cssi/SciSciGPT-SciSciNet huggingface dataset:
Suicide in Happy Places: Is There Really a Paradox?

In 2011 researchers published a paper that exposed a puzzling paradox: the happiest states in the U.S. also tend to have the highest suicide rates. In the current study, we re-examine this relationship by combining data from the Multiple Mortality Cause-of-Death Records, the Behavioral Risk Factor Surveillance System, and the American Communities Survey to determine how subjective well-being and suicide are related across 1563 U.S. counties. We extend the original study in important ways: by incorporating both absolute and relative measures of subjective well-being; by examining the happiness-suicide association at a more suitable level of analysis; and by including a more robust set of control variables in the model. Contrary to the previous study, we do not observe any significant relationship, negative or positive, between the absolute and relative well-being of places and suicide rates at the county-level. Implications for the study of suicide rates and relative deprivation are discussed.
Extended Gray–Wyner System With Complementary Causal Side Information

We establish the rate region of an extended Gray–Wyner system (EGW) for 2-DMS $(X,Y)$ with two additional decoders having complementary causal side information. We show that the 5-D rate region of the EGW system is equivalent to the 3-D mutual information region consisting of the set of all triples of the form $(I(X;U),\,I(Y;U),\,I(X,Y;U))$ for some $p_{U|X,Y}$ . This correspondence greatly simplifies the exploration of the the extreme points of the rate region. In addition to the operationally significant extreme points of the original Gray–Wyner rate region, which include Wyner’s common information, Gacs-Korner common information, and the information bottleneck, the extreme points of the rate region for the EGW system also include the Korner graph entropy, the privacy funnel and excess functional information, as well as three new quantities of potential interest. We further show that projections of the mutual information region yield the rate regions for many settings involving a two discrete memoryless source (2-DMS), including lossless source coding with causal side information, distributed channel synthesis, and lossless source coding with a helper. To further motivate the mutual information region itself, we draw analogies between set operations and its extreme points. This allows us to find random variables that can be considered as intersection, difference, and symmetric difference of two random variables. Finally, we establish the rate regions for two related setups to the EGW system, namely, the noncausal EGW system and the lossy EGW system.
Use of the Internet and its Impact on Productivity and Sales Growth in Female-Owned Firms: Evidence from India

The Internet has completely transformed our lives on an individual basis in many ways, ranging from the way we communicate through the way we socialize to the way we shop and travel. Businesses are no exception to this premise. This paper studies the adoption of the Internet by female-owned firms in India. It uses the World Bank’s Enterprise Surveys Program data set for the year 2014 to study the adoption of the Internet by more than 10,000 firms in the country. After controlling for a large number of firm-level characteristics, empirical results obtained indicate that female-owned firms are more likely to use the Internet than their male counterparts. However, further empirical analysis shows that more intensive adoption of the Internet by these female-owned firms does not necessarily translate into better performance. Specifically, the adoption of the Internet does not make female-owned firms more or less likely to have better productivity and sales growth in contrast to that of their male counterparts.
How Diverse Users and Activities Trigger Connective Action via Social Media: Lessons from the Twitter Hashtag Campaign #ILookLikeAnEngineer

We present a study that examines how a social media activism campaign aimed at improving gender diversity within engineering gained and maintained momentum in its early period. We examined over 50,000 Tweets posted over the first ~75 days of the #ILookLikeAnEngineer campaign and found that diverse participation - of types of users - increased activity at crucial moments. We categorize these triggers into four types: 1) Event-Driven: Alignment of the campaign with offline events related to the issue (Diversity SFO, Disrupt, etc.); 2) Media-Driven: News coverage of the events in the media (TechCrunch, CNN, BBC, etc.); 3) Industry-Driven: Web participation in the campaign by large organizations (Microsoft, Tesla, GE, Cisco, etc.); and 4) Personality-Driven: Alignment of the events with popular and/or known personalities (e.g. Isis Anchalee; Michelle Sun; Ada Lovelace.) This study illustrates how one mechanism - triggering - supports connective action in social media campaign.
NiIn as an Ohmic Contact to P-GaN

Based on the criteria for the solid state exchange reaction with p-GaN, we have investigated the intermetallic compound NiIn as a possible ohmic contact. The contacts were fabricated by depositing NiIn on p-GaN films (p ∼ 2 × 1017 cm−3) using RF sputtering from a compound target. The as-deposited, NiIn contacts were found to be rectifying and using I-V characterization a Schottky barrier height of 0.82 eV was measured. Rapid thermal annealing of the contacts was shown to significantly decrease their resistance, with contacts annealed at 800 °C for 1 min yielding the lowest resistance. When annealed at 800 °C for 1 min NiIn contacts exhibited a specific contact resistance of 8-9 × 10−3 Ω cm2 as measured by the circular transmission line model. To allow a more universal comparison the more traditional Ni/Au contacts, processed under the same conditions, were used as a standard. Their measured specific contact resistance (ρc = 1.2 − 2.1 × 10−2 Ωcm2) was significantly higher than that of the NiIn contacts. Demonstrating that NiIn has promise as an ohmic contact to p-GaN and should be studied in greater detail.
What do Workplace Wellness Programs do? Evidence from the Illinois Workplace Wellness Study

Workplace wellness programs cover over 50 million U.S. workers and are intended to reduce medical spending, increase productivity, and improve well-being. Yet limited evidence exists to support these claims. We designed and implemented a comprehensive workplace wellness program for a large employer and randomly assigned program eligibility and financial incentives at the individual level for nearly 5,000 employees. We find strong patterns of selection: during the year prior to the intervention, program participants had lower medical expenditures and healthier behaviors than nonparticipants. The program persistently increased health screening rates, but we do not find significant causal effects of treatment on total medical expenditures, other health behaviors, employee productivity, or self-reported health status after more than two years. Our 95% confidence intervals rule out 84% of previous estimates on medical spending and absenteeism.
A Reactive Inelasticity Theoretical Framework for Modeling Viscoelasticity, Plastic Deformation, and Damage in Soft Tissue

Fibrous tissues are biopolymeric materials that are made of extracellular proteins including several collagens and proteoglycans, and have a high water content. These tissues have non-linear, anisotropic, and inelastic mechanical behaviors that are often categorized into viscoelastic behavior, plastic deformation, and damage. While tissue's elastic and viscoelastic mechanical properties have been measured for decades, there is no comprehensive theoretical framework for modeling inelastic behaviors of these tissues that is based on their structure. To model the three major inelastic mechanical behaviors of tissue's fibrous matrix we formulated a structurally inspired continuum mechanics framework based on the energy of molecular bonds that break and reform in response to external loading (reactive bonds). In this framework, we employed the theory of internal state variables and kinetics of molecular bonds. The number fraction of bonds, their reference deformation gradient, and damage parameter were used as state variables that allowed for consistent modeling of all three of the inelastic behaviors of tissue by using the same sets of constitutive relations. Several numerical examples are provided that address practical problems in tissue mechanics, including the difference between plastic deformation and damage. This model can be used to identify relationships between tissue's mechanical response to external loading and its biopolymeric structure.
Maximal Correlation Secrecy

This paper shows that the Hirschfeld–Gebelein–Renyi maximal correlation between the message and the ciphertext provides good secrecy guarantees for cryptosystems that use short keys. We first establish a bound on the eavesdropper’s advantage in guessing functions of the message in terms of maximal correlation and the Renyi entropy of the message. This result implies that the maximal correlation is stronger than the notion of entropic security introduced by Russell and Wang. We then show that a small maximal correlation $\rho $ can be achieved via a randomly generated cipher with key length $\approx 2\log (1/\rho )$ , independent of the message length, and by a stream cipher with key length $2\log (1/\rho )+\log n+2$ for a message of length $n$ . We establish a converse showing that these ciphers are close to optimal. This is in contrast with the entropic security for which there is a gap between the lower and upper bounds. Finally, we show that a small maximal correlation implies secrecy with respect to several mutual information-based criteria but is not necessarily implied by them. Hence, maximal correlation is a stronger and more practically relevant measure of secrecy than the mutual information.
Conv-RAM: An energy-efficient SRAM with embedded convolution computation for low-power CNN-based machine learning applications

Convolutional neural networks (CNN) provide state-of-the-art results in a wide variety of machine learning (ML) applications, ranging from image classification to speech recognition. However, they are very computationally intensive and require huge amounts of storage. Recent work strived towards reducing the size of the CNNs: [1] proposes a binary-weight-network (BWN), where the filter weights (w i 's) are ±1 (with a common scaling factor per filter: α). This leads to a significant reduction in the amount of storage required for the W i 's, making it possible to store them entirely on-chip. However, in a conventional all-digital implementation [2, 3], reading the wj i s and the partial sums from the embedded SRAMs require a lot of data movement per computation, which is energy-hungry. To reduce data-movement, and associated energy, we present an SRAM-embedded convolution architecture (Fig. 31.1.1), which does not require reading the w i 's explicitly from the memory. Prior work on embedded ML classifiers have focused on 1b outputs [4] or a small number of output classes [5], both of which are not sufficient for CNNs. This work uses 7b inputs/outputs, which is sufficient to maintain good accuracy for most of the popular CNNs [1]. The convolution operation is implemented as voltage averaging (Fig. 31.1.1), since the wj's are binary, while the averaging factor (1/N) implements the weight-coefficient α (with a new scaling factor, M, implemented off-chip).
Early catheter removal after pelvic floor reconstructive surgery: a randomized trial

Studies have yet to examine the impact of day-of-surgery voiding trials on post-operative urinary retention in women undergoing obliterative and apical suspension procedures for pelvic organ prolapse. Our objective was to evaluate if time to spontaneous void after these procedures is shorter when a voiding trial is performed on the day of surgery compared with our standard practice of post-operative day 1. We conducted a randomized, parallel-arm trial in patients undergoing major pelvic floor reconstructive surgery. Women were randomized 1:1 to an early (4 h post-operatively on the day of surgery) or a standard (6 am on post-operative day 1) retrograde voiding trial. A total of 57 women consented. Mean age and BMI were 65 ± 11 and 27.9 ± 4.4. Most women had stage III pelvic organ prolapse (77.2%). Groups had similar baseline characteristics. In the intention-to-treat analysis (n = 57), there was no difference in time to spontaneous void in the early versus standard voiding trial groups (15.9 ± 3.8 vs 28.4 ± 3.1 hours, p = 0.081). In the adjusted analysis using mutlivariable linear regression, an early voiding trial decreased the time to spontaneous void (abeta −2.00 h, p = 0.031) when controlling for vaginal packing and stage IV prolapse. In the per-protocol analysis, which excluded 4 patients for crossover, spontaneous void occurred 17 hours faster in the early voiding trial group (14.6 ± 3.7 vs 31.8 ± 2.9 hours; p = 0.022). Early voiding trial patients experienced ambulation sooner and more often than the standard group (p = 0.02). A day-of-surgery voiding trial did not prolong catheter use after obliterative and apical suspension procedures.
Synchronized Aggregate Signatures from the RSA Assumption

In this work we construct efficient aggregate signatures from the RSA assumption in the synchronized setting. In this setting, the signing algorithm takes as input a (time) period t as well the secret key and message. A signer should sign at most once for each t. A set of signatures can be aggregated so long as they were all created for the same period t. Synchronized aggregate signatures are useful in systems where there is a natural reporting period such as log and sensor data, or for signatures embedded in a blockchain protocol.
Electronic Cigarette Awareness, Use, and Perceptions among Cancer Patients.

ObjectiveElectronic cigarettes (e-cigs) are an emerging trend, yet little is known about their use in the cancer population. The objectives of this study were (1) to describe characteristics of e-c...
Reciprocal modulation between amyloid precursor protein and synaptic membrane cholesterol revealed by live cell imaging

The amyloid precursor protein (APP) has been extensively studied because of its association with Alzheimer's disease (AD). However, APP distribution across different subcellular membrane compartments and its function in neurons remains unclear. We generated an APP fusion protein with a pH-sensitive green fluorescent protein at its ectodomain and a pH-insensitive blue fluorescent protein at its cytosolic domain and used it to measure APP's distribution, subcellular trafficking, and cleavage in live neurons. This reporter, closely resembling endogenous APP, revealed only a limited correlation between synaptic activities and APP trafficking. However, the synaptic surface fraction of APP was increased by a reduction in membrane cholesterol levels, a phenomenon that involves APP's cholesterol-binding motif. Mutations at or near binding sites not only reduced both the surface fraction of APP and membrane cholesterol levels in a dominant negative manner, but also increased synaptic vulnerability to moderate membrane cholesterol reduction. Our results reveal reciprocal modulation of APP and membrane cholesterol levels at synaptic boutons.
AUCTSP: an improved biomarker gene pair class predictor

The Top Scoring Pair (TSP) classifier, based on the concept of relative ranking reversals in the expressions of pairs of genes, has been proposed as a simple, accurate, and easily interpretable decision rule for classification and class prediction of gene expression profiles. The idea that differences in gene expression ranking are associated with presence or absence of disease is compelling and has strong biological plausibility. Nevertheless, the TSP formulation ignores significant available information which can improve classification accuracy and is vulnerable to selecting genes which do not have differential expression in the two conditions (“pivot" genes). We introduce the AUCTSP classifier as an alternative rank-based estimator of the magnitude of the ranking reversals involved in the original TSP. The proposed estimator is based on the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) and as such, takes into account the separation of the entire distribution of gene expression levels in gene pairs under the conditions considered, as opposed to comparing gene rankings within individual subjects as in the original TSP formulation. Through extensive simulations and case studies involving classification in ovarian, leukemia, colon, breast and prostate cancers and diffuse large b-cell lymphoma, we show the superiority of the proposed approach in terms of improving classification accuracy, avoiding overfitting and being less prone to selecting non-informative (pivot) genes. The proposed AUCTSP is a simple yet reliable and robust rank-based classifier for gene expression classification. While the AUCTSP works by the same principle as TSP, its ability to determine the top scoring gene pair based on the relative rankings of two marker genes across all subjects as opposed to each individual subject results in significant performance gains in classification accuracy. In addition, the proposed method tends to avoid selection of non-informative (pivot) genes as members of the top-scoring pair.
The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games

Multiplayer Online Battle Arena (MOBA) games have received increasing popularity recently. In a match of such games, players compete in two teams of five, each controlling an in-game avatar, known as heroes, selected from a roster of more than 100. The selection of heroes, also known as pick or draft, takes place before the match starts and alternates between the two teams until each player has selected one hero. Heroes are designed with different strengths and weaknesses to promote team cooperation in a game. Intuitively, heroes in a strong team should complement each other's strengths and suppress those of opponents. Hero drafting is therefore a challenging problem due to the complex hero-to-hero relationships to consider. In this paper, we propose a novel hero recommendation system that suggests heroes to add to an existing team while maximizing the team's prospect for victory. To that end, we model the drafting between two teams as a combinatorial game and use Monte Carlo Tree Search (MCTS) for estimating the values of hero combinations. Our empirical evaluation shows that hero teams drafted by our recommendation algorithm have a significantly higher win rate against teams constructed by other baseline and state-of-the-art strategies.
Future Directions in Father Inclusion, Engagement, Retention, and Positive Outcomes in Child and Adolescent Research

Fathers make important and unique contributions to positive child development. In spite of these findings, the research literature has lagged in the study of the role and impact of fathers on child development and in the development of effective approaches and interventions for fathers. Parameters for additional study include the inclusion of fathers in treatment outcome studies, the engagement of fathers within studies once included, the retention of fathers in interventions and studies once engaged, and the appropriate measurement of father-related outcomes. A systematic review of 64 studies indicated that there is evidence that fathers have been included within multiple studies aimed at improving parenting but that there are relatively fewer studies of other targeted outcomes such as coparenting. A set of recommendations for future directions in the next generation of father-focused studies in the child and adolescent psychology literature is presented, with an emphasis on improving study of the parameters of inclusion, engagement, retention, and measurement of outcomes.
A Developer-Friendly Library for Smart Home IoT Privacy-Preserving Traffic Obfuscation

The number and variety of Internet-connected devices have grown enormously in the past few years, presenting new challenges to security and privacy. Research has shown that network adversaries can use traffic rate metadata from consumer IoT devices to infer sensitive user activities. Shaping traffic flows to fit distributions independent of user activities can protect privacy, but this approach has seen little adoption due to required developer effort and overhead bandwidth costs. Here, we present a Python library for IoT developers to easily integrate privacy-preserving traffic shaping into their products. The library replaces standard networking functions with versions that automatically obfuscate device traffic patterns through a combination of payload padding, fragmentation, and randomized cover traffic. Our library successfully preserves user privacy and requires approximately 4 KB/s overhead bandwidth for IoT devices with low send rates or high latency tolerances. This overhead is reasonable given normal Internet speeds in American homes and is an improvement on the bandwidth requirements of existing solutions.
Corporate venture capital as a real option in the markets for technology

Research Summary: We apply real options (RO) theory to understand the role of corporate venture capital (CVC) investments and its relationship with internal RD engaging the markets for technology in distant technological fields; and, when their innovation pipeline is tilted toward the late‐stage development process. Finally, the licensing of high‐value technologies is the most likely form of option exercise when technological uncertainty is reduced post‐CVC. Managerial Summary: Despite the fact that one of the main goals of corporate venture capital (CVC) investments in high‐tech industries is to gain a window on future technologies, the relationship between CVC and other strategies used to acquire external technologies, such as licensing, has not been adequately explored. To address this gap, we formulate hypotheses about key drivers of the decision to make CVC investments as a wait‐and‐see strategy in the markets for technology (MFT) using a longitudinal dataset of global pharmaceutical firms and their biotech partners. We find that investors' scientific capabilities, technological domains, and research pipelines impact investors' decisions to make CVC investments prior to other MFT transactions. In our research setting, investors typically acquire high‐value technologies via licensing when technological uncertainty is reduced post‐CVC.
Differentially Private Change-Point Detection

The change-point detection problem seeks to identify distributional changes at an unknown change-point k* in a stream of data. This problem appears in many important practical settings involving personal data, including biosurveillance, fault detection, finance, signal detection, and security systems. The field of differential privacy offers data analysis tools that provide powerful worst-case privacy guarantees. We study the statistical problem of change-point problem through the lens of differential privacy. We give private algorithms for both online and offline change-point detection, analyze these algorithms theoretically, and then provide empirical validation of these results.
Polydopamine and eumelanin models in various oxidation states

We report a comprehensive ab initio structural investigation of more than 43 000 probable molecular structures of polydopamine (PDA) and eumelanin in various oxidation states. With the aid of a computational approach including a brute-force algorithmic generation of chemical isomers and density functional theory, all probable oxidized 5,6-dihydroxyindole (DHI) oligomers, ranging from dimers to tetramers, have been systematically generated and evaluated. We identify a set of the most stable molecular structures of PDA and eumelanin which represent the chemically diverse nature of these materials. Results show that more planar molecular structures have a tendency to be more stable. We also observe that, in some cases, forming cyclic molecular structures could reduce the energy of a DHI tetramer and make it more stable. This finding supports the hypothesis that cyclic molecules could exist in eumelanin-like materials. Additionally, the cyclic molecular models proposed in this work are energetically more favorable than the popular porphyrin-like models in this field.
Costs of energy efficiency mandates can reverse the sign of rebound

Abstract Improvements in energy efficiency reduce the cost of consuming services from household cars and appliances and can result in a positive rebound effect that offsets part of the direct energy savings. We use a general equilibrium model to derive analytical expressions that allow us to compare rebound effects from a costless technology shock (CTS) to those from a costly energy efficiency standard (EES). We decompose each total effect on the use of energy into a direct efficiency effect, direct rebound effect, and indirect rebound effect. We show which factors determine the sign and magnitude of each. Rebound from a CTS is generally positive, as in prior literature, but we also show how a pre-existing EES can negate the direct energy savings from the CTS – leaving only the positive rebound effect on energy use. Then we analyze increased stringency of an EES, and we show exactly when the increased costs reverse the sign of rebound. Using plausible parameter values in this model, we find that indirect effects can outweigh the direct effects captured in partial equilibrium models, and that the total rebound from a costly EES can be negative.
CURE-OR: Challenging Unreal and Real Environments for Object Recognition

In this paper, we introduce a large-scale, controlled, and multi-platform object recognition dataset denoted as Challenging Unreal and Real Environments for Object Recognition (CURE-OR). In this dataset, there are 1,000,000 images of 100 objects with varying size, color, and texture that are positioned in five different orientations and captured using five devices including a webcam, a DSLR, and three smartphone cameras in real-world (real) and studio (unreal) environments. The controlled challenging conditions include underexposure, overexposure, blur, contrast, dirty lens, image noise, resizing, and loss of color information. We utilize CURE-OR dataset to test recognition APIs—Amazon Rekognition and Microsoft Azure Computer Vision—and show that their performance significantly degrades under challenging conditions. Moreover, we investigate the relationship between object recognition and image quality and show that objective quality algorithms can estimate recognition performance under certain photometric challenging conditions. The dataset is publicly available at https://ghassanalregib.com/cure-or/ https://ghassanalregib.com/cure-or/.
WebRelate: Integrating Web Data with Spreadsheets using Examples

Data integration between web sources and relational data is a key challenge faced by data scientists and spreadsheet users. There are two main challenges in programmatically joining web data with relational data. First, most websites do not expose a direct interface to obtain tabular data, so the user needs to formulate a logic to get to different webpages for each input row in the relational table. Second, after reaching the desired webpage, the user needs to write complex scripts to extract the relevant data, which is often conditioned on the input data. Since many data scientists and end-users come from diverse backgrounds, writing such complex regular-expression based logical scripts to perform data integration tasks is unfortunately often beyond their programming expertise.
Are there long-term benefits from early childhood education in low- and middle-income countries?

We examine the relationship between participation in early childhood education (ECE) and various long-term outcomes: post-ECE educational attainment, the development of both cognitive and socioemotional skills, and labor market outcomes. The data are from the recent Skills Toward Employability and Productivity surveys of urban adults in 12 low- and middle-income countries. Using OLS regression and propensity score matching techniques, we find suggestive evidence of long-term benefits across countries, as well as mixed evidence within countries. Notably, we find positive and statistically significant associations between ECE participation and post-ECE educational attainment (a mean of 0.9 additional years across countries). We find relatively fewer cases of positive associations between ECE and long-term socioemotional outcomes. The evidence on ECE and labor market outcomes is varied, with positive associations for skill-use but weak associations with earnings. Such mixed results suggest that improvements in the quality of ECE programs are necessary for realizing the full range of long-term benefits.
Fat-Tailed Regression Modeling with Spliced Distributions

Insurance claims data usually contain a large number of zeros and exhibits fat-tail behavior. Misestimation of one end of the tail impacts the other end of the tail of the claims distribution and c...
A Multiagent System Approach to Scheduling Devices in Smart Homes.

Demand-side management (DSM) in the smart grid allows customers to make autonomous decisions on their energy consumption, helping energy providers to reduce the energy peaks in load demand. The automated scheduling of smart devices in residential and commercial buildings plays a key role in DSM. Due to data privacy and user autonomy, such an approach is best implemented through distributed multi-agent systems. This paper makes the following contributions: (i) It introduces the Smart Home Device Scheduling (SHDS) problem, which formalizes the device scheduling and coordination problem across multiple smart homes as a multi-agent system; (ii) It describes a mapping of this problem to a distributed constraint optimization problem; (iii) It proposes a distributed algorithm for the SHDS problem; and (iv) It presents empirical results from a physically distributed system of Raspberry Pis, each capable of controlling smart devices through hardware interfaces, as well as larger scale synthetic experiments.
From a Smoking Gun to Spent Fuel: Principled Subsampling Methods for Building Big Language Data Corpora from Monitor Corpora

With the influence of Big Data culture on qualitative data collection, acquisition, and processing, it is becoming increasingly important that social scientists understand the complexity underlying data collection and the resulting models and analyses. Systematic approaches for creating computationally tractable models need to be employed in order to create representative, specialized reference corpora subsampled from Big Language Data sources. Even more importantly, any such method must be tested and vetted for its reproducibility and consistency in generating a representative model of a particular population in question. This article considers and tests one such method for Big Language Data downsampling of digitally accessible language data to determine both how to operationalize this form of corpus model creation, as well as testing whether the method is reproducible. Using the U.S. Nuclear Regulatory Commission’s public documentation database as a test source, the sampling method’s procedure was evaluated to assess variation in the rate of which documents were deemed fit for inclusion or exclusion from the corpus across four iterations. After performing multiple sampling iterations, the approach pioneered by the Tobacco Documents Corpus creators was deemed to be reproducible and valid using a two-proportion z-test at a 99% confidence interval at each stage of the evaluation process–leading to a final mean rejection ratio of 23.5875 and variance of 0.891 for the documents sampled and evaluated for inclusion into the final text-based model. The findings of this study indicate that such a principled sampling method is viable, thus necessitating the need for an approach for creating language-based models that account for extralinguistic factors and linguistic characteristics of documents.
Molecular phylogenetics supports a clade of red algal parasites retaining native plastids: taxonomy and terminology revised

Parasitism is a life strategy that has repeatedly evolved within the Florideophyceae. Historically, the terms adelphoparasite and alloparasite have been used to distinguish parasites based on the relative phylogenetic relationship of host and parasite. However, analyses using molecular phylogenetics indicate that nearly all red algal parasites infect within their taxonomic family, and a range of relationships exist between host and parasite. To date, all investigated adelphoparasites have lost their plastid, and instead, incorporate a host-derived plastid when packaging spores. In contrast, a highly reduced plastid lacking photosynthesis genes was sequenced from the alloparasite Choreocolax polysiphoniae. Here we present the complete Harveyella mirabilis plastid genome, which has also lost genes involved in photosynthesis, and a partial plastid genome from Leachiella pacifica. The H. mirabilis plastid shares more synteny with free-living red algal plastids than that of C. polysiphoniae. Phylogenetic analysis demonstrates that C. polysiphoniae, H. mirabilis, and L. pacifica form a robustly supported clade of parasites, which retain their own plastid genomes, within the Rhodomelaceae. We therefore transfer all three genera from the exclusively parasitic family, Choreocolacaceae, to the Rhodomelaceae. Additionally, we recommend applying the terms archaeplastic parasites (formerly alloparasites), and neoplastic parasites (formerly adelphoparasites) to distinguish red algal parasites using a biological framework rather than taxonomic affiliation with their hosts.
Job Market Prospects of Breast vs. Prostate Cancer Survivors in the US: A Double Hurdle Model of Ethnic Disparities

Labor market presence of cancer survivors has been significantly improved as medical technology revolutionized cancer-specific diagnoses and treatments. However, less understood are post-cancer variations in job market outcomes of racial and ethnic minorities in the US. Using a theoretical framework derived from family labor supply decision models and taking advantage of the rich data in the 2008–2014 Medical Expenditure Panel Survey (MEPS), this study employs a double-hurdle empirical model of labor force participation and hours worked to evaluate the employment decisions of Black and Hispanic cancer survivors. Hispanic and Black breast cancer survivors were less likely to be employed by 4% and 7.5%, respectively, when compared with Whites. Black prostate cancer survivors were 8% less likely to work than Whites, with nonsignificant differences between Hispanic and White prostate cancer survivors. Once employed, Black and Hispanic breast cancer survivors worked an extra 4 and 6 h than Whites, while Hispanic prostate cancer survivors worked 5 fewer weekly hours than Whites. In addition, our estimates indicate the significance of job types in labor market outcomes post-cancer. Employment of minorities in blue collar or service occupations decreased employment hours of survivors. Labor market disparities for minorities amplifies the socio-economic and familial burden of cancers. This timely work motivates informed public policy to reduce unexamined consequences of chronic conditions among minorities.
Accounting-Based Regulation: Evidence from Health Insurers and the Affordable Care Act

The Patient Protection and Affordable Care Act (ACA) requires that insurers spend a minimum amount of their premium revenue on policyholder benefits. The Act specifies enforcement via a combination...
On the Market Timing of Hedging: Evidence from U.S. Oil and Gas Producers

Using a hand-collected data, we provide evidence of extensive use of commodity derivative in hedging among U.S. oil and gas producers. We find large variations in hedging intensity and hedging profits while on average they generate significant positive profits. The profits relate positively to the intensity of hedging. We further decompose the hedge ratio into two components: the pure hedging component and the market timing component. We find that the hedging profits relate strongly and positively to the market timing component. We also identify a group of firms that can consistently generate profits from their hedging activities. Among firms who actively change their hedging positions, the winners tend to be larger firms. The hedging outcome does not increase equity beta while the pure hedging component tends to decrease equity beta. The positive profits are exclusive for the commodity derivative transactions of the oil and gas producers, while they do not profit from their interest rate or foreign exchange derivative transactions.
Graph odometry

We address the problem of determining edge weights on a graph using non-backtracking closed walks from a vertex. We show that the weights of all of the edges can be determined from any starting vertex exactly when the graph has minimum degree at least three. We also determine the minimum number of walks required to reveal all edge weights.
A remote sensing look at the economy of a Russian region (Rostov) adjacent to the Ukrainian crisis

Abstract Satellite data used in combination with a stochastic production function method reveal an inefficient formal economy in rural Rostov Oblast 2013–2015 embedded in an overall (formal and informal) relatively efficient economy with the measurement of both important to better understand non-economic impacts of sanctions. Increased military activity may have insulated the formal economy of the border area from poor economic performance and the deindustrialization that characterizes adjacent areas. The current Oblast Administration’s grant program to localities does not reward relatively efficient economic performance with a model suggested here to change the policy. The region’s economy has the ability to absorb many Ukrainian refugees though non-economic issues support the current assistance from other Russian regions in helping relocate refugees beyond Rostov region. Like other conflict zones, urban areas experience less of an impact relative to rural areas.
Friends in low places: How peer advice and expected leadership feedback affect staff auditors’ willingness to speak up

Abstract Junior auditors collect the bulk of audit evidence, yet they do not always speak up to communicate potentially important audit issues. Such inappropriate “voice” decisions can endanger audit quality. We examine whether and how staff auditors influence each other in making voice decisions. First, a survey provides descriptive evidence that staff auditors consult their peers for advice on whether to speak up. Next, two experiments provide evidence that voice advice among peers at the staff level can be problematic. We find that staff auditors consistently underestimate the importance of raising issues compared to their supervisors, and they rely on social cues that are not diagnostic of issue importance in giving voice advice to peers. Finally, we predict and find that staff auditors tend to follow peer advice when it confirms their initial stance, and that an expectation of high (versus low) quality supervisor feedback increases their willingness to speak up. Most importantly, we find that contradictory peer advice only influences staff auditors’ willingness to speak up when leadership feedback is not expected to be of high quality. Together these results indicate that staff auditors seek out and follow voice advice from their peers, but appropriate leadership feedback practices can mitigate the negative impact of peer advice on upward communication.
Semiclassical dynamics and nonlinear charge current

Electron conductivity is an important material property that can provide a wealth of information about the underlying system. Especially, the response of the conductivity with respect to electromagnetic fields corresponds to various nonlinear charge currents, which have distinct symmetry requirements and hence can be used as efficient probes of different systems. To help the band-structure engineering of such nonlinear currents, a universal treatment of electron dynamics up to second order expressed in the basis of the unperturbed states are highly useful. In this work, we review the general semiclassical framework of the nonlinear charge currents.
Towards a Taxonomy of Idea Generation Techniques

Business organizations often need to manage creative work. An important way of promoting creative work is to use idea generation techniques (IGTs). Numerous IGTs have been developed, and choosing from such a big pool of candidates can be demanding, which is further complicated by the elusiveness of the mechanisms of these IGTs. This study aims at developing a taxonomy for IGTs based on their underlying mechanisms of supporting ideation. First, the current literature for the classification of IGTs is reviewed. Then some related creativity theories are consulted and a new classification system is proposed based on these theories and previous studies. Eighty seven IGTs are classified according to the system. The implications for research and practice are discussed.
Stability in matching markets with peer effects

Abstract The paper investigates conditions which guarantee the existence of a stable outcome in a school matching in the presence of peer effects. We consider an economy where students are characterized by their type and schools are characterized by their quality and capacity. We divide students and schools into groups, so that going to a school outside of one's group is associated with additional costs or prohibited. A student receives utility from a school per se and from one's classmates. We find that sufficient condition for a stable matching to exist is that a directed graph, which governs the possibility to go from one group to another, should not have (undirected) cycles. We construct a polynomial time algorithm, which produces a stable matching. Furthermore, we show that if the graph has a cycle, then there exist other economy parameters (types, costs and so on), so that no stable matching exists.
The Clinical Rationale for the Sentry Bioconvertible Inferior Vena Cava Filter for the Prevention of Pulmonary Embolism

The Sentry inferior vena cava (IVC) filter is designed to provide temporary protection against pulmonary embolism (PE) during transient high-risk periods and then to bioconvert after 60 days after implantation. At the time of bioconversion, the device’s nitinol arms retract from the filtering position into the caval wall. Subsequently, the stable stent-like nitinol frame is endothelialized. The Sentry bioconvertible IVC filter has been evaluated in a multicenter investigational-device-exemption pivotal trial ( NCT01975090 ) of 129 patients with documented deep vein thrombosis (DVT) or PE, or at temporary risk of developing DVT or PE, and with contraindications to anticoagulation. Successful filter conversion was observed in 95.7% of patients at 6 months (110/115) and 96.4% at 12 months (106/110). Through 12 months, there were no cases of symptomatic PE. The rationale for development of the Sentry bioconvertible device includes the following considerations: (1) the period of highest risk of PE for the vast majority of patients occurs within the first 60 days after an index event, with most of the PEs occurring in the first 30 days; (2) the design of retrievable IVC filters to support their removal after a transitory high-PE-risk period has, in practice, been associated with insecure filter dynamics and time-dependent complications including tilting, fracture, embolization, migration, and IVC perforation; (3) most retrievable IVC filters are placed for temporary protection, but for a variety of reasons they are not removed in any more than half of implanted patients, and when removal is attempted, the procedure is not always successful even with advanced techniques; and (4) analysis of Medicare hospital data suggests that payment for the retrieval procedure does not routinely compensate for expense. The Sentry device is not intended for removal after bioconversion. In initial clinical use, complications have been limited. Long-term results for the Sentry bioconvertible IVC filter are anticipated soon.
Roost selection by male northern long-eared bats (Myotis septentrionalis) in a managed fire-adapted forest

Abstract Wildlife conservation in multi-use landscapes requires identifying and conserving critical resources that may otherwise be destroyed or degraded by human activity. Summer day-roost sites are critical resources for bats, so conserving roost sites is a focus of many bat conservation plans. Studies quantifying day-roost characteristics typically focus on female bats due to their much stronger influence on reproductive success, but large areas of species’ ranges can be occupied predominantly by male bats due to sexual segregation. We used VHF telemetry to identify and characterize summer day-roost selection by male northern long-eared bats (Myotis septentrionalis) in a ponderosa pine (Pinus ponderosa) forest in South Dakota, USA. We tracked 18 bats to 43 tree roosts and used an information-theoretic approach to determine the relative importance of tree- and plot-level characteristics for roost site selection. Bats selected roost trees that were larger in diameter, more decayed, and under denser canopy than other trees available on the landscape. Much like studies of female northern long-eared bats have shown, protecting large-diameter snags within intact forest is important for the conservation of male northern long-eared bats. Unlike female-specific studies, however, many roosts in our study (39.5%) were located in short (≤3 m) snags. Protecting short snags may be a low-risk, high-reward strategy for conservation of resources important to male northern long-eared bats. Other tree-roosting bat species in fire-prone forests may benefit from forest management practices that promote these tree characteristics, particularly in high-elevation areas where populations largely consist of males.
Synthesis and Metal Ion Binding Studies of Enediyne-Containing Crown Ethers

The 3-ene-1,5-diyne crown ether 5 is a novel enediyne-containing crown ether that was designed as a model system for a class of enediynes that might undergo alkali metal ion-triggered Bergman cyclization. We report the preparation of 5 by two different routes. In the shorter and preferable route, a carbenoid coupling reaction is employed to simultaneously construct the enediyne moiety and effect a macrocyclization of an acyclic bis(propargyl)bromide 15 to the 24-membered crown ether 5. Under standard reaction conditions, this carbenoid coupling produces as the major product the isomeric 5-ene-1,3-diyne-crown ethers (Z)-16 and (E)-16. The formation of 5-ene-1,3-diynes from the carbenoid coupling of propargyl bromides is unprecedented. We present evidence that it is the polyether nature of dibromide 15 that leads to the formation of the 5-ene-1,3-diyne-crown ether products. Judicious control of the reaction conditions can be used to produce either 5 or (Z)-16 from 15 in synthetically useful yields. Both ene...
Invertible Universal Hashing and the TET Encryption Mode.

This work describes a mode of operation, TET, that turns a regular block cipher into a length-preserving enciphering scheme for messages of (almost) arbitrary length. When using an n-bit block cipher, the resulting scheme can handle input of any bit-length between n and 2 and associated data of arbitrary length. The mode TET is a concrete instantiation of the generic mode of operation that was proposed by Naor and Reingold, extended to handle tweaks and inputs of arbitrary bit length. The main technical tool is a construction of invertible “universal hashing” on wide blocks, which is as efficient to compute and invert as polynomial-evaluation hash.
Microwave-assisted synthesis utilizing supported reagents: a rapid and versatile synthesis of 1,5-diarylpyrazoles

The application of microwave heating to a silica-assisted solution-phase synthesis technique has been utilized to develop a rapid and efficient two-step protocol for the preparation of pyrazoles from aryl methyl ketone and aryl hydrazine monomers.