cssi/SciSciGPT-SciSciNet huggingface dataset:
Facets, weak facets, and extreme functions of the Gomory–Johnson infinite group problem

We investigate three competing notions that generalize the notion of a facet of finite-dimensional polyhedra to the infinite-dimensional Gomory–Johnson model. These notions were known to coincide for continuous piecewise linear functions with rational breakpoints. We show that two of the notions, extreme functions and facets, coincide for the case of continuous piecewise linear functions, removing the hypothesis regarding rational breakpoints. We prove an if-and-only-if version of the Gomory–Johnson Facet Theorem. Finally, we separate the three notions using discontinuous examples.
Synthesis and pharmacokinetic study of a 11C-labeled cholesterol 24-hydroxylase inhibitor using ‘in-loop’ [11C]CO2 fixation method

Cholesterol 24-hydroxylase, also known as CYP46A1 (EC 1.14.13.98), is a monooxygenase and a member of the cytochrome P450 family. CYP46A1 is specifically expressed in the brain where it controls cholesterol elimination by producing 24S-hydroxylcholesterol (24-HC) as the major metabolite. Modulation of CYP46A1 activity may affect Aβ deposition and p-tau accumulation by changing 24-HC formation, which thereafter serves as potential therapeutic pathway for Alzheimer's disease. In this work, we showcase the efficient synthesis and preliminary pharmacokinetic evaluation of a novel cholesterol 24-hydroxylase inhibitor 1 for use in positron emission tomography.
Reduced Kv3.1 Activity in Dentate Gyrus Parvalbumin Cells Induces Vulnerability to Depression

Abstract Background Parvalbumin (PV)-expressing interneurons are important for cognitive and emotional behaviors. These neurons express high levels of p11, a protein associated with depression and action of antidepressants. Methods We characterized the behavioral response to subthreshold stress in mice with conditional deletion of p11 in PV cells. Using chemogenetics, viral-mediated gene delivery, and a specific ion channel agonist, we studied the role of dentate gyrus PV cells in regulating anxiety-like behavior and resilience to stress. We used electrophysiology, imaging, and biochemical studies in mice and cells to elucidate the function and mechanism of p11 in dentate gyrus PV cells. Results p11 regulates the subcellular localization and cellular level of the potassium channel Kv3.1 in cells. Deletion of p11 from PV cells resulted in reduced hippocampal level of Kv3.1, attenuated capacity of high-frequency firing in dentate gyrus PV cells, and altered short-term plasticity at synapses on granule cells, as well as anxiety-like behavior and a pattern separation deficit. Chemogenetic inhibition or deletion of p11 in these cells induced vulnerability to depressive behavior, whereas upregulation of Kv3.1 in dentate gyrus PV cells or acute activation of Kv3.1 using a specific agonist induced resilience to depression. Conclusions The activity of dentate gyrus PV cells plays a major role in the behavioral response to novelty and stress. Activation of the Kv3.1 channel in dentate gyrus PV cells may represent a target for the development of cell-type specific, fast-acting antidepressants.
The Financial Center Leverage Cycle: Does it Spread Around the World?

With a novel database, we examine the evolution of capital flows to the periphery since the collapse of the Bretton Woods System in the early 1970s. We decompose capital flows into global, regional, and idiosyncratic factors. In contrast to previous findings, which mostly use data from the 2000s, we find that booms and busts in capital flows are mainly explained by regional factors and not the global factor. We then ask, what drives these regional factors. Is it the leverage cycle in the financial center? What triggers the leverage cycle in the financial center? Is it a change in global investors’ risk appetite? Or, is it a change in the demand for capital in the periphery? We link leverage in the financial center to regional capital flows and the cost of borrowing in international capital markets to answer these questions. Our estimations indicate that regional capital flows are driven by supply shocks. Interestingly, we find that the leverage in the financial center has a time-varying behavior, with a movement away from lending to the emerging periphery in the 1970s to the 1990s towards lending to the advanced periphery in the 2000s.
Design Trade-offs for Decentralized Baseband Processing in Massive MU-MIMO Systems

Massive multi-user (MU) multiple-input multiple- output (MIMO) provides high spectral efficiency by means of spatial multiplexing and fine-grained beamforming. However, conventional base-station (BS) architectures for systems with hundreds of antennas that rely on centralized baseband processing inevitably suffer from (i) excessive interconnect data rates between radio-frequency circuitry and processing fabrics, and (ii) prohibitive complexity at the centralized baseband processor. Recently, decentralized baseband processing (DBP) architectures and algorithms have been proposed, which mitigate the interconnect bandwidth and complexity bottlenecks. This paper systematically explores the design trade-offs between error-rate performance, computational complexity, and data transfer latency of DBP architectures under different system configurations and channel conditions. Considering architecture, algorithm, and numerical precision aspects, we provide practical guidelines to select the DBP architecture and algorithm that are able to realize the full benefits of massive MU-MIMO in the uplink and downlink.
Training DNA Perceptrons via Fractional Coding

This paper describes a novel approach to synthesize molecular reactions to train a perceptron, i.e., a single-layered neural network, with sigmoidal activation function. The approach is based on fractional coding where a variable is represented by two molecules. The synergy between fractional coding in molecular computing and stochastic logic implementations in electronic computing is key to translating known stochastic logic circuits to molecular computing. In prior work, a DNA perceptron with bipolar inputs and unipolar output was proposed for inference. The focus of this paper is on synthesis of molecular reactions for training of the DNA perceptron. A new molecular scaler that performs multiplication by a factor greater than 1 is proposed based on fractional coding. The training of the perceptron proposed in this paper is based on a modified backpropagation equation as the exact equation cannot be easily mapped to molecular reactions using fractional coding.
Tumor microtubes connect pancreatic cancer cells in an Arp2/3 complex-dependent manner

Actin-based tubular connections between cells have been observed in many cell types. Termed "tunneling nanotubes (TNTs)," "membrane nanotubes," "tumor microtubes (TMTs)," or "cytonemes," these protrusions interconnect cells in dynamic networks. Structural features in these protrusions vary between cellular systems, including tubule diameter and the presence of microtubules. We find tubular protrusions, which we classify as TMTs, in a pancreatic cancer cell line, Dartmouth-Hitchcock Pancreatic Cancer (DHPC)-018. TMTs are present in DHPC-018-derived tumors in mice, as well as in a mouse model of pancreatic cancer and a subset of primary human tumors. DHPC-018 TMTs have heterogeneous diameter (0.39-5.85 µm, median 1.92 µm) and contain actin filaments, microtubules, and cytokeratin 19-based intermediate filaments. TMTs do not allow intercellular transfer of cytoplasmic GFP. Actin filaments are cortical within the protrusion, as opposed to TNTs, in which filaments run down the center. TMTs are dynamic in length, but are long lived (median >60 min). Inhibition of actin polymerization, but not microtubules, results in TMT loss. Extracellular calcium is necessary for TMT maintenance. A second class of tubular protrusion, which we term cell-substrate protrusion, has similar width range and cytoskeletal features but makes contact with the substratum as opposed to another cell. Similar to previous work on TNTs, we find two assembly mechanisms for TMTs, which we term "pull-away" and "search-and-capture." Inhibition of Arp2/3 complex inhibits TMT assembly by both mechanisms. This work demonstrates that the actin architecture of TMTs in pancreatic cancer cells is fundamentally different from that of TNTs and demonstrates the role of Arp2/3 complex in TMT assembly.
Where Has All the Data Gone

As financial technology improves and data becomes more abundant, do market prices reflect this data growth? While recent studies documented rises in the information content of prices, we show that, across asset types, there is data divergence. Large, growth stock prices increasingly reflect information about future firm earnings. This is the rise reflected in the previous studies. But over the same time period, the information content of small and value firm prices was flat or declining. Our structural estimation allows us to disentangle these informational trends from changing asset characteristics. These facts pose a new puzzle: Amidst the explosion of data processing, why has this data informed only the prices of a subset of firms, instead of benefiting the market as a whole? Our structural model offers a potential answer: Large growth firms' data grew in value, as big firms got bigger and growth magnified the effect of these changes in size.
A model for the interplay between plastic tradeoffs and evolution in changing environments

Performance tradeoffs are ubiquitous in both ecological and evolutionary modeling, yet they are usually postulated and built into fitness and ecological landscapes. However, tradeoffs depend on genetic background and evolutionary history and can themselves evolve. We present a simple model capable of capturing the key feedback loop: evolutionary history shapes tradeoff strength, which, in turn, shapes evolutionary future. One consequence of this feedback is that genomes with identical fitness can have different evolutionary properties shaped by prior environmental exposure. Another is that, generically, the best adaptations to one environment may evolve in another. Our simple framework bridges the gap between the phenotypic Fisher’s Geometric Model and the genotypic properties, such as modularity and evolvability, and can serve as a rich playground for investigating evolution in multiple or changing environments.
Highly robust model of transcription regulator activity predicts breast cancer overall survival

While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes. Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome. We built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients. Our findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression.
Bayesian Projected Calibration of Computer Models

We develop a Bayesian approach called the Bayesian projected calibration to address the problem of calibrating an imperfect computer model using observational data from an unknown complex physical ...
On the Adversarial Robustness of Robust Estimators

Motivated by recent data analytics applications, we study the adversarial robustness of robust estimators. Instead of assuming that only a fraction of the data points are outliers as considered in the classic robust estimation setup, in this paper, we consider an adversarial setup in which an attacker can observe the whole dataset and can modify all data samples in an adversarial manner so as to maximize the estimation error caused by his attack. We characterize the attacker’s optimal attack strategy, and further introduce adversarial influence function (AIF) to quantify an estimator’s sensitivity to such adversarial attacks. We provide an approach to characterize AIF for any given robust estimator, and then design optimal estimator that minimizes AIF, which implies it is least sensitive to adversarial attacks and hence is most robust against adversarial attacks. From this characterization, we identify a tradeoff between AIF (i.e., robustness against adversarial attack) and influence function, a quantity used in classic robust estimators to measure robustness against outliers, and design estimators that strike a desirable tradeoff between these two quantities.
Density of the signature process of fBm

We study the density of the signature of fractional Brownian motions with parameter $H>1/4$. In particular, we prove existence, smoothness, global Gaussian upper bounds and Varadhan's type asymptotics for this density. A key result is that the estimates on the density we obtain are controlled by the Carnot-Caratheodory distance of the group.
International Student Mentor Development Study

Peer mentorship programs are promoted as reciprocal, where both mentors and mentees benefit; however, the majority of qualitative research focuses on the positive outcomes for mentees, while few (Haggard et al., 2011; Heirdsfield et al., 2008) focus on the experiences and positive outcomes for mentors. International student peer mentorship programs help mentors develop leadership, intercultural communication, and professional skills as they help others and interact with students from different cultures and backgrounds (Haggard et al., 2011). This research study is going to fill the gap and contribute to international higher education by focusing on student peer mentors’ self-experience and how they value their roles. The research project specifically seeks to address the following questions: How do student mentors perceive and value the experiences of being peer mentors for international students? How does the international student peer mentor program contribute to mentors’ development?
An algebraic representation of globular sets

We describe a fully faithful embedding of the category of (reflexive) globular sets into the category of counital cosymmetric $R$-coalgebras when $R$ is an integral domain. This embedding is a lift of the usual functor of $R$-chains and the extra structure consists of a derived form of cup coproduct. Additionally, we construct a functor from group-like counital cosymmetric \mbox{$R$-coalgebras} to $\omega$-categories and use it to connect two fundamental constructions associated to oriented simplices: Steenrod's cup-$i$ coproducts and Street's orientals. The first defines the square operations in the cohomology of spaces, the second, the nerve of higher-dimensional categories.
Revisiting China’s Social Volcano: Attitudes toward Inequality and Political Trust in China:

Existing literature suggests that despite rising inequality in China, Chinese people tend to tolerate inequality, so it would be unlikely that rising inequality would cause sociopolitical instabili...
Insula functional connectivity in schizophrenia.

Abstract The insula is structurally abnormal in schizophrenia, demonstrating reductions in volume, cortical thickness, and altered gyrification during prodromal, early and chronic stages of the illness. Despite compelling structural alterations, less is known about its functional connectivity, limited by studies considering the insula as a whole or only within the context of resting-state networks. There is evidence, however, from healthy subjects that the insula is comprised of sub-regions with distinct functional profiles, with dorsal anterior insula (dAI) involved in cognitive processing, ventral anterior insula (vAI) involved in affective processing, and posterior insula (PI) involved in somatosensory processing. The current study builds on this prior work and characterizes insula resting-state functional connectivity sub-region profiles in a large cohort of schizophrenia (N = 191) and healthy (N = 196) participants and hypothesizes specific associations between insula sub-region connectivity abnormalities and clinical characteristics related to their functional profiles. Functional dysconnectivity of the insula in schizophrenia is broadly characterized by reduced connectivity within insula sub-networks and greater connectivity with regions not normally connected with that sub-region, reflected in significantly greater similarity of dAI and PI connectivity profiles and significantly lower similarity of dAI and vAI connectivity profiles (p
Lithium-niobate-on-insulator waveguide-integrated superconducting nanowire single-photon detectors

We demonstrate waveguide-integrated superconducting nanowire single-photon detectors on thin-film lithium niobate (LiNbO3, LN). Using a 250 μm-long NbN superconducting nanowire lithographically defined on top of a 125 μm-long LN nanowaveguide, an on-chip detection efficiency of 46% is realized with simultaneous high performance in dark count rates and timing jitter. As LN possesses high χ ( 2 ) second-order nonlinear and electro-optic properties, an efficient single-photon detector on thin-film LN opens up the possibility to construct a small-scale fully integrated quantum photonic chip, which includes single-photon sources, filters, tunable quantum gates, and detectors.
Do College-Prep Programs Improve Long-Term Outcomes?

This paper presents an analysis of the longer-run effects of a college-preparatory program implemented in inner-city schools that provided teacher training in addition to payments to eleventh- and twelfth- grade students and their teachers for passing scores on Advanced Placement (AP) exams. Affected students passed more AP exams, were more likely to remain in college beyond their first and second years, and earned higher wages. Effects are particularly pronounced for Hispanic students who experienced a 2.5-percentage-point increase in college degree attainment and an 11-percent increase in earnings. While the study is based on non-experimental variation, the results are robust across a variety of specifications, and most plausible sources of bias are ruled out. The results provide credible evidence that implementing high-quality college-preparatory programs in existing urban schools can improve the long-run educational and labor market outcomes of disadvantaged youth.
Chapter 14 – Conservation Biology

Conservation of amphibian and reptile populations has been extensively studied during the last 20 years; however, questions remain about the lack of success in translating academic studies to real-world actions that lead to saving species. Numerous reasons for this situation are discussed, including lack of funds, growth-based economies in most countries, and the dramatically increasing human population. Advancements in the field of genetics have lead to an increasing understanding of diversity and causes of declines in amphibians and reptiles. Phylogenetic relationships have changed dramatically as a result of DNA studies, leading to the discovery of many unknown species and descriptions of new families. Genetic studies contribute to the studies of viruses and other diseases, at times pinpointing the origin of an outbreak. The single greatest threat to amphibian and reptile populations remains habitat destruction and modification by humans as our numbers increase. Examples of numerous ways humans are impacting populations are discussed, including agricultural practices, logging, pollution, climate change, and various activities that occur outside reserves that impact presumably protected populations. Invasive species are a major threat, and numerous examples of harm done to and by amphibians and reptiles are given.
X-ray magneto-optic Kerr effect studies of spring magnet heterostructures

Abstract The complex 3-dimensional magnetization reversal behavior of Sm–Co/Fe exchange spring films is used to test the sensitivity of different resonant soft X-ray magneto-optical Kerr effect (MOKE) measurements to changes in longitudinal and transverse moments within the soft Fe layer and to changes in these moments in depth within the Fe layer. As in the visible MOKE, changes in longitudinal and net transverse moments are resolved by measuring both Kerr rotation and intensity loops, respectively, near the Fe 2p core resonance. These X-ray MOKE signals measured using linear incident polarization are more directly interpreted in terms of longitudinal and transverse moments than are the same signals measured using elliptical polarization. Varying photon energy near the Fe L 3 line is shown to be an effective means of resolving distinctly different reversal behavior at the top and bottom of the 20 nm thick Fe layer resulting from the strong exchange coupling at the Sm–Co/Fe interface. Measured X-ray MOKE spectra and signals are in qualitative agreement with those calculated using standard magneto-optical formalisms incorporating interference between different layers and measured helicity-dependent magneto-optical constants for Fe.
Equilibrium Diffusion of Technological Change through Multiple Processes

Abstract This paper provides a synthesis of recent contributions to the literature of equilibrium diffusion of technological change, points out a difficulty common to all, and offers a proposal to resolve the difficulty. Diffusion can be regarded as the result of processes involving changing circumstances in an environment of heterogenous agents. If diffusion arises from simultaneous operation of multiple processes, the ceteris paribus qualification necessary for theoretical work may be stringent; for empirical work, parameters of individual processes cannot be identified without specifying a multiple-process model. But nontrivial multiple-process models are generally analytically intractable. The paper's synthesis of the literature is based on a heuristic multiprocess equilibrium model of the adoption decision and proposes numerical simulation as an avenue to escape the related problems of tractability and identification. A numerical experiment with a prototype multiprocess simulation model suggests the possible importance of interaction among processes. Recent econometric advances offer new prospects for estimation of the parameters of such models.
Where's the greenium?

Abstract In this study, we investigate whether investors are willing to trade off wealth for societal benefits. We take advantage of unique institutional features of the municipal securities market to provide insight into this question. Since 2013, states and other governmental entities have issued over $23 billion of green bonds to fund eco-friendly projects. Comparing green securities to nearly identical securities issued for non-green purposes by the same issuers on the same day, we observe economically identical pricing for green and non-green issues. In contrast to a number of recent theoretical and experimental studies, we find that in real market settings investors appear entirely unwilling to forgo wealth to invest in environmentally sustainable projects. When risk and payoffs are held constant and are known to investors ex-ante, investors view green and non-green securities by the same issuer as almost exact substitutes. Thus, the greenium is essentially zero.
Chapter 4 – Reservoir Engineering

Reservoir engineering is the art of describing quantitatively the behavior of fluids in a porous or fractured rock formation and using that description to effectively manage the production and injection of those fluids. This task is complicated by the fact that no one can be sure of the underground patterns of fractures or porosity that give rise to the permeable channels through which the fluids may move. Furthermore, even if that were possible for one moment, the fracture patterns very likely will change over time since the geothermal environment is a geologically dynamic one.
Chapter 2 – The Evolution of Computers

Publisher Summary The history of the evolution of computers begins thousands of years ago with the abacus, the world's oldest known computing device. Significant advances in computer systems have been categorized by generations. First generation computer systems used vacuum tubes, which were bulky, used a great deal of energy, and were prone to failure. Second generation computers used transistors instead of vacuum tubes. Transistors were smaller, more reliable, and used less energy. The third generation computers—like the IBM/360 series—used integrated circuits. The 360 introduced the family concept of computers, by which an organization could start with a small computer and then upgrade to larger systems as it grew. During the fourth generation, the microcomputer was introduced, signaling a revolution in the computer industry. The Japanese are attempting to develop fifth generation computers by 1990. They believe that the key to the fifth generation would be software breakthroughs that make it possible to build truly intelligent machines.
The glassy solid as a statistical ensemble of crystalline microstates

We present an alternative and, for the purpose of non-crystalline materials design, a more suitable description of covalent and ionic glassy solids as statistical ensembles of crystalline local minima on the potential energy surface. Motivated by the concept of partially broken ergodicity, we analytically formulate the set of approximations under which the structural features of ergodic systems such as the radial distribution function (RDF) and powder X-ray diffraction (XRD) intensity can be rigorously expressed as statistical ensemble averages over different local minima. Validation is carried out by evaluating these ensemble averages for elemental Si and SiO2 over the local minima obtained through the first-principles random structure sampling that we performed using relatively small simulation cells, thereby restricting the sampling to a set of predominantly crystalline structures. The comparison with XRD and RDF from experiments (amorphous silicon) and molecular dynamics simulations (glassy SiO2) shows excellent agreement, thus supporting the ensemble picture of glasses and opening the door to fully predictive description without the need for experimental inputs.
The Social Costs of Gun Ownership

Abstract This paper provides new estimates of the effect of household gun prevalence on homicide rates, and infers the marginal external cost of handgun ownership. The estimates utilize a superior proxy for gun prevalence, the percentage of suicides committed with a gun, which we validate. Using county- and state-level panels for 20 years, we estimate the elasticity of homicide with respect to gun prevalence as between + 0.1 and + 0.3. All of the effect of gun prevalence is on gun homicide rates. Under certain reasonable assumptions, the average annual marginal social cost of household gun ownership is in the range $100 to $1800
WHAT WOULD YOU DO? CHALLENGES IN HIP SURGERY

The challenges faced by hip surgeons have changed over the last decade. Historically, fixation, polyethylene wear, osteolysis, loosening and failure to osseointegrate dominated the discussions at hip surgery meetings. With the introduction of highly crosslinked polyethylene, wear and osteolysis are currently not significant issues. Improved surgical technique has resulted in a high rate of osseointegration and once fixed, loosening of cementless components is rare. In this section, we will focus on issues that orthopaedic surgeons performing hip surgery routinely face including bearing couples in the young active patient, implant choices in the dysplastic hip and osteoporotic femur, evaluation and management of the unstable hip and differential diagnosis of the painful THR.
A simple, ecologically rational rule for settling found property disputes

Abstract Who has property in a found item X, which is contained in Y? The finder of X or the person who has property in Y? The common law says it depends. It depends upon whether the owner of Y knew about X, or whether X was lost or mislaid, or how small the weight of X is relative to Y (as compared to its value), or whether the finder was an employee of the owner of Y, to name just a few. Wilson (2020) hypothesizes that humans universally cognize property as being contained in a thing. A testable implication of the hypothesis reveals a simpler, clearer rule for settling found property disputes in the common law: if A has property in Y and X is in Y, then A has property in X, even if B finds X. Using a 2 × 2 design, I report the results of a three-dimensional virtual world experiment to test how incentivized panels of participants award a found item to one of two actual parties who have an all-or-nothing financial stake in the panel's decision. The results of the experiment strongly support the hypothesis, even, unexpectedly, under counterfactual conditions.
Evolution of brain-wide activity in the awake behaving mouse after acute fear by longitudinal manganese-enhanced MRI

Abstract Life threatening fear after a single exposure evolves in a subset of vulnerable individuals to anxiety, which may persist for their lifetime. Yet neither the whole brain's response to innate acute fear nor how brain activity evolves over time is known. Sustained neuronal activity may be a factor in the development of anxiety. We couple two experimental protocols to obtain a fear response leading to anxiety. Predator stress (PS) is a naturalistic approach that induces fear in rodents; and the serotonin transporter knockout (SERT-KO) mouse responds to PS with sustained defensive behavior. Behavior was monitored before, during and at short and long times after PS in WT and SERT-KO mice. Both genotypes responded to PS with defensive behavior, and SERT-KO retained defensive behavior for 23 days, while wild type (WT) mice return to baseline exploratory behavior by 9 days. Thus, differences in neural activity between WT and SERT-KO at 9 days after PS will identify neural correlates of persistent defensive behavior. We used longitudinal manganese-enhanced magnetic resonance imaging (MEMRI) to identify brain-wide neural activity between behavioral sessions. Mn2+ accumulation in active neurons occurs in awake behaving mice and is retrospectively imaged. To confirm expected effects of PS, behavior was monitored throughout. Following the same two cohorts of mice, WT and SERT-KO, longitudinally allowed unbiased quantitative comparisons of brain-wide activity by statistical parametric mapping (SPM). During natural behavior in WT, only low levels of activity-induced Mn2+-accumulation were detected, while much more accumulation appeared immediately after PS in both WT and SERT-KO, and evolved at 9 days to a new activity pattern at p
Bayesian Regression With Undirected Network Predictors With an Application to Brain Connectome Data

This article focuses on the relationship between a measure of creativity and the human brain network for subjects in a brain connectome dataset obtained using a diffusion weighted magnetic resonanc...
Am I the big fish? The effect of ordinal rank on student academic performance in middle school

Abstract This paper investigates the causal effect of ordinal rank on students’ academic performance in the short run. This paper provides the first direct evidence of the relationship between objective rank and students’ self-perceived rank, as well as of the impact of the self-perceived rank on students’ academic attainments. The results show that both students’ objective ability and self-perceived rank have a significant positive effect on students’ test scores. Taking advantage of the very detailed survey questions aimed at students, parents, and teachers, a large set of potential mechanisms are examined in the paper. I also find a positive effect of having a female teacher on the self-perceived rank of female students.
The effect of distracted audit committee members on earnings quality

In this paper, we examine the impact of distracting events to audit committee members on the firms’ earnings quality. Specifically, we focus on major events occurring simultaneously at other firms in which the audit committee members also serve as board members or CEOs. We find that during the years of major events, the number of board meetings at event firms significantly increases while there is no difference in board meetings at non-event firms. During this period, distracted directors miss more board meetings at the non-event firms than non-distracted directors. Consequently, firms with more distracted audit committee members have lower earnings quality. Our results indicate that director distractions, not director busyness, are associated with the decline in earnings quality. Notably, this decline in earnings quality at non-event firms is confined to the distraction years and audit committee members only. Our results have implications for shareholders and policy makers in assessing the tradeoffs between hiring experienced, qualified directors and the potential distractions that may result from their other commitments.
Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management

People increasingly use social media to report emergencies, seek help or share information during disasters, which makes social networks an important tool for disaster management. To meet these time-critical needs, we present a weakly supervised approach for rapidly building high-quality classifiers that label each individual Twitter message with fine-grained event categories. Most importantly, we propose a novel method to create high-quality labeled data in a timely manner that automatically clusters tweets containing an event keyword and asks a domain expert to disambiguate event word senses and label clusters quickly. In addition, to process extremely noisy and often rather short user-generated messages, we enrich tweet representations using preceding context tweets and reply tweets in building event recognition classifiers. The evaluation on two hurricanes, Harvey and Florence, shows that using only 1-2 person-hours of human supervision, the rapidly trained weakly supervised classifiers outperform supervised classifiers trained using more than ten thousand annotated tweets created in over 50 person-hours.
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness

We turn the definition of individual fairness on its head---rather than ascertaining the fairness of a model given a predetermined metric, we find a metric for a given model that satisfies individual fairness. This can facilitate the discussion on the fairness of a model, addressing the issue that it may be difficult to specify a priori a suitable metric. Our contributions are twofold: First, we introduce the definition of a minimal metric and characterize the behavior of models in terms of minimal metrics. Second, for more complicated models, we apply the mechanism of randomized smoothing from adversarial robustness to make them individually fair under a given weighted $L^p$ metric. Our experiments show that adapting the minimal metrics of linear models to more complicated neural networks can lead to meaningful and interpretable fairness guarantees at little cost to utility.
Emittance measurements for a thin liquid sheet flow

The Liquid Sheet Radiator (LSR) is an external flow radiator that uses a triangular-shaped flowing liquid sheet as the radiating surface. It has potentially much lower mass than solid wall radiators such as pumped loop and heat pipe radiators, along with being nearly immune to micrometeoroid penetration. The LSR has an added advantage of simplicity. Surface tension causes a thin (100-300 microns) liquid sheet to coalesce to a point, causing the sheet flow to have a triangular shape. Such a triangular sheet is desirable since it allows for simple collection of the flow at a single point. A major problem for all external flow radiators is the requirement that the working fluid be of very low (approx. 10(sup -8) torr) vapor pressure to keep evaporative losses low. As a result, working fluids are limited to certain oils (such as used in diffusion pumps) for low temperatures (300-400 K) and liquid metals for higher temperatures. Previous research on the LSR has been directed at understanding the fluid mechanics of thin sheet flows and assessing the stability of such flows, especially with regard to the formation of holes in the sheet. Taylor studied extensively the stability of thin liquid sheets both theoretically and experimentally. He showed that thin sheets in a vacuum are stable. The latest research has been directed at determining the emittance of thin sheet flows. The emittance was calculated from spectral transmittance data for the Dow Corning 705 silicone oil. By experimentally setting up a sheet flow, the emittance was also determined as a function of measurable quantities, most importantly, the temperature drop between the top of the sheet and the temperature at the coalescence point of the sheet. Temperature fluctuations upstream of the liquid sheet were a potential problem in the analysis and were investigated.
Translationese as a Language in “Multilingual” NMT

Machine translation has an undesirable propensity to produce “translationese” artifacts, which can lead to higher BLEU scores while being liked less by human raters. Motivated by this, we model translationese and original (i.e. natural) text as separate languages in a multilingual model, and pose the question: can we perform zero-shot translation between original source text and original target text? There is no data with original source and original target, so we train a sentence-level classifier to distinguish translationese from original target text, and use this classifier to tag the training data for an NMT model. Using this technique we bias the model to produce more natural outputs at test time, yielding gains in human evaluation scores on both accuracy and fluency. Additionally, we demonstrate that it is possible to bias the model to produce translationese and game the BLEU score, increasing it while decreasing human-rated quality. We analyze these outputs using metrics measuring the degree of translationese, and present an analysis of the volatility of heuristic-based train-data tagging.
Long weekend sleep is linked to stronger academic performance in male but not female pharmacy students

Poor sleep hygiene portends loss of physical and mental stamina. Therefore, maintaining a regular sleep/wake schedule on both weekdays and weekends is highly recommended. However, this advice runs contrary to the habits of university students who sleep late on weekends. Pharmacy students at Duquesne University sit for frequent examinations, typically commencing at 7:30 AM, and they complain about mental fatigue. Here, we tested the central hypothesis that longer sleep durations on both weekdays and weekends are linked to stronger academic performance in men and women. Students in their first professional year were administered three surveys to collect data on sleep habits and factors that might influence sleep, such as roommates, long commute times, and sleep interruptions. Grade point averages (GPAs) were collected from the Dean's office, with individual permissions from the students. Longer weekend-but not weekday-sleep durations were significantly correlated with higher cumulative GPAs in men and not in women. Women achieved slightly higher cumulative GPAs than men. Students who fell asleep within 15 min of going to bed had higher professional-phase GPAs than those who fell asleep after an hour or more. Our observations cannot establish causal links, but, given the body of prior evidence on the salutary properties of sleep, men may reap more benefit from recovery sleep on weekends. Rather than recommending that students force themselves awake early on weekends in an attempt to maintain a consistent sleep routine, the real-life habits of students should also be given consideration.
Connecting secretome to hematopoietic stem cell phenotype shifts in an engineered bone marrow niche.

Hematopoietic stem cells (HSCs) primarily reside in the bone marrow, where they receive external cues from their local microenvironment. The complex milieu of biophysical cues, cellular components and cell-secreted factors regulates the process by which HSC produce the blood and immune system. We previously showed direct coculture of primary murine hematopoietic stem and progenitor cells with a population of marrow-derived mesenchymal stromal and progenitor cells (MSPCs) in a methacrylamide-functionalized gelatin (GelMA) hydrogel improves hematopoietic progenitor maintenance. However, the mechanism by which MSPCs influenced HSC fate decisions remained unknown. Herein, we report the use of proteomic analysis to correlate HSC phenotype to a broad candidate pool of 200 soluble factors produced by combined mesenchymal and hematopoietic progeny. Partial least squares regression (PLSR), along with an iterative filter method, identified TGFβ-1, MMP-3, c-RP and TROY as positively correlated with HSC maintenance. Experimentally, we then observe exogenous stimulation of HSC monocultures in GelMA hydrogels with these combined cytokines increases the ratio of hematopoietic progenitors to committed progeny after a 7-day culture 7.52 ± 3.65-fold compared to non-stimulated monocultures. Findings suggest a cocktail of the downselected cytokines amplifies hematopoietic maintenance potential of HSCs beyond that of MSPC-secreted factors alone. This work integrates empirical and computation methods to identify cytokine combinations to improve HSC maintenance within an engineered HSC niche, suggesting a route toward identifying feeder-free culture platforms for HSC expansion. Insight Hematopoietic stem cells within an artificial niche receive maintenance cues in the form of soluble factors from hematopoietic and mesenchymal progeny. Applying a proteomic regression analysis, we identify a reduced set of soluble factors correlated to maintenance of a hematopoietic phenotype during culture in a biomaterial model of the bone marrow niche. We identify a minimum factor cocktail that promotes hematopoietic maintenance potential in a gelatin-based culture, regardless of the presence of mesenchymal feeder cells. By combining empirical and computational methods, we report an experimentally feasible number of factors from a large dataset, enabling exogenous integration of soluble factors into an engineered hematopoietic stem cell for enhanced maintenance potential of a quiescent stem cell population.
Curvature: A Signature for Action Recognition in Video Sequences

In this paper, a novel signature of human action recognition, namely the curvature of a video sequence, is introduced. In this way, the distribution of sequential data is modeled, which enables few-shot learning. Instead of depending on recognizing features within images, our algorithm views actions as sequences on the universal time scale across a whole sequence of images. The video sequence, viewed as a curve in pixel space, is aligned by reparameterization using the arclength of the curve in pixel space. Once such curvatures are obtained, statistical indexes are extracted and fed into a learning-based classifier. Overall, our method is simple but powerful. Preliminary experimental results show that our method is effective and achieves state-of-the-art performance in video-based human action recognition.
Radiation Efficiency Limits in Direct Antenna Modulation Transmitters

Relative bounds on radiation efficiency are established for time-modulated antenna systems, where radiation is generated by broadband conduction currents impressed using idealized nonradiating time-varying subsystems, such as those found in direct antenna modulation (DAM) transmitters. Analytical and numerical examples demonstrate that the condition of quasi-resonance, common in nearly all practical DAM transmitters, imposes severe restrictions on the otherwise unbounded gains in effective efficiency theoretically achievable by this class of time-modulated transmitters.
Experimental Analysis of Safety Application Reliability in V2V Networks

Vehicle-to-Vehicle (V2V) communication networks enable safety applications via periodic broadcast of Basic Safety Messages (BSMs) or safety beacons. Beacons include time-critical information such as sender vehicle’s location, speed and direction. The vehicle density may be very high in certain scenarios and such V2V networks suffer from channel congestion and undesirable level of packet collisions; which in turn may seriously jeopardize safety application reliability and cause collision risky situations. In this work, we perform experimental analysis of safety application reliability (in terms of collision risks), and conclude that there exists a unique beacon rate for which the safety performance is maximized, and this rate is unique for varying vehicle densities. The collision risk of a certain vehicle is computed using a simple kinematics-based model, and is based on tracking error, defined as the difference between vehicle’s actual position and the perceived location of that vehicle by its neighbors (via most-recent beacons). Furthermore, we analyze the interconnection between the collision risk and two well-known network performance metrics, Age of Information (AoI) and throughput. Our experimentation shows that AoI has a strong correlation with the collision risk and AoI-optimal beacon rate is similar to the safety-optimal beacon rate, irrespective of the vehicle densities, queuing sizes and disciplines. Whereas throughput works well only under higher vehicle densities.
Probing Single Molecules in Single Living Cells

Direct observation of single molecules and single molecular events inside living cells could dramatically improve our understanding of basic cellular processes (e.g., signal transduction and gene transcription) as well as improving our knowledge on the intracellular transport and fate of therapeutic agents (e.g., antisense RNA and gene therapy vectors). However, a key remaining question is whether single-molecule methodologies could be developed to study complex molecular processes in living cells. in contrast to clean and well-controlled conditions in-vitro, the intracellular environment contains a broad collection of biological macromolecules and fluorescent materials such as porphyrins and flavins. This complex environment is known to produce intense background fluorescence, commonly known as autofluorescence. Thus, a major concern is that this intracellular background could overwhelm the relatively weak signals arising from single molecules.We demonstrate that fluorescence detection of single molecules can be achieved by tightly focusing a laser beam into a living cell (see Figure 1). The observed background fluorescence is indeed higher than that in-vitro (e.g., pure biological buffer), but this background is continuous and stable, and does not significantly interfere with the measurement of single-molecule photon bursts. Specifically, we report single-molecule results on three types of extrinsic fluorescent molecules in cultured human HeLa cells (a cervical cancer cell line).