cssi/SciSciGPT-SciSciNet huggingface dataset:
On the number of experiments sufficient and in the worst case necessary to identify all causal relations among N variables

We show that if any number of variables are allowed to be simultaneously and independently randomized in any one experiment, log2(N) + 1 experiments are sufficient and in the worst case necessary to determine the causal relations among N ≥ 2 variables when no latent variables, no sample selection bias and no feedback cycles are present. For all K, 0 < K < 1/2N we provide an upper bound on the number experiments required to determine causal structure when each experiment simultaneously randomizes K variables. For large N, these bounds are significantly lower than the N - 1 bound required when each experiment randomizes at most one variable. For kmax < N/2, we show that (N/kmaz -1) + N/2kmax log2(kmax) experiments are sufficient and in the worst case necessary. We offer a conjecture as to the minimal number of experiments that are in the worst case sufficient to identify all causal relations among N observed variables that are a subset of the vertices of a DAG.
Equivariant quantum Schubert polynomials

Abstract We establish an equivariant quantum Giambelli formula for partial flag varieties. The answer is given in terms of a specialization of universal double Schubert polynomials. Along the way, we give new proofs of the presentation of the equivariant quantum cohomology ring, as well as Graham-positivity of the structure constants in equivariant quantum Schubert calculus.
Moser stability for volume forms on noncompact fiber bundles

Abstract We prove a stability result for volume forms on fiber bundles with compact base and noncompact fibers. This generalizes the classical results of Moser and Greene–Shiohama, and recent work by the authors.
Exercising control when confronted by a (Brownian) spider

We consider the Brownian "spider," a construct introduced in Dubins and Schwarz (1988) and in Barlow and Pitman (1989). In this note, the author proves the "spider" bounds by using the dynamic programming strategy of guessing the optimal reward function and subsequently establishing its optimality by proving its excessiveness.
Permanence and Stability of a Kill the Winner Model in Marine Ecology.

We focus on the long-term dynamics of “killing the winner” Lotka–Volterra models of marine communities consisting of bacteria, virus, and zooplankton. Under suitable conditions, it is shown that there is a unique equilibrium with all populations present which is stable, the system is permanent, and the limiting behavior of its solutions is strongly constrained.
Tuning goodness-of-fit tests†

As modern precision cosmological measurements continue to show agreement with the broad features of the standard $\Lambda$-Cold Dark Matter ($\Lambda$CDM) cosmological model, we are increasingly motivated to look for small departures from the standard model's predictions which might not be detected with standard approaches. While searches for extensions and modifications of $\Lambda$CDM have to date turned up no convincing evidence of beyond-the-standard-model cosmology, the list of models compared against $\Lambda$CDM is by no means complete and is often governed by readily-coded modifications to standard Boltzmann codes. Also, standard goodness-of-fit methods such as a naive $\chi^2$ test fail to put strong pressure on the null $\Lambda$CDM hypothesis, since modern datasets have orders of magnitudes more degrees of freedom than $\Lambda$CDM. Here we present a method of tuning goodness-of-fit tests to detect potential sub-dominant extra-$\Lambda$CDM signals present in the data through compressing observations in a way that maximizes extra-$\Lambda$CDM signal variation over noise and $\Lambda$CDM variation. This method, based on a Karhunen-Loeve transformation of the data, is tuned to be maximally sensitive to particular types of variations characteristic of the tuning model; but, unlike direct model comparison, the test is also sensitive to features that only partially mimic the tuning model. As an example of its use, we apply this method in the context of a nonstandard primordial power spectrum compared against the $2015$ $Planck$ CMB temperature and polarization power spectrum. We find weak evidence of extra-$\Lambda$CDM physics, conceivably due to known systematics in the 2015 Planck polarization release.
Cache-Aided Interference Management using Hypercube Combinatorial Cache Designs

We consider a cache-aided interference network which consists of a library of N files, K&#60;sub&#62;T&#60;&#x002F;sub&#62; transmitters and K&#60;sub&#62;R&#60;&#x002F;sub&#62; receivers (users), each equipped with a local cache of size M&#60;sub&#62;T&#60;&#x002F;sub&#62; and M&#60;sub&#62;R&#60;&#x002F;sub&#62; files respectively, and connected via a discrete-time additive white Gaussian noise channel. Each receiver requests an arbitrary file from the library. The objective is to design a cache placement without knowing the receivers' requests and a communication scheme such that the sum Degrees of Freedom (sum-DoF) of the delivery is maximized. This network model has been investigated by Naderializadeh et al., who proposed a prefetching and a delivery scheme that achieve a sum-DoF of min{M&#60;sub&#62;T&#60;&#x002F;sub&#62; K&#60;sub&#62;T&#60;&#x002F;sub&#62; &#x002B; K&#60;sub&#62;R&#60;&#x002F;sub&#62; M&#60;sub&#62;R&#60;&#x002F;sub&#62;&#x002F;N, K&#60;sub&#62;R&#60;&#x002F;sub&#62;}. One of the biggest limitations of this scheme is the requirement of high subpacketization level. This paper attempts to design new algorithms to reduce the file subpacketization in such a network. In particular, we propose a new approach for both prefetching and linear delivery based on a combinatorial design called hypercube. We show that the required number of packets per file can be exponentially reduced compared to the state-of-the-art scheme proposed by Naderializadeh et al., or the NMA scheme. When M&#60;sub&#62;T&#60;&#x002F;sub&#62; K&#60;sub&#62;T&#60;&#x002F;sub&#62; &#x002B; K&#60;sub&#62;R&#60;&#x002F;sub&#62; M&#60;sub&#62;R&#60;&#x002F;sub&#62; &#x2264; K&#60;sub&#62;R&#60;&#x002F;sub&#62;, the achievable one-shot sum-DoF using this approach is M&#60;sub&#62;T&#60;&#x002F;sub&#62; K&#60;sub&#62;T&#60;&#x002F;sub&#62; &#x002B; K&#60;sub&#62;R&#60;&#x002F;sub&#62; M&#60;sub&#62;R&#60;&#x002F;sub&#62;&#x002F;N, which shows that 1) the one-shot sum-DoF scales linearly with the aggregate cache size in the network and 2) it is within a factor of 2 to the information-theoretic optimum. Surprisingly, the identical and near optimal sum-DoF performance can be achieved using the hypercube approach with a much less file subpacketization.
RePr: Improved Training of Convolutional Filters

A well-trained Convolutional Neural Network can easily be pruned without significant loss of performance. This is because of unnecessary overlap in the features captured by the network’s filters. Innovations in network architecture such as skip/dense connections and inception units have mitigated this problem to some extent, but these improvements come with increased computation and memory requirements at run-time. We attempt to address this problem from another angle - not by changing the network structure but by altering the training method. We show that by temporarily pruning and then restoring a subset of the model’s filters, and repeating this process cyclically, overlap in the learned features is reduced, producing improved generalization. We show that the existing model-pruning criteria are not optimal for selecting filters to prune in this context, and introduce inter-filter orthogonality as the ranking criteria to determine under-expressive filters. Our method is applicable both to vanilla convolutional networks and more complex modern architectures, and improves the performance across a variety of tasks, especially when applied to smaller networks.
Scale-Free Interpersonal Influences on Opinions in Complex Systems

An important side effect of the evolution of the human brain is an increased capacity to form opinions in a very large domain of issues, which become points of aggressive interpersonal disputes. Remarkably, such disputes are often no less vigorous on small differences of opinion than large differences. Opinion differences that may be measured on the real number line may not directly correspond to the subjective importance of an issue and extent of resistance to opinion change. This is a hard problem for the field of opinion dynamics, a field that has become increasingly prominent as it has attracted more contributions to it from investigators in the natural and engineering sciences. The paper contributes a scale-free approach to assessing the extents to which individuals, with unknown heterogeneous resistances to influence, have been influenced by the opinions of others.
Asymptotic Miss Ratio of LRU Caching with Consistent Hashing

To efficiently scale data caching infrastructure to support emerging big data applications, many caching systems rely on consistent hashing to group a large number of servers to form a cooperative cluster. These servers are organized together according to a random hash function. They jointly provide a unified but distributed hash table to serve swift and voluminous data item requests. Different from the single least-recently-used (LRU) server that has already been extensively studied, theoretically characterizing a cluster that consists of multiple LRU servers remains yet to be explored. These servers are not simply added together; the random hashing complicates the behavior. To this end, we derive the asymptotic miss ratio of data item requests on a LRU cluster with consistent hashing. We show that these individual cache spaces on different servers can be effectively viewed as if they could be pooled together to form a single virtual LRU cache space parametrized by an appropriate cache size. This equivalence can be established rigorously under the condition that the cache sizes of the individual servers are large. For typical data caching systems this condition is common. Our theoretical framework provides a convenient abstraction that can directly apply the results from the simpler single LRU cache to the more complex LRU cluster with consistent hashing.
Intrinsic defects and dopability of zinc phosphide

Zinc phosphide (Zn_3P_2) could be the basis for cheap and highly efficient solar cells. Its use in this regard is limited by the difficulty in n-type doping of the material. In an effort to understand the mechanism behind this, the energetics and electronic structure of intrinsic point defects in zinc phosphide are studied using generalized Kohn-Sham theory and utilizing the Heyd, Scuseria, and Ernzerhof (HSE) hybrid functional for exchange and correlation. Novel “perturbation extrapolation” is utilized to extend the use of the computationally expensive HSE functional to this large-scale defect system. According to calculations, the formation energy of charged phosphorus interstitial defects are very low in n-type Zn_3P_2 and act as “electron sinks,” nullifying the desired doping and lowering the Fermi-level back toward the p-type regime. This is consistent with experimental observations of both the tendency of conductivity to rise with phosphorus partial pressure, and with current partial successes in n-type doping in very zinc-rich growth conditions.
Generalized Springer theory and weight functions

We show that each Weyl group which enters in the generalized Springer correspondence carries a natural weight function.
SMCQL: Secure Query Processing for Private Data Networks.

People and machines are recording data at an unprecedented rate. At the same time, progress has been slow in making data available for open science and other research initiatives. Many of these efforts are stymied by privacy concerns and regulatory compliance issues. For example, numerous hospitals are interested in combining their patient records with those of other healthcare sites for clinical data research, but they cannot disclose the contents of their databases without violating patient confidentiality. We propose a novel generalization of federated database systems called a private data network (PDN), and it is designed for querying over the collective data of mutually distrustful parties. In a PDN, participants do not reveal their raw data, nor do they encrypt and upload it to the cloud. Rather, they perform secure multiparty computation (SMC) with other federation members to produce query results over the data of both parties. Here, a user submits their SQL query to an honest broker that plans and coordinates its distributed execution using SMC. Within SMC, the participating database providers compute a joint function with an output that is only revealed to the user and the honest broker. The databases computing the query learn nothing about the inputs provided by their peers, nor can they see the output of the group's computation. This capability comes at a high cost-SMC programs typically have runtimes that are orders of magnitude slower than their insecure counterparts. We address this challenge with a query planner that automatically identifies the minimal set of coordination points between parties in a given query plan. The planner translates these distributed steps into SMC as needed and feeds the secure code into our query executor. Our framework, SMCQL, plans and executes PDN queries. We are preparing SMCQL for an open-source release.
On Bayes risk lower bounds

This paper provides a general technique for lower bounding the Bayes risk of statistical estimation, applicable to arbitrary loss functions and arbitrary prior distributions. A lower bound on the Bayes risk not only serves as a lower bound on the minimax risk, but also characterizes the fundamental limit of any estimator given the prior knowledge. Our bounds are based on the notion of f-informativity (Csiszar, 1972), which is a function of the underlying class of probability measures and the prior. Application of our bounds requires upper bounds on the f-informativity, thus we derive new upper bounds on f-informativity which often lead to tight Bayes risk lower bounds. Our technique leads to generalizations of a variety of classical minimax bounds (e.g., generalized Fano's inequality). Our Bayes risk lower bounds can be directly applied to several concrete estimation problems, including Gaussian location models, generalized linear models, and principal component analysis for spiked covariance models. To further demonstrate the applications of our Bayes risk lower bounds to machine learning problems, we present two new theoretical results: (1) a precise characterization of the minimax risk of learning spherical Gaussian mixture models under the smoothed analysis framework, and (2) lower bounds for the Bayes risk under a natural prior for both the prediction and estimation errors for high-dimensional sparse linear regression under an improper learning setting.
A signal-space analysis of spatial self-interference isolation for full-duplex wireless

The challenge to in-band full-duplex wireless communication is managing self-interference. Many designs have employed spatial isolation mechanisms, such as shielding or multi-antenna beamforming, to isolate the self-interference wave from the receiver. Such spatial isolation methods are effective, but by confining the transmit and receive signals to a subset of the available space, the full spatial resources of the channel be under-utilized, expending a cost that may nullify the net benefit of operating in full-duplex mode. In this paper we leverage an antenna-theory-based channel model to analyze the spatial degrees of freedom available to a full-duplex capable base station, and observe that whether or not spatial isolation out-performs time-division (i.e. half-duplex) depends heavily on the geometric distribution of scatterers. Unless the angular spread of the objects that scatter to the intended users is overlapped by the spread of objects that backscatter to the base station, then spatial isolation outperforms time division, otherwise time division may be optimal.
REFLEXIVITY AND CONNECTEDNESS

Given a finitely generated module over a commutative noetherian ring that satisfies certain reflexivity conditions, we show how failure of the semidualizing property for the module manifests in a disconnection of the prime spectrum of the ring.
Distributed Robust Set-Invariance for Interconnected Linear Systems

We introduce a class of distributed control policies for networks of discrete-time linear systems with polytopic additive disturbances. The objective is to restrict the network-level state and controls to user-specified polyhedral sets for all times. This problem arises in many safety-critical applications. We consider two problems. First, given a communication graph characterizing the structure of the information flow in the network, we find the optimal distributed control policy by solving a single linear program. Second, we find the sparsest communication graph required for the existence of a distributed invariance-inducing control policy. Illustrative examples, including one on platooning, are presented.
Recommendations for Datasets for Source Code Summarization

Source Code Summarization is the task of writing short, natural language descriptions of source code. The main use for these descriptions is in software documentation e.g. the one-sentence Java method descriptions in JavaDocs. Code summarization is rapidly becoming a popular research problem, but progress is restrained due to a lack of suitable datasets. In addition, a lack of community standards for creating datasets leads to confusing and unreproducible research results – we observe swings in performance of more than 33% due only to changes in dataset design. In this paper, we make recommendations for these standards from experimental results. We release a dataset based on prior work of over 2.1m pairs of Java methods and one sentence method descriptions from over 28k Java projects. We describe the dataset and point out key differences from natural language data, to guide and support future researchers.
POLYNOMIAL COCYCLES OF ALEXANDER QUANDLES AND APPLICATIONS

Cocycles are constructed by polynomial expressions for Alexander quandles. As applications, non-triviality of some quandle homology groups are proved, and quandle cocycle invariants of knots are studied. In particular, for an infinite family of quandles, the non-triviality of quandle homology groups is proved for all odd dimensions.
Jamming Aided Generalized Data Attacks: Exposing Vulnerabilities in Secure Estimation

Jamming refers to the deletion, corruption or damage of meter measurements that prevents their further usage. This is distinct from adversarial data injection that changes meter readings while preserving their utility in state estimation. This paper presents a generalized attack regime that uses jamming of secure and insecure measurements to greatly expand the scope of common 'hidden' and 'detectable' data injection attacks in literature. For 'hidden' attacks, it is shown that with jamming, the optimal attack is given by the minimum feasible cut in a specific weighted graph. More importantly, for 'detectable' data attacks, this paper shows that the entire range of relative costs for adversarial jamming and data injection can be divided into three separate regions, with distinct graph-cut based constructions for the optimal attack. Approximate algorithms for attack design are developed and their performances are demonstrated by simulations on IEEE test cases. Further, it is proved that prevention of such attacks require security of all grid measurements. This work comprehensively quantifies the dual adversarial benefits of jamming: (a) reduced attack cost and (b) increased resilience to secure measurements, that strengthen the potency of data attacks.
Scheduling to Approximate Minimization Objectives on Identical Machines

This paper considers scheduling on identical machines. The scheduling objective considered in this paper generalizes most scheduling minimization problems. In the problem, there are $n$ jobs and each job $j$ is associated with a monotonically increasing function $g_j$. The goal is to design a schedule that minimizes $\sum_{j \in [n]} g_{j}(C_j)$ where $C_j$ is the completion time of job $j$ in the schedule. An $O(1)$-approximation is known for the single machine case. On multiple machines, this paper shows that if the scheduler is required to be either non-migratory or non-preemptive then any algorithm has an unbounded approximation ratio. Using preemption and migration, this paper gives a $O(\log \log nP)$-approximation on multiple machines, the first result on multiple machines. These results imply the first non-trivial positive results for several special cases of the problem considered, such as throughput minimization and tardiness. Natural linear programs known for the problem have a poor integrality gap. The results are obtained by strengthening a natural linear program for the problem with a set of covering inequalities we call job cover inequalities. This linear program is rounded to an integral solution by building on quasi-uniform sampling and rounding techniques.
Associations among Fish Length, Dam Passage History, and Survival to Adulthood in Two At-Risk Species of Pacific Salmon

Abstract Threatened or endangered salmon and steelhead originating in the Snake River basin must pass through a series of eight major hydroelectric dams during their seaward migration. Understanding the effects of specific dam passage routes on lifetime survival for these stocks is essential for successful management. Juvenile fish may pass these dams via three primary routes: 1) spillways; 2) turbines; or 3) juvenile bypass systems, which divert fish away from turbines and route them downstream. Bypass systems may expose fish to trauma, increased stress, or disease. However, numerous studies have indicated that direct survival through bypass systems is comparable to and often higher than that through spillways. Some researchers have suggested that route of dam passage affects mortality in the estuary or ocean, but this is complicated by studies finding fish size affects route of passage. We tested whether passage through bypass systems was associated with probability of adult return after accounting for fish length and other covariates for two species of concern. We also investigated the association between fish length and probability of bypass at dams, and how this relationship could lead to spurious conclusions regarding effects of bypass systems on survival if length was ignored. We found that: 1) larger fish had lower bypass probabilities at 6 of 7 dams; 2) larger fish had higher probability of surviving to adulthood; 3) bypass history had little association with adult return after accounting for length; and 4) simulations indicated spurious effects of bypass on survival may arise when no true bypass effect exists, especially in models without length. Our results suggest that after fish leave the hydropower system, bypass passage history has little effect on mortality. Our findings underscore the importance of accounting for fish size in studies of dam passage or survival.
Cooperation Enhances Robustness of Coexistence in Spatially Structured Consortia

Designing synthetic microbial consortia is an emerging area in synthetic biology and a major goal is to realize stable and robust coexistence of multiple species. Cooperation and competition are fundamental intra/interspecies interactions that shape population level behaviors, yet it is not well-understood how these interactions affect the stability and robustness of coexistence. In this paper, we show that communities with cooperative interactions are more robust to population disturbance, e.g., depletion by antibiotics, by forming intermixed spatial patterns. Meanwhile, competition leads to population spatial heterogeneity and more fragile coexistence in communities. Using reaction-diffusion and nonlocal PDE models and simulations of a two-species E. coli consortium, we demonstrate that cooperation is more beneficial than competition in maintaining coexistence in spatially structured consortia, but not in well-mixed environments. This also suggests a tradeoff between constructing heterogeneous communities with localized functions and maintaining robust coexistence. The results provide general strategies for engineering spatially structured consortia by designing interspecies interactions and suggest the importance of cooperation for biodiversity in microbial community.
FECBench: A Holistic Interference-aware Approach for Application Performance Modeling

Services hosted in multi-tenant cloud platforms often encounter performance interference due to contention for non-partitionable resources, which in turn causes unpredictable behavior and degradation in application performance. To grapple with these problems and to define effective resource management solutions for their services, providers often must expend significant efforts and incur prohibitive costs in developing performance models of their services under a variety of interference scenarios on different hardware. This is a hard problem due to the wide range of possible co-located services and their workloads, and the growing heterogeneity in the runtime platforms including the use of fog and edge-based resources, not to mention the accidental complexities in performing application profiling under a variety of scenarios. To address these challenges, we present FECBench (Fog/Edge/Cloud Benchmarking), an open source framework comprising a set of 106 applications covering a wide range of application classes to guide providers in building performance interference prediction models for their services without incurring undue costs and efforts. Through the design of FECBench, we make the following contributions. First, we develop a technique to build resource stressors that can stress multiple system resources all at once in a controlled manner, which helps to gain insights into the impact of interference on an application's performance. Second, to overcome the need for exhaustive application profiling, FECBench intelligently uses the design of experiments (DoE) approach to enable users to build surrogate performance models of their services. Third, FECBench maintains an extensible knowledge base of application combinations that create resource stresses across the multi-dimensional resource design space. Empirical results using real-world scenarios to validate the efficacy of FECBench show that the predicted application performance has a median error of only 7.6% across all test cases, with 5.4% in the best case and 13.5% in the worst case.
Predicting patent citations to measure economic impact of scholarly research

A crucial goal of funding research and development has always been to advance economic development. On this basis, a considerable body of research undertaken with the purpose of determining what exactly constitutes economic impact and how to accurately measure that impact has been published. Numerous indicators have been used to measure economic impact, although no single indicator has been widely adapted. Based on patent data collected from Altmetrics we predict patent citations through various social media features using several classification models. Patents citing a research paper implies the potential it has for direct application in its field. These predictions can be utilized by researchers in determining the practical applications for their work when applying for patents.
Energetic electron dynamics near Callisto

Abstract We examine the dynamics of energetic magnetospheric electrons exposed to the highly perturbed and asymmetric plasma environment of Jupiter’s moon Callisto. The interaction of the (nearly) corotating magnetospheric plasma with Callisto’s ionosphere and induced dipole locally generates intense electromagnetic pileup and draping signatures which vary as a function of the moon’s distance to the center of Jupiter’s magnetospheric current sheet. In our study, these field perturbations are represented using output from the AIKEF hybrid (kinetic ions, fluid electrons) model of Callisto’s interaction with the corotating plasma. In order to constrain the influence of Callisto’s variable electromagnetic environment on the dynamics of energetic electrons, we trace the trajectories of more than 6.7 million test particles as they travel through a distinct configuration of the locally perturbed fields. We present spatially resolved maps that display the accessibility of Callisto to electrons at energies E between 10 1 keV ≤ E ≤ 10 5 keV for multiple sets of these perturbed fields, corresponding to select distances of the moon to the center of the Jovian current sheet. The electromagnetic field perturbations near Callisto play a crucial role in generating inhomogeneous precipitation of energetic electrons onto the top of the moon’s atmosphere. In particular, Callisto’s Jupiter-facing and Jupiter-averted hemispheres are partially protected from energetic electron precipitation: when located far above or below the center of Jupiter’s current sheet, Callisto’s induced dipole shields the apices of these hemispheres, whereas near the center of the sheet, strong field line draping protects these regions. In contrast to this, the apex of Callisto’s trailing hemisphere is exposed to intense energetic electron precipitation at any distance to the center of the Jovian current sheet. We also present maps of energetic electron accessibility during the Galileo C3, C9, and C10 flybys, and calculate the intensity of energetic electron flux onto multiple locations at the top of Callisto’s atmosphere. These non-uniform electron fluxes likely cause inhomogeneous ionization of Callisto’s atmosphere and may even contribute to irregular erosion of the surface. This paper is a companion to Liuzzo et al. (2019), who studied the dynamics of energetic ions near Callisto.
Type 2 Diabetes Mellitus Increases The Risk of Late-Onset Alzheimer's Disease: Ultrastructural Remodeling of the Neurovascular Unit and Diabetic Gliopathy.

Type 2 diabetes mellitus (T2DM) and late-onset Alzheimer’s disease–dementia (LOAD) are increasing in global prevalence and current predictions indicate they will only increase over the coming decades. These increases may be a result of the concurrent increases of obesity and aging. T2DM is associated with cognitive impairments and metabolic factors, which increase the cellular vulnerability to develop an increased risk of age-related LOAD. This review addresses possible mechanisms due to obesity, aging, multiple intersections between T2DM and LOAD and mechanisms for the continuum of progression. Multiple ultrastructural images in female diabetic db/db models are utilized to demonstrate marked cellular remodeling changes of mural and glia cells and provide for the discussion of functional changes in T2DM. Throughout this review multiple endeavors to demonstrate how T2DM increases the vulnerability of the brain’s neurovascular unit (NVU), neuroglia and neurons are presented. Five major intersecting links are considered: i. Aging (chronic age-related diseases); ii. metabolic (hyperglycemia advanced glycation end products and its receptor (AGE/RAGE) interactions and hyperinsulinemia-insulin resistance (a linking linchpin); iii. oxidative stress (reactive oxygen–nitrogen species); iv. inflammation (peripheral macrophage and central brain microglia); v. vascular (macrovascular accelerated atherosclerosis—vascular stiffening and microvascular NVU/neuroglial remodeling) with resulting impaired cerebral blood flow.
Challenging the Boundaries of Speech Recognition: The MALACH Corpus.

There has been huge progress in speech recognition over the last several years. Tasks once thought extremely difficult, such as SWITCHBOARD, now approach levels of human performance. The MALACH corpus (LDC catalog LDC2012S05), a 375-Hour subset of a large archive of Holocaust testimonies collected by the Survivors of the Shoah Visual History Foundation, presents significant challenges to the speech community. The collection consists of unconstrained, natural speech filled with disfluencies, heavy accents, age-related coarticulations, un-cued speaker and language switching, and emotional speech - all still open problems for speech recognition systems. Transcription is challenging even for skilled human annotators. This paper proposes that the community place focus on the MALACH corpus to develop speech recognition systems that are more robust with respect to accents, disfluencies and emotional speech. To reduce the barrier for entry, a lexicon and training and testing setups have been created and baseline results using current deep learning technologies are presented. The metadata has just been released by LDC (LDC2019S11). It is hoped that this resource will enable the community to build on top of these baselines so that the extremely important information in these and related oral histories becomes accessible to a wider audience.
Proximal Recursion for Solving the Fokker-Planck Equation

We develop a new method to solve the Fokker-Planck or Kolmogorov's forward equation that governs the time evolution of the joint probability density function of a continuous-time stochastic nonlinear system. Numerical solution of this equation is fundamental for propagating the effect of initial condition, parametric and forcing uncertainties through a nonlinear dynamical system, and has applications encompassing but not limited to forecasting, risk assessment, nonlinear filtering and stochastic control. Our methodology breaks away from the traditional approach of spatial discretization for solving this second-order partial differential equation (PDE), which in general, suffers from the “curse-of-dimensionality”. Instead, we numerically solve an infinite dimensional proximal recursion in the space of probability density functions, which is theoretically equivalent to solving the Fokker-Planck-Kolmogorov PDE. We show that the dual formulation along with the introduction of an entropic regularization, leads to a smooth convex optimization problem that can be implemented via suitable block co-ordinate iteration and has fast convergence due to certain contraction property that we establish. This approach enables meshless implementation leading to remarkably fast computation.
An extension of Minkowski's theorem and its applications to questions about projections for measures

Abstract Minkowski's Theorem asserts that every centered measure on the sphere which is not concentrated on a great subsphere is the surface area measure of some convex body, and the surface area measure determines a convex body uniquely up to a shift. In this manuscript we prove an extension of Minkowski's theorem. Consider a measure μ on R n with positive degree of concavity and positive degree of homogeneity. We show that a surface area measure of a convex set K, weighted with respect to μ, determines a convex body uniquely up to μ-measure zero. We also establish an existence result under natural conditions including symmetry. We apply this result to extend the solution to classical Shephard's problem. To do this, we introduce a new notion which relates projections of convex bodies to a given measure μ, and is a generalization of the Lebesgue volume of a projection.
Persuading policy-makers:

Interest groups persuade policy-makers by publicly providing information about policies—for example, through commissioning scientific studies or piloting programs—or about constituents’ views—for e...
Clustering of Data with Missing Entries using Non-convex Fusion Penalties.

The presence of missing entries in data often creates challenges for pattern recognition algorithms. Traditional algorithms for clustering data assume that all the feature values are known for every data point. We propose a method to cluster data in the presence of missing information. Unlike conventional clustering techniques where every feature is known for each point, our algorithm can handle cases where a few feature values are unknown for every point. For this more challenging problem, we provide theoretical guarantees for clustering using a l0 fusion penalty based optimization problem. Furthermore, we propose an algorithm to solve a relaxation of this problem using saturating non-convex fusion penalties. It is observed that this algorithm produces solutions that degrade gradually with an increase in the fraction of missing feature values. We demonstrate the utility of the proposed method using a simulated dataset, the Wine dataset and also an under-sampled cardiac MRI dataset. It is shown that the proposed method is a promising clustering technique for datasets with large fractions of missing entries.
Acquisitions and funding conditions

Abstract We find evidence that aggregate funding conditions play an instrumental role in mergers and acquisitions (M&A). Funding conditions impact the benefits, participants and the number of deals transacted and this impact extends well beyond merger waves. Specifically, when aggregate funding conditions are favorable, the merger market is especially active and small, financially-constrained firms participate heavily. These same firms, however, are largely absent from the deal market when funding conditions are tight. Furthermore, investors view deals during favorable environments as relatively attractive, particularly if the deals are initiated by small bidders. In contrast, deals transacted by large firms during easy-money periods are viewed as value-destroying. We also document that these value-destroying deals are particularly prevalent among large bidders with significant potential for agency costs. Overall, our results suggest that aggregate funding conditions do not merely cause bidders to adjust the scope of their investment decisions consistent with capital rationing, but rather, the changing state of aggregate funding appears to significantly determine the size and composition of the M&A potential bidder pool.
Tel1 Activation by the MRX Complex Is Sufficient for Telomere Length Regulation but Not for the DNA Damage Response in Saccharomyces cerevisiae

Previous models suggested that regulation of telomere length in Saccharomyces cerevisiae by Tel1(ATM) and Mec1(ATR) would parallel the established pathways regulating the DNA damage response. Here, we provide evidence that telomere length regulation differs from the DNA damage response in both the Tel1 and Mec1 pathways. We found that Rad53 mediates a Mec1 telomere length regulation pathway but is dispensable for Tel1 telomere length regulation, whereas in the DNA damage response, Rad53 is regulated by both Mec1 and Tel1. Using epistasis analysis with a Tel1 hypermorphic allele, Tel1-hy909, we found that the MRX complex is not required downstream of Tel1 for telomere elongation but is required downstream of Tel1 for the DNA damage response. Our data suggest that nucleolytic telomere end processing is not a required step for telomerase to elongate telomeres.
How we got here? Transition failures, their causes and the populist interest in the constitution:

How is it possible, that after the exhilarating start of democratic transitions in the late 1980s and 1990s, today authoritarian–populist options seem to be emerging in many new, as well as old dem...
Allegiance, Ability, and Achievement in the American Civil War: Commander Traits and Battlefield Military Effectiveness

We investigate the role of leadership in the outcome of militarized conflict. Specifically, we examine whether commanding officers systematically affected the outcome of battles during the American Civil War. Using battle-level data and biographical information about hundreds of leaders on both sides, we determine whether different commanders can produce different outcomes, and which attributes of military leaders are most closely associated with battlefield success. Our analysis suggests higher-quality leaders do generate better outcomes on the battlefield, whereas the effects of loyalty are mixed. These results have implications for the study of conflict as well as bureaucratic politics.
Free Energy Principle in Human Postural Control System: Skin Stretch Feedback Reduces the Entropy

Human upright standing involves an integration of multiple sensory inputs such as vision, vestibular and somatosensory systems. It has been known that sensory deficits worsen the standing balance. However, how the modulation of sensory information contributes to postural stabilization still remains an open question for researchers. The purpose of this work was to formulate the human standing postural control system in the framework of the free-energy principle, and to investigate the efficacy of the skin stretch feedback in enhancing the human standing balance. Previously, we have shown that sensory augmentation by skin stretch feedback at the fingertip could modulate the standing balance of the people with simulated sensory deficits. In this study, subjects underwent ten 30-second trials of quiet standing balance with and without skin stretch feedback. Visual and vestibular sensory deficits were simulated by having each subject close their eyes and tilt their head back. We found that sensory augmentation by velocity-based skin stretch feedback at the fingertip reduced the entropy of the standing postural sway of the people with simulated sensory deficits. This result aligns with the framework of the free energy principle which states that a self-organizing biological system at its equilibrium state tries to minimize its free energy either by updating the internal state or by correcting body movement with appropriate actions. The velocity-based skin stretch feedback at the fingertip may increase the signal-to-noise ratio of the sensory signals, which in turn enhances the accuracy of the internal states in the central nervous system. With more accurate internal states, the human postural control system can further adjust the standing posture to minimize the entropy, and thus the free energy.
Economic Democracy and Enterprise Form in Finance

This article considers the relative advantages of alternative enterprise forms in finance from the point of view of public accountability. The business corporation is compared to the state agency o...
Exploring Gender in the Selected Short Stories of Rabindranath Tagore

Human societies, since the time immemorial, have always tended to assign different roles, codes of behavior and morality, and even different feelings and thoughts to men and women based on the biological distinction of sex (between male and female) thereby leading to the construction of the social distinction of gender (between masculine and feminine). As a literary genre, short story developed in the 19th century and by the end of 20thcentury occupied the role as one of the major literary forms. In the field of academia and literary circles, Rabindranath Tagore is mainly known as a bard, thinker, philosopher, painter and social activist but few know the first Asian Nobel laureate Tagore as a feminist, with gender issues forming the underlying theme in many of his works. Rabindranath Tagore is one of those pioneer short story writers whose writings reflect maturity. He is regarded as one of the progressive modern Indian short story writers. Tagore has been very successful in depicting woman psychology in his short stories and has made very scathing comments against gender suppression. The focus of this paper will be on the female protagonist of the short stories titled, “A Wife’s letter” and “Musolmanir Galpo” or “The story of a Muslim Woman,” by Tagore that how they remained unperturbed although the society in which they lived were dominated by male patriarchal norms and in what ways they have been successful in protecting their rights thereby becoming the champions for women mainly through their progressive thought, courage, and determination.
Evidence for pre-climacteric activation of AOX transcription during cold-induced conditioning to ripen in European pear (Pyrus communis L.).

European pears (Pyrus communis L.) require a range of cold-temperature exposure to induce ethylene biosynthesis and fruit ripening. Physiological and hormonal responses to cold temperature storage in pear have been well characterized, but the molecular underpinnings of these phenomena remain unclear. An established low-temperature conditioning model was used to induce ripening of ‘D’Anjou’ and ‘Bartlett’ pear cultivars and quantify the expression of key genes representing ripening-related metabolic pathways in comparison to non-conditioned fruit. Physiological indicators of pear ripening were recorded, and fruit peel tissue sampled in parallel, during the cold-conditioning and ripening time-course experiment to correlate gene expression to ontogeny. Two complementary approaches, Nonparametric Multi-Dimensional Scaling and efficiency-corrected 2-(ΔΔCt), were used to identify genes exhibiting the most variability in expression. Interestingly, the enhanced alternative oxidase (AOX) transcript abundance at the pre-climacteric stage in ‘Bartlett’ and ‘D’Anjou’ at the peak of the conditioning treatments suggests that AOX may play a key and a novel role in the achievement of ripening competency. There were indications that cold-sensing and signaling elements from ABA and auxin pathways modulate the S1-S2 ethylene transition in European pears, and that the S1-S2 ethylene biosynthesis transition is more pronounced in ‘Bartlett’ as compared to ‘D’Anjou’ pear. This information has implications in preventing post-harvest losses of this important crop.
Institucionalismo, realismo crítico y crítica de la economía dominante

Los realistas criticos han recibido gran apoyo dentro de las comunidades de investigacion post-keynesiana y marxista, y es probable que la influencia del realismo critico en el institucionalismo aumente en los proximos anos. Los post-keynesianos y los marxistas mantienen discusiones sobre las fortalezas y las debilidades del realismo critico. Los institucionalistas deben tener una discusion similar. Este escrito aborda una caracteristica clave del programa realista critico: su critica de la economia dominante. En particular, critica el uso de los realistas criticos del concepto de clausura, y argumenta que el realismo critico se equivoca al considerar que la ontologia de la economia dominante es humeana. El proposito del articulo es promover la discusion critica sobre el papel del realismo critico en el institucionalismo.