cssi/SciSciGPT-SciSciNet huggingface dataset:
Fully Threaded Tree for Adaptive Refinement Fluid Dynamics Simulations

A fully threaded tree (FTT) for adaptive refinement of regular meshes is described. By using a tree threaded at all levels, tree traversals for finding nearest neighbors are avoided. All operations on a tree including tree modifications are O(N), where N is a number of cells, and are performed in parallel. An efficient implementation of the tree is described that requires 2N words of memory. A filtering algorithm for removing high frequency noise during mesh refinement is described. A FTT can be used in various numerical applications. In this paper, it is applied to the integration of the Euler equations of fluid dynamics. An adaptive mesh time stepping algorithm is described in which different time steps are used at different l evels of the tree. Time stepping and mesh refinement are interleaved to avoid extensive buffer layers of fine mesh which were otherwise required ahead of moving shocks. Test examples are presented, and the FTT performance is evaluated. The three dimensional simulation of the interaction of a shock wave and a spherical bubble is carried out that shows the development of azimuthal perturbations on the bubble surface.
Geophysical potential for wind energy over the open oceans

Wind turbines continuously remove kinetic energy from the lower troposphere, thereby reducing the wind speed near hub height. The rate of electricity generation in large wind farms containing multiple wind arrays is, therefore, constrained by the rate of kinetic energy replenishment from the atmosphere above. In recent years, a growing body of research argues that the rate of generated power is limited to around 1.5 W m−2 within large wind farms. However, in this study, we show that considerably higher power generation rates may be sustainable over some open ocean areas. In particular, the North Atlantic is identified as a region where the downward transport of kinetic energy may sustain extraction rates of 6 W m−2 and above over large areas in the annual mean. Furthermore, our results indicate that the surface heat flux from the oceans to the atmosphere may play an important role in creating regions where sustained high rates of downward transport of kinetic energy and thus, high rates of kinetic energy extraction may be geophysical possible. While no commercial-scale deep water wind farms yet exist, our results suggest that such technologies, if they became technically and economically feasible, could potentially provide civilization-scale power.
Analytical approaches for optimal placement of distributed generation sources in power systems

Power system deregulation and the shortage of transmission capacities have led to increased interest in distributed generation (DG) sources. Proper location of DGs in power systems is important for obtaining their maximum potential benefits. This paper presents analytical methods to determine the optimal location to place a DG in radial as well as networked systems to minimize the power loss of the system. Simulation results are given to verify the proposed analytical approaches.
Creating nanoscale emulsions using condensation

Nanoscale emulsions are essential components in numerous products, ranging from processed foods to novel drug delivery systems. Existing emulsification methods rely either on the breakup of larger droplets or solvent exchange/inversion. Here we report a simple, scalable method of creating nanoscale water-in-oil emulsions by condensing water vapor onto a subcooled oil-surfactant solution. Our technique enables a bottom-up approach to forming small-scale emulsions. Nanoscale water droplets nucleate at the oil/air interface and spontaneously disperse within the oil, due to the spreading dynamics of oil on water. Oil-soluble surfactants stabilize the resulting emulsions. We find that the oil-surfactant concentration controls the spreading behavior of oil on water, as well as the peak size, polydispersity, and stability of the resulting emulsions. Using condensation, we form emulsions with peak radii around 100 nm and polydispersities around 10%. This emulsion formation technique may open different routes to creating emulsions, colloidal systems, and emulsion-based materials. Emulsions—stabilized mixtures of immiscible liquids—are found in many products, ranging from pharmaceuticals to food. Here Guha et al. propose a simple emulsification method where water vapor is condensed onto oil with surfactant, producing a water-in-oil emulsion with droplets as small as 100 nm.
Examining How Treatment Fidelity Is Supported, Measured, and Reported in K–3 Reading Intervention Research

Treatment fidelity data (descriptive and statistical) are critical to interpreting and generalizing outcomes of intervention research. Despite recommendations for treatment fidelity reporting from funding agencies and researchers, past syntheses have found treatment fidelity is frequently unreported (e.g., Swanson, The Journal of Special Education, 47, 3–13, 2011) in educational interventions and fidelity data are seldom used to analyze its relation to student outcomes (O’Donnell, Review of Educational Research, 78(1), 33–84, 2008). The purpose of this synthesis was to examine how treatment fidelity is supported, measured, and reported in reading intervention studies conducted with students at risk or with reading difficulties in grades K–3 from 1995 through 2015. All studies (k = 175) were coded to extract and classify information related to (a) the characteristics of the intervention study (e.g., publication year, research design); (b) treatment implementer training and support; (c) treatment fidelity data collection procedures, dimensions (i.e., adherence, quality, receipt, dosage, and differentiation), and levels of treatment fidelity data; and (d) the use of fidelity scores in the analysis of treatment effects. Results indicated that less than half (47%) of the reading intervention studies synthesized reported treatment fidelity data (numeric or narrative). Exploratory analyses showed that several study features were associated with the prevalence of fidelity reporting. Studies reporting treatment fidelity largely measured treatment adherence, and scores were, on average, high. Other dimensions of treatment fidelity (e.g., treatment differentiation), and analyses relating fidelity data to outcomes, were consistently absent from the corpus of reading intervention studies reviewed. Recommendations for enhancing how treatment fidelity data in intervention studies are collected and reported are presented.
Variant-based satisfiability in initial algebras

Abstract Although different satisfiability decision procedures can be combined by algorithms such as those of Nelson–Oppen or Shostak, current tools typically can only support a finite number of theories to use in such combinations. To make SMT solving more widely applicable one needs theory-generic satisfiability algorithms allowing a potentially infinite number of decidable theories to be user-definable, instead of needing to be built in by tool implementers. This work studies how folding variant narrowing, a generic unification algorithm that offers good extensibility in unification theory, can be extended to a generic variant-based satisfiability algorithm for the initial algebras of user-specified input theories when such theories satisfy Comon and Delaune's finite variant property (FVP) and some extra conditions. Several, increasingly larger infinite classes of theories whose initial algebras enjoy decidable variant-based satisfiability are identified and illustrated with examples. A method based on descent maps to bring other theories into these classes and to improve the generic algorithm's efficiency is also proposed.
TRADE, TECHNOLOGICAL CHANGE, AND WAGE INEQUALITY: THE CASE OF MEXICO

In the decade following the Mexico-U.S. trade integration, the manufacturing skill premium rose by almost 60 percent in Mexico and by only 12 percent in the U.S. Standard trade theory predicts that when countries with different levels of skilled labor integrate, the skill premium should fall - not rise - in the skill-scarce country. In this paper, I reconcile theory and data by building a model in which intermediate goods are produced using rented technology. After integration, producers in Mexico begin to rent technologies from the United States, which are more advanced and, hence, more skill-intensive. This has two effects: The skill premium in Mexico rises due to adoption of the more advanced technology and the skill premium in the U.S. rises due to increased investment in this technology, which is driven by the increased marginal return on technology arising from its adoption in Mexico. The mechanism is supported by industry-level evidence: Mexican industries which are integrated into the U.S. supply chain have higher skill premia than their non-integrated counterparts. The calibrated model can account for about two-thirds of the increase in the skill premium in each country.
Dangers of a double-bottom line? A poverty targeting experiment misses both targets

Two for-profit Philippine social enterprises, aiming to demonstrate corporate social responsibility by increasing microlending to the poor, incorporated a widely-used poverty measurement tool into their loan applications and tested the tool using randomized training content. Treated loan officers were instructed why and how to use the tool for targeting; control group training merely labelled the tool “additional household information”. The targeting training backfired, leading to no additional poor applicants and lower-performing loans. Descriptive evidence suggests the targeting training exacerbated loan officer misperceptions and multitasking problems. Our results help explain why corporate social responsibility efforts are often siloed from core operations.
Technology executives in the changing accounting information environment: Impact of IFRS adoption on CIO compensation

Abstract Accounting regulatory changes that affect the information technology (IT) infrastructure of firms have prompted Chief Information Officers (CIOs) to take the lead in aligning IT changes with new reporting requirements. This study investigates the associations between the mandatory adoption of International Financial Reporting Standards (IFRS) and CIO compensation. We find a significant increase in CIO compensation in the post-IFRS period, which is higher in non-IT firms than in IT firms. Moreover, pay is at a premium for CIOs equipped with more educational background in business. We discuss the implications of our study and offer suggestions for future research.
Learning directed acyclic graphs based on sparsest permutations

We consider the problem of learning a Bayesian network or directed acyclic graph (DAG) model from observational data. A number of constraint-based, score-based and hybrid algorithms have been developed for this purpose. For constraint-based methods, statistical consistency guarantees typically rely on the faithfulness assumption, which has been show to be restrictive especially for graphs with cycles in the skeleton. However, there is only limited work on consistency guarantees for score-based and hybrid algorithms and it has been unclear whether consistency guarantees can be proven under weaker conditions than the faithfulness assumption. In this paper, we propose the sparsest permutation (SP) algorithm. This algorithm is based on finding the causal ordering of the variables that yields the sparsest DAG. We prove that this new score-based method is consistent under strictly weaker conditions than the faithfulness assumption. We also demonstrate through simulations on small DAGs that the SP algorithm compares favorably to the constraintbased PC and SGS algorithms as well as the score-based Greedy Equivalence Search and hybrid MaxMin Hill-Climbing method. In the Gaussian setting, we prove that our algorithm boils down to finding the permutation of the variables with sparsest Cholesky decomposition for the inverse covariance matrix. Using this connection, we show that in the oracle setting, where the true covariance matrix is known, the SP algorithm is in fact equivalent to `0-penalized maximum likelihood estimation.
Housing Choice Under Borrowing Constraints

A dramatic decline in the maximum loan amount eligible for Federal Housing Administration (FHA) mortgage insurance in the Salt Lake City, Utah, metropolitan statistical area between 2013 and 2014 p...
Detecting, quantifying, and discriminating the mechanism of mosaic chromosomal aneuploidies using MAD-seq

Current approaches to detect and characterize mosaic chromosomal aneuploidy are limited by sensitivity, efficiency, cost, or the need to culture cells. We describe the mosaic aneuploidy detection by massively parallel sequencing (MAD-seq) capture assay and the MADSEQ analytical approach that allow low (<10%) levels of mosaicism for chromosomal aneuploidy or regional loss of heterozygosity to be detected, assigned to a meiotic or mitotic origin, and quantified as a proportion of the cells in the sample. We show results from a multi-ethnic MAD-seq (meMAD-seq) capture design that works equally well in populations of diverse racial and ethnic origins and how the MADSEQ analytical approach can be applied to exome or whole-genome sequencing data, revealing previously unrecognized aneuploidy or copy number neutral loss of heterozygosity in samples studied by the 1000 Genomes Project, cell lines from public repositories, and one of the Illumina Platinum Genomes samples. We have made the meMAD-seq capture design and MADSEQ analytical software open for unrestricted use, with the goal that they can be applied in clinical samples to allow new insights into the unrecognized prevalence of mosaic chromosomal aneuploidy in humans and its phenotypic associations.
Benchmarking costs of financial intermediation around the world

The costs of financial intermediation have important consequences for financial development. Using bank-level data for 160 countries during 2005-14, this paper analyzes the composition and sources of bank net interest margins. First, it uses an accounting decomposition framework to provide summary statistics on the size of net interest margins and highlight the cost and profit components in countries, regions, and income groups. Second, it uses regression analysis to examine the underlying bank-level, structural, macroeconomic, and institutional determinants of net interest margins. Finally, the paper uses the results of the econometric analysis to construct country-level bar charts of relative contributing factors to financial intermediation costs. The results provide evidence-based guidance on key areas of structural reforms to reduce the costs of financial intermediation.
A zonal level safety investigation of pedestrian crashes in Riyadh, Saudi Arabia

In the recent decade, walking has been encouraged as an active mode of transportation, which could reduce congestion and air pollution and also improve community health. However, pedestrians are mo...
Do Hybrid Firms Out-Provide Traditional Business Structures? An Examination of Prosocial Behavior in North Carolina Firms:

With the rise of social enterprises has come a push for formal hybrid legal forms. Hybrid structures formalize a for-profit model with a social mission but carry no tax benefits. Using the case of ...
Simulations of splashing high and low viscosity droplets

In this work, simulations are presented for low viscosity ethanol and high viscosity silicone oil droplets impacting on a dry solid surface at atmospheric and reduced ambient pressure. The simulations are able to capture both the effect of the ambient gas pressure and liquid viscosity on the droplet impact and breakup. The results suggest that at early times droplet impact and gas film behavior for both low and high viscosity liquids share the same physics. However, at later times, during liquid sheet formation and breakup, high and low viscosity liquids behave differently. These results explain why for both kinds of liquids the pressure effect can be observed, while at the same time different high and low viscosity splashing regimes have been identified experimentally.
Commons and Cognition

Garrett Hardin’s Tragedy of the Commons primarily concerns actions rather than thoughts. But he did famously describe the cognitive state of a hypothetical herder on a grassy field. With respect to the field and its other users, Hardin’s herder is both ignorant and indifferent; he coolly calculates that his best option is to take the full benefit of grazing his stock while suffering only a fraction of the cost — an action that contributes to the decimation of a common resource. While Hardin viewed the herder’s attitude as identical to that of actors in many other collective action situations, the work of other commons theorists suggests several different cognitive stances among such actors, largely depending on the scale of the commons issues they face. Thus participants in the Prisoner’s Dilemma (a very small commons) would appear to be dominated by distrust rather than the hypothetical herder’s ignorance or indifference. Participants in midsized commons — such as Hardin’s herders in real life — show some distrust, but also great knowledge and engagement in common pool management. Participants in the largest-scale commons issues are actually those most likely to exhibit the ignorance and indifference that Hardin attributed to the herder. This Article discusses the ways in which these different cognitive stances track the scale of collective action “tragedies” as described by major theorists and concludes with some observations about the cognitive aspects of climate change.
Defining adenoma detection rate benchmarks in average-risk male veterans.

Background and Aims Veterans have higher prevalence of colorectal neoplasia than non-veterans; however, it is not known whether specific Veterans Affairs (VA) adenoma detection rate (ADR) benchmarks are required. We compared ADRs of a group of endoscopists for colonoscopies performed at a VA center with their ADRs at a non-VA academic medical center. Methods This was a retrospective review of screening colonoscopies performed by endoscopists who practice at the Indianapolis VA and Indiana University (IU). Patients were average-risk men aged 50 years or older. ADR, proximal ADR, advanced ADR, and adenomas per colonoscopy were compared between IU and the VA groups. Results Six endoscopists performed screening colonoscopies at both locations during the study period (470 at IU vs 608 at the VA). The overall ADR was not significantly different between IU and the VA (58% vs 61%; P = .21). Advanced neoplasia detection rate (13% vs 17%; P = .46), proximal ADR (46% vs 47%; P = .31), and adenomas per colonoscopy (1.59 vs 1.84; P = .24) were not significantly different. There were no significant differences in cecal intubation rate (100% vs 99%; P = .13) or withdrawal time (10.9 vs 11.1 min; P = .28). In regression analysis, there was significant correlation between the attending-specific ADRs at IU and the VA (P = .041, r2 = 0.69). Conclusions In this study of average-risk men undergoing screening colonoscopies by the same group of endoscopists, the ADRs of VA and non-VA colonoscopies were not significantly different. This suggests that a VA-specific ADR target is not required for endoscopists with high ADRs.
Greedy and Evolutionary Algorithms for Mining Relationship-Based Access Control Policies

Abstract Relationship-based access control (ReBAC) provides a high level of expressiveness and flexibility that promotes security and information sharing. We formulate ReBAC as an object-oriented extension of attribute-based access control (ABAC) in which relationships are expressed using fields that refer to other objects, and path expressions are used to follow chains of relationships between objects. ReBAC policy mining algorithms have potential to significantly reduce the cost of migration from legacy access control systems to ReBAC, by partially automating the development of a ReBAC policy from an existing access control policy and attribute data. This paper presents two algorithms for mining ReBAC policies from access control lists (ACLs) and attribute data represented as an object model: a greedy algorithm guided by heuristics, and a grammar-based evolutionary algorithm. An evaluation of the algorithms on four sample policies and two large case studies demonstrates their effectiveness.
ON THE BEHAVIOR OF THE EXPECTATION-MAXIMIZATION ALGORITHM FOR MIXTURE MODELS

Finite mixture models are among the most popular statistical models used in different data science disciplines. Despite their broad applicability, inference under these models typically leads to computationally challenging non-convex problems. While the Expectation-Maximization (EM) algorithm is the most popular approach for solving these non-convex problems, the behavior of this algorithm is not well understood. In this work, we focus on the case of mixture of Laplacian (or Gaussian) distribution. We start by analyzing a simple equally weighted mixture of two single dimensional Laplacian distributions and show that every local optimum of the population maximum likelihood estimation problem is globally optimal. Then, we prove that the EM algorithm converges to the ground truth parameters almost surely with random initialization. Our result extends the existing results for Gaussian distribution to Laplacian distribution. Then we numerically study the behavior of mixture models with more than two components. Motivated by our extensive numerical experiments, we propose a novel stochastic method for estimating the mean of components of a mixture model. Our numerical experiments show that our algorithm outperforms the Naive EM algorithm in almost all scenarios.
No one is alone: Strategic complementarities, capacity utilization, growth, and distribution

Abstract A longstanding criticism to Keynesian and Kaleckian growth theories is the question: why would firms operating with underutilized capacity accumulate capital stock? Our answer hinges on firms’ utilization choices depending on their beliefs about the level of demand, as captured by aggregate utilization. In a simple growth and distribution model, we show that: (i) desired utilization is endogenous to beliefs; and (ii) the equilibrium utilization rate is inefficiently low. We then turn to different model closures to draw policy implications: (iii) with a Classical closure, equilibrium growth and profitability are both strictly below their efficient values; (iv) with a Kaldor/Pasinetti closure, the equilibrium labor share is strictly below the value corresponding to efficient utilization. Spending policies can be used to achieve the efficient outcome. Finally, we use state-by-sector BEA data to validate our hypothesis: estimation results provide strong and robust support for our model in the US.
The Lure of Incredible Certitude

Forthright characterization of scientific uncertainty is important in principle and in practice. Nevertheless, economists and other researchers commonly report findings with incredible certitude, reporting point predictions and estimates. To motivate expression of incredible certitude, economists suggest that researchers respond to incentives that make the practice tempting. This temptation is the ‘lure’ of incredible certitude. I appraise some of the rationales that observers may have in mind when they state that incredible certitude responds to incentives. I conclude that scientific expression of incredible certitude at most has appeal in limited contexts. It should not be a general practice.
Perspective: Will We Ever Know the Optimal Hgb Level in ESRD?

The determination of an optimal hemoglobin (Hgb) level in patients with ESRD requires a thorough assessment of the risks and benefits of the Hgb level itself and the therapy required to achieve it. The 1997 Dialysis Outcomes Quality Initiative anemia treatment guideline[1][1] recommended against
Learning Geo-Temporal Image Features.

We propose to implicitly learn to extract geo-temporal image features, which are mid-level features related to when and where an image was captured, by explicitly optimizing for a set of location and time estimation tasks. To train our method, we take advantage of a large image dataset, captured by outdoor webcams and cell phones. The only form of supervision we provide are the known capture time and location of each image. We find that our approach learns features that are related to natural appearance changes in outdoor scenes. Additionally, we demonstrate the application of these geo-temporal features to time and location estimation.
A sulfotransferase dosage-dependently regulates mouthpart polyphenism in the nematode Pristionchus pacificus

Polyphenism, the extreme form of developmental plasticity, is the ability of a genotype to produce discrete morphologies matched to alternative environments. Because polyphenism is likely to be under switch-like molecular control, a comparative genetic approach could reveal the molecular targets of plasticity evolution. Here we report that the lineage-specific sulfotransferase SEUD-1, which responds to environmental cues, dosage-dependently regulates polyphenism of mouthparts in the nematode Pristionchus pacificus. SEUD-1 is expressed in cells producing dimorphic morphologies, thereby integrating an intercellular signalling mechanism at its ultimate target. Additionally, multiple alterations of seud-1 support it as a potential target for plasticity evolution. First, a recent duplication of seud-1 in a sister species reveals a direct correlation between genomic dosage and polyphenism threshold. Second, inbreeding to produce divergent polyphenism thresholds resulted in changes in transcriptional dosage of seud-1. Our study thus offers a genetic explanation for how plastic responses evolve.
Stratigraphic control of landscape response to base-level fall, Young Womans Creek, Pennsylvania, USA

Abstract Landscapes are thought to respond to changes in relative base level through the upstream propagation of a boundary that delineates relict from adjusting topography. However, spatially-variable rock strength can influence the topographic expression of such transient landscapes, especially in layered rocks, where strength variations can mask topographic signals expected due to changes in climate or tectonics. Here, we analyze the landscape response to base-level fall in Young Womans Creek, a 220 km2 catchment on the Appalachian Plateau, USA underlain by gently folded Paleozoic sedimentary rocks. We measured in situ 10Be concentrations in stream sands from 17 nested watersheds, and used a spatially-distributed model of sediment and 10Be production to constrain a threefold increase in the rate of base-level fall propagating upstream from the catchment outlet. Using lidar topography and a nearby detailed stratigraphic section, we map the extent of continuous, blocky, resistant sandstone strata that act as a caprock overlying more easily erodible sandstones and siltstones. The caprock influences landscape response in two ways. First, it serves as a boundary between slowly eroding (11.5 m Myr−1), low-sloping (3–5°) areas of relict topography and lower, steeper portions of the landscape adjusting to base-level fall. Second, hillslopes supported by the overlying caprock are armored with coarse sediment and are significantly steeper (20–30°) than hillslopes where the caprock has been eroded (10°), despite having similar erosion rates (36 m Myr−1) and bedrock substrate. Our results illustrate how gently dipping, layered rocks engender complicated relationships between lithology, topography and erosion rate, highlighting the importance of understanding how rock material properties influence surface processes and landscape evolution.
Heteroresistance to the model antimicrobial peptide polymyxin B in the emerging Neisseria meningitidis lineage 11.2 urethritis clade: mutations in the pilMNOPQ operon.

Clusters of Neisseria meningitidis (Nm) urethritis among primarily heterosexual males in multiple US cities have been attributed to a unique non-encapsulated meningococcal clade (the US Nm urethritis clade, US_NmUC) within the hypervirulent clonal complex 11. Resistance to antimicrobial peptides (AMPs) is a key feature of urogenital pathogenesis of the closely related species, Neisseria gonorrhoeae. The US_NmUC isolates were found to be highly resistant to the model AMP, polymyxin B (PmB, MICs 64-256 µg ml-1 ). The isolates also demonstrated stable subpopulations of heteroresistant colonies that showed near total resistant to PmB (MICs 384-1024 µg ml-1 ) and colistin (MIC 256 µg ml-1 ) as well as enhanced LL-37 resistance. This is the first observation of heteroresistance in N. meningitidis. Consistent with previous findings, overall PmB resistance in US_NmUC isolates was due to active Mtr efflux and LptA-mediated lipid A modification. However, whole genome sequencing, variant analyses and directed mutagenesis revealed that the heteroresistance phenotypes and very high-level AMP resistance were the result of point mutations and IS1655 element movement in the pilMNOPQ operon, encoding the type IV pilin biogenesis apparatus. Cross-resistance to other classes of antibiotics was also observed in the heteroresistant colonies. High-level resistance to AMPs may contribute to the pathogenesis of US_NmUC.
Simultaneous Particle Image Velocimetry (Piv)-Schlieren Photography Of Fluid Flow In Liquid Induced By Plasma- Driven Interfacial Forces

Understanding the transport of plasma-derived reactive species into bulk liquid is crucial for effective plasma-based water purification and other environmental applications. Physical and chemical interactions at the plasma-liquid interface region drive flow in the bulk liquid. The mechanisms of such flow are not well-understood. A 2-D plasma-in-liquid apparatus is used to study this interface region to understand the plasma-driven fluid dynamics. Previous shadowgraphs showed density gradients in the bulk liquid, while particle image velocimetry (PIV) measurements showed velocity shear at the interface region. These measurements indicate the presence of fluid instabilities. Using simultaneous PIV-Schlieren photography, the interplay effect of such instabilities observed in the bulk liquid is investigated to better understand the plasma-driven forces at the interface.
Photon counting performance of amorphous selenium and its dependence on detector structure.

Photon counting detectors (PCD) have the potential to improve x-ray imaging; however, they are still hindered by high costs and performance limitations. By using amorphous selenium (a-Se), the cost of PCDs can be significantly reduced compared with modern crystalline semiconductors, and enable large-area deposition. We are developing a direct conversion field-shaping multiwell avalanche detector (SWAD) to overcome the limitation of low carrier mobility and low charge conversion gain in a-Se. SWAD’s dual-grid design creates separate nonavalanche interaction (bulk) and avalanche sensing (well) regions, achieving depth-independent avalanche gain. Unipolar time differential (UTD) charge sensing, combined with tunable avalanche gain in the well region allows for fast response and high charge gain. We developed a probability-based numerical simulation to investigate the impact of UTD charge sensing and avalanche gain on the photon counting performance of different a-Se detector configurations. Pulse height spectra (PHS) for 59.5 and 30 keV photons were simulated. We observed excellent agreement between our model and previously published PHS measurements for a planar detector. The energy resolution significantly improved from 33 keV for the planar detector to ∼7 keV for SWAD. SWAD was found to have a linear response approaching 200 kcps / pixel.
Effect of non-uniform flexibility on hydrodynamic performance of pitching propulsors

Many aquatic animals propel themselves efficiently through water by oscillating flexible fins. ese fins are, however, not homogeneously flexible, but instead their flexural stiffness varies along their chord and span. Here, we developed a low order model of these functionally-graded materials where the chordwise flexibility of the foil is modeled by one or two torsional springs along the chordline. The torsional spring structural model is then strongly coupled to a boundary element fluid model to simulate the fluid-structure interactions. We show that the effective flexibility of the combined fluid-structure system scales with the ratio of the added mass forces acting on the passive portion of the foil and the elastic forces defined by the torsional spring hinge. We further detail the dependency of the propulsive performance on the flexibility and location of the single torsional spring for a foil that is actively pitching about its leading edge. Our results show that increasing the flexion ratio by moving the spring away from the leading edge leads to enhanced propulsive efficiency, but compromises the thrust production. Proper combination of two flexible hinges, however, can result in a gain in both the thrust production and propulsive efficiency.
Scarcity of fresh water resources in the Ganges Delta of Bangladesh

Abstract Understanding the interdependency, availability, and accessibility of surface water and groundwater plays a major role in identifying and managing water security. The Ganges Delta in Bangladesh is a classic example of a water insecurity scenario in a transboundary river basin where concerns in quantity, quality, and timing of available water are producing disastrous conditions. This study examines surface water and groundwater uses and demands, seasonal availability, sustainability, and potential water security concerns. Human interventions that can influence seasonal water availability and shifting demands between surface water and groundwater are also examined. Surface water availability was analyzed using streamflow including the effects of upstream water diversions, rainfall, temperature, and evapotranspiration. Groundwater data was collected from 283 locations established by the Bangladesh Water Development Board. Total water storage anomaly data from the GRACE satellite (2002–2016) was analyzed to assess changes in groundwater availability. Both in situ and GRACE data show a significant declining trend in groundwater. Comparisons of groundwater recharge and withdrawal amounts in six different years (1983, 2009–2012, 2015) indicate an unsustainable water withdrawal condition. Irrigation is the largest sector of off-stream water use with total water withdrawal amounting to 31% for surface water and 68% for groundwater. The region’s domestic water use entirely depends on groundwater, which is problematic due to arsenic pollution. This study provides insight into the changes in surface water and groundwater resources and limitations to freshwater availability, thereby encouraging a better management strategy for water resources in the region.
Independence in randomizations

The randomization of a complete first-order theory T is the complete continuous theory TR with two sorts, a sort for random elements of models of T and a sort for events in an underlying atomless p...
The effects on anchoring of increasing quantities of disconfirming evidence

Anchoring has been shown to influence judgements in a wide variety of contexts, often in a dysfunctional manner (particularly when anchors are deemed unreliable). Identifying methods for mitigating the effects of anchors is important. Our experimental study utilises three abstract settings and arbitrary anchor values. We find strong anchoring effects in initial judgements. Providing disconfirming evidence of moderate helpfulness does, however, reduce the anchoring effects. Specifically, providing one or two items of disconfirming information is shown to have significant incremental benefits in reducing or even eliminating anchoring effects. However, surprisingly, providing three items of disconfirming information, in our setting, did not further reduce anchoring, suggesting some diminishing effect of additional evidence. This is consistent with prior research suggesting that individuals adjust until they are 'close enough', and then stop considering additional information. Our results have implications for a wide variety of judgement contexts, and the results are encouraging in suggesting that a relatively small quantity of disconfirming evidence could be sufficient for overcoming anchoring.
Rcs Phosphorelay Activation in Cardiolipin-Deficient Escherichia coli Reduces Biofilm Formation

Biofilm formation is a complex process that requires a number of transcriptional, proteomic, and physiological changes to enable bacterial survival. The lipid membrane presents a barrier to communication between the machinery within bacteria and the physical and chemical features of their extracellular environment, and yet little is known about how the membrane influences biofilm development. We found that depleting the anionic phospholipid cardiolipin reduces biofilm formation in Escherichia coli cells by as much as 50%. The absence of cardiolipin activates the regulation of colanic acid synthesis (Rcs) envelope stress response, which represses the production of flagella, disrupts initial biofilm attachment, and reduces biofilm growth. We demonstrate that a reduction in the concentration of cardiolipin impairs translocation of proteins across the inner membrane, which we hypothesize activates the Rcs pathway through the outer membrane lipoprotein RcsF. Our study demonstrates a molecular connection between the composition of membrane phospholipids and biofilm formation in E. coli and suggests that altering lipid biosynthesis may be a viable approach for altering biofilm formation and possibly other multicellular phenotypes related to bacterial adaptation and survival.IMPORTANCE There is a growing interest in the role of lipid membrane composition in the physiology and adaptation of bacteria. We demonstrate that a reduction in the anionic phospholipid cardiolipin impairs biofilm formation in Escherichia coli cells. Depleting cardiolipin reduced protein translocation across the inner membrane and activated the Rcs envelope stress response. Consequently, cardiolipin depletion produced cells lacking assembled flagella, which impacted their ability to attach to surfaces and seed the earliest stage in biofilm formation. This study provides empirical evidence for the role of anionic phospholipid homeostasis in protein translocation and its effect on biofilm development and highlights modulation of the membrane composition as a potential method of altering bacterial phenotypes related to adaptation and survival.
Output Feedback Boundary Control of a Heat PDE Sandwiched Between Two ODEs

We present designs for exponential stabilization of an ordinary differential equation (ODE)-heat partial differential equation (PDE)-ODE coupled system where the control actuation only acts in one ODE. The combination of PDE backstepping and ODE backstepping is employed in a state feedback control law and in an observer that estimates PDE and two ODE states using only one PDE boundary measurement. Based on the state feedback control law and the observer, the output feedback control law is then proposed. The exponential stability of the closed-loop system and the boundedness and exponential convergence of the control law are proved via Lyapunov analysis. Finally, numerical simulations validate the effectiveness of this method for the “sandwiched” system.
Do immigrants delay retirement and social security claiming

We use data from the Health and Retirement Study (HRS) to examine how immigrants’ retirement and Social Security claiming patterns compare to those of natives. We find that immigrants retire and cl...
CoRE kernels

The term "CoRE kernel" stands for correlation-resemblance kernel. In many real-world applications (e.g., computer vision), the data are often high-dimensional, sparse, and non-binary. We propose two types of (nonlinear) CoRE kernels for non-binary sparse data and demonstrate the effectiveness of the new kernels through a classification experiment. CoRE kernels are simple with no tuning parameters. However, training nonlinear kernel SVM can be costly in time and memory and may not be always suitable for truly large-scale industrial applications (e.g., search). In order to make the proposed CoRE kernels more practical, we develop basic probabilistic hashing (approximate) algorithms which transform nonlinear kernels into linear kernels.
The Inefficiency of the ECPR Yet Again: A Reply to Larson

We extend the results of our article, "Access and Interconnection Pricing? How Efficient Is the "Efficient Component Pricing Rule?," Antitrust Bulletin (1995). In the presence of a monopolized essential input, we show that application of the Efficient Component Pricing Rule ("ECPR") in pricing this input to downstream competitors perpetuates monopoly distortions and high prices of final goods services. We show these results for various demand conditions, including conditions that are accepted to hold in the telecommunications sector. We also respond to various criticisms raised by A. Larson in "The Efficiency of the Efficient-Component-Pricing Rule: A Comment," Antitrust Bulletin, (this issue) (1997).
Effects of inhibiting antioxidant pathways on cellular hydrogen sulfide and polysulfide metabolism.

Abstract Elaborate antioxidant pathways have evolved to minimize the threat of excessive reactive oxygen species (ROS) and to regulate ROS as signaling entities. ROS are chemically and functionally similar to reactive sulfur species (RSS) and both ROS and RSS have been shown to be metabolized by the antioxidant enzymes, superoxide dismutase and catalase. Here we use fluorophores to examine the effects of a variety of inhibitors of antioxidant pathways on metabolism of two important RSS, hydrogen sulfide (H2S with AzMC) and polysulfides (H2Sn, where n = 2–7, with SSP4) in HEK293 cells. Cells were exposed to inhibitors for up to 5 days in normoxia (21% O2) and hypoxia (5% O2), conditions also known to affect ROS production. Decreasing intracellular glutathione (GSH) with l -buthionine-sulfoximine (BSO) or diethyl maleate (DEM) decreased H2S production for 5 days but did not affect H2Sn. The glutathione reductase inhibitor, auranofin, initially decreased H2S and H2Sn but after two days H2Sn increased over controls. Inhibition of peroxiredoxins with conoidin A decreased H2S and increased H2Sn, whereas the glutathione peroxidase inhibitor, tiopronin, increased H2S. Aminoadipic acid, an inhibitor of cystine uptake did not affect either H2S or H2Sn. In buffer, the glutathione reductase and thioredoxin reductase inhibitor, 2-AAPA, the glutathione peroxidase mimetic, ebselen, and tiopronin variously reacted directly with AzMC and SSP4, reacted with H2S and H2S2, or optically interfered with AzMC or SSP4 fluorescence. Collectively these results show that antioxidant inhibitors, generally known for their ability to increase cellular ROS, have various effects on cellular RSS. These findings suggest that the inhibitors may affect cellular sulfur metabolism pathways that are not related to ROS production and in some instances they may directly affect RSS or the methods used to measure them. They also illustrate the importance of carefully evaluating RSS metabolism when biologically or pharmacologically attempting to manipulate ROS.
Disability and Distress: The Effect of Disability Programs on Financial Outcomes

We provide the first evidence on the relationship between disability programs and markers of financial distress: bankruptcy, foreclosure, eviction, and home sale. Rates of these adverse financial events peak around the time of disability application and subsequently fall for both allowed and denied applicants. To estimate the causal effect of disability programs on these outcomes, we use variation induced by an age-based eligibility rule and find that disability allowance substantially reduces the likelihood of adverse financial events. Within three years of the decision, the likelihood of bankruptcy falls by 0.81 percentage point (30 percent), and the likelihood of foreclosure and home sale among homeowners falls by 1.7 percentage points (30 percent) and 2.5 percentage points (20 percent), respectively. We find suggestive evidence of reductions in eviction rates. Conversely, the likelihood of home purchases increases by 0.86 percentage point (20 percent) within three years. We present evidence that these changes reflect true reductions in financial distress. In our model of optimal disability benefits, considering these extreme events increases optimal disability benefits and potentially shortens waiting times.
Predictive Bayesian selection of multistep Markov chains, applied to the detection of the hot hand and other statistical dependencies in free throws

Consider the problem of modelling memory effects in discrete-state random walks using higher-order Markov chains. This paper explores cross-validation and information criteria as proxies for a model's predictive accuracy. Our objective is to select, from data, the number of prior states of recent history upon which a trajectory is statistically dependent. Through simulations, I evaluate these criteria in the case where data are drawn from systems with fixed orders of history, noting trends in the relative performance of the criteria. As a real-world illustrative example of these methods, this manuscript evaluates the problem of detecting statistical dependencies in shot outcomes in free throw shooting. Over three National Basketball Association (NBA) seasons analysed, several players exhibited statistical dependencies in free throw hitting probability of various types-hot handedness, cold handedness and error correction. For the 2013-2014 to 2015-2016 NBA seasons, I detected statistical dependencies in 23% of all player-seasons. Focusing on a single player, in two of these three seasons, LeBron James shot a better percentage after an immediate miss than otherwise. Conditioning on the previous outcome makes for a more-predictive model than treating free throw makes as independent. When extended specifically to LeBron James' 2016-2017 season, a model depending on the previous shot (single-step Markovian) does not clearly beat a model with independent outcomes. An error-correcting variable length model of two parameters, where James shoots a higher percentage after a missed free throw than otherwise, is more predictive than either model.
Blind Group Testing

The main goal in group testing is to recover a small subset of defective items from a larger population while efficiently reducing the total number of (possibly noisy ) required tests/measurements. Under the assumption that the input-output statistical relationship (i.e., channel law) is known to the recovery algorithm, the fundamental as well as the computational limits of the group testing problem are relatively better understood than when these statistical relationships are unknown. Practical considerations, however, render this assumption inapplicable, and “blind” recovery/estimation procedures, independent of the input-output statistics, are desired. In this paper, we analyze the fundamental limits of a general noisy group testing problem, when this relationship is unknown. Specifically, in the first part of this paper, we propose an efficient scheme, based on the idea of separate-decoding of items (where each item is recovered separately), for which we derive sufficient conditions on the number of tests required for exact recovery. The difficulty in obtaining these conditions stems from the fact that we allow the number of defective items to grow with the population size, which in turn requires delicate concentration analysis of certain probabilities. Furthermore, we show that in several scenarios, our proposed scheme achieves the same performance as that of the corresponding non-blind recovery algorithm (where the input-output statistics are known), implying that the proposed blind scheme is robust/universal. Finally, in the second part of this paper, we propose also an inefficient combinatorial-based scheme (or, “joint-decoding”), for which we derive similar sufficient conditions.