J, Dosa G, et al (2013) Black and white bin packing. In: Erlebach T, Persiano G (eds) Approximation and Online Algorithms. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 131–144, https://doi.org/10.1007/978-3-642-38016-7_12 [3] Balogh J, B´ek´esi J, D´osa G, et al (2015) Offline black and white bin packing. Theoretical Computer Science 596:92–101. https://doi.org/10.1016/j.tcs.2015.06.045 [4] Belov G, Scheithauer G (2006) A branch-and-cut-and-price algorithm for one-dimensional stock cutting and two-dimensional two-stage cutting. European Journal of Operational Research 171(1):85–106. https://doi.org/10.1016/j.ejor.2004.08.036 [5] B¨ohm M, Sgall J, Vesel´y P (2015) Online colored bin packing. In: Bampis E, Svensson O (eds) Approximation and Online Algorithms. Springer International Publishing, Cham, pp 35–46, https://doi.org/10.1007/978-3-319-18263-6_4 [6] B¨ohm M, D´osa G, Epstein L, et al (2018) Colored bin packing: Online algorithms and lower bounds. Algorithmica 80(1):155–184. https://doi.org/10.1007/s00453-016-0248-2 [7] Borges Y, Schouery R (2020) Modelos pseudo polinomiais para o problema do empacotamento colorido. In: Anais do V Encontro de Teoria da Computa¸c˜ao, pp 37–40, https://doi.org/ 10.5753/etc.2020.11084, (In Portuguese) [8] Borges YGF, Schouery RCS, Miyazawa FK (2023) Mathematical models and exact algorithms for the colored bin packing problem. 2305.15291 [9] Brand˜ao F, Pedroso JP (2016) Bin packing and related problems: General arc-flow formulation with graph compression. Computers & Operations Research 69:56–67. https://doi.org/10. 1016/j.cor.2015.11.009 [10] Buljubaˇsi´c M, Vasquez M (2016) Consistent neighborhood search for one-dimensional bin packing and two-dimensional vector packing. Computers & Operations Research 76:12–21. https://doi.org/10.1016/j.cor.2016.06.009 [11] Carvalho JMVd (1999) Exact solution of bin-packing problems using column generation and branch-and-bound. Annals of Operations Research 86(0):629–659. https://doi.org/10. 1023/A:1018952112615 [12] Castelli M, Vanneschi L (2014) A hybrid harmony search algorithm with variable neighbourhood search for the bin-packing problem. 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014) pp 1–6. https://doi.org/10.1109/NaBIC.2014. 6921849 [13] Chen J, Han X, Bein W, et al (2015) Black and white bin packing revisited. In: Lu Z, Kim D, Wu W, et al (eds) Combinatorial Optimization and Applications. Springer International Publishing, Cham, pp 45–59, https://doi.org/10.1007/978-3-319-26626-8_4 [14] Delorme M, Iori M (2020) Enhanced pseudo-polynomial formulations for bin packing and cutting stock problems. INFORMS Journal on Computing 32(1):101–119. https://doi.org/ 10.1287/ijoc.2018.0880 [15] Delorme M, Iori M, Martello S (2018) Bpplib: a library for bin packing and cutting stock problems. Optimization Letters 12(2):235–250. https://doi.org/10.1007/s11590-017-1192-z [16] Demˇsar J (2006) Statistical comparisons of classifiers over multiple data sets. The Journal of Machine learning research 7:1–30 [17] D´osa G, Epstein L (2014) Colorful bin packing. In: Ravi R, Gørtz IL (eds) Algorithm Theory – SWAT 2014. Springer International Publishing, Cham, pp 170–181, https://doi.org/10. 1007/978-3-319-08404-6_15 [18] Feo TA, Resende MG (1989) A probabilistic heuristic for a computationally difficult set covering problem. Operations Research Letters 8(2):67–71. https://doi.org/https://doi.org/ 10.1016/0167-6377(89)90002-3 [19] Fleszar K, Hindi KS (2002) New heuristics for one-dimensional bin-packing. Computers & Operations Research 29(7):821–839. https://doi.org/10.1016/S0305-0548(00)00082-4 [20] Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32(200):675–701. https: //doi.org/10.1080/01621459.1937.10503522 [21] Gilmore PC, Gomory RE (1961) A linear programming approach to the cutting-stock problem. Operations Research 9(6):849–859. https://doi.org/10.1287/opre.29.6.1092 [22] Gonz´alez-San-Mart´ın J, Cruz-Reyes L, G´omez-Santill´an C, et al (2023) Comparative Study of Heuristics for the One-Dimensional Bin Packing Problem, Springer Nature Switzerland, Cham, pp 293–305. https://doi.org/10.1007/978-3-031-28999-6_19 [23] Gupta JND, Ho JC (1999) A new heuristic algorithm for the one-dimensional binpacking problem. Production Planning & Control 10(6):598–603. https://doi.org/10.1080/ 095372899232894 [24] Iman RL, Davenport JM (1980) Approximations of the critical region of the fbietkan statistic. Communications in Statistics - Theory and Methods 9(6):571–595. https://doi.org/10. 1080/03610928008827904 [25] Karp RM (1972) Reducibility among Combinatorial Problems, Springer US, Boston, MA, pp 85–103. https://doi.org/10.1007/978-1-4684-2001-2_9 [26] de Lima VL, Iori M, Miyazawa FK (2022) Exact solution of network flow models with strong relaxations. Mathematical Programming pp 1–34. https://doi.org/10.1007/ s10107-022-01785-9 [27] Loh KH, Golden B, Wasil E (2008) Solving the one-dimensional bin packing problem with a weight annealing heuristic. Computers & Operations Research 35(7):2283–2291. https:// doi.org/10.1016/j.cor.2006.10.021 [28] Mladenovi´c N, Hansen P (1997) Variable neighborhood search. Computers & Operations Research 24(11):1097–1100. https://doi.org/10.1016/S0305-0548(97)00031-2 [29] Nemenyi PB (1963) Distribution-free multiple comparisons. PhD thesis, Princeton University [30] Pessoa A, Sadykov R, Uchoa E, et al (2020) A generic exact solver for vehicle routing and related problems. Mathematical Programming 183(1):483–523. https://doi.org/10.1007/ s10107-020-01523-z [31] Vance PH (1998) Branch-and-price algorithms for the one-dimensional cutting stock problem. Computational Optimization and Applications 9(3):211–228. https://doi.org/10.1023/A: 1018346107246 [32] Wei L, Luo Z, Baldacci R, et al (2020) A new branch-and-price-and-cut algorithm for onedimensional bin-packing problems. INFORMS Journal on Computing 32(2):428–443. https://doi.org/10.1287/ijoc.2018.0867 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

Fast Neighborhood Search Heuristics for the Colorful Bin Packing Problem: Conclusion and References

LONDON, United Kingdom, April 9th, 2024/Chainwire/--NeuroMesh (nmesh.io), a trailblazer in artificial intelligence, announces the rollout of its distributed AI training protocol, poised to revolutionize global access and collaboration in AI development. Embracing DePIN's decentralized framework, NeuroMesh bridges the gaps between the demand for training large AI models and distributed GPUs. This initiative aims to foster inclusivity in AI development, facilitating participation across diverse sectors and geographies. Visionaries in AI: The Team's Global Ambition The team behind NeuroMesh, composed of researchers and engineers from Oxford, NTU, PKU, THU, HKU, Google, and Meta, pioneers a democratic AI training process. This visionary approach addresses the limitations of centralized AI development by enabling GPU owners worldwide to contribute to a vast training network, empowering entities of all sizes to leverage this service for their training needs. NeuroMesh transcends traditional AI by fostering collaboration. Their vision is to equip every developer and organization, regardless of location or resources, with the ability to train and utilize cutting-edge AI models. This aligns perfectly with the vision of AI pioneers like Yann LeCun, who advocate for a future powered by crowdsourced and distributed AI training. A Revolutionary Design Based on PCN At the heart of NeuroMesh's distributed training protocol lies the groundbreaking PCN (Predictive Coding Network) training algorithm - a true game-changer in this field. This approach empowers GPU owners worldwide to contribute their power, fostering a vast collaborative effort. The PCN Training Algorithm: The magic behind NeuroMesh lies in the PCN training algorithm. Unlike traditional backpropagation (BP) methods, PCN enables fully local, parallel, and autonomous training. The team aims to create a vast network, where each node—representing a participating GPU—learns independently. PCN minimizes inter-layer communication, reducing data traffic and facilitating asynchronous training. Think of it as a symphony where each musician plays their part independently, yet contributes to a harmonious whole. This cutting-edge model, inspired by recent advancements in neuroscience research pioneered by Oxford University, mimics the human brain's localized learning approach. By storing error values and optimizing for a local target in each layer, it replicates the behavior of brain neurons. This allows NeuroMesh to define models that are much larger, with individual components that contribute to the same ultimate optimization objective for the whole network, just like the human brain where different stimuli are handled by different groups of neurons. This biologically-inspired approach, combined with its inherent distribution capabilities, unlocks a new era of AI development. A Call to Forge Global Partnerships NeuroMesh invites partnerships globally, aiming to forge an AI future that everyone can participate in. Its protocol is the bedrock upon which a diverse ecosystem is being built. The ecosystem is designed to be dynamic, collaborative, and adaptable, ensuring that it can serve the AI model training needs of any size, from any industry. Individuals, projects with GPU resources, and entities with training needs are all welcome to join this transformative initiative. For comprehensive details on NeuroMesh and to participate in this leading-edge endeavor, users can visit nmesh.io. About NeuroMesh NeuroMesh comprises researchers and engineers from esteemed institutions such as Oxford, NTU, PKU, THU, HKU, Google and Meta. By empowering developers and organizations to deploy robust AI models, NeuroMesh is cultivating an inclusive AI ecosystem, bridging the gaps between the demand of training large AI models and distributed GPUs worldwide. For more information, users can visit NeuroMesh's | Twitter Telegram Contact CMO Kenchia Lee NeuroMesh kenchia@nmesh.io 07746906341 This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program . here

NeuroMesh: Spearheading The New Era Of AI With a Distributed Training Protocol

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