cssi/SciSciGPT-SciSciNet huggingface dataset:
Exploring transfer learning for end-to-end spoken language understanding

Voice Assistants such as Alexa, Siri, and Google Assistant typically use a two-stage Spoken Language Understanding pipeline; first, an Automatic Speech Recognition (ASR) component to process customer speech and generate text transcriptions, followed by a Natural Language Understanding (NLU) component to map transcriptions to an actionable hypothesis. An end-to-end (E2E) system that goes directly from speech to a hypothesis is a more attractive option. These systems were shown to be smaller, faster, and better optimized. However, they require massive amounts of end-to-end training data and in addition, don't take advantage of the already available ASR and NLU training data. In this work, we propose an E2E system that is designed to jointly train on multiple speech-to-text tasks, such as ASR (speech-transcription) and SLU (speech-hypothesis), and text-to-text tasks, such as NLU (text-hypothesis). We call this the Audio-Text All-Task (AT-AT) Model and we show that it beats the performance of E2E models trained on individual tasks, especially ones trained on limited data. We show this result on an internal music dataset and two public datasets, FluentSpeech and SNIPS Audio, where we achieve state-of-the-art results. Since our model can process both speech and text input sequences and learn to predict a target sequence, it also allows us to do zero-shot E2E SLU by training on only text-hypothesis data (without any speech) from a new domain. We evaluate this ability of our model on the Facebook TOP dataset and set a new benchmark for zeroshot E2E performance. We release the audio data collected for the TOP dataset for future research.
When Falling Just Short is a Good Thing: The Effect of Past Performance on Improvement:

Models of reference-dependent preferences show that an individual’s utility depends on the difference between the outcome and a “neutral” reference point. Our paper investigates how distance from r...
Near-Zero Downtime Recovery From Transient-Error-Induced Crashes

Due to the system scaling, transient errors caused by external noise, e.g., heat fluxes and particle strikes, have become a growing concern for the current and upcoming exa-scale high-performance-computing (HPC) systems. Applications running on these systems are expected to experience transient errors more frequently than ever before, which will either lead them to generate incorrect outputs or cause them to crash. However, since such errors are still quite rare as compared to no-fault cases, desirable solutions call for low/no-overhead systems that do not compromise the performance under no-fault conditions and also allow very fast fault recovery to minimize downtime. In this article, we present IterPro , a light-weight compiler-assisted resilience technique to quickly and accurately recover processes from transient-error-induced crashes. During the compilation of applications, IterPro constructs a set of recovery kernels for crash-prone instructions. These recovery kernels are executed to repair the corrupted process states on-the-fly upon occurrences of errors, enabling applications to continue their executions instead of being terminated. When constructing recovery kernels, IterPro exploits side effects introduced by induction variable based code optimization techniques based on loop unrolling and strength reduction to improve its recovery capability. To this end, two new code transformation passes are introduced to expose the side effects for resilience purposes. We evaluated IterPro with 4 scientific workloads as well as the NPB benchmarks suite. During their normal execution, IterPro incurs almost zero runtime overhead and a small, fixed 27MB memory overhead. Meanwhile, IterPro can recover on an average 83.55 percent of crash-causing errors within dozens of milliseconds with negligible downtime. We also evaluated IterPro with parallel jobs running on 3072 cores and showed that IterPro can successfully mask the impact of crash-causing errors by providing almost uninterrupted execution. Finally, we present our preliminary evaluation result for BLAS, which shows that IterPro is capable of recovering failures in libraries with a very high coverage rate of 83 percent and negligible overheads. With such an effective recovery mechanism, IterPro could tremendously mitigate the overheads and resource requirements of the resilience subsystem in future exa-scale systems.
Dissipative models of swell propagation across the Pacific

Ocean swell plays an important role in the transport of energy across the ocean, yet its evolution is still not well understood. In the late 1960s, the nonlinear Schr{\"o}dinger (NLS) equation was ...
Protest Puzzles: Tullock's Paradox, Hong Kong Experiment, and the Strength of Weak States

Tullock's (1971) Paradox of Revolution uses an Olsonian logic to conclude that revolutions should not happen in large societies. Cantoni et al.'s (2018) Hong Kong Experiment shows that, in sharp contrast to the literature that models protest as a coordination problem, actions can be strategic substitutes. We develop a model to address these standing puzzles, and investigate its empirical implications. We show that when the movement's goal is modest, free-riding concerns dominate the citizens' interactions, making their actions strategic substitutes. By contrast, when the movement's goal is to topple the regime, coordination concerns dominate, and actions become strategic complements. Moreover, with natural other-regarding preferences, some citizens participate in costly revolt even in large societies. A new empirical implication of the model is that as a regime grows stronger in the sense that a larger fraction of citizens is needed to overthrow it, the likelihood of regime change may rise.
Optimal Feedback in Contests

We derive an optimal dynamic contest for environments where effort can be monitored only through a coarse, binary performance measure and the principal chooses prize-allocation and termination rules together with a real-time feedback policy for the contestants. The optimal contest takes a stark cyclical form: contestants are kept fully apprised of their own successes, and at the end of each fixed-length cycle, if at least one agent has succeeded, the contest ends and the prize is shared equally among all successful agents irrespective of when they succeeded; otherwise, the designer informs all contestants that nobody has yet succeeded and the contest resets. Applications include promotions, innovation contests, and proof-of-work protocols.
Low $c$-differential and $c$-boomerang uniformity of the swapped inverse function

Abstract Modifying the binary inverse function in a variety of ways, like swapping two output points has been known to produce a 4-differential uniform permutation function. Recently, in [21] it was shown that this swapped version of the inverse function has boomerang uniformity exactly 10, if n ≡ 0 ( mod 6 ) , 8, if n ≡ 3 ( mod 6 ) , and 6, if n ≢ 0 ( mod 3 ) . Based upon the c-differential and c-boomerang uniformity notions we defined in [16] , respectively, [30] , in this paper we characterize the c-differential and c-boomerang uniformity for the ( 0 , 1 ) -swapped inverse function in even characteristic, x 2 n − 2 + x 2 n − 1 + ( x + 1 ) 2 n − 1 on F 2 n : we show that for all c ≠ 1 , the c-differential uniformity is upper bounded by 4 and the c-boomerang uniformity by 5 with both bounds being attained for n ≥ 4 .
Shape, Sizing, and Topology Design of a Wingbox Under Aeroelastic Constraints

This work considers the aeroelastic optimization of transport wingbox structures under three different types of design variables: sizing (for example, skin thickness), shape (planform and airfoil t...
Designing Efficient and High-Performance AI Accelerators With Customized STT-MRAM

We demonstrate the design of efficient and high-performance artificial intelligence (AI)/deep learning accelerators with customized spin transfer torque (STT)-MRAM (STT-MRAM) and a reconfigurable core. Based on model-driven detailed design space exploration, we present the design methodology of an innovative scratchpad-assisted on-chip STT-MRAM-based buffer system for high-performance accelerators. Using analytically derived expression of memory occupancy time of AI model weights and activation maps, the volatility of STT-MRAM is adjusted with process and temperature variation aware scaling of thermal stability factor to optimize the retention time, energy, read/write latency, and area of STT-MRAM. From the analysis of AI workloads and accelerator implementation in 14-nm technology, we verify the efficacy of our AI accelerator with STT-MRAM (STT-AI). Compared to an SRAM-based implementation, the STT-AI accelerator achieves 75% area and 3% power savings at isoaccuracy. Furthermore, with a relaxed bit error rate and negligible AI accuracy tradeoff, the designed STT-AI Ultra accelerator achieves 75.4% and 3.5% savings in area and power, respectively, over regular SRAM-based accelerators.
The emergence of heterogeneous scaling in research institutions

Research institutions provide the infrastructure for scientific discovery, yet their role in the production of knowledge is not well characterized. To address this gap, we analyze interactions of researchers within and between institutions from millions of scientific papers. Our analysis reveals that collaborations densify as each institution grows, but at different rates (heterogeneous densification). We also find that the number of institutions scales with the number of researchers as a power law (Heaps’ law) and institution sizes approximate Zipf’s law. These patterns can be reproduced by a simple model in which researchers are preferentially hired by large institutions, while new institutions complimentarily generate more new institutions. Finally, new researchers form triadic closures with collaborators. This model reveals an economy of scale in research: larger institutions grow faster and amplify collaborations. Our work deepens the understanding of emergent behavior in research institutions and their role in facilitating collaborations. The scientific ecosystem is characterized by complex multifaceted relationships between institutions, researchers, and their collaborators. In this work, the authors find common patterns in these relationships expressed through superlinear scaling, Heaps’ law, and Zipf’s law within the global collaboration network, and propose a minimal network model to explain these patterns based on preferential hiring by larger institutions, the “adjacent possible” capturing the birth of new institutions, and triadic closure of collaborations.
RDC complex executes a dynamic piRNA program during Drosophila spermatogenesis to safeguard male fertility

piRNAs are small non-coding RNAs that guide the silencing of transposons and other targets in animal gonads. In Drosophila female germline, many piRNA source loci dubbed "piRNA clusters" lack hallmarks of active genes and exploit an alternative path for transcription, which relies on the Rhino-Deadlock-Cutoff (RDC) complex. RDC was thought to be absent in testis, so it remains to date unknown how piRNA cluster transcription is regulated in the male germline. We found that components of RDC complex are expressed in male germ cells during early spermatogenesis, from germline stem cells (GSCs) to early spermatocytes. RDC is essential for expression of dual-strand piRNA clusters and transposon silencing in testis; however, it is dispensable for expression of Y-linked Suppressor of Stellate piRNAs and therefore Stellate silencing. Despite intact Stellate repression, males lacking RDC exhibited compromised fertility accompanied by germline DNA damage and GSC loss. Thus, piRNA-guided repression is essential for normal spermatogenesis beyond Stellate silencing. While RDC associates with multiple piRNA clusters in GSCs and early spermatogonia, its localization changes in later stages as RDC concentrates on a single X-linked locus, AT-chX. Dynamic RDC localization is paralleled by changes in piRNA cluster expression, indicating that RDC executes a fluid piRNA program during different stages of spermatogenesis. These results disprove the common belief that RDC is dispensable for piRNA biogenesis in testis and uncover the unexpected, sexually dimorphic and dynamic behavior of a core piRNA pathway machinery.
Energy-Harvesting Distributed Machine Learning

This paper provides a first study of utilizing energy harvesting for sustainable machine learning in distributed networks. We consider a distributed learning setup in which a machine learning model is trained over a large number of devices that can harvest energy from the ambient environment, and develop a practical learning framework with theoretical convergence guarantees. We demonstrate through numerical experiments that the proposed framework can significantly out- perform energy-agnostic benchmarks. Our framework is scalable, requires only local estimation of the energy statistics, and can be applied to a wide range of distributed training settings, including machine learning in wireless networks, edge computing, and mobile internet of things.
Transfer rate of enveloped and non-enveloped viruses between fingerpads and surfaces.

Fomites can represent a reservoir for pathogens, which may be subsequently transferred from surfaces to skin. In this study, we aim to understand how different factors (including virus type, surface type, time since last hand wash, and direction of transfer) affect virus transfer rates, defined as the fraction of virus transferred, between fingerpads and fomites. To determine this, 360 transfer events were performed with 20 volunteers using Phi6 (a surrogate for enveloped viruses), MS2 (a surrogate for nonenveloped viruses), and three clean surfaces (stainless steel, painted wood, and plastic). Considering all transfer events (all surfaces and both transfer directions combined), the mean transfer rates of Phi6 and MS2 were 0.17 and 0.26, respectively. Transfer of MS2 was significantly higher than that of Phi6 (P < 0.05). Surface type was a significant factor that affected the transfer rate of Phi6: Phi6 is more easily transferred to and from stainless steel and plastic than to and from painted wood. Direction of transfer was a significant factor affecting MS2 transfer rates: MS2 is more easily transferred from surfaces to fingerpads than from fingerpads to surfaces. Data from these virus transfer events, and subsequent transfer rate distributions, provide information that can be used to refine quantitative microbial risk assessments. This study provides a large-scale data set of transfer events with a surrogate for enveloped viruses, which extends the reach of the study to the role of fomites in the transmission of human enveloped viruses like influenza and SARS-CoV-2. IMPORTANCE This study created a large-scale data set for the transfer of enveloped viruses between skin and surfaces. The data set produced by this study provides information on modeling the distribution of enveloped and nonenveloped virus transfer rates, which can aid in the implementation of risk assessment models in the future. Additionally, enveloped and nonenveloped viruses were applied to experimental surfaces in an equivalent matrix to avoid matrix effects, so results between different viral species can be directly compared without confounding effects of different matrices. Our results indicating how virus type, surface type, time since last hand wash, and direction of transfer affect virus transfer rates can be used in decision-making processes to lower the risk of viral infection from transmission through fomites.
A Comprehensive Revisit of Select Galileo/NIMS Observations of Europa

The Galileo Near Infrared Mapping Spectrometer (NIMS) collected spectra of Europa in the 0.7-5.2 $\mu$m wavelength region, which have been critical to improving our understanding of the surface composition of this moon. However, most of the work done to get constraints on abundances of species like water ice, hydrated sulfuric acid, hydrated salts and oxides have used proxy methods, such as absorption strength of spectral features or fitting a linear mixture of laboratory generated spectra. Such techniques neglect the effect of parameters degenerate with the abundances, such as the average grain-size of particles, or the porosity of the regolith. In this work we revisit three Galileo NIMS spectra, collected from observations of the trailing hemisphere of Europa, and use a Bayesian inference framework, with the Hapke reflectance model, to reassess Europa's surface composition. Our framework has several quantitative improvements relative to prior analyses: (1) simultaneous inclusion of amorphous and crystalline water ice, sulfuric-acid-octahydrate (SAO), CO$_2$, and SO$_2$; (2) physical parameters like regolith porosity and radiation-induced band-center shift; and (3) tools to quantify confidence in the presence of each species included in the model, constrain their parameters, and explore solution degeneracies. We find that SAO strongly dominates the composition in the spectra considered in this study, while both forms of water ice are detected at varying confidence levels. We find no evidence of either CO$_2$ or SO$_2$ in any of the spectra; we further show through a theoretical analysis that it is highly unlikely that these species are detectable in any 1-2.5 $\mu$m Galileo NIMS data.
Pricing ethics in the foreign exchange market: Environmental, Social and Governance ratings and currency premia

Abstract We examine the cross-sectional predictive ability of the Refinitiv Environmental, Social and Governance (ESG) score for returns in the foreign exchange market, using ESG scores aggregated at the national level, and find that ESG is a strong negative predictor of currency returns. Intuitively, investors require a premium for financing low-ESG countries while high-ESG countries offer lower returns and provide a hedge in the bad state of the world. We show that ESG is priced in the cross-section of currency returns. We also consider the different components of ESG and show that its predictability is driven by the environmental pillar of the ESG ratings. Our results have strong implications for portfolios of individual investors and fund managers and offer new insights for policymakers in the foreign exchange market. The profitability of the ESG currency strategy is not driven by the carry trade and is robust to transaction costs.
Repairing Human Trust by Promptly Correcting Robot Mistakes with An Attention Transfer Model

In human-robot collaboration (HRC), human trust in the robot is the human expectation that a robot executes tasks with desired performance. A higher-level trust increases the willingness of a human operator to assign tasks, share plans, and reduce the interruption during robot executions, thereby facilitating human-robot integration both physically and mentally. However, due to real-world disturbances, robots inevitably make mistakes, decreasing human trust and further influencing collaboration. Trust is fragile and trust loss is triggered easily when robots show incapability of task executions, making the trust maintenance challenging. To maintain human trust, in this research, a trust repair framework is developed based on a human-to-robot attention transfer (H2R-AT) model and a user trust study. The rationale of this framework is that a prompt mistake correction restores human trust. With H2R-AT, a robot localizes human verbal concerns and makes prompt mistake corrections to avoid task failures in an early stage and to finally improve human trust. User trust study measures trust status before and after the behavior corrections to quantify the trust loss. Robot experiments were designed to cover four typical mistakes, wrong action, wrong region, wrong pose, and wrong spatial relation, validated the accuracy of H2R-AT in robot behavior corrections; a user trust study with 252 participants was conducted, and the changes in trust levels before and after corrections were evaluated. The effectiveness of the human trust repairing was evaluated by the mistake correction accuracy and the trust improvement.
Minimax optimal conditional independence testing

We consider the problem of conditional independence testing of X and Y given Z where X,Y and Z are three real random variables and Z is continuous. We focus on two main cases—when X and Y are both discrete, and when X and Y are both continuous. In view of recent results on conditional independence testing [Ann. Statist. 48 (2020) 1514–1538], one cannot hope to design nontrivial tests, which control the type I error for all absolutely continuous conditionally independent distributions, while still ensuring power against interesting alternatives. Consequently, we identify various, natural smoothness assumptions on the conditional distributions of X,Y|Z=z as z varies in the support of Z, and study the hardness of conditional independence testing under these smoothness assumptions. We derive matching lower and upper bounds on the critical radius of separation between the null and alternative hypotheses in the total variation metric. The tests we consider are easily implementable and rely on binning the support of the continuous variable Z. To complement these results, we provide a new proof of the hardness result of Shah and Peters [Ann. Statist. 48 (2020) 1514–1538].
Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition

Human pose is a useful feature for fine-grained sports action understanding. However, pose estimators are often unreliable when run on sports video due to domain shift and factors such as motion blur and occlusions. This leads to poor accuracy when downstream tasks, such as action recognition, depend on pose. End-to-end learning circumvents pose, but requires more labels to generalize. We introduce Video Pose Distillation (VPD), a weakly-supervised technique to learn features for new video domains, such as individual sports that challenge pose estimation. Under VPD, a student network learns to extract robust pose features from RGB frames in the sports video, such that, whenever pose is considered reliable, the features match the output of a pretrained teacher pose detector. Our strategy retains the best of both pose and end-to-end worlds, exploiting the rich visual patterns in raw video frames, while learning features that agree with the athletes' pose and motion in the target video domain to avoid over-fitting to patterns unrelated to athletes' motion. VPD features improve performance on few-shot, fine-grained action recognition, retrieval, and detection tasks in four real-world sports video datasets, without requiring additional ground-truth pose annotations.
easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application

Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it can be used with other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples.
Understanding Barriers and Design Opportunities to Improve Healthcare and QOL for Older Adults through Voice Assistants

Voice-based Intelligent Virtual Assistants (IVAs) promise to improve healthcare management and Quality of Life (QOL) by introducing the paradigm of hands-free and eye-free interactions. However, there has been little understanding regarding the challenges for designing such systems for older adults, especially when it comes to healthcare related tasks. To tackle this, we consider the processes of care delivery and QOL enhancements for older adults as a collaborative task between patients and providers. By interviewing 16 older adults living independently or semi–independently and 5 providers, we identified 12 barriers that older adults might encounter during daily routine and while managing health. We ultimately highlighted key design challenges and opportunities that might be introduced when integrating voice-based IVAs into the life of older adults. Our work will benefit practitioners who study and attempt to create full-fledged IVA-powered smart devices to deliver better care and support an increased QOL for aging populations.
How Field Experiments in Economics Can Complement Psychological Research on Judgment Biases

This review summarizes results of field experiments examining individual behaviors across several market settings—from open-air markets to rideshare markets to tax-compliance markets—where people s...
Iterative hard thresholding for low CP-rank tensor models

Recovery of low-rank matrices from a small number of linear measurements is now well-known to be possible under various model assumptions on the measurements. Such results demonstrate robustness an...
Visuomotor brain network activation and functional connectivity among individuals with autism spectrum disorder.

Sensorimotor abnormalities are common in autism spectrum disorder (ASD) and predictive of functional outcomes, though their neural underpinnings remain poorly understood. Using functional magnetic resonance imaging, we examined both brain activation and functional connectivity during visuomotor behavior in 27 individuals with ASD and 30 typically developing (TD) controls (ages 9-35 years). Participants maintained a constant grip force while receiving visual feedback at three different visual gain levels. Relative to controls, ASD participants showed increased force variability, especially at high gain, and reduced entropy. Brain activation was greater in individuals with ASD than controls in supplementary motor area, bilateral superior parietal lobules, and contralateral middle frontal gyrus at high gain. During motor action, functional connectivity was reduced between parietal-premotor and parietal-putamen in individuals with ASD compared to controls. Individuals with ASD also showed greater age-associated increases in functional connectivity between cerebellum and visual, motor, and prefrontal cortical areas relative to controls. These results indicate that visuomotor deficits in ASD are associated with atypical activation and functional connectivity of posterior parietal, premotor, and striatal circuits involved in translating sensory feedback information into precision motor behaviors, and that functional connectivity of cerebellar-cortical sensorimotor and nonsensorimotor networks show delayed maturation.
Physical interaction as communication: Learning robot objectives online from human corrections:

When a robot performs a task next to a human, physical interaction is inevitable: the human might push, pull, twist, or guide the robot. The state of the art treats these interactions as disturbanc...
Recent advances in bianisotropic boundary conditions: theory, capabilities, realizations, and applications

In recent years, new functionality and unprecedented wavefront control has been enabled by the introduction of bianisotropic metasurfaces. A bianisotropic metasurface is characterized by an electric response, a magnetic response, and an electromagnetic/magnetoelectric response. In general, these metasurfaces consists of an array of metallic or dielectric particles located within a subwavelength thick host medium, and are approximated and modelled as infinitely thin, idealized sheet boundaries defined along a surface. An appropriate sheet boundary condition which effectively models the tangential field discontinuity due to the array of magnetoelectric inclusions is the Generalized Sheet Transition Condition or GSTC. Several forms of the GSTC appear in literature. Here, we present each interpretation and show how they are related. Synthesis approaches unique to each form are overviewed. By utilizing the GSTC in metasurface design, new possibilities emerge which are not possible with conventional design techniques incorporating only electric or only magnetic responses. Since the metasurfaces are designed using bianisotropic boundary conditions, they must be realized using particles which contain magnetoelectric responses. This review article discusses the design of metasurfaces using the GSTC, and the bianisotropic particles used to realize the GSTC. Further, it discusses new and recent applications that have emerged due to bianisotropy, and future prospects in metasurface design using bianisotropic boundary conditions. The intent is to provide a comprehensive overview of metasurface design involving bianisotropy and for this review article to serve as a starting point for engineers and scientist that wish to introduce bianisotropy into metasurface design.
Segmentation for classification of screening pancreatic neuroendocrine tumors

This work presents comprehensive results to detect in the early stage the pancreatic neuroendocrine tumors (PNETs), a group of endocrine tumors arising in the pancreas, which are the second common type of pancreatic cancer, by checking the abdominal CT scans. To the best of our knowledge, this task has not been studied before as a computational task. To provide radiologists with tumor locations, we adopt a segmentation framework to classify CT volumes by checking if at least a sufficient number of voxels is segmented as tumors. To quantitatively analyze our method, we collect and voxelwisely label a new abdominal CT dataset containing $376$ cases with both arterial and venous phases available for each case, in which $228$ cases were diagnosed with PNETs while the remaining $148$ cases are normal, which is currently the largest dataset for PNETs to the best of our knowledge. In order to incorporate rich knowledge of radiologists to our framework, we annotate dilated pancreatic duct as well, which is regarded as the sign of high risk for pancreatic cancer. Quantitatively, our approach outperforms state-of-the-art segmentation networks and achieves a sensitivity of $89.47\%$ at a specificity of $81.08\%$, which indicates a potential direction to achieve a clinical impact related to cancer diagnosis by earlier tumor detection.
Was Venus Ever Habitable? Constraints from a Coupled Interior–Atmosphere–Redox Evolution Model

Venus's past climate evolution is uncertain. General circulation model simulations permit a habitable climate as late as ~0.7 Ga, and there is suggestive-albeit inconclusive-evidence for previous liquid water from surface geomorphology and mineralogy. However, it is unclear whether a habitable past can be reconciled with Venus's inferred atmospheric evolution. In particular, the lack of leftover atmospheric oxygen argues against recent water loss. Here, we apply a fully coupled model of Venus's atmospheric-interior-climate evolution from post-accretion magma ocean to present. The model self-consistently tracks C-, H-, and O-bearing volatiles and surface climate through the entirety of Venus's history. Atmospheric escape, mantle convection, melt production, outgassing, deep water cycling, and carbon cycling are explicitly coupled to climate and redox evolution. Plate tectonic and stagnant lid histories are considered. Using this coupled model, we conclude that both a habitable Venusian past and one where Venus never possessed liquid surface water can be reconciled with known constraints. Specifically, either scenario can reproduce bulk atmospheric composition, inferred surface heat flow, and observed $^{40}$Ar and $^{4}$He. Moreover, the model suggests that Venus could have been habitable with a ~100 m global ocean as late as 1 Ga, without violating any known constraints. In fact, if diffusion-limited water loss is throttled by a cool, CO$_2$-dominated upper atmosphere, then a habitable past is tentatively favored by our model. This escape throttling makes it difficult to simultaneously recover negligible water vapor and ~90 bar CO$_2$ in the modern atmosphere without temporarily sequestering carbon in the interior via silicate weathering to enhance H escape.
Core Protein-Directed Antivirals and Importin β Can Synergistically Disrupt HBV Capsids

Viral structural proteins can have multiple activities. Antivirals that target structural proteins have potential to exhibit multiple antiviral mechanisms. Hepatitis B Virus (HBV) core protein (Cp) is involved in most stages of the viral lifecycle: it assembles into capsids, packages viral RNA, is a metabolic compartment for reverse transcription, interacts with nuclear trafficking machinery, and disassembles to release the viral genome into the nucleus. During nuclear localization, HBV capsids bind to host importins (e.g. Impβ) via Cp's C-terminal domain (CTD); the CTD is localized to the interior of the capsid and is transiently exposed on the exterior. We used HAP12 as a representative Cp Allosteric Modulators (CpAMs), a class of antivirals that inappropriately stimulates and misdirects HBV assembly and deforms capsids. CpAM impact on other aspects of the HBV lifecycle is poorly understood. We investigated how HAP12 influenced the interactions between empty or RNA-filled capsids with Impβ and trypsin in vitro. We showed that HAP12 can modulate CTD accessibility and capsid stability, depending on the saturation of HAP12-binding sites. We demonstrated that Impβ synergistically contributes to capsid disruption at high levels of HAP12 saturation, using electron microscopy to visualize disruption and rearrangement of Cp dimers into aberrant complexes. However, RNA-filled capsids resisted the destabilizing effects of HAP12 and Impβ. In summary, we show host protein-induced catalysis of capsid disruption, an unexpected additional mechanism of action for CpAMs. Potentially, untimely capsid disassembly can hamper the HBV lifecycle and also cause the virus to become vulnerable to host innate immune responses. IMPORTANCE The HBV core, an icosahedral complex of 120 copies of the homodimeric core (capsid) protein with or without packaged nucleic acid, is transported to the host nucleus by its interaction with host importin proteins. Importin-core interaction requires the core protein C-terminal domain, which is inside the capsid, to "flip" to the capsid exterior. Core-protein directed drugs that affect capsid assembly and stability have been developed recently. We show that these molecules can, synergistically with importins, disrupt capsids. This mechanism of action, synergism with host protein, has potential to disrupt the virus lifecycle and activate the innate immune system.
Employee satisfaction and stock returns during the COVID-19 Pandemic

Abstract The COVID-19 Pandemic has had an unprecedented impact on how employees and employers operate. Employees, directly affected by workplace changes, may provide information regarding future efficiencies. As a result, crowdsourced employee satisfaction ( E S ) reviews mentioning the COVID-19 Pandemic may contain useful information regarding the future profitability of these firms. We utilize crowdsourced COVID-19 Pandemic specific E S obtained from Glassdoor.com to determine the impact on abnormal stock returns for public firms from March-December 2020. We find evidence that higher COVID-19 E S is related to higher abnormal stock returns. While non-COVID E S is found not to be related to abnormal stock returns.
Granger Causality: A Review and Recent Advances

Introduced more than a half-century ago, Granger causality has become a popular tool for analyzing time series data in many application domains, from economics and finance to genomics and neuroscie...
Chapter 6 Overview: Renal Potassium Transport along the Nephron

Publisher Summary This chapter discusses the renal potassium (K) handling along the nephron. Renal mechanisms for excretion of K indicate that K excretion depends on secretion of K at a distal tubule site and that the secretory process behaves as though it involves an exchange of reabsorbed Na for secreted K. The idea that a distal secretory process provides the major route by which K gains access to the urine and is ultimately excreted has been confirmed in several respects. The rate of distal secretion is variable and is changed from near zero to rates exceeding the K filtration rate by factors that change urinary excretion in the same direction. K is not totally reabsorbed by the proximal tubule and by the ascending limb of the loop of Henle, but the quantity of K left unreabsorbed at the beginning of the distal secretory region does not vary over as wide a range as the quantity reaching the collecting duct or the final urine.
Unmasking Proteolytic Activity for Adult Visual Cortex Plasticity by the Removal of Lynx1.

Experience-dependent cortical plasticity declines with age. At the molecular level, experience-dependent proteolytic activity of tissue plasminogen activator (tPA) becomes restricted in the adult brain if mice are raised in standard cages. Understanding the mechanism for the loss of permissive proteolytic activity is therefore a key link for improving function in adult brains. Using the mouse primary visual cortex (V1) as a model, we demonstrate that tPA activity in V1 can be unmasked following 4 d of monocular deprivation when the mice older than 2 months are raised in standard cages by the genetic removal of Lynx1, a negative regulator of adult plasticity. This was also associated with the reduction of stubby and thin spine density and enhancement of ocular dominance shift in adult V1 of Lynx1 knock-out (KO) mice. These structural and functional changes were tPA-dependent because genetic removal of tPA in Lynx1 KO mice can block the monocular deprivation-dependent reduction of dendritic spine density, whereas both genetic and adult specific inhibition of tPA activity can ablate the ocular dominance shift in Lynx1 KO mice. Our work demonstrates that the adult brain has an intrinsic potential for experience-dependent elevation of proteolytic activity to express juvenile-like structural and functional changes but is effectively limited by Lynx1 if mice are raised in standard cages. Insights into the Lynx1-tPA plasticity mechanism may provide novel therapeutic targets for adult brain disorders. SIGNIFICANCE STATEMENT Experience-dependent proteolytic activity of tissue plasminogen activator (tPA) becomes restricted in the adult brain in correlation with the decline in cortical plasticity when mice are raised in standard cages. We demonstrated that removal of Lynx1, one of negative regulators of plasticity, unmasks experience-dependent tPA elevation in visual cortex of adult mice reared in standard cages. This proteolytic elevation facilitated dendritic spine reduction and ocular dominance plasticity in adult visual cortex. This is the first demonstration of adult brain to retain the intrinsic capacity to elevate tPA in an experience-dependent manner but is effectively limited by Lynx1. tPA-Lynx1 may potentially be a new candidate mechanism for interventions that were shown to activate plasticity in adult brain.
Bayesian nonparametric modeling and theory for complex data

The dissertation focuses on solving some important theoretical and methodological problems associated with Bayesian modeling of infinite dimensional ‘objects’, popularly called nonparametric Bayes. The term ‘infinite dimensional object’ can refer to a density, a conditional density, a regression surface or even a manifold. Although Bayesian density estimation as well as function estimation are well-justified in the existing literature, there has been little or no theory justifying the estimation of more complex objects (e.g. conditional density, manifold, etc.). Part of this dissertation focuses on exploring the structure of the spaces on which the priors for conditional densities and manifolds are supported while studying how the posterior concentrates as increasing amounts of data are collected. With the advent of new acquisition devices, there has been a need to model complex objects associated with complex data-types e.g. millions of genes affecting a bio-marker, 2D pixelated images, a cloud of points in the 3D space, etc. A significant portion of this dissertation has been devoted to developing adaptive nonparametric Bayes approaches for learning low-dimensional structures underlying higher-dimensional objects e.g. a high-dimensional regression function supported on a lower dimensional space, closed curves representing the boundaries of shapes in 2D images and closed surfaces located on or near the point cloud data. Characterizing the distribution of these objects has a tremendous impact in several application areas ranging from tumor tracking for targeted radiation therapy, to classifying cells in the brain, to model based methods for 3D animation and so on. The first three chapters are devoted to Bayesian nonparametric theory and modeling in unconstrained Euclidean spaces e.g. mean regression and density regression, the next two focus on Bayesian modeling of manifolds e.g. closed curves and surfaces, and the final one on nonparametric Bayes spatial point pattern data modeling when the sampling locations are informative of the outcomes.
Bacteriophage of Haemophilus influenzae. II. Repair of ultraviolet-irradiated phage DNA and the capacity of irradiated cells to make phage.

Abstract Competent cells that can excise pyrimidine dimers repair a smaller fraction, of ultraviolet-irradiated phage than do the same cells in exponential growth. Transfecting phage DNA irradiated with u.v. is repaired less efficiently than phage DNA injected from whole phage, and is more u.v.-sensitive in hcr − hosts than whole phage in the same hosts. Irradiated transfecting DNA extracted from lysogenic cells is not repaired at all, and has approximately the same u.v. sensitivity when assayed in hcr − or hcr + hosts as whole phage assayed in hcr − hosts. Irradiation of wild-type cells with u.v. results in the loss of ability (capacity) to grow unirradiated phage. The loss varies markedly with the type of infection: with transfecting phage DNA, the capacity is the most sensitive, with DNA from lysogenic cells it is intermediate, and with whole phage it is resistant. The capacity of a recombination-defective cell mutant to be transfected with phage DNA is relatively u.v.-resistant. However, the capacity of irradiated cells to propagate phage from whole phage is unaffected by the recombination defect. This capacity in excision-defective cells is even more resistant to u.v. We conclude that the differences in repair of u.v.-irradiated phage DNA and the different u.v. sensitivities of capacity to support growth of unirradiated phage, observed for the different types of infection, reflect the different events necessary for successful infection when phage DNA enters the cell either by injection or as pure DNA or as part of the DNA from lysogenic cells.
Enzymatic synthesis of deoxyribonucleic acid. XXX. Binding of triphosphates to deoxyribonucleic acid polymerase.

Abstract The Escherichia coli DNA polymerase, in the absence of DNA, contains a single binding site for which all the deoxyribonucleoside 5'-triphosphates complete. Dissociation constants of the enzyme-triphosphate complexes range from 1 x 10-5 to 2 x 10-4 m. Various analogues of the deoxyribonucleoside 5'-triphosphates also bind to the same site on DNA polymerase. The principal structural requirement for detectable binding at this site appears to be possession of a triphosphate group. Binding of triphosphates is inhibited when the concentration of potassium phosphate is increased, and is inhibited, but to a lesser extent, by increasing potassium chloride concentration. In addition, binding is abolished in the absence of Mg++ and in the presence of 9 mm EDTA. The strength of binding decreases with increasing temperature. Binding measurements were made with equilibrium dialysis microcells, which require only 20 µl of protein solution and in which equilibrium with triphosphates is attained within 90 min at 22°.
Development of digital acoustic sensor for remote applications

Centralized sampling acquisition systems are commonly used to acquire and digitize data from arrays of acoustic sensors. These systems have centralized/co-located connection points for multiple sensor channels and contain digitization and processing electronics that can be shared across these inputs. While this system architecture can simplify the electronics design, it has several intrinsic properties that degrade the data quality and increase system complexity for certain application parameters. Advancements in high speed, low power electronics have made distributed sensor digitization feasible for applications with limited available power such as remote underwater surveillance and autonomous underwater vehicle systems. This paper explores some limitations of centralized systems in underwater acoustic applications and presents some examples of where the benefits of distributed digital sensors were realized.
Complex fragment emission in the E/A=60–100 MeV 14N+natAg, 197Au reactions☆

Abstract Excitation functions have been measured for complex fragments with Z=3–15 emitted in collisions of E/A=60, 80 and 100 MeV 14 N ions with targets of natAg and 197Au. The results are analyzed in terms of a three-source model: projectile fragmentation, non-equilibrium emission from the composite system, and statistical decay of an equilibrated heavy residue. Enhanced heavy fragment production is found for reactions with the natAg target above E/A⩾60 MeV. Above E/A≅50 MeV the ratio of equilibrium to non-equilibrium cross sections is found to be nearly independent of bombarding energy. Fit-parameter systematics are presented.