cssi/SciSciGPT-SciSciNet huggingface dataset:
The influence of meridional ice transport on Europa's ocean stratification and heat content

Jupiter's moon Europa likely hosts a saltwater ocean beneath its icy surface. Geothermal heating and rotating convection in the ocean may drive a global overturning circulation that redistributes heat vertically and meridionally, preferentially warming the ice shell at the equator. Here we assess the previously unconstrained influence of ocean-ice coupling on Europa's ocean stratification and heat transport. We demonstrate that a relatively fresh layer can form at the ice-ocean interface due to a meridional ice transport forced by the differential ice shell heating between the equator and the poles. We provide analytical and numerical solutions for the layer's characteristics, highlighting their sensitivity to critical ocean parameters. For a weakly turbulent and highly saline ocean, a strong buoyancy gradient at the base of the freshwater layer can suppress vertical tracer exchange with the deeper ocean. As a result, the freshwater layer permits relatively warm deep ocean temperatures.
Challenges in the Design and Interpretation of Noninferiority Trials

In this review, the authors consider the characteristics and challenges of noninferiority trial designs, including seven essential features of noninferiority trials.
Theory of optical absorption by interlayer excitons in transition metal dichalcogenide heterobilayers

We present a theory of optical absorption by interlayer excitons in a heterobilayer formed from transition metal dichalcogenides. The theory accounts for the presence of small relative rotations that produce a momentum shift between electron and hole bands located in different layers, and a moir\'e pattern in real space. Because of the momentum shift, the optically active interlayer excitons are located at the moir\'e Brillouin zone's corners, instead of at its center, and would have elliptical optical selection rules if the individual layers were translationally invariant. We show that the exciton moir\'e potential energy restores circular optical selection rules by coupling excitons with different center of mass momenta. A variety of interlayer excitons with both senses of circular optical activity, and energies that are tunable by twist angle, are present at each valley. The lowest energy exciton states are generally localized near the exciton potential energy minima. We discuss the possibility of using the moir\'e pattern to achieve scalable two-dimensional arrays of nearly identical quantum dots.
Temporal Relational Reasoning in Videos

Temporal relational reasoning, the ability to link meaningful transformations of objects or entities over time, is a fundamental property of intelligent species. In this paper, we introduce an effective and interpretable network module, the Temporal Relation Network (TRN), designed to learn and reason about temporal dependencies between video frames at multiple time scales. We evaluate TRN-equipped networks on activity recognition tasks using three recent video datasets - Something-Something, Jester, and Charades - which fundamentally depend on temporal relational reasoning. Our results demonstrate that the proposed TRN gives convolutional neural networks a remarkable capacity to discover temporal relations in videos. Through only sparsely sampled video frames, TRN-equipped networks can accurately predict human-object interactions in the Something-Something dataset and identify various human gestures on the Jester dataset with very competitive performance. TRN-equipped networks also outperform two-stream networks and 3D convolution networks in recognizing daily activities in the Charades dataset. Further analyses show that the models learn intuitive and interpretable visual common sense knowledge in videos (Code and models are available at http://relation.csail.mit.edu/.).
eCD4-Ig promotes ADCC activity of sera from HIV-1-infected patients

Antibody-dependent cell-mediated cytotoxity (ADCC) can eliminate HIV-1 infected cells, and may help reduce the reservoir of latent virus in infected patients. Sera of HIV-1 positive individuals include a number of antibodies that recognize epitopes usually occluded on HIV-1 envelope glycoprotein (Env) trimers. We have recently described eCD4-Ig, a potent and exceptionally broad inhibitor of HIV-1 entry that can be used to protect rhesus macaques from multiple high-dose challenges with simian-human immunodeficiency virus AD8 (SHIV-AD8). Here we show that eCD4-Ig bearing an IgG1 Fc domain (eCD4-IgG1) can mediate efficient ADCC activity against HIV-1 isolates with differing tropisms, and that it does so at least 10-fold more efficiently than CD4-Ig, even when more CD4-Ig molecules bound cell surface-expressed Env. An ADCC-inactive IgG2 form of eCD4-Ig (eCD4-IgG2) exposes V3-loop and CD4-induced epitopes on cell-expressed trimers, and renders HIV-1-infected cells susceptible to ADCC mediated by antibodies of these classes. Moreover, eCD4-IgG2, but not IgG2 forms of the broadly neutralizing antibodies VRC01 and 10-1074, enhances the ADCC activities of serum antibodies from patients by 100-fold, and significantly enhanced killing of two latently infected T-cell lines reactivated by vorinostat or TNFα. Thus eCD4-Ig is qualitatively different from CD4-Ig or neutralizing antibodies in its ability to mediate ADCC, and it may be uniquely useful in treating HIV-1 infection or reducing the reservoir of latently infected cells.
Specific Inhibition of the Bifunctional Farnesyl/Geranylgeranyl Diphosphate Synthase in Malaria Parasites via a New Small-Molecule Binding Site.

Summary The bifunctional farnesyl/geranylgeranyl diphosphate synthase (FPPS/GGPPS) is a key branchpoint enzyme in isoprenoid biosynthesis in Plasmodium falciparum (malaria) parasites. Pf FPPS/GGPPS is a validated, high-priority antimalarial drug target. Unfortunately, current bisphosphonate drugs that inhibit FPPS and GGPPS enzymes by acting as a diphosphate substrate analog show poor bioavailability and selectivity for Pf FPPS/GGPPS. We identified a new non-bisphosphonate compound, MMV019313, which is highly selective for Pf FPPS/GGPPS and showed no activity against human FPPS or GGPPS. Inhibition of Pf FPPS/GGPPS by MMV019313, but not bisphosphonates, was disrupted in an S228T variant, demonstrating that MMV019313 and bisphosphonates have distinct modes of inhibition. Molecular docking indicated that MMV019313 did not bind previously characterized substrate sites in Pf FPPS/GGPPS. Our finding uncovers a new, selective small-molecule binding site in this important antimalarial drug target with superior druggability compared with the known inhibitor site and sets the stage for the development of Plasmodium -specific FPPS/GGPPS inhibitors.
A dynamic power reduction in synchronous 2RW 8T dual-port SRAM by adjusting wordline pulse timing with same/different row access mode

An effective method is proposed to reduce dynamic power for synchronous 2-read/write (2RW) 8T dual-port (DP) SRAM. Adjusting the wordline (WL) pulse timing control circuit is newly introduced for both reading and writing operations. Row addresses of port-A and port-B are compared. The same row access is detected or not in each cycle, which is an inherent access mode of 2RW 8T DP SRAM. In different row access, the WL pulse width is shortened to reduce excessive bitline (BL) discharging power. A well balanced 8T DP SRAM bitcell layout is demonstrated using 40-nm technology. A test chip including 512 w × 73 b 36 kbit and 2 kw × 19 b (38 kbit) 2RW DP SRAM macros was designed and fabricated using 40-nm technology. The measured data show that reading and writing powers are reduced, respectively, by ∼7% and ∼18% using the proposed scheme.
Risk aversion, moral hazard, and gender differences in health care utilization

This paper uses truncated count model with endogeneity and simulated maximum likelihood estimation technique to estimate gender differences in moral hazard in health care insurance. We use the dataset that consists of invoices for all outpatient services from a regional hospital in Croatia. Our theoretical model predicts that higher risk aversion is associated with smaller ex-post moral hazard effect. If women are more risk averse than men, then the moral hazard effect due to health insurance should be lower in women than in men. After adjusting for the sample selection in the estimation, we found a statistically significant evidence of moral hazard for the general population but statistically insignificant difference in moral hazard between men and women.
Learning Differentially Private Recurrent Language Models

We demonstrate that it is possible to train large recurrent language models with user-level differential privacy guarantees with only a negligible cost in predictive accuracy. Our work builds on recent advances in the training of deep networks on user-partitioned data and privacy accounting for stochastic gradient descent. In particular, we add user-level privacy protection to the federated averaging algorithm, which makes "large step" updates from user-level data. Our work demonstrates that given a dataset with a sufficiently large number of users (a requirement easily met by even small internet-scale datasets), achieving differential privacy comes at the cost of increased computation, rather than in decreased utility as in most prior work. We find that our private LSTM language models are quantitatively and qualitatively similar to un-noised models when trained on a large dataset.
Mortality tradeoff between air quality and skin cancer from changes in stratospheric ozone

Skin cancer mortality resulting from stratospheric ozone depletion has been widely studied. Similarly, there is a deep body of literature on surface ozone and its health impacts, with modeling and observational studies demonstrating that surface ozone concentrations can be increased when stratospheric air mixes to the Earth's surface. We offer the first quantitative estimate of the trade-off between these two effects, comparing surface air quality benefits and UV-related harms from stratospheric ozone depletion. Applying an idealized ozone loss term in the stratosphere of a chemistry-transport model for modern-day conditions, we find that each Dobson unit of stratospheric ozone depletion results in a net decrease in the global annual mortality rate of ~40 premature deaths per billion population (d/bn/DU). The impacts are spatially heterogeneous in sign and magnitude, composed of a reduction in premature mortality rate due to ozone exposure of ~80 d/bn/DU concentrated in Southeast Asia, and an increase in skin cancer mortality rate of ~40 d/bn/DU, mostly in Western Europe. This is the first study to quantify air quality benefits of stratospheric ozone depletion, and the first to find that marginal decreases in stratospheric ozone around modern-day values could result in a net reduction in global mortality due to competing health impact pathways. This result, which is subject to significant methodological uncertainty, highlights the need to understand the health and environmental trade-offs involved in policy decisions regarding anthropogenic influences on ozone chemistry over the 21st century.
Using Fair Value Earnings to Assess Firm Value

SYNOPSIS Whether fair value accounting should be used in financial reporting has been the subject of debate for many years. A key dimension to this debate is whether fair value earnings can provide...
View from the Fringe of the Fringe

Formal analysis remains outside the mainstream of system design practice. Theorem proving is regarded by many to be on the margin of exploratory and applied research activity in this formalized system design. Although it may seem relatively academic, it is vital that this avenue continue to be as vigorously explored as approaches favoring highly automated reasoning. Design derivation, a term for design formalisms based on transformations and equivalence, represents just a small twig on the theorem-proving branch of formal system analysis. A perspective on current trends in is presented from this remote outpost, including a review of the author’s work since the early 1980s. A full accompanying paper can be found in the CHARME 2001 proceedings [1].
Live cell monitoring of double strand breaks in S. cerevisiae.

We have used two different live-cell fluorescent protein markers to monitor the formation and localization of double-strand breaks (DSBs) in budding yeast. Using GFP derivatives of the Rad51 recombination protein or the Ddc2 checkpoint protein, we find that cells with three site-specific DSBs, on different chromosomes, usually display 2 or 3 foci that may coalesce and dissociate. This motion is independent of Rad52 and microtubules. Rad51-GFP, by itself, is unable to repair DSBs by homologous recombination in mitotic cells, but is able to form foci and allow repair when heterozygous with a wild type Rad51 protein. The kinetics of formation and disappearance of a Rad51-GFP focus parallels the completion of site-specific DSB repair. However, Rad51-GFP is proficient during meiosis when homozygous, similar to rad51 “site II” mutants that can bind single-stranded DNA but not complete strand exchange. Rad52-RFP and Rad51-GFP co-localize to the same DSB, but a significant minority of foci have Rad51-GFP without visible Rad52-RFP. We conclude that co-localization of foci in cells with 3 DSBs does not represent formation of a homologous recombination “repair center,” as the same distribution of Ddc2-GFP foci was found in the absence of the Rad52 protein.
Reconstructing a metazoan genetic pathway with transcriptome-wide epistasis measurements.

RNA-sequencing (RNA-seq) is commonly used to identify genetic modules that respond to perturbations. In single cells, transcriptomes have been used as phenotypes, but this concept has not been applied to whole-organism RNA-seq. Also, quantifying and interpreting epistatic effects using expression profiles remains a challenge. We developed a single coefficient to quantify transcriptome-wide epistasis that reflects the underlying interactions and which can be interpreted intuitively. To demonstrate our approach, we sequenced four single and two double mutants of Caenorhabditis elegans. From these mutants, we reconstructed the known hypoxia pathway. In addition, we uncovered a class of 56 genes with HIF-1–dependent expression that have opposite changes in expression in mutants of two genes that cooperate to negatively regulate HIF-1 abundance; however, the double mutant of these genes exhibits suppression epistasis. This class violates the classical model of HIF-1 regulation but can be explained by postulating a role of hydroxylated HIF-1 in transcriptional control.
Jordan operator algebras: Basic theory

Jordan operator algebras are norm‐closed spaces of operators on a Hilbert space which are closed under the Jordan product. The discovery of the present paper is that there exists a huge and tractable theory of possibly nonselfadjoint Jordan operator algebras; they are far more similar to associative operator algebras than was suspected. We initiate the theory of such algebras.
Using Twitter trust network for stock market analysis

Abstract Online social networks are now attracting a lot of attention not only from their users but also from researchers in various fields. Many researchers believe that the public mood or sentiment expressed in social media is related to financial markets. We propose to use trust among users as a filtering and amplifying mechanism for the social media to increase its correlation with financial data in the stock market. Therefore, we used the real stock market data as ground truth for our trust management system. We collected stock-related data (tweets) from Twitter, which is a very popular Micro-blogging forum, to see the correlation between the Twitter sentiment valence and abnormal stock returns for eight firms in the S&P 500. We developed a trust management framework to build a user-to-user trust network for Twitter users. Compared with existing works, in addition to analyzing and accumulating tweets’ sentiment, we take into account the source of tweets – their authors. Authors are differentiated by their power or reputation in the whole community, where power is determined by the user-to-user trust network. To validate our trust management system, we did the Pearson correlation test for an eight months period (the trading days from 01/01/2015 through 08/31/2015). Compared with treating all the authors equally important, or weighting them by their number of followers, our trust network based reputation mechanism can amplify the correlation between a specific firm’s Twitter sentiment valence and the firm’s stock abnormal returns. To further consider the possible auto-correlation property of abnormal stock returns, we constructed a linear regression model, which includes historical stock abnormal returns, to test the relation between the Twitter sentiment valence and abnormal stock returns. Again, our results showed that by using our trust network power based method to weight tweets, Twitter sentiment valence reflect abnormal stock returns better than treating all the authors equally important or weighting them by their number of followers.
Posterior Concentration for Sparse Deep Learning

We introduce Spike-and-Slab Deep Learning (SS-DL), a fully Bayesian alternative to dropout for improving generalizability of deep ReLU networks. This new type of regularization enables provable recovery of smooth input-output maps with {\sl unknown} levels of smoothness. Indeed, we show that the posterior distribution concentrates at the near minimax rate for alpha-Holder smooth maps, performing as well as if we knew the smoothness level alpha ahead of time. Our result sheds light on architecture design for deep neural networks, namely the choice of depth, width and sparsity level. These network attributes typically depend on unknown smoothness in order to be optimal. We obviate this constraint with the fully Bayes construction. As an aside, we show that SS-DL does not overfit in the sense that the posterior concentrates on smaller networks with fewer (up to the optimal number of) nodes and links. Our results provide new theoretical justifications for deep ReLU networks from a Bayesian point of view.
Learning Semidefinite Regularizers

Regularization techniques are widely employed in optimization-based approaches for solving ill-posed inverse problems in data analysis and scientific computing. These methods are based on augmenting the objective with a penalty function, which is specified based on prior domain-specific expertise to induce a desired structure in the solution. We consider the problem of learning suitable regularization functions from data in settings in which precise domain knowledge is not directly available. Previous work under the title of ‘dictionary learning’ or ‘sparse coding’ may be viewed as learning a regularization function that can be computed via linear programming. We describe generalizations of these methods to learn regularizers that can be computed and optimized via semidefinite programming. Our framework for learning such semidefinite regularizers is based on obtaining structured factorizations of data matrices, and our algorithmic approach for computing these factorizations combines recent techniques for rank minimization problems along with an operator analog of Sinkhorn scaling. Under suitable conditions on the input data, our algorithm provides a locally linearly convergent method for identifying the correct regularizer that promotes the type of structure contained in the data. Our analysis is based on the stability properties of Operator Sinkhorn scaling and their relation to geometric aspects of determinantal varieties (in particular tangent spaces with respect to these varieties). The regularizers obtained using our framework can be employed effectively in semidefinite programming relaxations for solving inverse problems.
End of the Downsizing and World after that

The progress of the electronics has been conducted by the downsizing of electron devices for more than 100 years since its beginning in early 20th century. However, it is believed now that the downsizing will reach its limit within several years because of several sure reasons. After reaching the limit there is no Moore’s law, and we cannot expect such a tremendous progress in cost, performance and energy consumption as we experienced in the past. Although the market for CMOS devices will still keep increasing for future, the technology development will spread to large spectrum of different devices, such as sensor, memory, power, photovoltaic, battery, MEMS devices which are demanded for the coming IoT environment, where everything is connected with internet. This will become a virtual extension of Moore’s law, and will cause a big paradigm change in a system and society level. In a long term, however, even with the tremendous progress of AI technologies, the system fabricated on the solid-state devices and their network cannot compete with the existing bio system constructed on organic system, in efficiency and maintenance. Thus, the technology how to use the bio system better, or how to combine electron and bio systems better will become very important.
CagY-Dependent Regulation of Type IV Secretion in Helicobacter pylori Is Associated with Alterations in Integrin Binding.

Strains of Helicobacter pylori that cause ulcer or gastric cancer typically express a type IV secretion system (T4SS) encoded by the cag pathogenicity island (cagPAI). CagY is an ortholog of VirB10 that, unlike other VirB10 orthologs, has a large middle repeat region (MRR) with extensive repetitive sequence motifs, which undergo CD4+ T cell-dependent recombination during infection of mice. Recombination in the CagY MRR reduces T4SS function, diminishes the host inflammatory response, and enables the bacteria to colonize at a higher density. Since CagY is known to bind human α5β1 integrin, we tested the hypothesis that recombination in the CagY MRR regulates T4SS function by modulating binding to α5β1 integrin. Using a cell-free microfluidic assay, we found that H. pylori binding to α5β1 integrin under shear flow is dependent on the CagY MRR, but independent of the presence of the T4SS pili, which are only formed when H. pylori is in contact with host cells. Similarly, expression of CagY in the absence of other T4SS genes was necessary and sufficient for whole bacterial cell binding to α5β1 integrin. Bacteria with variant cagY alleles that reduced T4SS function showed comparable reduction in binding to α5β1 integrin, although CagY was still expressed on the bacterial surface. We speculate that cagY-dependent modulation of H. pylori T4SS function is mediated by alterations in binding to α5β1 integrin, which in turn regulates the host inflammatory response so as to maximize persistent infection.IMPORTANCE Infection with H. pylori can cause peptic ulcers and is the most important risk factor for gastric cancer, the third most common cause of cancer death worldwide. The major H. pylori virulence factor that determines whether infection causes disease or asymptomatic colonization is the type IV secretion system (T4SS), a sort of molecular syringe that injects bacterial products into gastric epithelial cells and alters host cell physiology. We previously showed that recombination in CagY, an essential T4SS component, modulates the function of the T4SS. Here we found that these recombination events produce parallel changes in specific binding to α5β1 integrin, a host cell receptor that is essential for T4SS-dependent translocation of bacterial effectors. We propose that CagY-dependent binding to α5β1 integrin acts like a molecular rheostat that alters T4SS function and modulates the host immune response to promote persistent infection.
Immigrant entrepreneurship in America: Evidence from the survey of business owners 2007 & 2012

Abstract We study immigrant entrepreneurship in 2007 and 2012 using the Survey of Business Owners. First-generation immigrants create about 25% of new firms in America, but this share exceeds 40% in some states. Conditional on basic regression controls, immigrant-owned firms tend to create fewer jobs than native-owned firms, have comparable pay levels, offer fewer benefits, and engage more in international activities. Prominent tech clusters display quite pronounced shares of immigrant entrepreneurs. Our results suggest that most of the impact of immigrant high-tech entrepreneurship for tech centers happens through the quantity dimension: Silicon Valley and similar tech hubs attract many immigrant founders.
Upward mobility for underrepresented students: a model for a cohort-based bachelor's degree in computer science

CSin3 is a cohort-based, three-year computer science bachelor's degree program that has increased graduation rates of traditionally underrepresented computer science students. A collaborative effort between a community college and a public university, CSin3 provides a clear pathway for upward socio-economic mobility into the high-paying technology industry. CSin3 students are 90% from traditionally underrepresented groups, 80% first-generation, 32% female, and have a three-year graduation rate of 71%, compared to a 22% four-year graduation rate for traditional computer science students. Upon graduation, CSin3 students score similarly on a standardized exam of computer science knowledge as compared to traditional students who graduate in 4 years or more. The first graduates had a job placement rate of 78% within two months of graduation, including positions at large technology companies like Apple, Salesforce, and Uber. By implementing a cohort-based learning community, a pre-defined course pathway, just-in-time academic and administrative support, comprehensive financial aid, and a focus on 21st century skills, the CSin3 program has demonstrated promising results in addressing the capacity, cost, quality, and diversity challenges present in the technology industry.
The collisional Penrose process

Shortly after the discovery of the Kerr metric in 1963, it was realized that a region existed outside of the black hole’s event horizon where no time-like observer could remain stationary. In 1969, Roger Penrose showed that particles within this ergosphere region could possess negative energy, as measured by an observer at infinity. When captured by the horizon, these negative energy particles essentially extract mass and angular momentum from the black hole. While the decay of a single particle within the ergosphere is not a particularly efficient means of energy extraction, the collision of multiple particles can reach arbitrarily high center-of-mass energy in the limit of extremal black hole spin. The resulting particles can escape with high efficiency, potentially serving as a probe of high-energy particle physics as well as general relativity. In this paper, we briefly review the history of the field and highlight a specific astrophysical application of the collisional Penrose process: the potential to enhance annihilation of dark matter particles in the vicinity of a supermassive black hole.
Rumors and Refugees: How Government-Created Information Vacuums Undermine Effective Crisis Management

Although more than 800,000 displaced people arrived in Greece by sea in 2015, fewer than 5 percent applied for asylum in this first country of arrival. Instead, they either traveled northward informally or remained in Greece in legal limbo. The resultant chaotic conditions deprived many refugees of the benefits of asylum and formal relocation procedures, and also reduced the Greek government's popularity among natives. We argue that governments, regional and international organizations, and aid groups can undermine compliance with their own policies by mishandling information dissemination. Common crisis-management tools—such as frequent policy changes, information dissemination limits, and ad-hoc policy implementation—can easily backfire. Information mismanagement can lead people to develop deep distrust in government and aid organizations, and instead turn to informal brokers like smugglers. To assess our theory, we draw on over 80 discussions with migrants and refugees in Greece, on 25 semistructured interviews with aid workers and government officials, and on weekly rumor correction newsletters produced by the nongovernmental organization Internews. We conclude that governments must prioritize effective communication and policy transparency, especially in crisis contexts.
Random Feature Stein Discrepancies

Computable Stein discrepancies have been deployed for a variety of applications, ranging from sampler selection in posterior inference to approximate Bayesian inference to goodness-of-fit testing. Existing convergence-determining Stein discrepancies admit strong theoretical guarantees but suffer from a computational cost that grows quadratically in the sample size. While linear-time Stein discrepancies have been proposed for goodness-of-fit testing, they exhibit avoidable degradations in testing power—even when power is explicitly optimized. To address these shortcomings, we introduce feature Stein discrepancies (ΦSDs), a new family of quality measures that can be cheaply approximated using importance sampling. We show how to construct ΦSDs that provably determine the convergence of a sample to its target and develop high-accuracy approximations—random ΦSDs (RΦSDs)—which are computable in near-linear time. In our experiments with sampler selection for approximate posterior inference and goodness-of-fit testing, RΦSDs perform as well or better than quadratic-time KSDs while being orders of magnitude faster to compute.
A Fixed-Point Iteration for Steady-State Analysis of Water Distribution Networks

This paper develops a fixed-point iteration to solve the steady-state water flow equations in an urban water distribution network. The fixed-point iteration is derived upon the assumption of turbulent flow solutions and the validity of the Hazen-Williams head loss formula for water flow. Local convergence is ensured if the spectral radius of the Jacobian at the solution is smaller than one. The implication is that the solution is at least locally unique and that the spectral radius of the Jacobian provides an estimate of the convergence speed. A sample water network is provided to assert the application of the proposed method.
Deltaic deposits indicative of a paleo-coastline at Aeolis Dorsa, Mars

Abstract Recent work at Aeolis Dorsa, Mars has identified exposure of fluvial sedimentary outcrop deposited early in martian history, likely during the late Hesperian or earlier. Here, we examine a ∼1200 km2 exposure of sedimentary outcrop in southeast Aeolis Dorsa. Total thickness of the stratigraphic section exceeds 100 m. We identify eight discrete complexes, each of which is primarily composed of branching channel-filling fluvial deposits associated with a primary feeder, or trunk, channel deposit. Relative ages for the branching complexes are derived from observed stacking relationships, and there is a pattern of eastward younging. Using digital elevation models derived from Context Camera (CTX) stereo pair images, we measure the strike and dip of stratal surfaces mapped throughout the study area. There is a trend of increasing dip magnitude from north to south. The branching complexes are interpreted as exhumed remnants of the lobes of an aggrading river delta that shifted its depo-center from west to east over time. The increasing dip magnitude of stratal surfaces towards the south records topset-foreset transitions, an architectural feature associated with river deltas, and indicates paleo-transport was locally southward. The interpreted deltaic lobes indicate that Aeolis Dorsa was a coastal region not presently bound by a modern crater basin, and the studied outcrop is part of a larger set of coastal sedimentary deposits identified in the region.
The age‐time‐cohort problem and the identification of structural parameters in life‐cycle models

A standard approach to estimating structural parameters in life‐cycle models imposes sufficient assumptions on the data to identify the “age profile” of outcomes, then chooses model parameters so that the model's age profile matches this empirical age profile. I show that this approach is both incorrect and unnecessary: incorrect, because it generally produces inconsistent estimators of the structural parameters, and unnecessary, because consistent estimators can be obtained under weaker assumptions. I derive an estimation method that avoids the problems of the standard approach. I illustrate the method's benefits analytically in a simple model of consumption inequality and numerically by reestimating the classic life‐cycle consumption model of Gourinchas and Parker (2002). Age‐time‐cohort identification problem life‐cycle models C23 D91 J1
Thermal expansion along one-dimensional chains and two-dimensional sheets within co-crystals based on halogen or hydrogen bonds

The ability to vary the thermal expansion parameters within halogen- or hydrogen-bonded co-crystals is reported. An acceptor molecule, 1,2-bis(4-pyridyl)acetylene, was selected due to its ability to form supramolecular one-dimensional chains, regardless of the ditopic donor type. We demonstrate that the smallest expansion occurs along the chain, and greater expansion occurs within the two-dimensional sheet, which is based on weaker halogen interactions.
Hard Non-Monotonic Attention for Character-Level Transduction

Character-level string-to-string transduction is an important component of various NLP tasks. The goal is to map an input string to an output string, where the strings may be of different lengths and have characters taken from different alphabets. Recent approaches have used sequence-to-sequence models with an attention mechanism to learn which parts of the input string the model should focus on during the generation of the output string. Both soft attention and hard monotonic attention have been used, but hard non-monotonic attention has only been used in other sequence modeling tasks and has required a stochastic approximation to compute the gradient. In this work, we introduce an exact, polynomial-time algorithm for marginalizing over the exponential number of non-monotonic alignments between two strings, showing that hard attention models can be viewed as neural reparameterizations of the classical IBM Model 1. We compare soft and hard non-monotonic attention experimentally and find that the exact algorithm significantly improves performance over the stochastic approximation and outperforms soft attention.
Contact Model Fusion for Event-Based Locomotion in Unstructured Terrains

As legged robots are sent into unstructured environments, the ability to robustly manage contact transitions will be a critical skill. This paper introduces an approach to probabilistically fuse contact models, managing uncertainty in terrain geometry, dynamic modeling, and kinematics to improve the robustness of contact initiation at touchdown. A discrete-time extension of the generalized-momentum disturbance observer is presented to increase the accuracy of proprioceptive force control estimates. This information is fused with other contact priors under a framework of Kalman Filtering to increase robustness of the method. This approach results in accurate contact detection with 99.3 % accuracy and a small 4-5ms delay. Using this new detector, an Event-Based Finite State Machine is implemented to deal with unexpected early and late contacts. This allows the robot to traverse cluttered environments by modifying the control actions for each individual leg based on the estimated contact state rather than adhering to a rigid time schedule regardless of actual contact state. Experiments with the MIT Cheetah 3 robot show the success of both the detection algorithm, as well as the Event-Based FSM while making unexpected contacts during trotting.
Tightwads and spendthrifts: An interdisciplinary review

Consumers rely on a “pain of paying” to help deter their spending. While this is beneficial for some consumers, others experience levels of pain that create problems. “Tightwads” experience too much pain when considering spending and therefore spend less than they would ideally like to spend. By contrast, “spendthrifts” experience too little pain and therefore spend more than they would ideally like to spend. Neither are happy with how they handle money. In the decade since the tightwad‐spendthrift construct was introduced, much has been learned about what it is and is not (e.g., frugality, greed), what contextual factors are likely to reduce its importance, how it plays a role within romantic relationships, and when it might first emerge in childhood. This paper reviews the wide range of interdisciplinary research relevant to the tightwad‐spendthrift construct and proposes several directions for new research. Full Text Available Here: https://doi.org/10.1002/cfp2.1010
Maximum-Entropy Fine Grained Classification

Fine-Grained Visual Classification (FGVC) is an important computer vision problem that involves small diversity within the different classes, and often requires expert annotators to collect data. Utilizing this notion of small visual diversity, we revisit Maximum-Entropy learning in the context of fine-grained classification, and provide a training routine that maximizes the entropy of the output probability distribution for training convolutional neural networks on FGVC tasks. We provide a theoretical as well as empirical justification of our approach, and achieve state-of-the-art performance across a variety of classification tasks in FGVC, that can potentially be extended to any fine-tuning task. Our method is robust to different hyperparameter values, amount of training data and amount of training label noise and can hence be a valuable tool in many similar problems.
Evidence and Actions on Mortgage Market Disparities: Research, Fair Lending Enforcement, and Consumer Protection

ABSTRACTIn this article, we present an overview of the research on discrimination in mortgage underwriting and pricing, the experiences of minority borrowers both prior to and during the financial ...
Identifying Tidal Disruption Events via Prior Photometric Selection of Their Preferred Hosts

A nuclear transient detected in a post-starburst galaxy or other quiescent galaxy with strong Balmer absorption is likely to be a Tidal Disruption Event (TDE). Identifying such galaxies within the planned survey footprint of the Large Synoptic Survey Telescope (LSST)---before a transient is detected---will make TDE classification immediate and follow-up more efficient. Unfortunately, spectra for identifying most such galaxies are unavailable, and simple photometric selection is ineffective; cutting on "green valley" UV/optical/IR colors produces samples that are highly contaminated and incomplete. Here we propose a new strategy using only photometric optical/UV/IR data from large surveys. Applying a machine learning Random Forest classifier to a sample of ~400k SDSS galaxies with GALEX and WISE photometry, including 13,592 quiescent Balmer-strong galaxies, we achieve 53-61% purity and 8-21% completeness, given the range in redshift. For the subset of 1299 post-starburst galaxies, we achieve 63-73% purity and 5-12% completeness. Given these results, the range of likely TDE and supernova rates, and that 36-75% of TDEs occur in quiescent Balmer-strong hosts, we estimate that 13-99% of transients observed in photometrically-selected host galaxies will be TDEs and that we will discover 119-248 TDEs per year with LSST. Using our technique, we present a new catalog of 67,484 candidate galaxies expected to have a high TDE rate, drawn from the SDSS, Pan-STARRS, DES, and WISE photometric surveys. This sample is 3.5x larger than the current SDSS sample of similar galaxies, thereby providing a new path forward for transient science and galaxy evolution studies.
Synthesis and Initial In Vivo Evaluation of [11C]AZ683-A Novel PET Radiotracer for Colony Stimulating Factor 1 Receptor (CSF1R).

Positron emission tomography (PET) imaging of Colony Stimulating Factor 1 Receptor (CSF1R) is a new strategy for quantifying both neuroinflammation and inflammation in the periphery since CSF1R is expressed on microglia and macrophages. AZ683 has high affinity for CSF1R (Ki = 8 nM; IC50 = 6 nM) and >250-fold selectivity over 95 other kinases. In this paper, we report the radiosynthesis of [11C]AZ683 and initial evaluation of its use in CSF1R PET. [11C]AZ683 was synthesized by 11C-methylation of the desmethyl precursor with [11C]MeOTf in 3.0% non-corrected activity yield (based upon [11C]MeOTf), >99% radiochemical purity and high molar activity. Preliminary PET imaging with [11C]AZ683 revealed low brain uptake in rodents and nonhuman primates, suggesting that imaging neuroinflammation could be challenging but that the radiopharmaceutical could still be useful for peripheral imaging of inflammation.
Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls

To inform product release and distribution strategies, research has analyzed cross-market spillovers in new product adoption. However, models that examine these effects for digital and viral media ...
Watermarking PRFs from Lattices: Stronger Security via Extractable PRFs

A software watermarking scheme enables one to embed a “mark” (i.e., a message) within a program while preserving the program’s functionality. Moreover, there is an extraction algorithm that recovers an embedded message from a program. The main security goal is that it should be difficult to remove the watermark without destroying the functionality of the program. Existing constructions of watermarking focus on watermarking cryptographic functions like pseudorandom functions (PRFs); even in this setting, realizing watermarking from standard assumptions remains difficult. The first lattice-based construction of secret-key watermarking due to Kim and Wu (CRYPTO 2017) only ensures mark-unremovability against an adversary who does not have access to the mark-extraction oracle. The construction of Quach et al. (TCC 2018) achieves the stronger notion of mark-unremovability even if the adversary can make extraction queries, but has the drawback that the watermarking authority (who holds the watermarking secret key) can break pseudorandomness of all PRF keys in the family (including unmarked keys).
Production planning with multiple production lines: Forward algorithm and insights on process design for volume flexibility

This paper considers the production planning problem of a firm that produces a single product using a process that has multiple production lines (or machines) in parallel, each with a finite production capacity. Specifically, the firm has m parallel production lines, each with capacity of P units per period. If needed, the firm can adjust the production rate in a period by adjusting the number of lines it operates in the period. The firm faces time‐varying demands. The objective is to find a production plan that meets the demands over the problem horizon and minimizes the sum of setup, holding and variable production costs. The paper develops an efficient forward dynamic programming algorithm and uses it to develop managerial insights on the effect of process design on “volume flexibility,” which is defined as “the ability to be operated profitably at different output levels.” Some forecast horizon results are also developed. The firm can use the results in the paper to optimize the process design for the demand it faces.
Flexible Polymer-Assisted Mesoscale Self-Assembly of Colloidal CsPbBr3 Perovskite Nanocrystals into Higher Order Superstructures with Strong Inter-Nanocrystal Electronic Coupling.

Surface-passivating ligands, although ubiquitous to colloidal nanocrystal (NC) syntheses, play a role in assembling NCs into higher order structures and hierarchical superstructures, which has not been demonstrated yet for colloidal CsPbX3 (X = Cl, Br, and I) NCs. In this work, we report that functional poly(ethylene glycols) (PEG6-Y, Y = −COOH and −NH2) represent unique surface-passivating ligands enabling the synthesis of near-uniform CsPbBr3 NCs with diameters of 3.0 nm. The synthesized NCs are assembled into individual pearl necklaces, bundled pearl necklaces, lamellar, and nanorice superstructures, in situ. It is believed a variety of forces, including van der Waals attractions between hydrophilic PEG tails in a nonpolar solvent and dipole–dipole attraction between NCs, drive mesoscale assembly to form superstructures. Furthermore, postsynthetic ligand treatment strengthens the argument for polymer-assisted mesoscale assembly as pearl necklace assemblies can be successfully converted into either lame...
Demographic consequences of climate variation along an elevational gradient for a montane terrestrial salamander

Global amphibian populations are declining and evidence suggests that future changes in climate will have a negative effect on many populations, especially salamanders within the southern Appalachians. However, for many salamander species, the relationship between demographic vital rates (i.e., survival, growth, and reproduction) and climate is unknown, which limits predictive models. We, therefore, describe the life history variation of Plethodon montanus using capture-recapture data over a period of four years, at five sites along an elevational gradient and determined how vital rates vary with body size, elevation, sex, and season. We used a hierarchical model to estimate growth rate, asymptotic size, and the variance in periodic growth, while we used a spatial Cormack-Jolly-Seber model to estimate probability of capture and survival, as well as dispersal variance. Our results show that highest elevation population had a larger asymptotic size, slower growth, but also had higher survival compared to the lower elevation populations. Moreover, we found a disparity in seasonal survival among our elevations, at higher elevations, survival was higher during the inactive season (late fall, winter, early spring) compared to the active season, whereas the lower elevations showed either no difference in seasonal survival or had lower survival during the inactive season compare to the active season. Our results provide uncertainty in vital rates for this P. montanus, which can inform population models. Furthermore, given that survival is reduced in warmer habitats compared to cooler, the effect of future warming in the southern Appalachians and the ability of salamanders to adapt to these novel climates should be a focus of future research.
Theoretical Explanation for Reduced Body Mass Index and Obesity Rates in Cannabis Users

Introduction: Obesity is treatment-resistant, and is linked with a number of serious, chronic diseases. Adult obesity rates in the United States have tripled since the early 1960s. Recent reviews show that an increased ratio of omega-6 to omega-3 fatty acids contributes to obesity rates by increasing levels of the endocannabinoid signals AEA and 2-AG, overstimulating CB1R and leading to increased caloric intake, reduced metabolic rates, and weight gain. Cannabis, or THC, also stimulates CB1R and increases caloric intake during acute exposures. Goals: To establish the relationship between Cannabis use and body mass index, and to provide a theoretical explanation for this relationship. Results: The present meta-analysis reveals significantly reduced body mass index and rates of obesity in Cannabis users, in conjunction with increased caloric intake. Theoretical explanation: We provide for the first time a causative explanation for this paradox, in which rapid and long-lasting downregulation of CB1R following acute Cannabis consumption reduces energy storage and increases metabolic rates, thus reversing the impact on body mass index of elevated dietary omega-6/omega-3 ratios.