cssi/SciSciGPT-SciSciNet huggingface dataset:
The Communities That Make Standards of Care Possible

This paper argues that negligence law depends on "communities" in order to fulfill its agenda of promoting both security and freedom. Although many disciplines and discourses favor divergent understandings of the word "community," for purposes of the law the defining trait of community is group-based constraint. Communities can include various human aggregations. As far as the law understands this term, members need not have joined communities voluntarily, and the community need not have any leadership or power to change the lives of its members. Negligence law reaps benefits from the fact that certain groups exist. Their constraints make individuals less likely to hurt others (and thereby advance the "security" agenda) while sparing negligence law itself the political costs of repressing and deterring (i.e., "freedom"). In recognition of this adjuvant support, negligence law deems some group memberships relevant to its judgments about the standard of care. "Communities" in this sense helps to answer three vexing questions about the standard of care in negligence. First, what exactly is the "objective" standard of care that courts and commentators purport to favor, and what justifies it? Second, if the objective standard of care is proper, what justifies the various subjective exceptions that courts have created? Third, should the standard of care be the same for both plaintiffs and defendants?
Does Belief in Dualism Protect against Maladaptive Psycho-Social Responses to Deep Brain Stimulation? An Empirical Exploration

We provide empirical evidence that people who believe in dualism are more likely to be uncomfortable with Deep Brain Stimulation (DBS) and to view it as threatening to their identity, humanity, or self. It is (neurocentric) materialists—who think the mind just is the brain—that are less inclined to fear DBS or to see it as threatening. We suggest various possible reasons for this connection. The inspiration for this brief report is a target article that addresses this issue from a theoretical perspective. Mecacci and Haselager (MH this issue) offer several interesting hypotheses about the negative psycho-social side-effects of having an electronic device implanted in one’s brain via Deep Brain Stimulation (DBS), such as feeling like a different person or a machine. The authors argue that one’s beliefs about the relation between the mind and the body (e.g., dualism vs. materialism) can promote or attenuate such “psycho-social maladaptations.” One of their core hypotheses is that a belief in dualism protects against these effects, since “the stimulations will not touch one’s ‘genuine self’” if one believes “the brain is not involved in the very nature of your mind and self” (ms. p. 3). On the other hand, Mecacci and Haselager claim a belief in “neurocentric” materialism may lead one to “feel exposed to a personal disruption, for a stimulator interferes with what is responsible for the entire personal dimension, the brain” (ms. p. 3). If M&H are right, people who accept dualism should (a) be less likely to view DBS as a threat to personal identity, (b) be more comfortable with DBS in general, and (c) not see DBS as a procedure that would make people “less human.” These views, if true, are likely to hold for DBS patients as well as the general public. For example, nonDBS patients who are dualists should see DBS as less of a threat to personal identity than materialists would.
UN-LOCKING PATH DEPENDENCE TO BUILD ON AN INNOVATIVE FIRM’S ABSORPTIVE CAPACITY

Using a sample of 893 SMEs over a ten year period, we test how firms may reduce the inefficiencies in their absorptive capacity (ACAP) due to path dependence. Our research shows that for frequent innovators, potential absorptive capacity (PACAP) has a greater effect than realized absorptive capacity (RACAP). The reverse is also true for firms that innovate infrequently. Greater conversion efficiency (η) between PACAP and RACAP is counterproductive for innovators, indicating they are better off enhancing PACAP. For infrequent innovators, efficiency is critically important. For firms to reduce the effects of path dependence, η must be lower i.e. they must expand their PACAP to alter effectively knowledge paths and routines. Finally, alliances may help further increase the effectiveness of η on path creation and innovative performance. Our research has notable implications for the types of ACAP that are relevant under different innovation regimes and how firms may reduce inefficiencies due to path dependence by emphasizing path creation. Guidelines developed from this research could potentially provide assistance in urging firms to develop the most beneficial types of ACAP, which could be a source of competitive advantage.
The labor supply of self-employed workers: The choice of working hours in worker co-ops☆

Abstract Workers in cooperatives are self-employed workers and, if they resemble employees in conventional workplaces, they care about the length of their working hours. In this paper, their choice of hours is characterized as a conventional labor supply decision and a familiar hours-wage relationship is derived. This is estimated using mill-year observations on the plywood co-ops in the Pacific Northwest. The results are compared with those from the work behavior of other self-employed workers and with working hours in capitalist plywood mills.
Taxation and Doing Business in Indian Country

Furthering investment in Indian country (a term that includes, but is not limited to, reservations) is an important goal, but potential investors are hesitant - and with reason. One disincentive to invest is uncertainty about tax liability. Understanding taxation in Indian country requires knowledge not only of traditional tax law, but also of American Indian law principles dating from the early nineteenth century, and not many practitioners are up to that task. This article tries to make sense, as much as is possible, of the doctrines that have developed over the centuries. The article first discusses some basics: the concept of Indian country and various other doctrines of American Indian law that can affect the analysis of taxation (federal plenary power, the federal government's obligation to act as trustee for American Indian nations, tribal sovereignty, the nature of treaties between the U.S. and many tribes, and the Indian canons of construction). The article then discusses the power of various governments (federal, state, and tribal) to tax within Indian country. Among the subjects considered in depth are the federal government's power to tax tribes and tribal corporations; doctrines affecting state governments - taxing powers (including legal versus economic incidence, the infringement test, and the federal preemption doctrine); the limits on tribal power to tax non-Indians within Indian country; and doctrines affecting the ability of tribes to waive their taxing power in order to attract investors.
China's Foreign Trade: Perspectives From the Past 150 Years

This paper studies the trade of China in the past 150 years, starting from the first opening of China after the Opium War. The main purpose of the paper is to identify what is (and was) China’s ‘normal’ level of foreign trade, and how these levels changed under different trade regimes, from 1840 to the present. We present new evidence on China’s foreign trade during the treaty port era (1842–1948), drawn from disaggregated trade data collected by the Chinese Maritime Customs Service, that yields important findings for current research. First, although the volume of foreign trade remained limited initially, there was a notable expansion in the diversity of products, with many new goods being imported into China. Second, the regional diffusion of foreign goods through China was greatly facilitated by the expansions of the port system. Third, the importance of Hong Kong as an intermediary in China’s trade has undergone long-term fluctuations suggestive of learning effects. China’s recent wave of liberalization has led by the early 1990s to a trade level comparable to the high of the 1920s. While much of China’s recent growth in world trade is in line with her income growth, there is no doubt that China’s trade openness today, comparable by some measures to Denmark’s, is a stunning reversal relative to the pre-1978 and also the pre-1840 period. The paper emphasises the roles that history and institutional change have played in this.
Perceptual dimensions differentiate emotions

Individuals often describe objects in their world in terms of perceptual dimensions that span a variety of modalities; the visual (e.g., brightness: dark-bright), the auditory (e.g., loudness: quiet-loud), the gustatory (e.g., taste: sour-sweet), the tactile (e.g., hardness: soft vs. hard) and the kinaesthetic (e.g., speed: slow-fast). We ask whether individuals use perceptual dimensions to differentiate emotions from one another. Participants in two studies (one where respondents reported on abstract emotion concepts and a second where they reported on specific emotion episodes) rated the extent to which features anchoring 29 perceptual dimensions (e.g., temperature, texture and taste) are associated with 8 emotions (anger, fear, sadness, guilt, contentment, gratitude, pride and excitement). Results revealed that in both studies perceptual dimensions differentiate positive from negative emotions and high arousal from low arousal emotions. They also differentiate among emotions that are similar in arousal and valence (e.g., high arousal negative emotions such as anger and fear). Specific features that anchor particular perceptual dimensions (e.g., hot vs. cold) are also differentially associated with emotions.
Blogs, Advertising, and Local-Market Movie Box Office Performance

We measure the effects of pre-and postrelease blog volume, blog valence, and advertising on the performance of 75 movies in 208 geographic markets in the United States. We attribute the variation in blog effects across markets to differences in demographic characteristics of markets combined with differences across demographic groups in their access and exposure to blogs as well as their responsiveness conditional on access. We study the effects of prerelease factors on opening day box office performance and of pre-and postrelease factors on box office performance one month after release. Our estimation accounts for confounding factors in the measurement of these effects via the use of instrumental variables. We find considerable heterogeneity in the effects across consumer-and firm-generated media and across geographic markets, with gender, income, race, and age driving across-market differences. Release day performance is impacted most by prerelease blog volume and advertising, whereas postrelease performance is influenced by postrelease blog valence and advertising. Across markets, there is more variance in advertising and blog valence postrelease elasticities than there is in blog volume prerelease elasticities. We identify the top 20 markets in terms of their elasticities to each of these three instruments. Further, we classify markets in terms of their sensitivities across these three instruments to identify the most sensitive markets that studios can target with their limited release strategies. Finally, we characterize the extent to which studios could have improved their limited release strategies by identifying the overlap between the actual release markets and the most responsive ones. We find that at the time of first-release studios cover only 53% of the most responsive advertising markets and 44% of the most responsive markets to prerelease blog volume in their limited release strategies, implying considerable room for improvement if these were the only metrics to assess those strategies. This paper was accepted by Gerard P. Cachon, marketing.
A Generalized Method for Detecting Abnormal Returns and Changes in Systematic Risk

We generalize traditional event-study techniques to allow for event-induced parameter shifts, shifting variances, and firm-specific event periods. Our method, which nests traditional methods, also permits systematic risk to change gradually during the event period and exit the period at higher or lower levels. We use our approach to study 123 banks that acquired other institutions between 1989 and 1995. We find a significant change in the systematic risk of the acquiring firms, significant ARCH effects, and an event period that ends before the date of the announcement. None of these results is detectable using conventional methods.
Time: Text and image mutual-translation adversarial networks

Focusing on text-to-image (T2I) generation, we propose Text and Image Mutual-Translation Adversarial Networks (TIME), a lightweight but effective model that jointly learns a T2I generator G and an image captioning discriminator D under the Generative Adversarial Network framework. While previous methods tackle the T2I problem as a uni-directional task and use pre-trained language models to enforce the image--text consistency, TIME requires neither extra modules nor pre-training. We show that the performance of G can be boosted substantially by training it jointly with D as a language model. Specifically, we adopt Transformers to model the cross-modal connections between the image features and word embeddings, and design an annealing conditional hinge loss that dynamically balances the adversarial learning. In our experiments, TIME achieves state-of-the-art (SOTA) performance on the CUB dataset (Inception Score of 4.91 and Frechet Inception Distance of 14.3 on CUB), and shows promising performance on MS-COCO dataset on image captioning and downstream vision-language tasks.
A Supply Chain Theory of Factoring and Reverse Factoring

Factoring is a financial arrangement where the supplier sells accounts receivable to the factor against a premium and receives cash for immediate working capital needs. Reverse factoring takes adva...
GraphEBM: Molecular Graph Generation with Energy-Based Models

We note that most existing approaches for molecular graph generation fail to guarantee the intrinsic property of permutation invariance, resulting in unexpected bias in generative models. In this work, we propose GraphEBM to generate molecular graphs using energy-based models. In particular, we parameterize the energy function in a permutation invariant manner, thus making GraphEBM permutation invariant. We apply Langevin dynamics to train the energy function by approximately maximizing likelihood and generate samples with low energies. Furthermore, to generate molecules with a desirable property, we propose a simple yet effective strategy, which pushes down energies with flexible degrees according to the properties of corresponding molecules. Finally, we explore the use of GraphEBM for generating molecules with multiple objectives in a compositional manner. Comprehensive experimental results on random, goal-directed, and compositional generation tasks demonstrate the effectiveness of our proposed method.
Robust and Sample Optimal Algorithms for PSD Low Rank Approximation

Recently, Musco and Woodruff (FOCS, 2017) showed that given an $n\times n$ positive semidefinite (PSD) matrix A, it is possible to compute a $(1+\epsilon$ -approximate relative-error low-rank approximation to A by querying $\tilde{O}(nk/\epsilon^{2.5})$ entries of A in time $\tilde{O}(nk/\epsilon^{2.5}+nk^{\omega-1}/\epsilon^{2(\omega-1)})$ . They also showed that any relative-error low-rank approximation algorithm must query $\Omega(nk/\epsilon)$ entries of A, this gap has since remained open. Our main result is to resolve this question by obtaining an optimal algorithm that queries $\tilde{O}(nk/\epsilon)$ entries of A and outputs a relative-error low-rank approximation in $\tilde{O}(n\cdot(k/\epsilon)^{\omega-1})$ time. Note, our running time improves that of Musco and Woodruff, and matches the information-theoretic lower bound if the matrix-multiplication exponent $\omega$ is 2. We then extend our techniques to negative-type distance matrices. Here, our input is a pair-wise distance matrix A corresponding to a point set $\mathcal{P}=\{x_{1}, x_{2}, \ldots, x_{n}\}$ such that $\mathrm{A}_{i, j}=\Vert x_{i}-x_{j}\Vert_{2}^{2}$ . Bakshi and Woodruff (NeurIPS, 2018) showed a bi-criteria, relative-error low-rank approximation for negative-type metrics. Their algorithm queries $\tilde{O}(nk/\epsilon^{2.5})$ entries and outputs a rank-( $k+4$ ) matrix. We show that the bi-criteria guarantee is not necessary and obtain an $\tilde{O}(nk/\epsilon)$ query algorithm, which is optimal. Our algorithm applies to all distance matrices that arise from metrics satisfying negative-type inequalities, including $\ell_{1},\ell_{2}$ , spherical metrics, hypermetrics and effective resistances on a graph. We also obtain faster algorithms for ridge regression. Next, we introduce a new robust low-rank approximation model which captures PSD matrices that have been corrupted with noise. We assume that the Frobenius norm of the corruption is bounded. Here, we relax the notion of approximation to additive-error, since it is information-theoretically impossible to obtain a relative-error approximation in this setting. While a sample complexity lower bound precludes sublinear algorithms for arbitrary PSD matrices, we provide the first sublinear time and query algorithms when the corruption on the diagonal entries is bounded. As a special case, we show sample-optimal sublinear time algorithms for low-rank approximation of correlation matrices corrupted by noise.
Phase boundary near a magnetic percolation transition

Motivated by recent experimental observations [Rowley et al. in Phys Rev 96:020407, 2017] on hexagonal ferrites, we revisit the phase diagrams of diluted magnets close to the lattice percolation threshold. We perform large-scale Monte Carlo simulations of XY and Heisenberg models on both simple cubic lattices and lattices representing the crystal structure of the hexagonal ferrites. Close to the percolation threshold $$p_\mathrm{c}$$ , we find that the magnetic ordering temperature $$T_\mathrm{c}$$ depends on the dilution p via the power law $$T_\mathrm{c} \sim |p-p_\mathrm{c}|^\phi $$ with exponent $$\phi =1.09$$ , in agreement with classical percolation theory. However, this asymptotic critical region is very narrow, $$|p-p_\mathrm{c}| \lesssim 0.04$$ . Outside of it, the shape of the phase boundary is well described, over a wide range of dilutions, by a nonuniversal power law with an exponent somewhat below unity. Nonetheless, the percolation scenario does not reproduce the experimentally observed relation $$T_\mathrm{c} \sim (x_\mathrm{c} -x)^{2/3}$$ in PbFe $$_{12-x}$$ Ga $$_x$$ O $$_{19}$$ . We discuss the generality of our findings as well as implications for the physics of diluted hexagonal ferrites.
Management of vestibular dysfunction and hearing loss in intralabyrinthine schwannomas.

Abstract Purpose Intralabyrinthine schwannomas (ILS) are rare, benign, slow-growing tumors arising from schwann cells of the cochlear or vestibular nerves within the bony labyrinth. This study provides insight into the management of this rare tumor through a large case series. Materials and methods After Institutional Review Board approval, a retrospective chart review was performed of all ILS patients treated at our institution between 2007 and 2019. Results 20 patients (9 male, 11 female) with ILS were managed at our institution. The right ear was affected in 9 patients (45%) and the left in 11 (55%). Subjective hearing loss was endorsed by all 20 patients. Average pure tone average at presentation was 72 dB nHL. Nine tumors (45%) were intravestibular, 6 (30%) were intracochlear, 4 (20%) were transmodiolar and 1 (5%) was intravestibulocochlear. Hearings aids were used in 3 patients (15%), BiCROS in 2 (10%), CI in 2 (10%), and bone conduction implant in 1 (5%). Vestibular rehabilitation was pursued in 5 patients. Surgical excision was performed for one patient (5%) via translabyrinthine approach due to intractable vertigo. No patients received radiotherapy or intratympanic gentamicin injections. Conclusion ILS presents a diagnostic and management challenge given the similarity of symptoms with other disorders and limited treatment options. Hearing loss may be managed on a case-by-case basis according to patient symptoms while vestibular loss may be mitigated with vestibular therapy. Surgical excision may be considered in patients with intractable vertigo, severe hearing loss with concurrent CI placement, or in other case-by-case situations.
Evaluating Resilience of Electricity Distribution Networks via a Modification of Generalized Benders Decomposition Method

This article presents a computational framework to evaluate the resilience of electricity distribution networks (DNs) to a class of cyber-physical failures. In our model, we consider an attacker who targets multiple DN components to maximize the loss of the DN operator. We consider two types of operator responses: i) coordinated emergency response and ii) uncoordinated autonomous disconnects, which may lead to cascading failures. To evaluate resilience under response i), we consider a bilevel mixed-integer second-order cone program. This problem is computationally challenging to solve due to mixed-integer variables in the inner problem and nonconvex constraints. Our solution approach exploits the properties of power flows on radial DNs operating in a postattack contingency state to refine the classical generalized Benders decomposition method. Specifically, we suggest a modification of the right-hand side of the generalized Benders cut to be a value determined by the sum of values of a subset of inner dual cost coefficients. We show how the size of this subset can be selected to achieve a reasonable tradeoff between solution accuracy and computational effort. Furthermore, we evaluate DN resilience under response ii) by sequentially computing autonomous component disconnects due to operating bound violations resulting from the initial attack and the potential cascading failures. Our approach is useful for estimating the gain in resilience under response i), relative to ii).
Experimental re-infected cats do not transmit SARS-CoV-2.

SARS-CoV-2 is the causative agent of COVID-19 and responsible for the current global pandemic. We and others have previously demonstrated that cats are susceptible to SARS-CoV-2 infection and can efficiently transmit the virus to naive cats. Here, we address whether cats previously exposed to SARS-CoV-2 can be re-infected with SARS-CoV-2. In two independent studies, SARS-CoV-2-infected cats were re-challenged with SARS-CoV-2 at 21 days post primary challenge (DPC) and necropsies performed at 4, 7 and 14 days post-secondary challenge (DP2C). Sentinels were co-mingled with the re-challenged cats at 1 DP2C. Clinical signs were recorded, and nasal, oropharyngeal, and rectal swabs, blood, and serum were collected and tissues examined for histologic lesions. Viral RNA was transiently shed via the nasal, oropharyngeal and rectal cavities of the re-challenged cats. Viral RNA was detected in various tissues of re-challenged cats euthanized at 4 DP2C, mainly in the upper respiratory tract and lymphoid tissues, but less frequently and at lower levels in the lower respiratory tract when compared to primary SARS-CoV-2 challenged cats at 4 DPC. Viral RNA and antigen detected in the respiratory tract of the primary SARS-CoV-2 infected cats at early DPCs were absent in the re-challenged cats. Naive sentinels co-housed with the re-challenged cats did not shed virus or seroconvert. Together, our results indicate that cats previously infected with SARS-CoV-2 can be experimentally re-infected with SARS-CoV-2; however, the levels of virus shed was insufficient for transmission to co-housed naive sentinels. We conclude that SARS-CoV-2 infection in cats induces immune responses that provide partial, non-sterilizing immune protection against re-infection.
Computing Helioseismic Sensitivity Kernels for the Sun’s Large-scale Internal Flows Using Global-scale Wave-propagation Simulations

Helioseismic waves observable at the solar surface can be used to probe the properties of the Sun's interior. By measuring helioseismic travel times between different location on the surface, flows and other interior properties can be inferred using so-called sensitivity kernels which relate the amount of travel-time shift with variations in interior proporties. In particular, sensitivity kernels for flows have been developed in the past, using either ray or Born approximation, and have been used to infer solar interior flows such as the meridional circulation which is of particular interest for understanding the structure and dynamics of the Sun. Here we introduce a new method for deriving three-dimensional sensitivity kernels for large-scale horizontal flows in the solar interior. We perform global-Sun wave-propagation simulations through 784 small flow perturbations placed individually in the interior of a simulated Sun, and measure the shifts in helioseismic travel times caused by these perturbations. Each measurement corresponds to a linear equation connecting the flow perturbation velocities and the sensitivity kernels. By solving the resulting large set of coupled linear equations, we derive three-dimensional sensitivity kernels for horizontal flows which have a longitudinal component (parallel to the wave's travel direction) and a transverse component (perpendicular to the wave's travel direction). The kernels exhibit a "banana" shape, similar to kernels derived using Born approximation methods, and show that transverse components are not negligible in inversions for interior flows.
Time-critical multiresolution volume rendering using 3D texture mapping hardware

This paper presents a LOD selection algorithm for multiresolution volume rendering using 3D texture mapping hardware. The goal of the algorithm is to select appropriate LODs automatically from a volume hierarchy so that the rendering speed will match the user's desired frame rate. To achieve this goal, we devise an intra-frame predictive-reactive scheme, which controls the rendering time by collecting run-time performance statistics and performing dynamic LOD selections. Our algorithm takes into account user-specified volume importance criteria when distributing the time budget, so regions of interest can be rendered at a higher quality. Experiments showed that our algorithm can control the rendering speed with less than 10% of error from the user's target frame rate.
Zoom on the Keystrokes: Exploiting Video Calls for Keystroke Inference Attacks.

Due to recent world events, video calls have become the new norm for both personal and professional remote communication. However, if a participant in a video call is not careful, he/she can reveal his/her private information to others in the call. In this paper, we design and evaluate an attack framework to infer one type of such private information from the video stream of a call -- keystrokes, i.e., text typed during the call. We evaluate our video-based keystroke inference framework using different experimental settings and parameters, including different webcams, video resolutions, keyboards, clothing, and backgrounds. Our relatively high keystroke inference accuracies under commonly occurring and realistic settings highlight the need for awareness and countermeasures against such attacks. Consequently, we also propose and evaluate effective mitigation techniques that can automatically protect users when they type during a video call.
In-Hospital Outcomes of Admissions and 30-day Re-Admissions for Acute Allograft Rejection after Heart Transplantation

Purpose The incidence of acute cardiac allograft rejection and mortality after heart transplantation (HT) have declined. We aimed to investigate the clinical outcomes of acute cardiac allograft rejection after HT requiring hospitalization. Methods Two distinct cohort were analyzed. The National Inpatient Sample (NIS) was queried to identify HT recipients admitted for acute rejection between 2015 to 2017 and analyze clinical outcomes and respective predictors. The National Readmission Database (NRD) was utilized to identify patients who underwent heart transplantation from 2016 to 2017 to analyze 30-day readmission. Results A total of 3,790 patients were admitted for HT rejection in the NIS cohort. Serious adverse events such as death in 4.1%, ventricular tachycardia in 5.4%, cardiogenic shock in 10.8% and use of extracorporeal membrane oxygenation in 2.5% were found. Female gender was associated with in-hospital death (odds ratio [OR] 4.48, 95% confidence interval [CI] 1.52-13.1, p=0.006). Younger age and end-stage renal disease were identified as independent predictors of transplant graft failure (OR 0.95, 95% CI 0.93-0.98, p=0.001, OR 3.65, 95% CI 1.22-10.99, p=0.021, respectively). Among 5,817 patients who were admitted for HT in the NRD cohort, 209 (3.6%) were readmitted within 30 days for transplant rejection with most occurring within 15 days. Younger age and female gender were associated with significantly increased risk of 30-day readmission for transplant rejection (OR 0.99, 95% CI 0.98-1.00, p=0.043; OR 1.43, 95% CI 1.00-2.03, p=0.048, respectively). No cases of mortality and utilization of mechanical circulatory support were identified. Conclusion Although early re-admissions for acute rejection after HT are infrequent and not associated with serious adverse effects, overall admissions for acute rejection are not uncommon and serious adverse events occur in a portion of these patients.
Flatter Is Better: Percentile Transformations for Recommender Systems

It is well known that explicit user ratings in recommender systems are biased toward high ratings and that users differ significantly in their usage of the rating scale. Implementers usually compensate for these issues through rating normalization or the inclusion of a user bias term in factorization models. However, these methods adjust only for the central tendency of users’ distributions. In this work, we demonstrate that a lack of flatness in rating distributions is negatively correlated with recommendation performance. We propose a rating transformation model that compensates for skew in the rating distribution as well as its central tendency by converting ratings into percentile values as a pre-processing step before recommendation generation. This transformation flattens the rating distribution, better compensates for differences in rating distributions, and improves recommendation performance. We also show that a smoothed version of this transformation can yield more intuitive results for users with very narrow rating distributions. A comprehensive set of experiments, with state-of-the-art recommendation algorithms in four real-world datasets, show improved ranking performance for these percentile transformations.
Early developmental asymmetries in cell lineage trees in living individuals

Mosaic mutations can be used to track cell lineages in humans. We used cell cloning to analyze embryonic cell lineages in two living individuals and a postmortem human specimen. Of 10 reconstructed postzygotic divisions, none resulted in balanced contributions of daughter lineages to tissues. In both living individuals, one of two lineages from the first cleavage was dominant across tissues, with 90% frequency in blood. We propose that the efficiency of DNA repair contributes to lineage imbalance. Allocation of lineages in postmortem brain correlated with anterior-posterior axis, associating lineage history with cell fate choices in embryos. We establish a minimally invasive framework for defining cell lineages in any living individual, which paves the way for studying their relevance in health and disease.
Party systems and public goods: the dynamics of good governance in the Indian states

We argue that two key party system characteristics – the effective number of parties and electoral volatility – have a curvilinear, inverted-U shaped, influence on public goods provision. Rejecting...
Re-examining rates of lithium-ion battery technology improvement and cost decline

Lithium-ion technologies are increasingly employed to electrify transportation and provide stationary energy storage for electrical grids, and as such their development has garnered much attention. However, their deployment is still relatively limited, and their broader adoption will depend on their potential for cost reduction and performance improvement. Understanding this potential can inform critical climate change mitigation strategies, including public policies and technology development efforts. However, many existing estimates of past cost decline, which often serve as starting points for forecasting models, rely on limited data series and measures of technological progress. Here we systematically collect, harmonize, and combine various data series of price, market size, research and development, and performance of lithium-ion technologies. We then develop representative series for these measures, while separating cylindrical cells from all types of cells. For both, we find that the real price of lithium-ion cells, scaled by their energy capacity, has declined by about 97% since their commercial introduction in 1991. We estimate that between 1992 and 2016, real price per energy capacity declined 13% per year for both all types of cells and cylindrical cells, and upon a doubling of cumulative market size, decreased 20% for all types of cells and 24% for cylindrical cells. We also consider additional performance characteristics including energy density and specific energy. When energy density is incorporated into the definition of service provided by a lithium-ion battery, estimated technological improvement rates increase considerably. The annual decline in real price per service increases from 13 to 17% for both all types of cells and cylindrical cells while learning rates increase from 20 to 27% for all cell shapes and 24 to 31% for cylindrical cells. These increases suggest that previously reported improvement rates might underestimate the rate of lithium-ion technologies' change. Moreover, our improvement rate estimates suggest the degree to which lithium-ion technologies' price decline might have been limited by performance requirements other than cost per energy capacity. These rates also suggest that battery technologies developed for stationary applications, where restrictions on volume and mass are relaxed, might achieve faster cost declines, though engineering-based mechanistic cost modeling is required to further characterize this potential. The methods employed to collect these data and estimate improvement rates are designed to serve as a blueprint for how to work with sparse data when making consequential measurements of technological change.
Towards an Open Format for Scalable System Telemetry

A data representation for system behavior telemetry for scalable big data security analytics is presented, affording telemetry consumers comprehensive visibility into workloads at reduced storage and processing overheads. The new abstraction, SysFlow, is a compact open data format that lifts the representation of system activities into a flow-centric, object-relational mapping that records how applications interact with their environment, relating processes to file accesses, network activities, and runtime information. The telemetry format supports single-event and volumetric flow representations of process control flows, file interactions, and network communications. Evaluation on enterprise-grade benchmarks shows that SysFlow facilitates deeper introspection into attack kill chains while yielding traces orders of magnitude smaller than current state-of-the-art system telemetry approaches—drastically reducing storage requirements and enabling feature-filled system analytics, process-level provenance tracking, and long-term data archival for cyber threat discovery and forensic analysis on historical data.
All Possible Symmetries of the S Matrix

We prove a new theorem on the impossibility of combining space-time and internal symmetries in any but a trivial way. The theorem is an improvement on known results in that it is applicable to infinite-parameter groups, instead of just to Lie groups. This improvement is gained by using information about the $S$ matrix; previous investigations used only information about the single-particle spectrum. We define a symmetry group of the $S$ matrix as a group of unitary operators which turn one-particle states into one-particle states, transform many-particle states as if they were tensor products, and commute with the $S$ matrix. Let $G$ be a connected symmetry group of the $S$ matrix, and let the following five conditions hold: (1) $G$ contains a subgroup locally isomorphic to the Poincar\'e group. (2) For any $Mg0$, there are only a finite number of one-particle states with mass less than $M$. (3) Elastic scattering amplitudes are analytic functions of $s$ and $t$, in some neighborhood of the physical region. (4) The $S$ matrix is nontrivial in the sense that any two one-particle momentum eigenstates scatter (into something), except perhaps at isolated values of $s$. (5) The generators of $G$, written as integral operators in momentum space, have distributions for their kernels. Then, we show that $G$ is necessarily locally isomorphic to the direct product of an internal symmetry group and the Poincar\'e group.
TURL: Table Understanding through Representation Learning

Relational tables on the Web store a vast amount of knowledge. Owing to the wealth of such tables, there has been tremendous progress on a variety of tasks in the area of table understanding. However, existing work generally relies on heavily-engineered task specific features and model architectures. In this paper, we present TURL, a novel framework that introduces the pre-training/finetuning paradigm to relational Web tables. During pre-training, our framework learns deep contextualized representations on relational tables in an unsupervised manner. Its universal model design with pre-trained representations can be applied to a wide range of tasks with minimal task-specific fine-tuning. Specifically, we propose a structure-aware Transformer encoder to model the row-column structure of relational tables, and present a new Masked Entity Recovery (MER) objective for pre-training to capture the semantics and knowledge in large-scale unlabeled data. We systematically evaluate TURL with a benchmark consisting of 6 different tasks for table understanding (e.g., relation extraction, cell filling). We show that TURL generalizes well to all tasks and substantially outperforms existing methods in almost all instances.
Optimal Taxation with Multiple Dimensions of Heterogeneity

Abstract This paper develops a general theory of optimal income taxation with multiple dimensions of agent heterogeneity. The main technical hurdle in developing this theory is the possibility that individuals have multiple optimal incomes. Using a perturbation approach, we derive optimal tax formulas that account for the possibility that individuals have multiple optima and, hence, account for the possibility that individuals jump between their optimal income levels when we perturb the tax schedule. We quantify the magnitude of these effects, thereby augmenting the optimal tax formulas from Saez (2001) with additional “jumping effect” terms. We provide a partial characterization of when individuals with multiple optimal incomes may exist under the optimal tax schedule. Finally, we derive a new methodology to simulate optimal income tax schedules with multidimensional heterogeneity. We implement this method numerically, showing that individuals with multiple optimal income levels can exist under the optimal tax schedule.
The Reissner Fiber is Highly Dynamic in Vivo and Controls Morphogenesis of the Spine

Spine morphogenesis requires the integration of multiple musculoskeletal tissues with the nervous system. Cerebrospinal fluid (CSF) physiology is important for development and homeostasis of the central nervous system and its disruption has been linked to scoliosis in zebrafish. Suspended in the CSF is an enigmatic glycoprotein thread called the Reissner fiber, which is secreted from the subcomissural organ (SCO) in the brain and extends caudally through the central canal to where it terminates at the base of the spinal cord. In zebrafish, scospondin null mutants are unable to assemble the Reissner fiber and fail to extend a straight body axis during embryonic development. Here, we describe zebrafish hypomorphic missense alleles, which assemble the Reissner fiber and straighten the body axis during early embryonic development, yet progressively lose the fiber, concomitant with the emergence of body curvature, alterations in neuronal gene expression, and scoliosis in adults. Using an endogenously tagged scospondin-GFP zebrafish knock-in line, we directly visualized Reissner fiber dynamics during the normal development and during the progression of scoliosis, and demonstrate that the Reissner fiber is critical for the morphogenesis of the spine. Our study establishes a framework for future investigations of mechanistic roles of the Reissner fiber including its dynamic properties, molecular interactions, and how these processes are involved in the regulation of spine morphogenesis and scoliosis.
Small Business and Copyright Ownership

This article attempts to facilitate the recognition of situations involving copyright and the appropriate arrangements regarding ownership of the right. Part II briefly outlines some copyright basics, including the varieties of copyrightable subject matter under the Copyright Act of 1976. Part III describes copyright ownership, focusing on the kinds of transactions most likely to take place in the context of small business, including the “work for hire” doctrine. Armed with these fundamentals, the small-business lawyer may find that copyright litigation will rarely become necessary.
Total Synthesis of (−)-Callystatin A

[reaction: see text] A convergent enantioselective synthesis of the natural product (-)-callystatin A (1) is described. Key features of the synthesis include a lipase-mediated kinetic resolution to install the C5 lactone stereochemistry, a hydrozirconation-based approach to the C8-C9 trisubstituted (Z)-olefin, and a stereoselective cross-coupling of a vinyl dibromide to install the C14-C15 trisubstituted (E)-olefin.
Improved Sobolev Inequality Under Constraints

We give a new proof of Aubin's improvement of the Sobolev inequality on $\mathbb{S}^{n}$ under the vanishing of first order moments of the area element and generalize it to higher order moments case. By careful study of an extremal problem on $\mathbb{S}^{n}$, we determine the constant explicitly in the second order moments case.
Multi-facet Universal Schema

Universal schema (USchema) assumes that two sentence patterns that share the same entity pairs are similar to each other. This assumption is widely adopted for solving various types of relation extraction (RE) tasks. Nevertheless, each sentence pattern could contain multiple facets, and not every facet is similar to all the facets of another sentence pattern co-occurring with the same entity pair. To address the violation of the USchema assumption, we propose multi-facet universal schema that uses a neural model to represent each sentence pattern as multiple facet embeddings and encourage one of these facet embeddings to be close to that of another sentence pattern if they co-occur with the same entity pair. In our experiments, we demonstrate that multi-facet embeddings significantly outperform their single-facet embedding counterpart, compositional universal schema (CUSchema) (Verga et al., 2016), in distantly supervised relation extraction tasks. Moreover, we can also use multiple embeddings to detect the entailment relation between two sentence patterns when no manual label is available.
Modeling Time-Varying Random Objects and Dynamic Networks

Samples of dynamic or time-varying networks and other random object data such as time-varying probability distributions are increasingly encountered in modern data analysis. Common methods for time...
Spatially Quasi-Periodic Water Waves of Infinite Depth

We formulate the two-dimensional gravity-capillary water wave equations in a spatially quasi-periodic setting and present a numerical study of solutions of the initial value problem. We propose a Fourier pseudo-spectral discretization of the equations of motion in which one-dimensional quasi-periodic functions are represented by two-dimensional periodic functions on a torus. We adopt a conformal mapping formulation and employ a quasi-periodic version of the Hilbert transform to determine the normal velocity of the free surface. Two methods of time-stepping the initial value problem are proposed, an explicit Runge–Kutta (ERK) method and an exponential time-differencing (ETD) scheme. The ETD approach makes use of the small-scale decomposition to eliminate stiffness due to surface tension. We perform a convergence study to compare the accuracy and efficiency of the methods on a traveling wave test problem. We also present an example of a periodic wave profile containing vertical tangent lines that is set in motion with a quasi-periodic velocity potential. As time evolves, each wave peak evolves differently, and only some of them overturn. Beyond water waves, we argue that spatial quasi-periodicity is a natural setting to study the dynamics of linear and nonlinear waves, offering a third option to the usual modeling assumption that solutions either evolve on a periodic domain or decay at infinity.
Cognitive and Motor Perseveration Are Associated in Older Adults.

Aging causes perseveration (difficulty to switch between actions) in motor and cognitive tasks, suggesting that the same neural processes could govern these abilities in older adults. To test this, we evaluated the relation between independently measured motor and cognitive perseveration in young (21.4 ± 3.7 y/o) and older participants (76.5 ± 2.9 y/o). Motor perseveration was measured with a locomotor task in which participants had to transition between distinct walking patterns. Cognitive perseveration was measured with a card matching task in which participants had to switch between distinct matching rules. We found that perseveration in the cognitive and motor domains were positively related in older, but not younger individuals, such that participants exhibiting greater perseveration in the motor task also perseverated more in the cognitive task. Additionally, exposure reduces motor perseveration: older adults who had practiced the motor task could transition between walking patterns as proficiently as naive, young individuals. Our results suggest an overlap in neural processes governing cognitive and motor perseveration with aging and that exposure can counteract the age-related motor perseveration.