cssi/SciSciGPT-SciSciNet huggingface dataset:
Embryonic Ethanol Exposure Affects Early- and Late-Added Cardiac Precursors and Produces Long-Lasting Heart Chamber Defects in Zebrafish

Drinking mothers expose their fetuses to ethanol, which produces birth defects: craniofacial defects, cognitive impairment, sensorimotor disabilities and organ deformities, collectively termed as fetal alcohol spectrum disorder (FASD). Various congenital heart defects (CHDs) are present in FASD patients, but the mechanisms of alcohol-induced cardiogenesis defects are not completely understood. This study utilized zebrafish embryos and older larvae to understand FASD-associated CHDs. Ethanol-induced cardiac chamber defects initiated during embryonic cardiogenesis persisted in later zebrafish life. In addition, myocardial damage was recognizable in the ventricle of the larvae that were exposed to ethanol during embryogenesis. Our studies of the pathogenesis revealed that ethanol exposure delayed differentiation of first and second heart fields and reduced the number of early- and late-added cardiomyocytes in the heart. Ethanol exposure also reduced the number of endocardial cells. Together, this study showed that ethanol-induced heart defects were present in late-stage zebrafish larvae. Reduced numbers of cardiomyocytes partly accounts for the ethanol-induced zebrafish heart defects.
Family history of alcoholism and the human brain response to oral sucrose.

Abstract A heightened hedonic response to sweet tastes has been associated with increased alcohol preference and alcohol consumption in both humans and animals. The principal goal of this study was to examine blood oxygenation level dependent (BOLD) activation to high- and low-concentration sweet solutions in subjects who are either positive (FHP) or negative (FHN) for a family history of alcoholism. Seventy-four non-treatment seeking, community-recruited, healthy volunteers (22.8 ± 1.6 SD years; 43% men) rated a range of sucrose concentrations in a taste test and underwent functional magnetic resonance imaging (fMRI) during oral delivery of water, 0.83 M, and 0.10 M sucrose. Sucrose compared to water produced robust activation in primary gustatory cortex, ventral insula, amygdala, and ventral striatum. FHP subjects displayed greater bilateral amygdala activation than FHN subjects in the low sucrose concentration (0.10 M). In secondary analyses, the right amygdala response to the 0.10 M sucrose was greatest in FHP women. When accounting for group differences in drinks per week, the family history groups remained significantly different in their right amygdala response to 0.10 M sucrose. Our findings suggest that the brain response to oral sucrose differs with a family history of alcoholism, and that this response to a mildly reinforcing primary reward might be an endophenotypic marker of alcoholism risk.
Fast, Exact Model Selection and Permutation Testing for l2-Regularized Logistic Regression

Regularized logistic regression is a standard classification method used in statistics and machine learning. Unlike regularized least squares problems such as ridge regression, the parameter estimates cannot be computed in closed-form and instead must be estimated using an iterative technique. This paper addresses the computational problem of regularized logistic regression that is commonly encountered in model selection and classifier statistical significance testing, in which a large number of related logistic regression problems must be solved for. Our proposed approach solves the problems simultaneously through an iterative technique, which also garners computational efficiencies by leveraging the redundancies across the related problems. We demonstrate analytically that our method provides a substantial complexity reduction, which is further validated by our results on real-world datasets.
Shining a Light on Purchasing Power Parities

Nighttime lights data are a measure of economic activity whose error is plausibly independent of the measurement errors of most conventional indicators. Therefore, we can use nighttime lights as an independent benchmark to assess existing measures of economic activity (Pinkovskiy and Sala-i-Martin (2016)). We employ this insight to generate three findings in the study of PPP-adjusted estimates of GDP around the world between 1992 and 2010. First, we find that while market exchange rates described poor economies better than did PPP-adjusted estimates in the late 1990s (Dowrick and Akmal 2008; Almas 2012), this pattern has disappeared by the 2010s. Second, we also find that estimates of PPPs have been steadily improving from one price survey round to the next, including during the controversial 2005 and 2011 rounds. Third, we leverage this fact to assess whether it is optimal to measure relative prices as close as possible to the year of interest or to use the latest available relative price data and discard the rest, and provide a theoretical framework in which the latter may be optimal. Using data from the Penn World Tables, we find that, indeed, it is optimal to only use the latest price data, and hence, to revise existing PPP-adjusted estimates whenever a new price survey is released.
Temperature Dependence of the Air/Water Interface Revealed by Polarization Sensitive Sum-Frequency Generation Spectroscopy

The temperature dependence of the vibrational sum-frequency generation (vSFG) spectra of the air/water interface is investigated using many-body molecular dynamics (MB-MD) simulations performed with the MB-pol potential energy function. The vSFG spectra calculated for different polarization combinations are then analyzed in terms of molecular autocorrelation and cross-correlation contributions. To provide molecular-level insights into interfacial hydrogen-bonding topologies, which give rise to specific spectroscopic features, the vSFG spectra are further investigated by separating contributions associated with water molecules donating zero, one, or two hydrogen bonds to neighboring water molecules. This analysis suggests that the low frequency shoulder of the free OH peak which appears at ∼3600 cm–1 is primarily due to intermolecular couplings between both singly and doubly hydrogen-bonded molecules.
Intrauterine growth restriction is not associated with decreased exercise capacity in adolescents with congenital heart disease.

Objective Multiple studies demonstrate the association of intrauterine growth restriction (IUGR) with impaired aerobic fitness in adolescents and adults. To our knowledge, there are no studies including individuals with the history of both IUGR and congenital heart disease (CHD). Thus, we sought to evaluate the impact of IUGR on exercise capacity in adolescents with CHD. Study Design We conducted a retrospective chart review of patients 18 years of age at time of CPET, those without a documented birth weight, gestational age, or Race. Results A total of 282 patients were included with CHD present in 86 IUGR cases and 86 controls. There was no difference in percent predicted exercise duration (IUGR: 65.2% ± 31.2, non-IUGR: 67.4% ± 27.2; P = .67). Resting heart rate, chronotropic index, percent-predicted peak oxygen consumption, and pulmonary function were similar between groups. Regression analyses confirmed that IUGR was not independently associated with difference in percent-predicted exercise duration. Conclusions Intrauterine growth restriction is not associated with the differences in the measurements of exercise capacity in adolescents with CHD. These findings contrast earlier studies, showing decreased fitness in individuals with low birth weight but without CHD. To our knowledge, this is the first study to examine the impact of IUGR on exercise capacity in patients with CHD.
On the susceptibility of coded OFDM to interference: A simulation study

The susceptibility of broadband wireless communications signals (e.g., LTE, IEEE 802.11) to interference has been a topic of significant research. In this paper, we implement a simulation-based study on the impact that interference can have on the bit error rate (BER) performance of coded orthogonal frequency-division multiplexing (OFDM) transmissions. Our study covers two types of interference (a narrow-band tone signal and a pulse train signal), and two popular coding schemes (Turbo and LDPC). Simulation results show that Turbo and low-density parity check (LDPC) coding schemes provide large coding gains in the presence of white noise (without other interference), but are not effective against the narrow-band tone and pulse train interference. This observation calls for more robust coding and/or filtering design against interference for coded OFDM transmissions.
The Riksbank, emergency finance, policy experimentation, and Sweden’s reversal of fortune

Abstract At the beginning of the 18th century, Sweden was an imperial power that had just sustained a century of modest economic growth. In 1800, Sweden’s empire was gone, after a series of military defeats. Real GDP per capita had fallen to the same level as the early 1600s. In other words, the 18th century witnessed the end of the Swedish Empire and a startling reversal of economic progress. In this paper, I propose a possible explanation for both of these outcomes. First, I argue that Sweden’s limited fiscal capacity played an important role. The creation of the Riksbank should have facilitated government borrowing and military spending as the Bank of England did for the British. However, the Riksbank was not designed or equipped for this role. I document the constraints on financing national defense through the Riksbank and argue that the bank was ill-equipped to finance an adequate national defense. This explains the reversal of the empire. Second, when the Hats took power in the Riksdag in 1739, they used the Riksbank to give loans to firms, which were financed through the issuance of bank notes. The objective was to increase investment and economic activity. I find no evidence that these loans had any effect on real GDP per capita. However, the resulting inflation has a negative and significant effect on output during the period of inconvertible paper money. The combined evidence suggests that Hat policy contributed to the decline in economic activity during the reversal of fortune.
Efficient, Sparse Representation of Manifold Distance Matrices for Classical Scaling

Geodesic distance matrices can reveal shape properties that are largely invariant to non-rigid deformations, and thus are often used to analyze and represent 3-D shapes. However, these matrices grow quadratically with the number of points. Thus for large point sets it is common to use a low-rank approximation to the distance matrix, which fits in memory and can be efficiently analyzed using methods such as multidimensional scaling (MDS). In this paper we present a novel sparse method for efficiently representing geodesic distance matrices using biharmonic interpolation. This method exploits knowledge of the data manifold to learn a sparse interpolation operator that approximates distances using a subset of points. We show that our method is 2x faster and uses 20x less memory than current leading methods for solving MDS on large point sets, with similar quality. This enables analyses of large point sets that were previously infeasible.
Combating Hysteresis With Output Targeting

Hysteresis, path dependence, and multiple equilibria are characteristic features of post-Keynesian economics. This paper constructs an otherwise conventional three-equation model that includes a hysteresis-generating mechanism and an invariant output target. We use it to explore the implications for monetary policy of an output-targeting policy framework that seeks to reverse the damage caused by hysteresis. We restrict ourselves to negative aggregate demand shocks and positive inflation shocks that in most instances require a disinflationary response from the central bank. One important finding is that as long as inflation expectations are to some degree anchored, the central bank can achieve its output target after an aggregate demand shock by overshooting its inflation target temporarily and running a â€˜high-pressure labor market.â€™ If expectations are unanchored, an aggregate demand shock will not have long-run hysteresis effects because the central bank is obliged to reflate aggressively, replacing on a cumulative basis all the demand that was lost through the shock. However, with unanchored expectations a pure inflation shock will create hysteresis effects since the central bank will need to disinflate and it does not have the option of running a high-pressure labor market. Anchoring gives the central bank this option, making inflation shocks manageable.
Ambient Backscatter Systems: Exact Average Bit Error Rate Under Fading Channels

The success of Internet-of-Things (IoT) paradigm relies on, among other things, developing energy-efficient communication techniques that can enable information exchange among billions of battery-operated IoT devices. With its technological capability of simultaneous information and energy transfer, ambient backscatter is quickly emerging as an appealing solution for this communication paradigm, especially for the links with low data rate requirement. In this paper, we study signal detection and characterize exact bit error rate (BER) for the ambient backscatter system. In particular, we formulate a binary hypothesis testing problem at the receiver and analyze system performance under three detection techniques: 1) mean threshold; 2) maximum likelihood threshold (MLT); and 3) approximate MLT. Motivated by the energy-constrained nature of IoT devices, we perform the above analyzes for two receiver types: 1) the ones that can accurately track channel state information and 2) the ones that cannot. Two main features of the analysis that distinguish this paper from the prior art are the characterization of the exact conditional density functions of the average received signal energy, and the characterization of exact average BER for this setup. The key challenge lies in the handling of correlation between channel gains of two hypotheses for the derivation of joint probability distribution of magnitude squared channel gains that is needed for the BER analysis.
The microbiologic profile of dacryocystitis.

Purpose: Recent studies suggest an increasing incidence of gram-negative bacteria and methicillin-resistant Staphylococcus aureus in dacryocystitis. Since patients are often treated empirically wit...
Transcriptome Analysis of C. elegans Reveals Novel Targets for DON Cytotoxicity

Deoxynivalenol (DON) is a mycotoxin produced by Fusarium spp. that causes Fusarium head blight (FHB) disease in cereal crops. Ingestion of food contaminated with DON poses serious human health complications. However, the DON cytotoxicity has been mostly deduced from animal studies. In this study, we used the nematode Caenorhabditis elegans (C. elegans) as a tractable animal model to dissect the toxic effect of DON. Our results indicate that DON reduces the fecundity and lifespan of C. elegans. Real-time quantitative polymerase chain reaction (RT-qPCR) analysis showed that DON upregulates innate immunity-related genes including C17H12.8 and K08D8.5 encoding PMK-1 (mitogen activated protein kinase-1)-regulated immune effectors, and F35E12.5 encoding a CUB-like domain-containing protein. Furthermore, our RNAseq data demonstrate that out of ~17,000 C. elegans genes, 313 are upregulated and 166 were downregulated by DON treatment. Among the DON-upregulated genes, several are ugt genes encoding UDP-glucuronosyl transferase (UGTs) which are known to be involved in chemical detoxification. The three upregulated genes, F52F10.4 (oac-32), C10H11.6 (ugt-26) and C10H11.4 (ugt-28) encoding the O-acyltransferase homolog, UGT26 and UGT 28, respectively, are shown to contribute to DON tolerance by a RNAi bacterial feeding experiment. The results of this study provide insights to the targets of DON cytotoxicity and potential mitigation measures.
MicroRNA Control of TGF-β Signaling

Transcriptional and post-transcriptional regulation shapes the transcriptome and proteome changes induced by various cellular signaling cascades. MicroRNAs (miRNAs) are small regulatory RNAs that are approximately 22 nucleotides long, which direct the post-transcriptional regulation of diverse target genes and control cell states. Transforming growth factor (TGF)-β family is a multifunctional cytokine family, which plays many regulatory roles in the development and pathogenesis of diverse diseases, including fibrotic disease, cardiovascular disease and cancer. Previous studies have shown that the TGF-β pathway includes the miRNA pathway as an important component of its downstream signaling cascades. Multiple studies of epithelial–mesenchymal transition (EMT)-related miRNAs have highlighted that miRNAs constitute the intrinsic bistable molecular switches of cell states by forming double negative feedback loops with EMT-inducing transcription factors. This may be important for understanding the reversibility of EMT at the single-cell level, the presence of distinct EMT transition states and the intra- and inter-tumor heterogeneity of cancer cell phenotypes. In the present review, I summarize the connection between TGF-β signaling and the miRNA pathway, placing particular emphasis on the regulation of miRNA expression by TGF-β signaling, the modulation of TGF-β signaling by miRNAs, the miRNA-mediated modulation of EMT and endothelial–mesenchymal transition as well as the crosstalk between miRNA and TGF-β pathways in the tumor microenvironment.
Non-monotone Submodular Maximization in Exponentially Fewer Iterations

In this paper we consider parallelization for applications whose objective can be expressed as maximizing a non-monotone submodular function under a cardinality constraint. Our main result is an algorithm whose approximation is arbitrarily close to 1/2e in O(log^2 n) adaptive rounds, where n is the size of the ground set. This is an exponential speedup in parallel running time over any previously studied algorithm for constrained non-monotone submodular maximization. Beyond its provable guarantees, the algorithm performs well in practice. Specifically, experiments on traffic monitoring and personalized data summarization applications show that the algorithm finds solutions whose values are competitive with state-of-the-art algorithms while running in exponentially fewer parallel iterations.
Belief heterogeneity in the option markets and the cross-section of stock returns

Abstract Standard deviations of the implied-historical volatility spread, of implied volatility innovations, and of the volatility term structure spread in equity options help explain the cross-section of one-month-ahead underlying stock returns. The explanatory power from standard deviations is robust to the levels of these three variables, volatility of volatility, firm characteristics, and common risk factor models. We find support for interpreting the standard deviations of these option-based measures as forward-looking proxies for heterogeneous beliefs. The negative relationship between our three measures and future underlying returns is consistent with the Miller (1977) overvaluation model which implies that divergence of investor opinions in the presence of short-sale constraints leads to lower expected returns.
Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering

Question answering is an important task for autonomous agents and virtual assistants alike and was shown to support the disabled in efficiently navigating an overwhelming environment. Many existing methods focus on observation-based questions, ignoring our ability to seamlessly combine observed content with general knowledge. To understand interactions with a knowledge base, a dataset has been introduced recently and keyword matching techniques were shown to yield compelling results despite being vulnerable to misconceptions due to synonyms and homographs. To address this issue, we develop a learning-based approach which goes straight to the facts via a learned embedding space. We demonstrate state-of-the-art results on the challenging recently introduced fact-based visual question answering dataset, outperforming competing methods by more than \(5\%\).
Potential utility of an independent decision-making board for seriously ill patients lacking decisional capacity

Summary Physicians acknowledge that they are providing unnecessary medical care at the end of life for a variety of reasons, including fear of malpractice litigation, Medicare's fee-for-service reimbursement mechanism, patient and family requests for care, a culture of denial of mortality, and a physician culture which views a patient's death as a professional failure. Recent data suggest that more than one-fifth of medical care provided at the end of life is unnecessary. Although the problem of over-provision of medical care is now well recognized in the legal and medical literatures, private-ordering solutions, such as better communication training for physicians or improved patient decision aids, will have only marginally ameliorating effects. The inherent challenges in making medical decisions during terminal illness become even more complex when patients are unable to make these choices for themselves. Although patient autonomy, implemented via informed consent, is the primary principle that governs medical decision-making, including on behalf of patients who have lost decisional capacity, insufficient evidence of the patient's wishes coupled with uncertainty about prognosis often leaves physicians and family members in a quandary as to whether to implement or to continue providing therapeutic treatment or life-prolonging care. The default operation of the surrogate consent process in the U.S. means that, for patients who do not clearly opt out of life-prolonging treatment before losing decisional capacity, the path of least resistance often will lead to decisions in favour of initiating or continuing life-prolonging care. This state of affairs can lead to substantial stress for all parties concerned, along with the potential for conflict. This paper considers the potential utility and transplantability of a Canadian public decision-support mechanism in this context. In 1996, the provincial government of Ontario implemented a Consent and Capacity Board (CCB), an independent expert body charged, among other things, to mediate and resolve disputes in the context of surrogate decision-making. Two-plus decades of CCB evidence suggest this it provides a better shared, less confrontational and more robust decision-making process than is currently available within the U.S. surrogate decision-making rules. Thus, a CCB type mechanism has the potential to also improve surrogate decision-making at the end of life in the U.S. and this paper discusses the extent to which it is capable of being “transplanted” into the U.S. health system on a state-by-state basis.
Engaging Older Adults in the Participatory Design of Intelligent Health Search Tools

Engaging older adults (adults 65+) in technology design can be challenging. At the same time, it is becoming ever more important to ensure inclusion of diverse perspectives in design research. Several strategies currently exist for successfully recruiting and engaging older adults in design. However, there is still much to learn about how to effectively engage older adults in the design process. In this position paper, we reflect on our experiences engaging older adults in participatory design of "smart" tools for health information search. We share our study design, including our recruitment process and procedures. We then discuss the strategies we used in the design process and challenges we encountered when designing and implementing our research protocol. We contribute our experiences in an effort to facilitate discussion of strategies and opportunities for including older adults in design research.
Audio-Based Activities of Daily Living (ADL) Recognition with Large-Scale Acoustic Embeddings from Online Videos

Over the years, activity sensing and recognition has been shown to play a key enabling role in a wide range of applications, from sustainability and human-computer interaction to health care. While many recognition tasks have traditionally employed inertial sensors, acoustic-based methods offer the benefit of capturing rich contextual information, which can be useful when discriminating complex activities. Given the emergence of deep learning techniques and leveraging new, large-scale multimedia datasets, this paper revisits the opportunity of training audio-based classifiers without the onerous and time-consuming task of annotating audio data. We propose a framework for audio-based activity recognition that can make use of millions of embedding features from public online video sound clips. Based on the combination of oversampling and deep learning approaches, our framework does not require further feature processing or outliers filtering as in prior work. We evaluated our approach in the context of Activities of Daily Living (ADL) by recognizing 15 everyday activities with 14 participants in their own homes, achieving 64.2% and 83.6% averaged within-subject accuracy in terms of top-1 and top-3 classification respectively. Individual class performance was also examined in the paper to further study the co-occurrence characteristics of the activities and the robustness of the framework.
Integrating Systems and Theories in the SAL Hybrid Architecture.

The Synthesis of ACT-R and Leabra (SAL) hybrid cognitive architecture is the integration of two theories of cognitive functioning, each itself a highly integrative theory of cognition, ACT-R being predominantly a symbolic production-rule based architecture and Leabra a neural modeling architecture. The combination of the two architectures allows for richer dynamics that take advantage of neural and symbolic aspects and provides mutual constraints that promote convergence towards models that are both neurophysiologically and psychologically valid. We present a hybrid model that makes use of multi-level and multi-system integration to allow an instructed assembly task to be carried out in way that is noise and error robust. Specifically, the model shows how higher-level error recovery routines can interface with lower-level sensory, motor, and error detection processes and result in a robustness to noise and noise-induced errors. Multiple systems and processes operating at multiple levels are recruited to provide a way around the limitations of simpler systems composed of isolated modules that do not allow information to be propagated as easily. The benefits of this approach provide motivation for the adoption of a generally integrated approach to cognitive systems.
Non‐competes, business dynamism, and concentration: Evidence from a Florida case study

Author(s): Kang, H; Fleming, L | Abstract: Most research on non-competes has focused on employees; here we study how non-competes affect firm location choice, growth, and consequent regional concentration, using Florida's 1996 legislative change that eased restrictions on their enforcement. Difference-in-differences models show that following the change, establishments of large firms were more likely to enter Florida; they also created a greater proportion of jobs and increased their share of employment in the state. Entrepreneurs or establishments of small firms, in contrast, were less likely to enter Florida following the law change; they also created a smaller proportion of new jobs and decreased their share of employment. Consistent with these location and job creation dynamics, regional business concentration increased following the law change in Florida. Nationwide cross-sections demonstrate consistent correlations between state-level non-compete enforcement and the location, employment, and concentration dynamics illustrated in Florida.
H2 Binding, Splitting, and Net Hydrogen Atom Transfer at a Paramagnetic Iron Complex.

While diamagnetic transition metal complexes that bind and split H2 have been extensively studied, paramagnetic complexes that exhibit this behavior remain rare. The square planar S = 1/2 FeI(P4N2)+ cation (FeI+) reversibly binds H2/D2 in solution, exhibiting an inverse equilibrium isotope effect of KH2/KD2 = 0.58(4) at −5.0 °C. In the presence of excess H2, the dihydrogen complex FeI(H2)+ cleaves H2 at 25 °C in a net hydrogen atom transfer reaction, producing the dihydrogen-hydride trans-FeII(H)(H2)+. The proposed mechanism of H2 splitting involves both intra- and intermolecular steps, resulting in a mixed first- and second-order rate law with respect to initial [FeI+]. The key intermediate is a paramagnetic dihydride complex, trans-FeIII(H)2+, whose weak FeIII–H bond dissociation free energy (calculated BDFE = 44 kcal/mol) leads to bimetallic H–H homolysis, generating trans-FeII(H)(H2)+. Reaction kinetics, thermodynamics, electrochemistry, EPR spectroscopy, and DFT calculations support the proposed mech...
Light-emitting diodes

Inorganic semiconductor light-emitting diodes (LEDs) are environmentally benign and have found widespread use as indicator lights, mobile displays, large-area displays, signage applications, and lighting applications. The entire visible spectrum can be covered by light-emitting semiconductors: AlGaInP and AlGaInN compound semiconductors are capable of emission in the red-to-yellow wavelength range and violet-to-green wavelength range, respectively. For white light sources based on LEDs, the most common approach is the combination of a blue LED chip with a yellow phosphor. Alternatively, a group of red, green, and blue (RGB) LEDs can be used; such source allows for color tunability. White LEDs are currently used to replace incandescent and fluorescent sources. In this review, the properties of inorganic LEDs will be presented, including emission spectra, electrical characteristics, and current-flow patterns. Structures providing high internal quantum efficiency, namely heterostructures and multiple quantum well structures, will be discussed. Advanced techniques enhancing the external quantum efficiency will be reviewed, including die shaping (chip shaping) and surface roughening. Different approaches to white LEDs will be presented and figures-of-merit such as the color rendering index and luminous efficacy will be explained. Besides visible LEDs, the technical challenges of newly evolving deep ultraviolet (UV) LEDs will be introduced. Finally, the packaging of low-power and high-power LED dies will be discussed.
Compressed counting

We propose Compressed Counting (CC) for approximating the αth frequency moments (0 < α ≤ 2) of data streams under a relaxed strict-Turnstile model, using maximally-skewed stable random projections. Estimators based on the geometric mean and the harmonic mean are developed. When α = 1, a simple counter suffices for counting the first moment (i.e., sum). The geometric mean estimator of CC has asymptotic variance α Δ = |α - 1|, capturing the intuition that the complexity should decrease as Δ = |α - 1| → 0. However, the previous classical algorithms based on symmetric stable random projections[12, 15] required O (1/e2) space, in order to approximate the αth moments within a 1 + e factor, for any 0 < α ≤ 2 including α = 1. We show that using the geometric mean estimator, CC requires O [EQUATION] space, as Δ → 0. Therefore, in the neighborhood of α = 1, the complexity of CC is essentially O (1/e) instead of O (1/e2). CC may be useful for estimating Shannon entropy, which can be approximated by certain functions of the αth moments with α → 1. [10, 9] suggested using α = 1 + Δ with (e.g.,) Δ < 0.0001 and e < 10−7, to rigorously ensure reasonable approximations. Thus, unfortunately, CC is "theoretically impractical" for estimating Shannon entropy, despite its empirical success reported in [16].
Decision-making in livestock biosecurity practices amidst environmental and social uncertainty: Evidence from an experimental game

Livestock industries are vulnerable to disease threats, which can cost billions of dollars and have substantial negative social ramifications. Losses are mitigated through increased use of disease-related biosecurity practices, making increased biosecurity an industry goal. Currently, there is no industry-wide standard for sharing information about disease incidence or on-site biosecurity strategies, resulting in uncertainty regarding disease prevalence and biosecurity strategies employed by industry stakeholders. Using an experimental simulation game, with primarily student participants, we examined willingness to invest in biosecurity when confronted with disease outbreak scenarios. We varied the scenarios by changing the information provided about 1) disease incidence and 2) biosecurity strategy or response by production facilities to the threat of disease. Here we show that willingness to invest in biosecurity increases with increased information about disease incidence, but decreases with increased information about biosecurity practices used by nearby facilities. Thus, the type or context of the uncertainty confronting the decision maker may be a major factor influencing behavior. Our findings suggest that policies and practices that encourage greater sharing of disease incidence information should have the greatest benefit for protecting herd health.
Predicting the optimal growth temperatures of prokaryotes using only genome derived features.

Motivation Optimal growth temperature is a fundamental characteristic of all living organisms. Knowledge of this temperature is central to the study of a prokaryote, the thermal stability and temperature dependent activity of its genes, and the bioprospecting of its genome for thermally adapted proteins. While high throughput sequencing methods have dramatically increased the availability of genomic information, the growth temperatures of the source organisms are often unknown. This limits the study and technological application of these species and their genomes. Here, we present a novel method for the prediction of growth temperatures of prokaryotes using only genomic sequences. Results By applying the reverse ecology principle that an organism's genome includes identifiable adaptations to its native environment, we can predict a species' optimal growth temperature with an accuracy of 5.17°C root-mean-square error and a coefficient of determination of 0.835. The accuracy can be further improved for specific taxonomic clades or by excluding psychrophiles. This method provides a valuable tool for the rapid calculation of organism growth temperature when only the genome sequence is known. Availability and implementation Source code, genomes analyzed and features calculated are available at: https://github.com/DavidBSauer/OGT_prediction. Supplementary information Supplementary data are available at Bioinformatics online.
Convergence of the point vortex method for the 3‐D euler equations

We prove consistency, stability, and convergence of a point vortex approximation to the 3-D incompressible Euler equations with smooth solutions. The 3-D algorithm we consider here is similar to the corresponding 3-D vortex blob algorithm introduced by Beale and Majda; see [3]. We first show that the discretization error is second-order accurate. Then we show that the method is stable in lp norm for the particle trajectories and in w−1.p norm for discrete vorticity. Consequently, the method converges up to any time for which the Euler equations have a smooth solution. One immediate application of our convergence result is that the vortex filament method without smoothing also converges.
Bootstrapping: Using SMT Hardware to Improve Single-Thread Performance

Single-thread performance improvement remains a central design goal for general purpose processors. Microarchitectural designs for the core have reached a plateau over the past years. However, we are still far from exhausting the implicit parallelism available in today's programs. One approach is to use a separate thread context to improve data and instruction supply to the main pipeline. Such decoupled look-ahead (DLA) architectures have been shown to be an effective way to improve single-thread performance. However, a default implementation requires an additional core. While an SMT flavor is possible, a naive implementation is inefficient and thus slow. In this paper, we propose an optimized implementation called Bootstrapping that makes DLA just as effective on a single (SMT) core as using two cores. While fusing two cores can improve single-thread performance by 1.22x, Bootstrapping provides a speedup of 1.48 over a broad range of benchmark suites, making it a compelling microarchitectural feature for general-purpose microarchitectures.
Bacillus Calmette-Guérin Overexpressing an Endogenous Stimulator of Interferon Genes Agonist Provides Enhanced Protection Against Pulmonary Tuberculosis.

BACKGROUND Stimulator of interferon genes (STING) is a key cytosolic receptor for small nucleotides and plays a key role in anticancer and antiviral immunity. Cyclic dinucleotide STING agonists may comprise a novel class of vaccine adjuvants capable of inducing cellular immune responses and protective efficacy against intracellular pathogens. METHODS We generated a recombinant Bacillus Calmette-Guerin ([BCG] BCG-disA-OE) that overexpresses the endogenous mycobacterial diadenylate cyclase gene and releases high levels of the STING agonist bis-(3'-5')-cyclic dimeric adenosine monophosphate (c-di-AMP). We used a 24-week guinea pig vaccination-Mycobacterium tuberculosis (M.tb.) challenge model to test the protective efficacy of BCG-disA-OE versus wild-type BCG and measured lung weights, pathology scores, and M.tb. organ colony-forming unit (CFU) counts. RESULTS BCG-disA-OE elicited significantly stronger tumor necrosis factor-α, interleukin (IL)-6, IL-1β, interferon (IFN) regulatory factor 3, and IFN-β levels than BCG-wild type (WT) in vitro in murine macrophages. In vivo in guinea pigs, we found that BCG-disA-OE reduced lung weights, pathology scores, and M.tb. CFU counts in lungs by 28% (P < .05), 34%, and 2.0 log10 CFU units (P < .05) compared with BCG-WT, respectively. CONCLUSIONS We report a strategy of delivering a STING agonist from within live BCG. Overproduction of the STING agonist c-di-AMP significantly enhanced the protective efficacy of BCG against pulmonary and extrapulmonary tuberculosis. Our findings support the development of BCG-vectored STING agonists as a tuberculosis vaccine strategy.
Robust Resource Allocation Using Edge Computing for Vehicle to Infrastructure (V2I) Networks

Development of autonomous and self-driving vehicles requires agile and reliable services to manage hazardous road situations. Vehicular Network is the medium that can provide high-quality services for self-driving vehicles. The majority of service requests in Vehicular Networks are delay intolerant (e.g., hazard alerts, lane change warning) and require immediate service. Therefore, Vehicular Networks, and particularly, Vehicle-to-Infrastructure (V2I) systems must provide a consistent real-time response to autonomous vehicles. During peak hours or disasters, when a surge of requests arrives at a Base Station, it is challenging for the V2I system to maintain its performance, which can lead to hazardous consequences. Hence, the goal of this research is to develop a V2I system that is robust against uncertain request arrivals. To achieve this goal, we propose to dynamically allocate service requests among Base Stations. We develop an uncertainty-aware resource allocation method for the federated environment that assigns arriving requests to a Base Station so that the likelihood of completing it on-time is maximized. We evaluate the system under various workload conditions and oversubscription levels. Simulation results show that edge federation can improve robustness of the V2I system by reducing the overall service miss rate by up to 45%.
Increasing maltreated and nonmaltreated children's recall disclosures of a minor transgression: the effects of back-channel utterances, a promise to tell the truth, and a post-recall putative confession

Abstract Background Children are often hesitant to disclose transgressions, particularly when they feel implicated, and frequently remain reluctant until confronted with direct questions. Given the risks associated with direct questions, an important issue is how interviewers can encourage honesty through recall questions. Objective The present study examined the use of three truth induction strategies for increasing the accuracy and productivity of children’s reports about a transgression. Participants A total of 285 4-to-9-year-old maltreated and nonmaltreated children. Methods Each child took part in a play session with a stranger during which the child appeared to break some toys. A research assistant interviewed the child with narrative practice rapport building and recall questions. The study included manipulations of back-channel utterances (brief expressions used to communicate attention and interest), whether (and when) the child was asked to promise to tell the truth, and the use of a post-recall putative confession. Results Back-channel utterances failed to increase disclosure (OR = 0.79 [95% CI: 0.48, 1.31]) but increased the productivity of children’s reports about broken (p = 0.04, ηp = 0.02) and unbroken toys (p = 0.004, ηp = 0.03). A promise to tell the truth significantly increased children’s disclosures, but only among nonmaltreated children (OR = 3.65 [95% CI: 1.23, 10.90]). The post-recall putative confession elicited new disclosures from about half of children who had failed to disclose. Conclusions The findings highlight the difficulties of eliciting honest responses from children about suspected transgressions and the need for flexible questioning strategies.
Growing Skylines: The Economic Determinants of Skyscrapers in China

Since 1978, when China instituted economic reforms, cities throughout the country have embraced skyscraper construction. Despite their importance to the domestic economy, little is understood about what has been driving skyscraper heights and frequencies in China. This work explores the degree to which skyscraper construction patterns are the result of economic fundamentals, versus political factors and intercity competition. We find a strong economic rational across China, but we also find evidence of noneconomic factors. We show that incentives for political officials, such as career promotion, are helping to contribute to the growth in China’s skylines. We also find that small cities tend to overbuild skyscrapers. Spatial autoregression results further suggest some intercity competition, especially for those within the same tier.
PRMT5 is upregulated by B-cell receptor signaling and forms a positive-feedback loop with PI3K/AKT in lymphoma cells

PRMT5, which regulates gene expression by symmetric dimethylation of histones and non-histone target proteins, is overexpressed and plays a pathogenic role in many cancers. In diffuse large B cell lymphoma (DLBCL), the mechanisms of PRMT5 dysregulation and its role in lymphomagenesis remain largely unknown. Here we demonstrate that B cell receptor (BCR) signaling regulates PRMT5 expression in DLBCL cells. Immunohistochemical analysis reveals elevated levels of PRMT5 expression in DLBCL cases and in germinal center (GC) B cells when compared to naive B cells. PRMT5 can be induced in naive B cells by BCR stimulation. We discovered that BTK-NF-κB signaling induces PRMT5 transcription in activated B cell-like (ABC) DLBCL cells while BCR downstream PI3K-AKT-MYC signaling upregulates PRMT5 expression in both ABC and GCB DLBCL cells. PRMT5 inhibition inhibits the growth of DLBCL cells in vitro and patient derived xenografts. Genomic and biochemical analysis demonstrate that PRMT5 promotes cell cycle progression and activates PI3K-AKT signaling, suggesting a feedback regulatory mechanism to enhance cell survival and proliferation. Co-targeting PRMT5 and AKT by their specific inhibitors is lethal to DLBCL cell lines and primary cancer cells. Therefore, this study provides a mechanistic rationale for clinical trials to evaluate PRMT5 and AKT inhibitors for DLBCL.
An Adaptive Approach to Real-Time Estimation of Vehicle Sideslip, Road Bank Angles, and Sensor Bias

Robust estimation of vehicle sideslip angle is essential for stability control applications. However, the direct measurement of sideslip angle is expensive for production vehicles. This paper presents a novel sideslip estimation algorithm which relies only on sensors available on passenger and commercial vehicles. The proposed method uses both kinematics and dynamics vehicle models to construct extended Kalman filter observers. The estimate relies on the results provided from the dynamics model observer where the tire cornering stiffness parameters are updated using the information provided from the kinematics model observer. The stability property of the proposed algorithm is discussed and proven. Finally, multiple experimental tests are conducted to verify its performance in practice. The results show that the proposed approach provides smooth and accurate sideslip angle estimation. In addition, our novel algorithm provides reliable estimates of bank angles and lateral acceleration sensor bias.
Evidence for the Effect of Monitoring Costs on Foreign Direct Investment

Abstract A proposed reason for the significant inverse relationship between distance (both physical and cultural) and foreign direct investment is the increased costs for a parent firm to monitor an affiliate when there is greater distance between them. We provide the first direct test of this hypothesis using O*NET data on occupational skills to construct industry-level measures of the importance of monitoring-related skills. We exploit this cross-industry variation to examine whether physical and cultural distances have a greater impact on cross-border M&A in industries where monitoring-related skills are more important. Using data on worldwide cross-border M&A activity from 2005 through 2014, we find significant evidence for the effect of monitoring costs on cross-border M&A activity. We also show that the relatively low importance of monitoring-related costs in manufacturing industries compared to those in other sectors is an important factor in explaining why cross-border M&A in manufacturing is so large despite its relatively small share in most countries.
Enabling High-Voltage Lithium-Metal Batteries under Practical Conditions

Summary Rechargeable lithium (Li)-metal batteries (LMBs) offer a great opportunity for applications needing high-energy-density battery systems. However, rare progress has been demonstrated so far under practical conditions, including high voltage, high-loading cathode, thin Li anode, and lean electrolyte. Here, in opposition to common wisdom, we report an ether-based localized high-concentration electrolyte that can greatly enhance the stability of a Ni-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) cathode under 4.4 and 4.5 V with an effective protection interphase enriched in LiF. This effect, in combination with the superior Li stability in this electrolyte, enables dramatically improved cycling performances of Li||NMC811 batteries under highly challenging conditions. The LMBs can retain over 80% capacity in 150 stable cycles with extremely limited amounts of the Li anode and electrolyte. The findings in this work point out a very promising strategy to develop practical high-energy LMBs.
Epoxidation of olefins with peracid at low temperature with copper catalysis

Abstract Treatment of a wide range of olefins with m -chloroperbenzoic acid (MCPBA) at low temperature in the presence of copper(I) and (II) catalysts in methylene chloride provides epoxides in good to excellent yields.
Novel ring-cleaving reaction of 4-nitro-1,1,2,2,9,9,10,10-octafluoro[2.2]paracyclophane with nucleophiles

Abstract When 4-nitro-AF4 is treated with nucleophiles such as alkoxides and cyanide, a novel ring opening, cyclophane destroying reaction is observed whereby, via an S N Ar mechanism, the nucleophile attacks the bridgehead aryl carbon vicinal to the nitro group with subsequent aryl-CF 2 bond cleavage.