We study the generic theory of algebraically closed fields of fixed positive characteristic with a predicate for an additive subgroup, called $\mathrm {ACFG}$. This theory was introduced in [16] as a new example of $\mathrm {NSOP}_{1}$ nonsimple theory. In this paper we describe more features of $\mathrm {ACFG}$, such as imaginaries. We also study various independence relations in $\mathrm {ACFG}$, such as Kim-independence or forking independence, and describe interactions between them.

The development of causal modelling since the 1950s has been accompanied by a number of controversies, the most striking of which concerns the Markov condition. Reichenbach's conjunctive forks did satisfy the Markov condition, while Salmon's interactive forks did not. Subsequently some experts in the field have argued that adequate causal models should always satisfy the Markov condition, while others have claimed that non-Markovian causal models are needed in some cases. This paper argues for the second position by (...) considering the multi-causal forks, which are widespread in contemporary medicine (Section 2). A non-Markovian causal model for such forks is introduced and shown to be mathematically tractable (Sections 6, 7, and 8). The paper also gives a general discussion of the controversy about the Markov condition (Section 1), and of the related controversy about probabilistic causality (Sections 3, 4, and 5). (shrink)

Hereditary breast and ovarian cancers are frequently attributed to germline mutations in the tumor suppressor genes BRCA1 and BRCA2. BRCA1/2 act to repair double‐strand breaks (DSBs) and suppress the demise of unstable replication forks. Our work elucidated a dynamic interplay between BRCA2 and the WRN DNA helicase/exonuclease defective in the premature aging disorder Werner syndrome. WRN and BRCA2 participate in complementary pathways to stabilize replication forks in cancer cells, allowing them to proliferate. Whether the functional overlap of WRN (...) and BRCA2 is relevant to replication at gaps between newly synthesized DNA fragments, protection of telomeres, and/or metabolism of secondary DNA structures remain to be determined. Advances in understanding the mechanisms elicited during replication stress have prompted the community to reconsider avenues for cancer therapy. Insights from studies of PARP or topoisomerase inhibitors provide working models for the investigation of WRN's mechanism of action. We discuss these topics, focusing on the implications of the WRN‐BRCA2 genetic interaction under conditions of replication stress. (shrink)

"What can we expect from the study of Chinese philosophy? « In the philosophical systems of the Hindoos and the Chinese there are still hidden treasures, in which the anticipation of scientific discoveries, the results of thousands of years of occidental research, is most striking. Such are the words of Edward von Hartmann, the most famous living German philosopher1. Much labour has been spent in Europe on the Indian Vedanta philosophy, which had such a marked influence on Arthur Schopenhauer. « (...) The Upanishads, says the author of the Parerga and Paralipomena, are the outcome of the highest human wisdom.... They afford the most remunerative and sublime reading possible in this world, which has been the consolation of my life, as it will be that of my death 2. I do not see why the many germs scattered over the vast field of Chinese philosophy should not have a similar fertilizing influence on some philosophical European mind also. The deep impression caused by the Tao-tê-king will support my view. But much work remains to be done before Chinese philosophy will take its proper place in the history of philosophy. The burden of this task lies with us who are living in China and studying her language and literature, for, while great care is bestowed on all her sister languages in Europe and America, Chinese, the oldest of all, but the youngest in the curriculum of our high-schools, is treated as a step-child by public opinion. This paper is meant as a move in the direction just indicated.". (shrink)

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be (...) preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

Cervical spinal cord injuries often lead to loss of motor function in both hands and legs, limiting autonomy and quality of life. While it was shown that unilateral hand function can be restored after SCI using a hybrid electroencephalography/electrooculography brain/neural hand exoskeleton, it remained unclear whether such hybrid paradigm also could be used for operating two hand exoskeletons, e.g., in the context of bimanual tasks such as eating with fork and knife. To test whether EEG/EOG signals allow for fluent and (...) reliable as well as safe and user-friendly bilateral B/NHE control, eight healthy participants as well as four chronic tetraplegics performed a complex sequence of EEG-controlled bilateral grasping and EOG-controlled releasing motions of two exoskeletons visually presented on a screen. A novel EOG command performed by prolonged horizontal eye movements to the left or right was introduced as a reliable switch to activate either the left or right exoskeleton. Fluent EEG control was defined as average “time to initialize” grasping motions below 3 s. Reliable EEG control was assumed when classification accuracy exceeded 80%. Safety was defined as “time to stop” all unintended grasping motions within 2 s. After the experiment, tetraplegics were asked to rate the user-friendliness of bilateral B/NHE control using Likert scales. Average TTI and accuracy of EEG-controlled operations ranged at 2.14 ± 0.66 s and 85.89 ± 15.81% across healthy participants and at 1.90 ± 0.97 s and 81.25 ± 16.99% across tetraplegics. Except for one tetraplegic, all participants met the safety requirements. With 88 ± 11% of the maximum achievable score, tetraplegics rated the control paradigm as user-friendly and reliable. These results suggest that hybrid EEG/EOG B/NHE control of two assistive devices is feasible and safe, paving the way to test this paradigm in larger clinical trials performing bimanual tasks in everyday life environments. (shrink)

pt. 1. Philosophical essays -- pt. 2. Miscellaneous essays.

THE ART OF CAUSAL CONJECTURE Glenn Shafer Table of Contents Chapter 1. Introduction........................................................................................ ...........1 1.1. Probability Trees..........................................................................................3 1.2. Many Observers, Many Stances, Many Natures..........................................8 1.3. Causal Relations as Relations in Nature’s Tree...........................................9 1.4. Evidence............................................................................................ ...........13 1.5. Measuring the Average Effect of a Cause....................................................17 1.6. Causal Diagrams..........................................................................................20 1.7. Humean Events............................................................................................23 1.8. Three Levels of Causal Language................................................................27 1.9. An Outline of the Book................................................................................27 Chapter 2. Event Trees............................................................................................... .....31 2.1. Situations and Events...................................................................................32 2.2. The Ordering of Situations and Moivrean Events.......................................35 2.3. Cuts................................................................................................ ..............39 2.4. Humean Events............................................................................................43 2.5. (...) Moivrean Variables......................................................................................49 2.6. Humean Variables........................................................................................53 2.7. Event Trees for Stochastic Processes...........................................................54 2.8. Timing in Event Trees.................................................................................56 2.9. Intersecting Event Trees...............................................................................60 2.10. Notes on the Literature...............................................................................61 Chapter 3. Probability Trees...........................................................................................63 3.1. Some Types of Probability Trees.................................................................64 ii 3.2. Axioms for the Probabilities of Moivrean Events.......................................68 3.3. Zero Probabilities....................................................................................... ..70 3.4. A Sample-Space Analysis of the Event-Tree Axioms.................................72 3.5. Probabilities and Expected Values for Variables.........................................74 3.6. Martingales......................................................................................... .........79 3.7. The Expectation of a Variable in a Cut........................................................83 3.8. Conditional Expected Value and Conditional Expectation.........................87 Chapter 4. The Meaning of Probability...........................................................................91 4.1. The Interpretation of Expected Value..........................................................92 4.2. The Interpretation of Expectation................................................................95 4.3. The Long Run..............................................................................................98 4.4. Changes in Belief.........................................................................................101 4.5. The Empirical Validation of Probability......................................................106 4.6. The Diversity of Uses of Probability...........................................................108 4.7. Notes on the Literature.................................................................................110 Chapter 5. Independent Events.......................................................................................113 5.1. Independence........................................................................................ .......114 5.2. Weak Independence.....................................................................................118 5.3. The Principle of the Common Cause...........................................................121 5.4. Conditional Independence............................................................................128 5.5. Notes on the Literature.................................................................................133 Chapter 6. Events Tracking Events.................................................................................135 6.1. Tracking............................................................................................ ...........137 6.2. Tracking and Conditional Independence.....................................................142 6.3. Stochastic Subsequence...............................................................................143 6.4. Singular Diagrams for Stochastic Subsequence...........................................147 6.5. Conjunctive and Interactive Forks...............................................................149 Chapter 7. Events as Signs of Events..............................................................................153 iii 7.1. Sign................................................................................................ ..............154 7.2. Weak Sign................................................................................................ ....159 7.3. The Ethics of Causal Talk............................................................................160 7.4. Screening Off...............................................................................................16 2 Chapter 8. Independent Variables...................................................................................167 8.1. Unconditional Independence........................................................................170 8.2. Conditional Independence............................................................................175 8.3. Independence for Partitions.........................................................................177 8.4. Independence for Families of Variables......................................................182 8.5. Individual Properties of the Independence Relations...................................186 Chapter 9. Variables Tracking Variables........................................................................189 9.1. Tracking and Conditional Independence: A Summary...............................190 9.2. Strong Tracking............................................................................................ 192 9.3. Strong Tracking and Conditional Independence..........................................198 9.4. Stochastic Subsequence...............................................................................201 9.5. Functional Dependence................................................................................203 9.6. Tracking in Mean.........................................................................................204 9.7. Linear Tracking............................................................................................ 207 9.8. Tracking by Partitions..................................................................................210 9.9. Tracking by Families of Variables...............................................................212 Chapter 10. Variables as Signs of Variables...................................................................215 10.1. Sign................................................................................................ ............219 10.2. Linear Sign................................................................................................ .222 10.3. Scored Sign................................................................................................ 225 10.4. Families of Variables.................................................................................227 Chapter 11. AnTheory of Event Trees.............................................................229 11.1. Event Trees as Sets of Sets........................................................................230 11.2. Event Trees as Partially Ordered Sets........................................................232 iv 11.3. Regular Event Trees...................................................................................240 11.4. The Resolution of Moivrean Variables......................................................244 11.5. Humean Events and Variables...................................................................246 Chapter 12. Martingale Trees..........................................................................................247 12.1. Examples of Decision Trees......................................................................249 12.2. The Meaning of Probability in a Decision Tree.........................................253 12.3. Martingales......................................................................................... .......257 12.4. The Structure of Martingale Trees.............................................................261 12.5. Probability and Causality...........................................................................265 12.6. Lower and Upper Probability.....................................................................269 12.7. The Law of Large Numbers.......................................................................272 12.8. Notes on the Literature...............................................................................274 Chapter 13. Refining............................................................................................ ...........275 13.1. Examples of Refinement............................................................................277 13.2. A Constructive Definition of Finite Refinement.......................................281 13.3. Axioms for Refinement..............................................................................282 13.4. Lifting Moivrean Events and Variables.....................................................288 13.5. Refining Martingale Trees.........................................................................288 13.6. Grounding........................................................................................... .......294 Chapter 14. Principles of Causal Conjecture..................................................................299 14.1. The Diversity of Causal Explanation.........................................................302 14.2. The Mean Effect of the Happening of a Moivrean Event..........................305 14.3. The Effect of a Humean Variable..............................................................311 14.4. Attribution and Generality.........................................................................316 14.5. The Statistical Measurement of the Effect of a Cause...............................319 14.6. Measurement by Experiment.....................................................................320 14.7. Using Our Knowledge of How Things Work............................................322 v 14.8. Sampling Error...........................................................................................329 14.9. The Sampling Frame..................................................................................329 14.10. Notes on the Literature.............................................................................330 Chapter 15. Causal Models.............................................................................................3 31 15.1. The Causal Interpretation of Statistical Prediction....................................333 15.2. Generalizing to a Family of Exogenous Variables....................................337 15.3 Some Joint Causal Diagrams......................................................................339 15.4. Causal Path Diagrams................................................................................342 15.5. Causal Relevance Diagrams.......................................................................346 15.6. The Meaning of Latent Variables..............................................................352 15.7. Notes on the Literature...............................................................................357 Chapter 16. Representing Probability Trees...................................................................359 16.1. Three Graphical Representations...............................................................361 16.2. Skeletal Simplifications.............................................................................368 16.3. Martingale Trees in Type Theory...............................................................371 Appendix A. Huygens’s Probability Trees.....................................................................379 Huygens’s Manuscript in Translation..................................................................380 Appendix B. Some Elements of Graph Theory..............................................................385 B1. Undirected Graphs........................................................................................385 B2. Directed Graphs............................................................................................38 6 Appendix C. Some Elements of Order Theory...............................................................393 C1. Partial and Quasi Orderings.........................................................................393 C2. Singular and Joint Diagrams for Binary Relations.......................................394 C3. Lattices............................................................................................ .............395 C4. The Lattice of Partitions of a Set..................................................................396 Appendix D. The Sample-Space Framework for Probability.........................................399 D1. Probability Measures....................................................................................399 D2. Variables........................................................................................... ...........400 vi D3. Families of Variables...................................................................................401 D4. Expected Value............................................................................................402 D5. The Law of Large Numbers.........................................................................405 D6. Conditional Probability................................................................................406 D7. Conditional Expected Value........................................................................407 Appendix E. Prediction in Probability Spaces................................................................409 E1. Conditional Distribution...............................................................................411 E2. Regression on a Single Variable...................................................................412 E3. Regression on a Partition or a Family of Variables......................................415 E4. Linear Regression on a Single Variable.......................................................418 E5. Linear Regression on a Family of Variables................................................422 Appendix F. Sample-Space Concepts of Independence.................................................425 F1. Overview............................................................................................ ...........426 F2. Independence Proper.....................................................................................432 F3. Unpredictability in Mean..............................................................................434 F4. Simple Uncorrelatedness..............................................................................437 F5. Mixed Uncorrelatedness...............................................................................438 F6. Partial Uncorrelatedness...............................................................................440 F7. Independence for Partitions..........................................................................442 F8. Independence for Families of Variables.......................................................445 F9. The Basic Role of Uncorrelatedness.............................................................448 F10. Dawid’s Axioms.........................................................................................449 Appendix G. Prediction Diagrams..................................................................................453 G1. Path Diagrams............................................................................................ ..454 G2. Generalized Path Diagrams..........................................................................462 G3. Relevance Diagrams.....................................................................................466 G4. Bubbled Relevance Diagrams......................................................................475 Appendix H. Abstract Stochastic Processes...................................................................479 vii H1. Probability Conditionals and Probability Distributions...............................477 H2. Abstract Stochastic Processes......................................................................479 H3. Embedding Variables and Processes in a Sample Space.............................480 References.......................................................................................... ..............................491. (shrink)

We offer a review of some of the most influential views on the status of Reichenbach’s Principle of the Common Cause (RPCC) for genuinely indeterministic systems. We first argue that the RPCC is properly a conjunction of two distinct claims, one metaphysical and another methodological. Both claims can and have been contested in the literature, but here we simply assume that the metaphysical claim is correct, in order to focus our analysis on the status of the methodological claim. We briefly (...) review the most entrenched or classical positions, including Salmon’s ‘interactive forks’, van Fraassen’s scepticism, and Cartwright’s generalisation of the fork criterion. We then go on to review the results of the ‘Budapest school’ on the existence of formally defined screening­ off events for any correlation —by means of the ideas of probability space extensibility and (Reichenbachian common cause) completability. We distinguish the Budapest doctrine clearly from any of the classical conceptions, and thus present an overall framework for discussions of causal inference in quantum mechanics. We argue that this review is preliminary essential work for a thorough assessment of the conditions under which RCCP may be a reliable tool for causal inference in a genuinely probabilistic (indeterministic) context. (shrink)

We offer a review of some of the most influential views on the status of Reichenbach’s Principle of the Common Cause (PCC) for genuinely indeterministic systems. We first argue that the PCC is properly a conjunction of two distinct claims, one metaphysical and another methodological. Both claims can and have been contested in the literature, but here we simply assume that the metaphysical claim is correct, in order to focus our analysis on the status of the methodological claim. We briefly (...) review the most entrenched or classical positions, including Salmon’s ‘interactive forks’, van Fraassen’s scepticism, and Cartwright’s generalisation of the fork criterion. We then go on to review the results of the ‘Budapest school’ on the existence of formally defined screening-off events for any correlation —by means of the ideas of probability space extensibility and (Reichenbachian common cause) completability. We distinguish the Budapest doctrine clearly from any of the classical conceptions, and thus present an overall framework for discussions of causal inference in quantum mechanics. The framework, however preliminary, is essential work for a thorough assessment of the conditions under which PCC may be a reliable tool for causal inference in a genuinely probabilistic (indeterministic) context. (shrink)

Replication forks inevitably stall at damaged DNA in every cell cycle. The ability to overcome DNA lesions is an essential feature of the replication machinery. A variety of specialized polymerases have recently been discovered, which enable cells to replicate past various forms of damage by a process termed translesion synthesis. Alternatively, homologous recombination can be used to restart DNA replication across the lesion. Genetic and biochemical studies have shed light on the impact of these two post‐replication repair pathways in (...) bacteria and yeast. In vertebrates, however, a genetic approach to study post‐replication repair has been compromised because many of the genes involved appear to be essential for embryonic development. We have taken advantage of the chicken cell line DT40 to perform a genetic analysis of translesion synthesis and homologous recombination and to characterize genetic interactions between these two pathways in vertebrates. In this article, we aim to summarize our current understanding of post‐replication repair in DT40 in the perspective of bacterial, yeast and mammalian genetics. BioEssays 26:151–158, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

This book, published in 2000, is a clear account of causation based firmly in contemporary science. Dowe discusses in a systematic way, a positive account of causation: the conserved quantities account of causal processes which he has been developing over the last ten years. The book describes causal processes and interactions in terms of conserved quantities: a causal process is the worldline of an object which possesses a conserved quantity, and a causal interaction involves the exchange of conserved quantities. Further, (...) things that are properly called cause and effect are appropriately connected by a set of causal processes and interactions. The distinction between cause and effect is explained in terms of a version of the fork theory: the direction of a certain kind of ordered pattern of events in the world. This particular version has the virtue that it allows for the possibility of backwards causation, and therefore time travel. (shrink)

A theory of causality based upon physical processes is developed. Causal processes are distinguished from pseudo-processes by means of a criterion of mark transmission. Causal interactions are characterized as those intersections of processes in which the intersecting processes are mutually modified in ways which persist beyond the point of intersection. Causal forks of three kinds (conjunctive, interactive, and perfect) are introduced to explicate the principle of the common cause. Causal forks account for the production of order and (...) modifications of order; causal processes account for the propagation of causal influence. (shrink)

There is much discourse and focus on the social determinants of health, but undergirding these multiple intersecting and interacting determinants are legal and political determinants that have operated at every level and impact the entire life continuum. The United States has long grappled with advancing health equity via public law and policy. Seventy years after the country was founded, lawmakers finally succeeded in passing the first comprehensive and inclusive law aimed at tackling the social determinants of health, but that effort (...) was short-lived. Today the United States is faced with another fork in the road relative to the advancement of health equity. This article draws on lessons from history and law to argue that researchers, providers, payers, lawmakers and the legal community have a moral, economic and national security imperative to address not only the negative outcomes of health disparities, but also the imbalance of inputs resulting from laws and policies which fail to employ an equity lens. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Dewey, Implementation, and Creating a Democratic Civic UniversityIra HarkavyThinking begins in... a forked-road situation, a situation that is ambiguous, that presents a dilemma, that poses alternatives.—John Dewey (How We Think 122)The social philosopher, dwelling in the region of his concepts, “solves” problems by showing the relationship of ideas, instead of helping men solve problems in the concrete by supplying them hypotheses to be used and tested in projects of (...) reform.—John Dewey (Reconstruction in Philosophy 192)Democracy must begin at home, and its home is the neighborly community.—John Dewey (The Public and Its Problems 213)democracy, as we all know, is seriously threatened throughout the world (Fisher). In the United States, the chasm-like inequities laid bare by COVID-19, the ongoing killing of black Americans, the violent insurrection at the Capitol, and the continuing attempt to subvert the electoral process are powerful indicators of a system under severe strain (Guardian Staff; Rubin). These developments are also a sign of deep and chronic problems, including the following:1. Increasing economic, political, social, educational, and health inequalities2. Increasing racism, anti-Semitism, and xenophobia3. Increasing attacks on science, knowledge, and democracy itself4. Declining trust in nearly all major institutionsMany things, obviously, contribute to the present situation. Among them is the failure of universities to successfully do what they are supposed to do: educate students to be ethical, empathetic, engaged, democratic citizens, and [End Page 49] advance knowledge for the continuous betterment of the human condition (Benson et al., Knowledge). To use a Marxian framework, but to reject its economic determinism, universities, in my judgment, are not a part of society’s superstructure. They are, to the contrary, a core component of its base (Marx, “Preface”). What they do matters enormously, significantly determining the kind of society we have now and will have in the future.Universities, as former Harvard president Derek Bok and others have emphasized, have become the central societal institutions in the world (Bok, Universities and the Future 3). Research universities, in my judgment, are the most central. They develop new ideas and technologies, incubate businesses, serve as cultural and artistic centers, and are engines of local, national, and global economies. As anchor institutions, they often engage in partnerships with government, the private sector, and community-based organizations to revitalize local neighborhoods and schools (“Anchor Institutions Task Force”). It is the university’s role as an educational institution, however, that is most important.The schooling system increasingly functions as the core subsystem—the strategic subsystem—of modern information societies. Schooling, more than any other subsystem, as John Dewey claimed, influences the functioning of the societal system as a whole. Viewed systemically, it has on balance the greatest “multiplier” effects, direct and indirect, short-term and long-term. Restating these points somewhat differently, I strongly agree with the Chilean sociologist Eugenio Tironi that the answer to the question “What kind of education do we need?” is to be found in the answer to the question “What kind of society do we want?” (Tironi). Education and society are dynamically interactive and interdependent. If human beings hope to maintain and develop a particular type of society, they must develop and maintain the particular type of education system conducive to it. As Dewey in effect argued: No effective democratic schooling system, no democratic society.1For William Rainey Harper, who, as the first president of the University of Chicago, brought Dewey to Chicago, universities are the primary shapers of the American schooling system. In an 1899 speech at the University of California, he perceptively observed that “[t]he school system, the character of which, in spite of itself, the university determines and in a large measure controls.... [T]hrough the school system every family in this entire broad land of ours is brought into touch with the university; for from it proceed the teachers or the teachers’ teachers” (Harper 25). Agreeing with Harper, I contend that higher education institutions powerfully shape the learning, values, and aspirations of students from kindergarten through graduate school. [End Page 50]Given the university’s societal role and influence, creating and sustaining an inclusive, just democratic society requires a... (shrink)

This article exploits the “binary license” offered by the title of the symposium in which it appears (“Comparative Relativism”) as a kind of promise of connection. The author suggests, however tentatively, that in the challenge of heterogeneity, fractality, perspective/-alism, and multiplicities lies the power of the forking pathway: the moment a relation is created through divergence. If we are invited—in the same breath—to consider forms of comparison and forms of relativism (dropping difference and similarity), we are also offered two paths, (...) one based on a world of singularities and multiplicities, and the other on a world of not-quite repetitions. The article asks if the binary is not essential to the epistemic work that Western (Euro-American) scholars might want to do, since we forever reinvent the divide between the modern and the post-/pre-modern. Strathern assumes the anthropologist's license to talk about concepts through persons, and begins by asking how Papua New Guineans who come together in a city compare themselves, and in contrast to ethnic comparisons elsewhere (e.g., contra Sarah Green's Balkan interactions). In talking about persons through concepts, it is worth asking what is entailed in relativizing one scholar's work through that of another. The author says that her “hunch” is that in both cases the analyst might wish to have the liberty of discerning—in the same breath—the multiplicities of what John Law and Annemarie Mol call perspectivalism (their very general alternative to comparison) and Eduardo Viveiros de Castro's radically divergent perspectivism (a self-contained, recursive and above all socially specific relativism). (shrink)

This study examines urban agriculture (UA) in Sacramento, California (USA), the nation's self-branded “Farm-to-Fork Capital,” in order to highlight UA’s distinct yet entangled roots. The study is based on 24 interviews with a diverse array of UA leaders, conducted as part of a five-year transdisciplinary study of UA in Sacramento. In it, we unearth three primary “taproots” of UA projects, each with its own historical legacies, normative visions, and racial dynamics. In particular, we examine UA projects with “justice taproots,” “health (...) taproots,” and “market taproots.” We use this analysis to understand how different kinds of UA projects are embedded in racial capitalism in ways that transform relationships between people, the city, and food systems. Unearthing these entangled roots helps illuminate UA’s underlying politics, showing how these roots grow in both competitive and symbiotic ways within the soil matrix of racial capitalism. We argue that these roots interact differently with racial capitalism, creating disparities in their growth trajectories. In particular, UA projects associated with the justice taproot are historically underrepresented and undervalued. However, we argue that there are some prospects for building alliances between the UA movement’s three roots, and that these are both promising and problematic. (shrink)

Replication protein A (RPA) is the main eukaryotic single‐stranded DNA (ssDNA) binding protein, having essential roles in all DNA metabolic reactions involving ssDNA. RPA binds ssDNA with high affinity, thereby preventing the formation of secondary structures and protecting ssDNA from the action of nucleases, and directly interacts with other DNA processing proteins. Here, we discuss recent results supporting the idea that one function of RPA is to prevent annealing between short repeats that can lead to chromosome rearrangements by microhomology‐mediated end (...) joining or the formation of hairpin structures that are substrates for structure‐selective nucleases. We suggest that replication fork catastrophe caused by depletion of RPA could result from cleavage of secondary structures by nucleases, and that failure to cleave hairpin structures formed at DNA ends could lead to gene amplification. These studies highlight the important role RPA plays in maintaining genome integrity. (shrink)

Computational imagination (CI) conceives imagination as an agent’s simulated sensorimotor interaction with the environment in the absence of sensory feedback, predicting consequences based on this interaction (Marques and Holland in Neurocomputing 72:743–759, 2009). Its bedrock is the simulation hypothesis whereby imagination resembles seeing or doing something in reality as both involve similar neural structures in the brain (Hesslow in Trends Cogn Sci 6(6):242–247, 2002). This paper raises two-forked doubts: (1) neural-level equivalence is escalated to make phenomenological equivalence. Even at an (...) abstract level, many imagined and real actions turn out to be dissimilar. More so, some imagined actions have no corresponding real actions and vice versa, even though neural regions involved in imaginings and real action-perception are the same (Sect. 1). (2) At the implementation level, the hypothesis presents a mutually exclusive view of imagination and perception whereby imagination functions in the absence of the sensory feedback and is action based. Both these issues are contested here: Neither imagination functions in the absence of perception nor all forms of imaginings are action based; it is, rather, about conceiving possibilities which emerge during the perceptual stage itself (Sect. 2). For the modal aspect to arise, it is submitted that an integrative framework is required which Kant can provide for whom imagination is an indispensable part of perception. Kant’s views on concept-formation are presented here to illustrate this aspect (Sect. 3). The Paper is concluded with emphasizing the relevance of Kant’s views to the problems identified in the two sections. (shrink)

Diversity is a good thing. Some of its value is instrumental. Having people around with diverse beliefs, or customs, or tastes, can expand our horizons and potentially raise to salience some potential true beliefs, useful customs or apt tastes. Even diversity of error can be useful. Seeing other people fall away from the true and the useful in distinctive ways can immunise us against similar errors. And there are a variety of pleasant interactions, not least philosophical exchange, that wouldn’t be (...) possible unless some kinds of diversity existed. Diversity may also have intrinsic value. It may be that a society with diverse views, customs and tastes is simply thereby a better society. But we will mostly focus on diversity’s instrumental value here. We think that what is true of these common types of diversity is also true of moral diversity. By moral diversity we mean not only diversity of moral views, though that is no doubt valuable, but diversity of moral behaviour. In a morally diverse society, at least some people will not conform as tightly to moral norms as others. In short, there will be some wrongdoers. To be sure, moral diversity has some costs, and too much of it is undoubtedly a bad thing. Having rapists and murderers adds to moral diversity (assuming, as we do, that most people are basically moral) but not in a way that is particularly valuable. Still, smaller amounts of moral diversity may be valuable, all things considered. It seems particularly clear that moral diversity within a subgroup has value, but sometimes society as a whole is better off for being morally diverse. Let us consider some examples. Many violations of etiquette are not moral transgressions. Eating asparagus spears with one’s fork is not sinful, just poor form. But more extreme violations may be sinful. Hurtful use of racial epithets, for example, is clearly immoral as well as a breach of etiquette. Even use of language that causes not hurt, but strong discomfort, may be morally wrong.. (shrink)

Phil Dowe, in Physical Causation, addresses such questions as 'What are causal processes and interactions?', 'What is the connection between causes and effects?', and 'What distinguishes a cause from its effect?' Dowe not only provides explicit and original answers to these questions, but, en route, provides important critiques of alternative answers as well as sophisticated discussions of negative causation, the fork asymmetry, and quantum mechanics.

We argue against some of Reichenbach's claims about causal forks are incorrect. We do not see why the Second Law of Thermodynamics rules out the existence of conjunctive forks open to the past. In addition, we argue that a common effect rarely forms a conjunctive fork with its joint causes, but it sometimes does. Nevertheless, we think there is something to be said for Reichenbach's idea that forks of various kinds are relevant to explaining why we know (...) more about the past than about the future. And entropy turns out to play a role in the explanation, though not the determining role that Reichenbach envisions. (shrink)

We prove that a theory T has stable forking if and only if Teq has stable forking.

For n≥3, define Tn to be the theory of the generic Kn-free graph, where Kn is the complete graph on n vertices. We prove a graph-theoretic characterization of dividing in Tn and use it to show that forking and dividing are the same for complete types. We then give an example of a forking and nondividing formula. Altogether, Tn provides a counterexample to a question of Chernikov and Kaplan.

We prove that in theories without the tree property of the second kind (which include dependent and simple theories) forking and dividing over models are the same, and in fact over any extension base. As an application we show that dependence is equivalent to bounded non-forking assuming NTP 2.

We discuss the role of weakly normal formulas in the theory of thorn forking, as part of a commentary on the paper [5]. We also give a counterexample to Corollary 4.2 from that paper, and in the process discuss “theories with selectors.”.

The stability theory of first order theories was initiated by Saharon Shelah in 1969. The classification of abstract elementary classes was initiated by Shelah, too. In several papers, he introduced non-forking relations. Later, Shelah [17, II] introduced the good non-forking frame, an axiomatization of the non-forking notion.We improve results of Shelah on good non-forking frames, mainly by weakening the stability hypothesis in several important theorems, replacing it by the almost λ-stability hypothesis: The number of types over a model of cardinality (...) λ is at most λ+.We present conditions on Kλ, that imply the existence of a model in Kλ+n for all n. We do this by providing sufficiently strong conditions on Kλ, that they are inherited by a properly chosen subclass of Kλ+. What are these conditions? We assume that there is a ‘non-forking’ relation which satisfies the properties of the non-forking relation on superstable first order theories. Note that here we deal with models of a fixed cardinality, λ.While in Shelah [17, II] we assume stability in λ, so we can use brimmed models, here we assume almost stability only, but we add an assumption: The conjugation property.In the context of elementary classes, the superstability assumption gives the existence of types with well-defined dimension and the ω-stability assumption gives the existence and uniqueness of models prime over sets. In our context, the local character assumption is an analog to superstability and the density of the class of uniqueness triples with respect to the relation ≼bs is the analog to ω-stability. (shrink)

We consider VC-minimal theories admitting unpackable generating families, and show that in such theories, forking of formulae over a model M is equivalent to containment in global types definable over M, generalizing a result of Dolich on o-minimal theories in [4].

We consider existentially closed fields with several orderings, valuations, and [Formula: see text]-valuations. We show that these structures are NTP2 of finite burden, but usually have the independence property. Moreover, forking agrees with dividing, and forking can be characterized in terms of forking in ACVF, RCF, and [Formula: see text]CF.