cssi/SciSciGPT-SciSciNet huggingface dataset:
New Young Stars and Brown Dwarfs in the Upper Scorpius Association

To improve the census of the Upper Sco association (~11 Myr, ~145 pc), we have identified candidate members using parallaxes, proper motions, and color-magnitude diagrams from several wide-field imaging surveys and have obtained optical and infrared spectra of several hundred candidates to measure their spectral types and assess their membership. We also have performed spectroscopy on a smaller sample of previously known or suspected members to refine their spectral types and evidence of membership. We have classified 530 targets as members of Upper Sco, 377 of which lack previous spectroscopy. Our new compilation of all known members of the association contains 1631 objects. Although the census of Upper Sco has expanded significantly over the last decade, there remain hundreds of candidates that lack spectroscopy. The precise parallaxes and proper motions from the second data release of Gaia should extend down to substellar masses in Upper Sco, which will greatly facilitate the identification of the undiscovered members.
Tectonic patterns of shortening landforms in Mercury's northern smooth plains

Abstract Mercury's northern smooth plains are volcanically emplaced units characterized by ghost craters, volcanically buried impact basins, and thrust fault-related landforms. We analyzed the thrust fault-related landforms, traditionally categorized as lobate scarps and wrinkle ridges, within the northern plains in order to describe trends in how these landforms are organized and oriented and what style of deformation (either thin or thick-skinned) their map patterns represent. Our analysis also establishes geologic constraints for which global processes may have produced stresses contributing to these tectonic patterns. We mapped 4853 thrust fault-related landforms in the northern plains at a map scale of 1:1,000,000 using three MErcury Surface, Space, ENvironment, GEochemistry, and Ranging (MESSENGER) global monochrome mosaics. These landforms, described as curvi-linear asymmetric ridges, frequently occur in complex geometrical arrangements that are interpreted to share similar structural characteristics. We called these arrangements “compound landforms”. Like prior studies, we observed thrust faults to follow rims of buried craters. We also observed (1) sigmoidal rises bounded by fault-related landforms, (2) V-shaped rises composed of two landforms terminating at a single sharp point, (3) broad arcuate rises of nearly equal width, (4) parallel, evenly-spaced ridges, and (5) landforms showing alternation in direction of tectonic transport along strike. Respectively, we interpreted these landforms as transpressional uplifts, faults with sharply juxtaposing ramps, pop-up structures, fold and thrust belts, and antithetic fault intersections. By comparison with Earth analogues and patterns produced in numerical and physical models, our results suggest that deformation in the NSPs is thin-skinned. Orientation analysis showed that the northernmost landforms (90°–70°N) were predominantly oriented east–west while most of the landforms between 50° and 30°N were oriented north–south. Variations in orientation with latitude indicate that the growth of thrust fault-related landforms was influenced by sources of stress other than global contraction. If reorientation of the pole due to the formation of the Caloris basin impact did occur, the pattern of fault orientations indicates that geologic processes producing the pattern operated after reorientation.
Profiling and improving the duty-cycling performance of Linux-based IoT devices

Minimizing the energy consumption of Linux-based devices is an essential step towards their wide deployment in various IoT scenarios. Energy saving methods such as duty-cycling aim to address this constraint by limiting the amount of time the device is powered on. In this work we study and improve the amount of time a Linux-based IoT device is powered on to accomplish its tasks. We analyze the processes of system boot up and shutdown on two platforms, the Raspberry Pi 3 and Raspberry Pi Zero Wireless, and enhance duty-cycling performance by identifying and disabling time-consuming or unnecessary units initialized in the userspace. We also study whether SD card speed and SD card capacity utilization affect boot up duration and energy consumption. In addition, we propose Pallex, a parallel execution framework built on top of the systemd init system to run a user application concurrently with userspace initialization. We validate the performance impact of Pallex when applied to various IoT application scenarios: (1) capturing an image, (2) capturing and encrypting an image, (3) capturing and classifying an image using the k-nearest neighbor algorithm, and (4) capturing images and sending them to a cloud server. Our results show that system lifetime is increased by 18.3%, 16.8%, 13.9% and 30.2%, for these application scenarios, respectively.
When Investor Incentives and Consumer Interests Diverge: Private Equity in Higher Education

This paper studies how private equity buyouts create value in higher education, a sector with opaque product quality and intense government subsidy. With novel data on 88 private equity deals involving 994 schools, we show that buyouts lead to higher tuition and per-student debt. Exploiting loan limit increases, we find that private equity-owned schools better capture government aid. After buyouts, we observe lower education inputs, graduation rates, loan repayment rates, and earnings among graduates. Neither school selection nor student body changes fully explain the results. The results indicate that in a subsidized industry maximizing value may not improve consumer outcomes.
Atmospheric mass loss due to giant impacts: the importance of the thermal component for hydrogen-helium envelopes.

Systems of close-in super-Earths and mini-Neptunes display striking diversity in planetary bulk density and composition. Giant impacts are expected to play a role in the formation of many of these worlds. Previous works, focused on the mechanical shock caused by a giant impact, have shown that these impacts can eject large fractions of the planetary envelope, offering a partial explanation for the observed spread in exoplanet compositions. Here, we examine the thermal consequences of giant impacts, and show that the atmospheric loss caused by these effects can significantly exceed that caused by mechanical shocks for hydrogen-helium (H/He) envelopes. Specifically, when a giant impact occurs, part of the impact energy is converted into thermal energy, heating the rocky core and the envelope. We find that the ensuing thermal expansion of the envelope can lead to a period of sustained, rapid mass loss through a Parker wind, resulting in the partial or complete erosion of the H/He envelope. The fraction of the envelope mass lost depends on the planet's orbital distance from its host star and its initial thermal state, and hence age. Planets closer to their host stars are more susceptible to thermal atmospheric loss triggered by impacts than ones on wider orbits. Similarly, younger planets, with rocky cores which are still hot and molten from formation, suffer greater atmospheric loss. This is especially interesting because giant impacts are expected to occur 10-100 Myr after formation, at a time when super-Earths still retain significant internal heat from formation. For planets where the thermal energy of the core is much greater than the envelope energy, i.e. super-Earths with H/He envelope mass fractions roughly less than 8 per cent, the impactor mass required for significant atmospheric removal is M imp/Mp ~ μ/μc ~ 0.1, approximately the ratio of the heat capacities of the envelope and core. In contrast, when the envelope energy dominates the total energy budget, complete loss can occur when the impactor mass is comparable to the envelope mass.
Common Factors and Spatial Dependence: An Application to US House Prices

This paper considers panel data models with cross-sectional dependence arising from both spatial autocorrelation and unobserved common factors. It derives conditions for model identification and proposes estimation methods that employ cross-sectional averages as factor proxies, including the 2SLS, Best 2SLS, and GMM estimations. The proposed estimators are robust to unknown heteroskedasticity and serial correlation in the disturbances, unrequired to estimate the number of unknown factors, and computationally tractable. The paper establishes the asymptotic distributions of these estimators and compares their consistency and efficiency properties. Extensive Monte Carlo experiments lend support to the theoretical findings and demonstrate the satisfactory finite sample performance of the proposed estimators. The empirical section of the paper finds strong evidence of spatial dependence of real house price changes across 377 Metropolitan Statistical Areas in the US from 1975Q1 to 2014Q4. The results also reveal that population and income growth have significantly positive direct and spillover effects on house price changes. These findings are robust to different specifications of the spatial weights matrix constructed based on distance, migration flows, and pairwise correlations.
Adversarial Attacks on Stochastic Bandits

We study adversarial attacks that manipulate the reward signals to control the actions chosen by a stochastic multi-armed bandit algorithm. We propose the first attack against two popular bandit algorithms: $\epsilon$-greedy and UCB, \emph{without} knowledge of the mean rewards. The attacker is able to spend only logarithmic effort, multiplied by a problem-specific parameter that becomes smaller as the bandit problem gets easier to attack. The result means the attacker can easily hijack the behavior of the bandit algorithm to promote or obstruct certain actions, say, a particular medical treatment. As bandits are seeing increasingly wide use in practice, our study exposes a significant security threat.
Basilar Thumb Arthritis: The Utility of Suture-Button Suspensionplasty.

Background: We sought to compare the functional outcomes, radiographic outcomes, and complications of trapeziectomy and flexor carpi radialis (FCR) to abductor pollicis longus (APL) side-to-side te...
Adaptive Strategic Cyber Defense for Advanced Persistent Threats in Critical Infrastructure Networks

Advanced Persistent Threats (APTs) have created new security challenges for critical infrastructures due to their stealthy, dynamic, and adaptive natures. In this work, we aim to lay a game-theoretic foundation by establishing a multi-stage Bayesian game framework to capture incomplete information of deceptive APTs and their multistage multi-phase movement. The analysis of the perfect Bayesian Nash equilibrium (PBNE) enables a prediction of attacker's behaviors and a design of defensive strategies that can deter the adversaries and mitigate the security risks. A conjugate-prior method allows online computation of the belief and reduces Bayesian update into an iterative parameter update. The forwardly updated parameters are assimilated into the backward dynamic programming computation to characterize a computationally tractable and timeconsistent equilibrium solution based on the expanded state space. The Tennessee Eastman (TE) process control problem is used as a case study to demonstrate the dynamic game under the information asymmetry and show that APTs tend to be stealthy and deceptive during their transitions in the cyber layer and behave aggressively when reaching the targeted physical plant. The online update of the belief allows the defender to learn the behavior of the attacker and choose strategic defensive actions that can thwart adversarial behaviors and mitigate APTs. Numerical results illustrate the defender's tradeoff between the immediate reward and the future expectation as well as the attacker's goal to reach an advantageous system state while making the defender form a positive belief.
An Energy Packet Switch for Digital Power Grids

We propose the design of an energy packet switch for forwarding and delivery of energy in digital power grids in this paper. The proposed switch may receive energy from one or multiple power sources, store and forward it in the form of energy packets to requesting loads connected to one or multiple ports of the switch. Energy packets carry discrete amounts of energy for a finely controlled supply. Loads receive discrete amounts of energy through packets rather than a continuing and discretionary energy flow. Using energy packets may help manage the delivery of power in a more reliable, robust, and economical form than that used by the present power grid. The control and management of the proposed switch are based on a request-grant protocol. The switch uses a data network for the transmission of these requests and grants. The energy packet switch may be the centerpiece for creating infrastructure in the realization of the digital power grid. The design of the energy packet switch is based on shared supercapacitors to shape and manage discretization of energy. We introduce the design and analysis of the electrical properties of the proposed switch and describe the procedure used in the switch to determine the amount of energy transmitted to requesting loads.
A nonparametric projection-based estimator for the probability of causation, with application to water sanitation in Kenya.

Current estimation methods for the probability of causation (PC) make strong parametric assumptions or are inefficient. We derive a nonparametric influence-function-based estimator for a projection of PC, which allows for simple interpretation and valid inference by making weak structural assumptions. We apply our estimator to real data from an experiment in Kenya, which found, by estimating the average treatment effect, that protecting water springs reduces childhood disease. However, before scaling up this intervention, it is important to determine whether it was the exposure, and not something else, that caused the outcome. Indeed, we find that some children, who were exposed to a high concentration of bacteria in drinking water and had a diarrheal disease, would likely have contracted the disease absent the exposure since the estimated PC for an average child in this study is 0.12 with a 95% confidence interval of (0.11, 0.13). Our nonparametric method offers researchers a way to estimate PC, which is essential if one wishes to determine not only the average treatment effect, but also whether an exposure likely caused the observed outcome.
Increased Exposure to Environmental Hazards: An Opportunity for Science, Technology, Engineering, and Math Education

Abstract Current trajectories of federal environmental policy will likely increase the percentage of the population exposed and impacted by environmental hazards. This likely expansion will cross e...
3D imaging of gems and minerals by multiphoton microscopy

Many optical approaches have been used to examine the composition and structure of gemstones, both recently and throughout history. The nonlinear optical behavior of different gemstones has not been investigated, and the higher order terms to the refractive index represent an unused tool for qualifying and examining a stone. We have used a multiphoton microscope to examine the nonlinear optical properties of 36 different gemstones and demonstrate that it is a useful tool for imaging them three-dimensionally up to the millimeter scale below the sample surface. The polarization dependence of second harmonic generation signals was used to examine the crystal orientations inside the minerals.
A Bibliometric Study of Authorship and Collaboration Trends Over the Past 30 Years in Four Major Musculoskeletal Science Journals

This study explored changes in bibliometric variables over the last 30 years for four major musculoskeletal science journals (BONE®), Calcified Tissue International® (CTI®), Journal of Bone and Mineral Research® (JBMR®), and Journal of Orthopaedic Research® (JOR®), with a specific focus on author gender. Bibliometric data were collected for all manuscripts in 1985 (BONE®, CTI®, JOR®), 1986 (JBMR®), 1995, 2005, and 2015; 2776 manuscripts met inclusion criteria. Manuscripts from Europe were more often published in BONE® or CTI®, while those from North America in JBMR® or JOR®. All journals demonstrated an increase over time in the number of authors (3.67–7.3), number of countries (1.1–1.4), number of institutions (1.4–3.1), and number of references (25.1–45.4). The number of manuscript pages increased (6.6–8.9) except for JOR® which showed a decline. CTI® had the lowest number of authors (4.9 vs. 5.6–6.8). There was a change in the corresponding author position from first to last for all journals; this change was highest for CTI® (35%) and lowest for BONE® (14.0%). All journals demonstrated an increase over time in female authors; however, CTI® was the highest amongst these four journals. The percentage of female first authors rose from 24.6 to 44.3% (CTI® 29.1–52.3%). The percentage of corresponding female authors rose from 17.5 to 33.6% (CTI® 22.9–40.0%). The proportion of female authors is increasing, likely reflecting the increasing number of women obtaining doctorates in science, medicine, and engineering.
Infectious Disease Issues in Underserved Populations

Infectious disease has a major impact on the health outcomes of underserved populations and is reported at significantly higher rates among these populations compared with the general population. Overcoming barriers and obstacles to health care access is key to addressing the disparity regarding the prevalence of infectious disease. Enhancing cultural competency and educating practitioners about underserved populations' basic health needs; optimizing health insurance for the underserved; increasing community resources; and improving access to comprehensive, continuous, compassionate, and coordinated health care are strategies for diminishing the burden of infectious disease in underserved populations.
Automated Image Quality Evaluation of Structural Brain Magnetic Resonance Images using Deep Convolutional Neural Networks

Automated evaluation of image quality is essential to assure accurate diagnosis and effective patient management. This is particularly important for multi-center studies, typically employed in clinical trials, in which the data are acquired on different machines with different protocols. Visual quality assessment of magnetic resonance imaging (MRI) data is subjective and impractical for large datasets. Data-intensive deep learning methods such as convolutional neural networks (CNNs) are promising tools for processing large-scale imaging datasets for automated quality assessment. In this study, we evaluate a CNN-based method for quality assessment of the Autism Brain Imaging Data Exchange (ABIDE) structural brain MRI dataset acquired from 17 sites on more than a thousand subjects. The CNN architecture consisted of an input layer, four convolution layers, two fully connected layers, and an output layer. A balanced set of 348 image volumes was used in the study. 60% of the data was used for training, 15% for validation, and 25% for testing. The results of the automated approach were compared with the evaluation by the radiologist. Performance of the CNN was assessed using the confusion matrix. The concordance in image quality labels between the expert and CNN was 86% (sensitivity = 81%, specificity = 92%). The present study shows that the proposed model can evaluate the image quality of brain MRI with higher classification accuracy compared to previous state-of-the-art classical machine learning algorithms.
Structured multiprogramming

This paper presents a proposal for structured representation of multiprogramming in a high level language. The notation used explicitly associates a data structure shared by concurrent processes with operations defined on it. This clarifies the meaning of programs and permits a large class of time-dependent errors to be caught at compile time. A combination of critical regions and event variables enables the programmer to control scheduling of resources among competing processes to any degree desired. These concepts are sufficiently safe to use not only within operating systems but also within user programs.
The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting

Abstract How to measure the evolution of technology in order to predict innovations that grow rapidly? This study suggests a new perspective based on the theory of technological parasitism, which can measure and assess the dynamics of technological evolution for technological forecasting. In particular, the evolution of technology is modelled here in terms of interaction between a host technology (system) and a parasitic technology (subsystem). The coefficient of evolutionary growth of the model here indicates the evolution of parasitic technology in relation to host technology, suggesting the evolutionary pathway of overall system of technology over time (i.e., underdevelopment, growth and development). This approach is illustrated with realistic examples using empirical data of of product and process technologies: farm tractor, freight locomotive, electricity generation and smartphone technology. Overall, then, the proposed model, based on the theory of technological parasitism, can be useful for bringing a new perspective to explain and generalize properties of the evolution of technology and predict which innovations are likely to evolve rapidly in society.
Health needs of refugees: port of arrival versus permanent camp settings.

Background The world's refugee population has surpassed 21 million, the large majority of which resides in developing countries. Refugees have relatively high rates of healthcare utilization for management of both long-term needs, such as diabetes, and acute conditions, such as scabies. Aims Using interviews of stakeholders in disparate healthcare settings, we aim to elucidate both common themes and areas of difference that should be recognized and addressed as the refugee crisis continues. Methods This qualitative interview study compares and contrasts two settings for healthcare provision for refugees: the permanent setting of Za'atari, a camp in Jordan, versus the transitory arrival location of Lampedusa, Italy. Results We present data from 12 semi-structured interviews with experts in refugee healthcare that have experience in these two locations. We focus on issues of disease burden and health screening, organizational structures and services, cultural competency, and international response. Conclusions We compiled recommendations to improve healthcare for refugees include recognizing differing health needs of refugees in Za'atari and Lampedusa, training providers in culturally-competent care, screening for and treating psychiatric disorders, and prioritizing agency coordination, documentation, and advocacy.
Generalizability Theory: Overview

Generalizability (G) theory is a statistical theory for evaluating the dependability (reliability) of behavioral measurements. G theory estimates multiple sources of measurement error and permits decision makers to design a measurement procedure that minimizes error. Keywords: dependability; generalizability theory; reliability
Chapter 1 – RNA and the Cellular Biochemistry Revisited

This chapter focuses on the forms and functions of ribonucleic acid (RNA) and its transcription. RNA is a long, unbranched polymer of ribonucleoside monophosphate moieties joined together by phosphodiester linkages, and both eukaryotic and prokaryotic RNAs are essentially single-stranded molecules. RNA molecules are produced by the process of transcription, the process by which a single-stranded RNA molecule is synthesized from a specific chromosome locus. There are important organizational differences in associated with genes and the ensuing RNA molecule that results from the transcription when comparing prokaryotic and eukaryotic organisms. The synthesis of RNA is mediated by the activity of enzymes known as RNA polymerases. These transcripts observed within a cell are traditionally classified as ribosomal RNA (rRNA), transfer RNA (tRNA), heterogeneous nuclear RNA (hnRNA), or messenger RNA (mRNA). Important new classes of RNA have been discovered, including microRNA (miRNA), circular RNA (circRNA), and noncoding RNA (ncRNA). The mRNA subpopulation drives the phenotype of the cell, although it is the least abundant of all transcript types and the expression of which is tightly coupled to the expression of other regulatory transcripts.
Paying to Program? Engineering Brand and High-Tech Wages

We test the hypothesis that information technology (IT) workers accept a compensating differential to work with emerging IT systems and that employers that invest in these systems can, in turn, cap...
Cycling usage and frequency determinants in college campuses

Abstract This study explores the cycling usage and frequency determinants in college campuses located in the Baltimore Metropolitan Area. The study discerns the attitudes of individuals toward the proposed infrastructure and environmental improvements with the goal of promoting biking to campus. We develop a structural equation model (SEM) using the travel information of 780 individuals, which was collected between December 2014 and June 2015. The results indicate risk factors have a higher explanatory value on bike-to-campus frequency than campus infrastructure and program. We further examine how and to what extent mixed populations on college campuses respond to latent factors. The findings pinpoint that males are less concerned about the risk-related indicators such as theft and road and environment-related obstacles such as poor road conditions. However, females have a positive attitude toward campus-related improvements such as pro-bike programs. Overall, students show a negative attitude toward the road and environmentally-related obstacles compared to staff and faculty. Minority groups, specifically African American and Asian, show a positive attitude toward campus-related improvements, unlike white participants. The findings can assist planners and advocates in implementing effective policy measures to increase bike-to-campus frequency.
Rheological Properties of Liquids Under Conditions of Elastohydrodynamic Lubrication

There is an ongoing debate concerning the best rheological model for liquid flows in elastohydrodynamic lubrication (EHL). Due to the small contact area and high relative velocities of bounding solids, the lubricant experiences pressures in excess of 500 MPa and strain rates that are typically $$10^5{-}10^7\,\text {s}^{-1}$$ . The high pressures lead to a dramatic rise in Newtonian viscosity $$\eta _{N}$$ and the high rates lead to large shear stresses and pronounced shear thinning. This paper presents detailed simulations of a model EHL fluid, squalane, using nonequilibrium molecular dynamics methods to extract the scaling of its viscosity with shear rate ( $$10^5{-}10^{10}\,\text {s}^{-1}$$ ) over a wide range of pressure P (0.1 MPa to 1.2 GPa), and temperature T ( $$150{-}373$$ K). Simulation results are consistent with a broad range of equilibrium and nonequilibrium experiments. At high T and low P, where $$\eta _{N}$$ is low, the response can be fit to a power law, as in the common Carreau model. Shear thinning becomes steeper as $$\eta _{N}$$ increases, and for $$\eta _{N}\gtrsim 1$$ Pa s, shear thinning is consistent with the thermally activated flow assumed by another common model, Eyring theory. Simulations for a bi-disperse Lennard–Jones (LJ) system show that the transition from Carreau to Eyring is generic. For both squalane and the LJ system, the viscosity decreases by only about a decade in the Carreau regime, but may fall by many orders of magnitude in the Eyring regime. Shear thinning is often assumed to reflect changing molecular alignment, but the alignment of squalane molecules saturates after the viscosity has dropped by only about a factor of three. In contrast, thermal activation describes shear thinning by six or more decades in viscosity. Changes in the diagonal elements of the stress tensor with rate and shear stress are also studied.
Why Do User Communities Matter for Strategy

User communities represent a unique organizing structure for the exchange of ideas and knowledge. They are organizations composed primarily of users working collaboratively, voluntarily, and with minimal oversight to freely and openly develop and exchange knowledge around a common artifact. The prevalence of user communities appears to be on the rise, as evidenced by communities across a variety of fields ranging from software to Legos to sports equipment. In this essay, we discuss how firms can benefit from working with user communities––that is, we discuss the opportunities for firms to leverage user communities as a source of open innovation. We theorize the conditions under which user communities will emerge and function, and discuss the benefits that user communities can provide and the challenges they can create for firms, thereby illustrating the relevance and import of user communities to firms and the strategic management literature.
Continuous Glucose Monitoring Predicts Progression to Diabetes in Autoantibody Positive Children.

Context Accurate measures are needed for the prediction and diagnosis of type 1 diabetes (T1D) in at-risk persons. Objective The purpose of this study was to explore the value of continuous glucose monitoring (CGM) in predicting T1D onset. Design and setting The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children at increased risk for development of islet autoantibodies (islet autoantibody positive; Ab+) and T1D. Participants We analyzed 23 Ab+ participants with available longitudinal CGM data. Main outcome measure CGM metrics as glycemic predictors of progression to T1D. Results Of 23 Ab+ participants with a baseline CGM, 8 progressed to diabetes at a median age of 13.8 years during a median follow-up of 17.7 years (interquartile range, 14.6 to 22.0 years). Compared with nonprogressors, participants who progressed to diabetes had significantly increased baseline glycemic variability (SD, 29 vs 21 mg/dL; P = 0.047), daytime sensor average (122 vs 106 mg/dL; P = 0.02), and daytime sensor area under the curve (AUC, 470,370 vs 415,465; P = 0.047). They spent 24% of time at >140 mg/dL and 12% at >160 mg/dL compared with, respectively, 8% and 3% for nonprogressors (both P = 0.005). A receiver-operating characteristic curve analysis showed an AUC of 0.85 for percentage of time spent at >140 or 160 mg/dL. The cutoff of 18% time spent at >140 mg/dL had 75% sensitivity, 100% specificity, and a 100% positive predictive value for diabetes prediction, although these values could change because some nonprogressors may develop diabetes with longer follow-up. Conclusions Eighteen percent or greater CGM time spent at >140 mg/dL predicts progression to diabetes in Ab+ children.
Dynamic pricing with fairness concerns and a capacity constraint

Although some firms use dynamic pricing to respond to demand fluctuations, other firms claim that fairness concerns prevent them from raising prices during periods when demand exceeds capacity. This paper explores conditions in which fairness concerns can or cannot cause shortages. In our model, a firm announces a price policy that states its prices during high and low demand, and customers must travel to a venue to learn the current price. We show that the interaction of fairness concerns with travel costs can cause the firm to set stable prices, which leads to shortages during high demand. However, if the firm is able to inform customers about the current price before they incur any travel costs, then dynamic pricing with no shortages is optimal even with strong fairness concerns.
Self-administered questionnaire to screen for polycystic ovarian syndrome

Background: Polycystic ovary syndrome (PCOS) is a common yet underdiagnosed endocrinopathy with potentially serious sequelae. A screening questionnaire for PCOS can improve early identification and...
Out-of-Pocket Expenditures on Health: A Global Stocktake

This paper provides an overview of research on out-of-pocket health expenditures by reviewing the various summary measures and the results of multi-country studies using these measures. The paper p...
An inquiry into the nature and causes of Climate Wealth of Nations: What temperature finance gravitates towards? Sketching a climate-finance nexus and outlook on climate change-induced finance prospects

What is the optimal temperature finance gravitates towards? While we have empirical evidence for the optimal cardinal temperature for GDP production and international development links external climate conditions to levels of societal development, no literature exists on climate-induced-finance flows. Research on temperature-dependent financial flows holds invaluable insights in light of climate change. The connection between climate change and finance will be drawn via price mechanisms. Given the extinction potential of crops, industry and service production, price mechanism will be prospected with a hyperbolic tilt towards the end of durability and the closeness to extinction. In contrast to classical and standard approaches in economics to determine prices, the following research thereby takes into account that agents in their behavior can be constrained by shrinking timeframes for production in light of global warming. The contemporary attention to global warming and climate shocks is thereby assumed to affect the price expectations and hence actual market prices of commodities. Paying attention to supply and demand side perspectives, inflated prices surrounding scarcity will be first modelled and then back-tested on data about prices in commodities of food and beverages. Future wealth of nations will be introduced by the concept of climate flexibility defined as the range of temperature variation of a country. So far, a broad spectrum of climate zones has not been defined as asset but climate change will require territories being more flexible in terms of changing economic production. The more climate variation a nation state possesses, this paper argues, the more degrees of freedom a country has in terms of GDP production capabilities in a differing climate. These preliminary insights aid in answering what financial patterns can we expect given predictions the earth will become hotter. Already now this paper presents human capital flows and financial market inflows into areas that are winning economically from a warming globe. The degree of climate flexibility is found to be related to human migration inflow.
Studies toward the synthesis of 3,7β,8α-Trihydroxy-9α, 10α-epoxy-7,8,9,10-tetrahydrobenzo[a]pyrene, a reactive metabolite of benzo[a]pyrene

Abstract Synthesis of 3,7β,8α-Trihydroxy-9α, 10α-epoxy-7,8,9,10-tetrahydrobenzo[a]pyrene by saponification of its 3-acetoxy analogue and by oxidation of 3,7α,8β-trihydroxy-7,8-dihydrobenzo[a]pyrene with dimethyldioxirane is investigated.
Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes

Four gene expression subtypes of high-grade serous ovarian cancer (HGSC) have been previously described. In these early studies, a fraction of samples that did not fit well into the four subtype classifications were excluded. Therefore, we sought to systematically determine the concordance of transcriptomic HGSC subtypes across populations without removing any samples. We created a bioinformatics pipeline to independently cluster the five largest mRNA expression datasets using k-means and nonnegative matrix factorization (NMF). We summarized differential expression patterns to compare clusters across studies. While previous studies reported four subtypes, our cross-population comparison does not support four. Because these results contrast with previous reports, we attempted to reproduce analyses performed in those studies. Our results suggest that early results favoring four subtypes may have been driven by the inclusion of serous borderline tumors. In summary, our analysis suggests that either two or three, but not four, gene expression subtypes are most consistent across datasets.
Proteomics of phosphorylation and protein dynamics during fertilization and meiotic exit in the Xenopus egg

Fertilization releases the meiotic arrest and initiates the events that prepare the egg for the ensuing developmental program. Protein degradation and phosphorylation are known to regulate protein activity during this process. However, the full extent of protein loss and phosphoregulation is still unknown. We examined absolute protein and phosphosite dynamics of the fertilization response by mass spectrometry-based proteomics in electroactivated eggs. To do this, we developed an approach for calculating the stoichiometry of phosphosites from multiplexed proteomics that is compatible with dynamic, stable, and multisite phosphorylation. Overall, the data suggest that degradation is limited to a few low-abundance proteins. However, this degradation promotes extensive dephosphorylation that occurs over a wide range of abundances during meiotic exit. We also show that eggs release a large amount of protein into the medium just after fertilization, most likely related to the blocks to polyspermy. Concomitantly, there is a substantial increase in phosphorylation likely tied to calcium-activated kinases. We identify putative degradation targets and components of the slow block to polyspermy. The analytical approaches demonstrated here are broadly applicable to studies of dynamic biological systems.
Algebraic Pseudorandom Functions with Improved Efficiency from the Augmented Cascade.

We construct an algebraic pseudorandom function (PRF) that is more efficient than the classic NaorReingold algebraic PRF. Our PRF is the result of adapting the cascade construction, which is the basis of HMAC, to the algebraic settings. To do so we define an augmented cascade and prove it secure when the underlying PRF satisfies a property called parallel security. We then use the augmented cascade to build new algebraic PRFs. The algebraic structure of our PRF leads to an efficient large-domain Verifiable Random Function (VRF) and a large-domain simulatable VRF.
F-FDN: Federation of Fog Computing Systems for Low Latency Video Streaming

Video streaming is growing in popularity and has become the most bandwidth-consuming Internet service. As such, robust streaming in terms of low latency and uninterrupted streaming experience, particularly for viewers in distant areas, has become a challenge. The common practice to reduce latency is to pre-process multiple versions of each video and use Content Delivery Networks (CDN) to cache videos that are popular in a geographical area. However, with the fast-growing video repository sizes, caching video contents in multiple versions on each CDN is becoming inefficient. Accordingly, in this paper, we propose the architecture for Fog Delivery Networks (FDN) and provide methods to federate them (called F-FDN) to reduce video streaming latency. In addition to caching, FDNs have the ability to process videos in an on-demand manner. F-FDN leverages cached contents on the neighboring FDNs to further reduce latency. In particular, F-FDN is equipped with methods that aim at reducing latency through probabilistically evaluating the cost benefit of fetching video segments either from neighboring FDNs or by processing them. Experimental results against alternative streaming methods show that both on-demand processing and leveraging cached video segments on neighboring FDNs can remarkably reduce streaming latency (on average 52%).
Copper-Catalyzed Tandem Conjugate Addition-Electrophilic Trapping: Ketones, Esters, and Nitriles as Terminal Electrophiles

Exposure of enone substrates 1a-18a, which possess appendant ketone, ester, and nitrile moieties, to Et2Zn in the presence of catalytic Cu(OTf)2/P(OEt)3 provides the cyclized products in good to excellent yields and diastereoselectivities. These results represent the first use of ketones, esters, and nitriles as terminal electrophiles in Cu-catalyzed conjugate addition-electrophilic trapping.
The diastereoselective influences of remote substituents on enolate alkylations

Abstract The methylation of a series of γ-oxygenated ketones enolates ( 3 ) has been examined with the result that poor to outstanding levels of diastereoselectivity are observed that appear to be predictably consistent with a general model for asymmetric electrophilic addition reactions.
Structural assignment of 2,3,7,8‐tetrahydro‐5H,10H‐[1,5,3]dioxazepino[3,2‐c]indolo[3,2‐g]pteridin‐7‐one, a New heterocyclic ring system

The structure of a new heterocyclic ring system, 2,3,7,8-tetrahydro-5H,10H-[1,5,3]dioxazepino[3,2-c]-indolo[3,2-g]pteridin-7-one, derived from isatins and 5-aminocytidine was assigned by establishing the regiochemistry with the aid of model reactions and 13C nmr techniques.
Finitary isomorphisms of some infinite entropy Bernoulli flows

A consequence of Ornstein theory is that the infinite entropy flows associated with Poisson processes and continuous-time irreducible Markov chains on a finite number of states are isomorphic as measure-preserving systems. We give an elementary construction of such an isomorphism that has an additional finitariness property, subject to the additional conditions that the Markov chain has a uniform holding rate and a mixing skeleton.
Barcode identification for single cell genomics

Single-cell sequencing experiments use short DNA barcode ‘tags’ to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes. Here we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Our approach is based on the observation that circularizing a barcode sequence can yield error-free k-mers even when the size of k is large relative to the length of the barcode sequence, a regime which is typical single-cell barcoding applications. This allows for assignment of reads to consensus fingerprints constructed from k-mers. We show that for single-cell RNA-Seq circularization improves the recovery of accurate single-cell transcriptome estimates, especially when there are a high number of errors per read. This approach is robust to the type of error (mismatch, insertion, deletion), as well as to the relative abundances of the cells. Sircel, a software package that implements this approach is described and publically available.
IMPROVED SYNTHESIS OF O-BENZENEDISULFONIMIDE

(1998). IMPROVED SYNTHESIS OF O-BENZENEDISULFONIMIDE. Organic Preparations and Procedures International: Vol. 30, No. 1, pp. 107-109.
A macrocyclic amide from dehydrochlorination of indole-3-carbonyl chloride

Indolyl-3-ketene 3 was generated from two precursors and was found to form a symmetrical tetramer 4 consisting of a sixteen-membered ring amide. The tetramer was characterized by mass spectrometry, infrared, 1 H and 13 C-nmr spectroscopy, and single crystal X-ray crystallography
Synthesis of 2′,3′-dideoxy-3′-hydroxymethylcytidine; a unique antiviral nucleoside

Abstract The synthesis of 2′,3′-dideoxy-3′-hydroxymethylcytidine 1 was accomplished using two different approaches. First, uridine and cytidine were used to prepare the key intermediate epoxides 15 and 31 which were opened with cyanide, deoxygenated by elimination to vinyl nitriles 17 and 36, and reduced by 1,4 hydride addition to the saturated nitriles 18 and 37. Secondly, a novel Rh-catalyzed hydroformylation reaction of 2′,3′-didehydro-2′,3′-dideoxycytidine 46 was used to prepare 1 in four steps. The attempted use of 2′-deoxyuridine and 2′-deoxycytidine to prepare 1 is also discussed.
Estimating relatedness between malaria parasites

Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent. Estimates based on IBS are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on IBD. To generate estimates with errors below an arbitrary threshold of 0.1, we recommend ∼100 polyallelic or 200 biallelic markers. Marker requirements are immediately applicable to haploid malaria parasites and other haploid eukaryotes. C.I.s facilitate comparison when different marker sets are used. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology. We hope it will provide a basis for statistically informed prospective study design and surveillance strategies.
New Reactions of Quaternary Ammonium Salts Derived from Vinamidinium Salt Reduction Products and A Reassignment of Structure

Abstract The structure of a vinamidinium salt reduction product is revised and some reactions of related allylic ammonium salts with sulfur nucleophiles is presented.
Global and local excitation and inhibition shape the dynamics of the cortico-striatal-thalamo-cortical pathway

The cortico-striatal-thalamo-cortical (CSTC) pathway is a brain circuit that controls movement execution, habit formation and reward. Hyperactivity in the CSTC pathway is involved in obsessive compulsive disorder (OCD), a neuropsychiatric disorder characterized by the execution of repetitive involuntary movements. The striatum shapes the activity of the CSTC pathway through the coordinated activation of two classes of medium spiny neurons (MSNs) expressing D1 or D2 dopamine receptors. The exact mechanisms by which balanced excitation/inhibition (E/I) of these cells controls the network dynamics of the CSTC pathway remain unclear. Here we use non-linear modeling of neuronal activity and bifurcation theory to investigate how global and local changes in E/I of MSNs regulate the activity of the CSTC pathway. Our findings indicate that a global and proportionate increase in E/I pushes the system to states of generalized hyper-activity throughout the entire CSTC pathway. Certain disproportionate changes in global E/I trigger network oscillations. Local changes in the E/I of MSNs generate specific oscillatory behaviors in MSNs and in the CSTC pathway. These findings indicate that subtle changes in the relative strength of E/I of MSNs can powerfully control the network dynamics of the CSTC pathway in ways that are not easily predicted by its synaptic connections.
Design of a cleavable linker for the synthesis of a cis-syn pyrimidine photodimer.

Abstract The stereospecific synthesis of a cis -syn pyrimidine photodimer has been achieved using a cleavable linker. Removal of the linker is accomplished via bromine addition followed by a dual retro-Michael reaction.