cssi/SciSciGPT-SciSciNet huggingface dataset:
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach

Zero-shot text classification (0Shot-TC) is a challenging NLU problem to which little attention has been paid by the research community. 0Shot-TC aims to associate an appropriate label with a piece of text, irrespective of the text domain and the aspect (e.g., topic, emotion, event, etc.) described by the label. And there are only a few articles studying 0Shot-TC, all focusing only on topical categorization which, we argue, is just the tip of the iceberg in 0Shot-TC. In addition, the chaotic experiments in literature make no uniform comparison, which blurs the progress. This work benchmarks the 0Shot-TC problem by providing unified datasets, standardized evaluations, and state-of-the-art baselines. Our contributions include: i) The datasets we provide facilitate studying 0Shot-TC relative to conceptually different and diverse aspects: the “topic” aspect includes “sports” and “politics” as labels; the “emotion” aspect includes “joy” and “anger”; the “situation” aspect includes “medical assistance” and “water shortage”. ii) We extend the existing evaluation setup (label-partially-unseen) – given a dataset, train on some labels, test on all labels – to include a more challenging yet realistic evaluation label-fully-unseen 0Shot-TC (Chang et al., 2008), aiming at classifying text snippets without seeing task specific training data at all. iii) We unify the 0Shot-TC of diverse aspects within a textual entailment formulation and study it this way.
Productive Pacifists: The Rise of Production-Oriented States and Decline of Profit-Motivated Conquest

Scholarship suggests the profits from conquest have decreased over time. Given this, why were some states faster to abandon profit-motivated conquest, and why are some still seeking wealth from territorial control? We argue that land-rent dependence influences a regime’s economic preference for territory. The more a state depends on rents extracted from land (i.e., the more land-oriented the economy), the greater its willingness to invest in securing control of territory. We develop a novel measure of land-orientation, with 200 years of data, to evaluate the linkages between land-orientation and military competition over territory. Across 160 regression models, we find robust evidence that land-orientation predicts territorial competition. These results hold in both democracies and autocracies. The global reduction in land-oriented states offers a plausible explanation for the decline in the number of large-scale territorial conquests. Our findings also explain why some states retain strong economic motivations for conquest.
Disinflation, external vulnerability, and fiscal intransigence: some unpleasant Mundellian arithmetic

ABSTRACTThis paper examines the policy challenges that a country faces when it wants to both reduce inflation and maintain a sustainable external position. Robert Mundell’s policy assignment framew...
Authentication over noisy channels

In this work, message authentication over noisy channels is studied. The model developed in this paper is the authentication theory counterpart of Wyner's wiretap channel model. Two types of opponent attacks, namely impersonation attacks and substitution attacks, are investigated for both single message and multiple message authentication scenarios. For each scenario, information theoretic lower and upper bounds on the opponent's success probability are derived. Remarkably, in both scenarios, lower and upper bounds are shown to match, and hence the fundamental limit of message authentication over noisy channels is fully characterized. The opponent's success probability is further shown to be smaller than that derived in the classic authentication model in which the channel is assumed to be noiseless. These results rely on a proposed novel authentication scheme in which key information is used to provide simultaneous protection again both types of attacks.
Program Analysis of Commodity IoT Applications for Security and Privacy: Challenges and Opportunities

Recent advances in Internet of Things (IoT) have enabled myriad domains such as smart homes, personal monitoring devices, and enhanced manufacturing. IoT is now pervasive—new applications are being used in nearly every conceivable environment, which leads to the adoption of device-based interaction and automation. However, IoT has also raised issues about the security and privacy of these digitally augmented spaces. Program analysis is crucial in identifying those issues, yet the application and scope of program analysis in IoT remains largely unexplored by the technical community. In this article, we study privacy and security issues in IoT that require program-analysis techniques with an emphasis on identified attacks against these systems and defenses implemented so far. Based on a study of five IoT programming platforms, we identify the key insights that result from research efforts in both the program analysis and security communities and relate the efficacy of program-analysis techniques to security and privacy issues. We conclude by studying recent IoT analysis systems and exploring their implementations. Through these explorations, we highlight key challenges and opportunities in calibrating for the environments in which IoT systems will be used.
Algorithms and the News: Social Media Platforms as News Publishers and Distributors

With billons of users, social media platforms (e.g. Facebook) are dominant players in a highly-concentrated online news market. They have great power over the distribution of information to their users, and over the organizations and individuals that produce it. Social media platforms use algorithms to perform functions traditionally belonging to news editors: deciding on the importance of news items and how they are disseminated. However, they do not acknowledge the role they play in informing the public as traditional news media always have and tend to ignore that they also act as publishers of news and the responsibilities associated with that role. This paper argues that it is essential for social media platforms to understand and embrace their role as both news publishers and distributors and highlights the essential responsibilities they must undertake so they can satisfy the information needs of their audiences and protect the public’s right to information.
Strong NP-hardness of AC power flows feasibility

Abstract We prove that testing feasibility for an AC power flow system is a strongly NP-hard problem.
Low Abundance of Circulating Tumor DNA in Localized Prostate Cancer.

PURPOSEDespite decreased screening-based detection of clinically insignificant tumors, most diagnosed prostate cancers are still indolent, indicating a need for better strategies for detection of c...
Intent-to-Treat Principle†

This article provides an overview of the concepts involved in intent-to-treat analyses of randomized controlled clinical trials. Implications for the interpretation of the results of randomized trials that arise when noncompliance, missing data, and losses to follow-up occur are described. Alternative approaches to analysis are described. Keywords: intent-to-treat; per-protocol analysis; as-treated analysis; noncompliance; missing data; randomized controlled trials; clinical trials; superiority trials; noninferiority trials
Sequential optimization of speed, thermal load, and power split in connected HEVs

The emergence of connected and automated vehicles (CAVs) provides an unprecedented opportunity to capitalize on these technologies well beyond their original designed intents. While abundant evidence has been accumulated showing substantial fuel economy improvement benefits achieved through advanced powertrain control, the implications of the CAV operation on power and thermal management have not been fully investigated. In this paper, in order to explore the opportunities for the coordination between the onboard thermal management and the power split control, we present a sequential optimization solution for eco-driving speed trajectory planning, air conditioning (A/C) thermal load planning (eco-cooling), and powertrain control in hybrid electric CAVs to evaluate the individual as well as the collective energy savings through proactive usage of traffic data for vehicle speed prediction. Simulation results over a real-world driving cycle show that compared to a baseline non-CAV, 11.9%, 14.2%, and 18.8% energy savings can be accumulated sequentially through speed, thermal load, and power split optimizations, respectively.
A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation Using Deep Learning

In PET/CT imaging, CT is used for PET attenuation correction (AC). Mismatch between CT and PET due to patient body motion results in AC artifacts. In addition, artifact caused by metal, beam-hardening and count-starving in CT itself also introduces inaccurate AC for PET. Maximum likelihood reconstruction of activity and attenuation (MLAA) was proposed to solve those issues by simultaneously reconstructing tracer activity (λ-MLAA) and attenuation map (μ-MLAA) based on the PET raw data only. However, μ-MLAA suffers from high noise and λ-MLAA suffers from large bias as compared to the reconstruction using the CT-based attenuation map (μ-CT). Recently, a convolutional neural network (CNN) was applied to predict the CT attenuation map (μ-CNN) from λ-MLAA and μ-MLAA, in which an image-domain loss (IM-loss) function between the μ-CNN and the ground truth μ-CT was used. However, IM-loss does not directly measure the AC errors according to the PET attenuation physics, where the line-integral projection of the attenuation map (μ) along the path of the two annihilation events, instead of the μ itself, is used for AC. Therefore, a network trained with the IM-loss may yield suboptimal performance in the μ generation. Here, we propose a novel line-integral projection loss (LIP-loss) function that incorporates the PET attenuation physics for μ generation. Eighty training and twenty testing datasets of whole-body 18F-FDG PET and paired ground truth μ-CT were used. Quantitative evaluations showed that the model trained with the additional LIP-loss was able to significantly outperform the model trained solely based on the IM-loss function.
Dispersion points and rational curves

We construct two connected plane sets which can be embedded into rational curves. The first is a biconnected set with a dispersion point. It answers a question of Joachim Grispolakis. The second is indecomposable. Both examples are completely metrizable.
Fixing a Fragmented System: Impact of a Comprehensive Geriatric Hip Fracture Program on Long-Term Mortality.

CONTEXT Geriatric hip fractures are increasingly common and confer substantial morbidity and mortality. Fragmentation in geriatric hip fracture care remains a barrier to improved outcomes. OBJECTIVE To evaluate the impact of a comprehensive geriatric hip fracture program on long-term mortality. DESIGN We conducted a retrospective cohort study of patients aged 65 years and older admitted to our academic medical center between January 1, 2012, and March 31, 2016 with an acute fragility hip fracture. Mortality data were obtained for in-state residents from the state public health department. MAIN OUTCOME MEASURES Mortality within 1 year of index admission and overall survival based on available follow-up data. RESULTS We identified 243 index admissions during the study period, including 135 before and 108 after program implementation in October 2014. The postintervention cohort trended toward a lower unadjusted 1-year mortality rate compared with the preintervention cohort (15.7% vs 24.4%, p = 0.111), as well as lower adjusted mortality at 1 year (relative risk = 0.73, 95% confidence interval = 0.46-1.16, p = 0.18), although the differences were not statistically significant. The postintervention cohort had significantly higher overall survival than did the preintervention cohort (hazard ratio for death = 0.43, 95% confidence interval = 0.25-0.74, p = 0.002). CONCLUSION Fixing fragmentation in geriatric hip fracture care such as through an orthogeriatric model is essential to improving overall survival for this patient population.
Workforce Issues in The Electricity Industry

The formation of the electric utility infrastructure in the United States was done by incorporating substantial human capital. This is a summary of the presentation on the panel titled "Power Industry Workforce of the Future" at the 2006 IEEE/PES PSCE in Atlanta, Georgia. It is clear from the demographics that massive changes in the workforce are imminent. In addition, technology advances are altering the technologies which will increasingly be deployed in the industry. The workforce issues facing the industry today are far more complex than they have ever been. EPRI has conducted extensive research into capturing valuable undocumented knowledge and making it avail able to other personnel when needed. This research was proven in nuclear generation facilities and now applied in power system engineering
The Boer-Mulders Function: Models and Universality

The sign of the Boer-Mulders function $h_1^\perp$ is related to the sign of the GPD $\bar{E}_T$ through the mechanism of chromodynamic lensing. Model calculations of the sign of $\bar{E}_T$ indicate that the sign of $h_1^\perp$ may be the same in all ground state hadrons.
Impact of water filling on terminal ileum intubation with a distal-tip mucosal exposure device.

Background and Aims Endocuff improves detection at colonoscopy but seems to impede terminal ileal (TI) intubation. We assessed the impact of Endocuff Vision (EV) on TI intubation using adult or pediatric colonoscopes and evaluated whether filling the cecum with gas versus water affected the impact of EV on TI intubation. Methods Using a prospectively recorded quality control database, we explored the impact of EV on TI intubation in ≤1 minute. We used adult and pediatric colonoscopes and tested the effect of filling the cecum with gas versus water. If the initial attempt failed, then the alternative (water vs gas) was tried as a rescue method. Results TI intubation in ≤1 minute occurred in 91% of colonoscopies without EV versus 65% with EV, but the use of the pediatric colonoscope with EV had a higher success rate for TI intubation in ≤1 minute compared with the adult colonoscope with EV (73% vs 57%, P = .043). TI intubation in ≤1 minute was more successful with EV when the cecum was filled with water rather than gas (74% vs 56%, P = .019), but the benefit of water filling was limited to the adult colonoscope with EV. When EV was in place, water filling was more successful as a rescue method of TI intubation (58% vs 21%, P = .011). Conclusions EV adversely affects TI intubation, particularly for adult colonoscopes. Water filling of the cecum mitigates the impact of EV on TI intubation with adult colonoscopes.
HUNK Phosphorylates Rubicon to Support Autophagy.

Background: Autophagy is a catabolic cellular recycling pathway that is essential for maintaining intracellular homeostasis. Autophagosome formation is achieved via the coordination of the Beclin-1 protein complex. Rubicon is a Beclin-1 associated protein that suppresses autophagy by impairing the activity of the class III PI3K, Vps34. However, very little is known about the molecular mechanisms that regulate Rubicon function. Methods: In this study, co-immunoprecipitation and kinase assays were used to investigate the ability of Hormonally Upregulated Neu-associated Kinase (HUNK) to bind to and phosphorylate Rubicon. LC3B was monitored by immunofluorescence and immunoblotting to determine whether phosphorylation of Rubicon by HUNK controls the autophagy suppressive function of Rubicon. Results: Findings from this study identify Rubicon as a novel substrate of HUNK and show that phosphorylation of Rubicon inhibits its function, promoting autophagy.
How seniors learn.

The learning capacity of older adults has direct, practical implications for professionals trying to educate older people and their families about health-care services and benefits, especially Medicare. In this brief, we discuss the issue of how older people learn, exploring research from the field of cognitive aging. We also offer some tips for how you can adapt your educational programs and materials to build on your clients' cognitive strengths and compensate for some of the losses that can occur with aging.
A Scalable Empirical Bayes Approach to Variable Selection in Generalized Linear Models

A new empirical Bayes approach to variable selection in the context of generalized linear models is developed. The proposed algorithm scales to situations in which the number of putative explanator...
ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network

Automated ICD coding, which assigns the International Classification of Disease codes to patient visits, has attracted much research attention since it can save time and labor for billing. The previous state-of-the-art model utilized one convolutional layer to build document representations for predicting ICD codes. However, the lengths and grammar of text fragments, which are closely related to ICD coding, vary a lot in different documents. Therefore, a flat and fixed-length convolutional architecture may not be capable of learning good document representations. In this paper, we proposed a Multi-Filter Residual Convolutional Neural Network (MultiResCNN) for ICD coding. The innovations of our model are two-folds: it utilizes a multi-filter convolutional layer to capture various text patterns with different lengths and a residual convolutional layer to enlarge the receptive field. We evaluated the effectiveness of our model on the widely-used MIMIC dataset. On the full code set of MIMIC-III, our model outperformed the state-of-the-art model in 4 out of 6 evaluation metrics. On the top-50 code set of MIMIC-III and the full code set of MIMIC-II, our model outperformed all the existing and state-of-the-art models in all evaluation metrics. The code is available at https://github.com/foxlf823/Multi-Filter-Residual-Convolutional-Neural-Network.
Competitive Revenue Management with Sequential Bargaining

When firms post prices to sell their products in a competitive market, buyers often seek to bargain down the prices. The existing studies on dynamic competition, however, focus on firms’ dynamic pricing strategies without considering the possibility of bargaining. We model a random stream of buyers with heterogeneous valuations who may choose to negotiate for a discount from a posted price. When bargaining is allowed, a seller firm's competing strategy depends not only on her reservation value (i.e., her gain from an unsold item when losing the current buyer to the opponent) but also on her disagreement point (i.e., the value of an unsold item when the negotiation with an arriving buyer breaks down). We show that the reservation values and the disagreement points can play opposite roles in competition—the seller firms’ posted prices are increasing in their reservation values but are decreasing in their disagreement points. In general, a seller becomes more aggressive in price competition when her reservation value becomes lower. However, it is not always the case that a seller with a lower reservation value can successfully win the deal from an arriving buyer, as it is in pure price competition. Because of the possibility of bargaining, the buyer may end up purchasing from a seller who has a higher inventory level and a higher reservation value when the seller's disagreement point is lower than that of her opponent. Interestingly, such an equilibrium outcome can only arise when the selling season is sufficiently long. Our analysis highlights the intriguing role played by negotiation in dynamic competition for sequential selling.
Applications of envelopes

Intuitively, an envelope of a family of curves is a curve that is tangent to a member of the family at each point. More precisely, there are three different, but related, types of envelopes associated to most families of curves. In this paper, we illustrate how one can use these envelopes to approach problems appearing in fields like matrix theory and hyperbolic geometry. As a first example, we use envelopes to fill in the details of a proof by Donoghue of the elliptical range theorem; this use of envelopes provides insight into how certain numerical ranges arise from families of circles. More generally, envelopes can be used to compute boundaries of families of curves. To demonstrate how such arguments work, we first deduce a general relationship between the envelopes and boundaries of families of circles and then use this to compute the boundaries of several families of pseudohyperbolic disks.
The nonsmooth landscape of phase retrieval

We consider a popular nonsmooth formulation of the real phase retrieval problem. We show that under standard statistical assumptions, a simple subgradient method converges linearly when initialized within a constant relative distance of an optimal solution. Seeking to understand the distribution of the stationary points of the problem, we complete the paper by proving that as the number of Gaussian measurements increases, the stationary points converge to a codimension two set, at a controlled rate. Experiments on image recovery problems illustrate the developed algorithm and theory.
Interpersonal relationship challenges among stroke survivors and family caregivers

A strong interpersonal relationship after stroke is important for the well-being of survivors and family caregivers. However, as many as 54% of families experience relationship problems after strok...
Distributed Optimal Voltage Control With Asynchronous and Delayed Communication

The increased penetration of volatile renewable energy into distribution networks necessities more efficient distributed voltage control. In this paper, we design distributed feedback control algorithms where each bus can inject both active and reactive power into the grid to regulate the voltages. The control law on each bus is only based on local voltage measurements and communication to its physical neighbors. Moreover, the buses can perform their updates asynchronously without receiving information from their neighbors for periods of time. The algorithm enforces hard upper and lower limits on the active and reactive powers at every iteration. We prove that the algorithm converges to the optimal feasible voltage profile, assuming linear power flows. This provable convergence is maintained under bounded communication delays and asynchronous communications. We further numerically test the performance of the algorithm using the full nonlinear AC power flow model. Our simulations show the effectiveness of our algorithm on realistic networks with both static and fluctuating loads, even in the presence of communication delays.
Automatic Generation of Application-Specific FPGA Overlays with RapidWright

In this paper, we introduce Application-Specific FPGA Overlays (AS-Overlays), a new approach to automatically generate overlays from high-level description language applications that can achieve bare-metal performances. Our approach is based on the automatic extraction of hardware kernels from data flow applications. Extracted kernels are then leveraged for application-specific generation of hardware accelerators. The reconfiguration of the overlay is done with RapidWright which allows to bypass the HDL design flow. Through prototyping, we demonstrated the viability and relevance of our approach. Experiments show a productivity improvement up to 20× compared to the state of the art FPGA overlays, while achieving over 1.33× higher Fmax than direct FPGA implementation and the possibility of lower resource and power consumption compared to bare metal.
Accurate and Sensitive Quantitation of the Dynamic Heat Shock Proteome Using Tandem Mass Tags.

Cells respond to environmental perturbations and insults through modulating protein abundance and function. However, the majority of studies have focused on changes in RNA abundance because quantit...
CSM-NN: Current Source Model Based Logic Circuit Simulation - A Neural Network Approach

The miniaturization of transistors down to 5nm and beyond, plus the increasing complexity of integrated circuits, significantly aggravate short channel effects, and demand analysis and optimization of more design corners and modes. Simulators need to model output variables related to circuit timing, power, noise, etc., which exhibit nonlinear behavior. The existing simulation and sign-off tools, based on a combination of closed-form expressions and lookup tables are either inaccurate or slow, when dealing with circuits with more than billions of transistors. In this work, we present CSM-NN, a scalable simulation framework with optimized neural network structures and processing algorithms. CSM-NN is aimed at optimizing the simulation time by accounting for the latency of the required memory query and computation, given the underlying CPU and GPU parallel processing capabilities. Experimental results show that CSM-NN reduces the simulation time by up to 6× compared to a state-of-the-art current source model based simulator running on a CPU. This speedup improves by up to 15× when running on a GPU. CSM-NN also provides high accuracy levels, with less than 2% error, compared to HSPICE.
Oscillation frequencies of solar models

Two solar models have been constructed, one with no diffusion of the atomic nuclei, and another including diffusive element separation. The opacity at the bottom of the convection zone was increased 15--20 percent (within its theoretical uncertainty) to obtain a few microhertz agreement with observed p-mode frequencies. Original helium mass fractions were 0.291 and 0.289 for the no-diffusion and diffusion models, respectively. The diffusion model evolved to a surface Y = 0.256 at the solar age, and the original Z value of 0.0200 decreased to 0.0179. Agreement of l = 0 and 2 p-mode frequency separations with those observed is good. The g-mode nonadiabatic solutions do not have equal period spacing until high radial order. The lowest order modes are more visible if they all have the same kinetic energy. High central temperatures, produce over 9 SNUs from the B and 1.5 SNUs from the Be reactions. Models with iron condensed-out below the convection zone, and with WIMPs cooling the central regions to reduce the SNUs, agree less well with p-mode frequency separations. 53 refs., 6 figs., 4 tabs.
Global Stabilization for Causally Consistent Partial Replication

Causally consistent distributed storage systems have received significant attention due to the potential for providing high throughput. Global stabilization is a technique established for achieving causal consistency in distributed multi-version key-value store systems, adopted by previous works such as GentleRain [6] and Cure [1]. However, previous designs with global stabilization assume full replication, where the set of the data is split into partitions with each partition replicated at all data centers, and each client is restricted to access servers within only one data center. In this paper, we propose a theoretical framework of global stabilization to support general partial replication with causal consistency, where each server can store an arbitrary subset of the data, and each client is allowed to communicate with any subset of the servers and migrate among them without extra delays. We propose an algorithm that implements causal consistency for distributed multi-version key-value stores with general partial replication, and our algorithm is optimal in terms of the remote update visibility latency, i.e. how fast update from a remote server is visible to the client, under general partial replication. Simulation results on the performance of our algorithm compared to the previous work are also provided.
Flip cycles in plabic graphs

Planar bicolored (plabic) graphs are combinatorial objects introduced by Postnikov to give parameterizations of the positroid cells of the totally nonnegative Grassmannian $$\text {Gr}^{\ge 0}(n,k)$$. Any two plabic graphs for the same positroid cell can be related by a sequence of certain moves. The flip graph has plabic graphs as vertices and has edges connecting the plabic graphs which are related by a single move. A recent result of Galashin shows that plabic graphs can be seen as cross-sections of zonotopal tilings for the cyclic zonotope Z(n, 3). Taking this perspective, we show that the fundamental group of the flip graph is generated by cycles of length 4, 5, and 10, and use this result to prove a related conjecture of Dylan Thurston about triple crossing diagrams. We also apply our result to make progress on an instance of the generalized Baues problem.
Learning-Based Proxy Collision Detection for Robot Motion Planning Applications

This article demonstrates that collision detection-intensive applications such as robotic motion planning may be accelerated by performing collision checks with a machine learning model. We propose Fastron, a learning-based algorithm, to model a robot's configuration space to be used as a proxy collision detector in place of standard geometric collision checkers. We demonstrate that leveraging the proxy collision detector results in up to an order of magnitude faster performance in robot simulation and planning than state-of-the-art collision detection libraries. Our results show that Fastron learns a model more than 100 times faster than a competing C-space modeling approach, while also providing theoretical guarantees of learning convergence. Using the open motion planning libraries (OMPLs), we were able to generate initial motion plans across all experiments with varying robot and environment complexities and workspace obstacle locations. With Fastron, we can repeatedly generate new motion plans at a 56 Hz rate, showing its application toward autonomous surgical assistance task in shared environments with human-controlled manipulators. All performance gains were achieved despite using only CPU-based calculations, suggesting further computational gains with a GPU approach that can parallelize tensor algebra. Code is available online. 1
Residual Balancing: A Method of Constructing Weights for Marginal Structural Models

When making causal inferences, post-treatment confounders complicate analyses of time-varying treatment effects. Conditioning on these variables naively to estimate marginal effects may inappropriately block causal pathways and may induce spurious associations between treatment and the outcome, leading to bias. To avoid such bias, researchers often use marginal structural models (MSMs) with inverse probability weighting (IPW). However, IPW requires models for the conditional distributions of treatment and is highly sensitive to their misspecification. Moreover, IPW is relatively inefficient, susceptible to finite-sample bias, and difficult to use with continuous treatments. We introduce an alternative method of constructing weights for MSMs, which we call “residual balancing”. In contrast to IPW, it requires modeling the conditional means of the post-treatment confounders rather than the conditional distributions of treatment, and it is therefore easier to use with continuous treatments. Numeric simulations suggest that residual balancing is both more efficient and more robust to model misspecification than IPW and its variants in a variety of scenarios. We illustrate the method by estimating (a) the cumulative effect of negative advertising on election outcomes and (b) the controlled direct effect of shared democracy on public support for war. Open-source software is available for implementing the proposed method.
Selective adsorption of carbon dioxide from mixed vapors by blockage of methane in graphene nanoribbons

We study numerically the adsorption of a mixture of $$\hbox {CO}_{2}$$ and $$\hbox {CH}_{4}$$ on a graphite substrate covered by graphene nanoribbons (NRs). The NRs are flat and parallel to the graphite surface, at a variable distance ranging from 6 to 14 A. We show that the NRs-graphite substrate acts as an effective filter for $$\hbox {CO}_{2}$$ . Our study is based on molecular dynamics simulations. Methane is considered a spherical molecule, and carbon dioxide is represented as a linear rigid body. Graphite is modeled as a continuous material, while the NRs are approached atomistically. We observe that when the NRs are placed 6 A above the graphite surface, methane is blocked out, while $$\hbox {CO}_{2}$$ molecules can diffuse and be collected in between the NRs and the graphite surface. Consequently, the selectivity of $$\hbox {CO}_{2}$$ is extremely high. We also observe that the initial rate of adsorption of $$\hbox {CO}_{2}$$ is much higher than $$\hbox {CH}_{4}$$ . Overall we show that the filter can be optimized by controlling the gap between NRs and the NRs-graphite separation.
Bone Adaptation in Adult Women Is Related to Loading Dose: A 12‐Month Randomized Controlled Trial

Although strong evidence exists that certain activities can increase bone density and structure in people, it is unclear what specific mechanical factors govern the response. This is important because understanding the effect of mechanical signals on bone could contribute to more effective osteoporosis prevention methods and efficient clinical trial design. The degree to which strain rate and magnitude govern bone adaptation in humans has never been prospectively tested. Here, we studied the effects of a voluntary upper extremity compressive loading task in healthy adult women during a 12-month prospective period. A total of 102 women age 21 to 40 years participated in one of two experiments: (i) low (n = 21) and high (n = 24) strain magnitude; or (ii) low (n = 21) and high (n = 20) strain rate. Control (n = 16) no intervention. Strains were assigned using subject-specific finite element models. Load cycles were recorded digitally. The primary outcome was change in ultradistal radius integral bone mineral content (iBMC), assessed with QCT. Interim time points and secondary outcomes were assessed with high resolution pQCT (HRpQCT) at the distal radius. Sixty-six participants completed the intervention, and interim data were analyzed for 77 participants. Likely related to improved compliance and higher received loading dose, both the low-strain rate and high-strain rate groups had significant 12-month increases to ultradistal iBMC (change in control: -1.3 ± 2.7%, low strain rate: 2.7 ± 2.1%, high strain rate: 3.4 ± 2.2%), total iBMC, and other measures. "Loading dose" was positively related to 12-month change in ultradistal iBMC, and interim changes to total BMD, cortical thickness, and inner trabecular BMD. Participants who gained the most bone completed, on average, 128 loading bouts of (mean strain) 575 μe at 1878 μe/s. We conclude that signals related to strain magnitude, rate, and number of loading bouts contribute to bone adaptation in healthy adult women, but only explain a small amount of variance in bone changes. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.
Law and Economics as We Grow Younger

The European Association of Law and Economics grants a biennial Lifetime Achievement Award and Honorary Membership to a scholar “for his or her significant contributions to the field of Law and Economics, in particular to the development of this scientific movement in Europe.” This paper is the award lecture delivered by Professor Francesco Parisi at the Annual Meeting of the European Association of Law and Economics, held at Tel-Aviv University on September, 19, 2019.
Screening for Cancer Using a Learning Internet Advertising System

Studies have shown that search engine queries are indicative of future diagnosis of several types of cancer. These studies were based on self-identification of illness and were limited in that diagnostic information could not be shared with screened individuals. Here I report on two studies that overcome these limitations. Advertisements were displayed on the Bing and Google ads systems to people who sought to self-diagnose one of three types of cancer. People who clicked on these ads were provided with clinically verified questionnaires and the outcomes of these questionnaires. A classifier trained to predict suspected cancer, inferred from questionnaire responses, from past Bing queries reached an area under the curve of 0.64. People who received information that their symptoms were consistent with suspected cancer increased searches for healthcare utilization. In a second study, questionnaire responses provided to the conversion optimization mechanism of the Google advertisement system enabled it to learn to identify people who were likely to have suspected cancer. Following a training period of approximately 10 days, 11% of people selected for showing of targeted campaign ads were found to have suspected cancer. These results demonstrate the utility of using modern advertising systems to identify people who are likely suffering from serious medical conditions.
Setting the Ground Rules: Use and Practice of Ground Rules in Child Forensic Interviews:

Most child forensic interviewing protocols recommend that interviewers administer a series of ground rules to emphasize concepts that are important to accurately answering interview questions. Limited research has examined whether interviewers follow ground rules recommendations in real-world forensic interviews. In this study, we examined how often highly trained interviewers presented and practiced each of the recommended ground rules. We also examined whether children accurately responded to practice questions. We coded transcripts from 241 forensic interviews of 4- to 12-year-old children conducted by interviewers in the United States who were largely trained using the Ten Step Investigative Interview. Results demonstrated that interviewers routinely presented and practiced the ground rules, but this significantly varied by children's age. Additionally, children often accurately responded to practice questions, but younger children were less accurate than older children. Taken together, results highlight that interviewers may deviate from ground rules recommendations based on the characteristics of the child, which has implications for both future research and practice.
Modern Monetary Theory: An Austrian Interpretation of Recrudescent Keynesianism

Modern monetary theory (MMT) argues that governments can never go bankrupt because they have the power to print money to finance budget deficits. Consequently, debt monetization can achieve virtually any government objective desired. This paper uses Austrian economics to argue that MMT suffers from the flaws of all forms of Keynesian economics, particularly the original version of the 1930s and 1940s. MMT fails to understand capital-based macroeconomics and how government policy affects the temporal structure of production. MMT also neglects the importance of profit and loss accounting compared to government allocation of resources. The Austrian school argues that traditional New Keynesian countercyclical monetary policy results in a credit-induced boom and bust (Austrian business cycle theory) by injecting new money into private sector loans through the banking sector. However, Austrian analysis demonstrates that MMT’s monetary policy to monetize government deficits and increase the money supply through government spending will instead lead to secular economic stagnation and a stunted capital structure. Overall, the policy prescriptions of MMT are far more dangerous than traditional New Keynesian policies.
Study on the Establishment of China-Russia Free Trade Zone under the One Belt And One Road Initiative

China’s One Belt and One Road initiative is meaningful in building new types of international relations. China and Russia share similarities in their histories of development, industrial structures, and geographical locations, which are instrumental in building the China-Russia Free Trade Zone. However, the existing structure of the merchandise trade between the two countries lacks variety. Additionally, the protectionist trade policy creates barriers to the set-up of the China-Russia Free Trade Zone. Nevertheless, building the China-Russia Free Trade Zone promotes the development of One Belt and One Road and the common progress of China and Russia and benefits the whole world. Therefore, establishing One Belt and One Road-based China-Russia Free Trade Zone is presented with both opportunities and challenges.
Simultaneous Separation and Transcription of Mixtures with Multiple Polyphonic and Percussive Instruments

We present a single deep learning architecture that can both separate an audio recording of a musical mixture into constituent single-instrument recordings and transcribe these instruments into a human-readable format at the same time, learning a shared musical representation for both tasks. This novel architecture, which we call Cerberus, builds on the Chimera network for source separation by adding a third "head" for transcription. By training each head with different losses, we are able to jointly learn how to separate and transcribe up to five instruments with a single network. We show that separation and transcription are highly complementary with one another and when learned jointly, lead to Cerberus networks that are better at both separation and transcription and generalize better to unseen mixtures.
Neural Network Training with Approximate Logarithmic Computations

The high computational complexity associated with training deep neural networks limits online and real-time training on edge devices. This paper proposed an end-to-end training and inference scheme that eliminates multiplications by approximate operations in the log-domain which has the potential to significantly reduce implementation complexity. We implement the entire training procedure in the log-domain, with fixed-point data representations. This training procedure is inspired by hardware-friendly approximations of log-domain addition which are based on look-up tables and bit-shifts. We show that our 16-bit log-based training can achieve classification accuracy within approximately 1% of the equivalent floating-point baselines for a number of commonly used datasets.
The Chandra X-Ray Observatory: An overview

Abstract The Chandra X-Ray Observatory, one of NASA's Great Observatories, was successfully launched on July 23, 1999 by the Space Shuttle Columbia. After release from Columbia, an Inertial Upper Stage was used to further boost the observatory. After five subsequent firings over 15 days of an internal propulsion system, the Observatory was placed in a highly elliptical orbit. The first x-rays focussed by the telescope were observed on August 12, 1999. Despite an initial surprise that the x-ray telescope was far more efficient for concentrating low-energy protons than had been anticipated, the observatory is performing well and is returning superb scientific data. Operating together with other space observatories, most notably the recently activated XMM-Newton, it is clear that with Chandra we are entering a new era of discovery in high-energy astrophysics.
Carsharing in North America: Market Growth, Current Developments, and Future Potential

Carsharing provides members access to a fleet of autos for short-term use throughout the day, reducing the need for one or more personal vehicles. More than 10 years ago, carsharing operators began to appear in North America. Since 1994, 40 programs have been deployed—28 are operating in 36 urban areas, and 12 are now defunct. Another four are planned to launch in the next year. Carsharing growth potential in North America is examined on the basis of a survey of 26 existing organizations conducted from April to July 2005. Since the mid-1990s, the number of members and vehicles supported by carsharing in the United States and Canada has continued to grow, despite program closures. The three largest providers in the United States and Canada both support 94% of the total carsharing membership. Growth potential in major metropolitan regions is estimated at 10% of individuals over the age of 21 in North America. Although carsharing continues to gain popularity and market share, the authors conclude that increa...
What Is Different about AMTRAN

As a programming language, AMTRAN is designed to satisfy two objectives: the reduction of programming cost and effort by at least an order of magnitude, and the provision of a semiautomatic numerical analytical problem solving system. It resembles a blend of FORTRAN and ALGOL but possesses certain additional features. These include the following.
Robust Clock Skew and Offset Estimation for IEEE 1588 in the Presence of Unexpected Deterministic Path Delay Asymmetries

IEEE 1588, built on the classical two-way message exchange scheme, is a popular clock synchronization protocol for packet-switched networks. Due to the presence of random queuing delays in a packet-switched network, the joint recovery of the clock skew and offset from the timestamps of the exchanged synchronization packets can be treated as a statistical estimation problem. In this paper, we address the problem of clock skew and offset estimation for IEEE 1588 in the presence of possible unknown asymmetries between the deterministic path delays of the forward master-to-slave path and reverse slave-to-master path, which can result from incorrect modeling or cyber-attacks. First, we develop lower bounds on the mean square estimation error for a clock skew and offset estimation scheme for IEEE 1588 assuming the availability of multiple master-slave communication paths and complete knowledge of the probability density functions (pdf) describing the random queuing delays. Approximating the pdf of the random queuing delays by a mixture of Gaussian random variables, we then present a robust iterative clock skew and offset estimation scheme that employs the space alternating generalized expectation-maximization (SAGE) algorithm for learning all the unknown parameters. Numerical results indicate that the developed robust scheme exhibits a mean square estimation error close to the lower bounds.