cssi/SciSciGPT-SciSciNet huggingface dataset:
CHURCH AUTONOMY, SEXUAL ORIENTATION, AND EMPLOYMENT POLICY IN BRITAIN: A LEGISLATIVE HISTORY OF THE EMPLOYMENT PROVISIONS OF THE EQUALITY ACT 2010

How much autonomy should religious institutions have when they employ paid staff? This paper lays out two contrasting models, blanket liberalism and liberal pluralism, that come into play in this area. It then examines in some detail how Parliament dealt with the issue as it considered the Equality Act 2010, especially as the law pertained to sexual orientation. Although the Labour government would have liked to have pushed the country more toward blanket liberalism, in the end it left the law as it was, which was a victory, for the moment at least, for those churches who wished to retain their present degree of autonomy.
Structural Change in West Africa : A Tale of Gain and Loss

Economic growth in Benin, Burkina Faso, and Cote d'Ivoire occurred in tandem with a rapid exodus of labor out of agriculture. This paper investigates the contribution (or lack thereof) of within- and between-sector productivity changes to overall productivity growth and output per capita growth since 2000. Productivity growth was relatively significant in Burkina Faso, modest in Benin, and in the negative territory in Cote d'Ivoire. The results show that static structural change drove growth in Burkina Faso and Benin, although it was partly offset by a dynamic loss in Benin. However, structural change made a smaller contribution in Cote d'Ivoire. Within-sector productivity loss generally held back growth. The pattern of structural change observed in Benin, Burkina Faso, and Cote d'Ivoire starkly contrasts with that of Asia, where within-sector productivity gains were preponderant and dynamic structural change was the norm rather than the exception. The bulk of Benin, Burkina Faso, and Cote d'Ivoire's displaced agricultural workers moved into still-low productivity service activities, as is typical of the African sample.
Inhibition of Cyanobacterial Growth on a Municipal Wastewater Sidestream Is Impacted by Temperature

ABSTRACT Sidestreams in wastewater treatment plants can serve as concentrated sources of nutrients (i.e., nitrogen and phosphorus) to support the growth of photosynthetic organisms that ultimately serve as feedstock for production of fuels and chemicals. However, other chemical characteristics of these streams may inhibit growth in unanticipated ways. Here, we evaluated the use of liquid recovered from municipal anaerobic digesters via gravity belt filtration as a nutrient source for growing the cyanobacterium Synechococcus sp. strain PCC 7002. The gravity belt filtrate (GBF) contained high levels of complex dissolved organic matter (DOM), which seemed to negatively influence cells. We investigated the impact of GBF on physiological parameters such as growth rate, membrane integrity, membrane composition, photosystem composition, and oxygen evolution from photosystem II. At 37°C, we observed an inverse correlation between GBF concentration and membrane integrity. Radical production was also detected upon exposure to GBF at 37°C. However, the dose-dependent relationship between the GBF concentration and the lack of membrane integrity was abolished at 27°C. Immediate resuspension of strains in high levels of GBF showed markedly reduced oxygen evolution rates relative to those seen with the control. Taken together, the data indicate that one mechanism responsible for GBF toxicity to Synechococcus is the interruption of photosynthetic electron flow and subsequent phenomena. We hypothesize that this is likely due to the presence of phenolic compounds within the DOM. IMPORTANCE Cyanobacteria are viewed as promising platforms to produce fuels and/or high-value chemicals as part of so-called “biorefineries.” Their integration into wastewater treatment systems is particularly interesting because removal of the nitrogen and phosphorus in many wastewater streams is an expensive but necessary part of wastewater treatment. In this study, we evaluated strategies for cultivating Synechococcus sp. strain PCC 7002 on media comprised of two wastewater streams, i.e., treated secondary effluent supplemented with the liquid fraction extracted from sludge following anaerobic digestion. This strain is commonly used for metabolic engineering to produce a variety of valuable chemical products and product precursors (e.g., lactate). However, initial attempts to grow PCC 7002 under otherwise-standard conditions of light and temperature failed. We thus systematically evaluated alternative cultivation conditions and then used multiple methods to dissect the apparent toxicity of the media under standard cultivation conditions.
Habits Are Negatively Regulated by Histone Deacetylase 3 in the Dorsal Striatum.

Abstract Background Optimal behavior and decision making result from a balance of control between two strategies, one cognitive/goal-directed and one habitual. These systems are known to rely on the anatomically distinct dorsomedial and dorsolateral striatum, respectively. However, the transcriptional regulatory mechanisms required to learn and transition between these strategies are unknown. Here we examined the role of one chromatin-based transcriptional regulator, histone modification via histone deacetylases (HDACs), in this process. Methods We combined procedures that diagnose behavioral strategy in rats with pharmacological and viral-mediated HDAC manipulations, chromatin immunoprecipitation, and messenger RNA quantification. Results The results indicate that dorsal striatal HDAC3 activity constrains habit formation. Systemic HDAC inhibition following instrumental (lever press → reward) conditioning increased histone acetylation throughout the dorsal striatum and accelerated habitual control of behavior. HDAC3 was removed from the promoters of key learning-related genes in the dorsal striatum as habits formed with overtraining and with posttraining HDAC inhibition. Decreasing HDAC3 function, either by selective pharmacological inhibition or by expression of dominant-negative mutated HDAC3, in either the dorsolateral striatum or the dorsomedial striatum accelerated habit formation, while HDAC3 overexpression in either region prevented habit. Conclusions These results challenge the strict dissociation between dorsomedial striatum and dorsolateral striatum function in goal-directed versus habitual behavioral control and identify dorsostriatal HDAC3 as a critical molecular directive of the transition to habit. Because this transition is disrupted in many neurodegenerative and psychiatric diseases, these data suggest a potential molecular mechanism for the negative behavioral symptoms of these conditions and a target for therapeutic intervention.
Inorganic carbon addition stimulates snow algae primary productivity.

Earth has experienced glacial/interglacial oscillations accompanied by changes in atmospheric CO2 throughout much of its history. Today over 15 million square kilometers of Earth’s land surface is covered in ice including glaciers, ice caps, and ice sheets. Glaciers are teeming with life and supraglacial snow and ice surfaces are often darkened by the presence of photoautotrophic snow algae, resulting in accelerated melt due to lowered albedo. Few studies report the productivity of snow algal communities and the parameters which constrain their growth on supraglacial surfaces—key factors for quantifying biologically induced albedo effects (bio-albedo). We demonstrate that snow algae primary productivity is stimulated by the addition of inorganic carbon. Our results indicate a positive feedback between increasing CO2 and snow algal primary productivity, underscoring the need for robust climate models of past and present glacial/interglacial oscillations to include feedbacks between supraglacial primary productivity, albedo, and atmospheric CO2.
Melting behavior of n-alkanes in anodic aluminum oxide (AAO) nanopores using Flash differential scanning calorimetry

Abstract Flash differential scanning calorimetry is used to study nanoconfinement effects on the melting and solid–solid transitions of n-hexadecane (C16H34) and n-nonadecane (C19H40) in an anodic aluminum oxide (AAO) nanoporous membrane with pore diameters of 20 and 55 nm. The size-dependent melting behavior of n-hexadecane (C16) was investigated as a function of pore fullness from underfilled to overfilled. A comparison between the bulk, underfilled, and overfilled pores indicates a melting point depression (ΔTm) of 4.20 ± 0.60 °C in 55 nm AAO pores and 6.01 ± 0.24 °C in 20 nm AAO pores, independent of pore fullness. Nanoconfined n-nonadecane (C19), shows a melting point depression of 2.46 ± 0.40 °C and 4.2 ± 0.51 °C in 55 and 20 nm AAO pores, and its solid–solid transition is depressed by 1.94 ± 0.15 °C and 3.01 ± 0.29 °C in 55 and 20 nm AAO pores, respectively. The size-dependent melting behavior (ΔTm vs 1/d) for both C16 and C19 was found not to extrapolate to the bulk melting point at infinite pore size, indicating that a different crystal structure, perhaps a nematocrystalline state may be formed in AAO nanopores, as backed up by X-ray diffraction.
Automated assessment of steatosis in murine fatty liver

Although mice are commonly used to study different aspects of fatty liver disease, currently there are no validated fully automated methods to assess steatosis in mice. Accurate detection of macro- and microsteatosis in murine models of fatty liver disease is important in studying disease pathogenesis and detecting potential hepatotoxic signature during drug development. Further, precise quantification of macrosteatosis is essential for quantifying effects of therapies. Here, we develop and validate the performance of automated classifiers built using image processing and machine learning methods for detection of macro- and microsteatosis in murine fatty liver disease and study the correlation of automated quantification of macrosteatosis with expert pathologist’s semi-quantitative grades. The analysis is performed on digital images of 27 Hematoxylin & Eosin stained murine liver biopsy samples. An expert liver pathologist scored the amount of macrosteatosis and also annotated macro- and microsteatosis lesions on the biopsy images using a web-application. Using these annotations, supervised machine learning and image processing techniques, we created classifiers to detect macro- and microsteatosis. For macrosteatosis prediction, the model’s precision, sensitivity and area under the receiver operator characteristic (AUROC) were 94.2%, 95%, 99.1% respectively. When correlated with pathologist’s semi-quantitative grade of steatosis, the model fits with a coefficient of determination value of 0.905. For microsteatosis prediction, the model has precision, sensitivity and AUROC of 79.2%, 77%, 78.1% respectively. Validation by the expert pathologist of classifier’s predictions made on unseen images of biopsy samples showed 100% and 63% accuracy for macro- and microsteatosis, respectively. This novel work demonstrates that fully automated assessment of steatosis is feasible in murine liver biopsies images. Our classifier has excellent sensitivity and accuracy for detection of macrosteatosis in murine fatty liver disease.
RC 4000 software: multiprogramming system

The RC 4000 multiprogramming system consists of a monitor program that can be extended with a hierarchy of operating systems to suit diverse requirements of program scheduling and resource allocation. This manual defines the functions of the monitor and the basic operating system, which allows users to initiate and control parallel program execution from typewriter consoles. The excerpt reprinted here is the general description of the philosophy and structure of the system. This part will be of interest to anyone wishing an understanding of the system in order to evaluate its possibilities and limitations without going into details about exact conventions. The discussion treats the hardware structure of the RC 4000 only in passing.
Atomistic study of the electronic contact resistivity between the half-Heusler alloys (HfCoSb, HfZrCoSb, HfZrNiSn) and the metal Ag

Half-Heusler (HH) alloys have shown promising thermoelectric properties in the medium- and high-temperature range. To harness these material properties for thermoelectric applications, it is important to realize electrical contacts with low electrical contact resistivity. However, little is known about the detailed structural and electronic properties of such contacts and the expected values of contact resistivity. Here, we employ atomistic ab initio calculations to study electrical contacts in a subclass of HH alloys consisting of the compounds HfCoSb, HfZrCoSb, and HfZrNiSn. By using Ag as a prototypical metal, we show that the termination of the HH material critically determines the presence or absence of strong deformations at the interface. Our study includes contacts to doped materials, and the results indicate that the $p$-type materials generally form ohmic contacts while the $n$-type materials have a small Schottky barrier. We calculate the temperature dependence of the contact resistivity in the low- to medium-temperature range and provide quantitative values that set lower limits for these systems.
The bankruptcy problem in financial networks

Abstract The bankruptcy problem of resolving a single debt owed to multiple creditors is extended to financial networks, where there are multiple debtors and creditors.
The Weather Conditions for Desired Smoke Plumes at a FASMEE Burn Site

Weather is an important factor that determines smoke development, which is essential information for planning smoke field measurements. This study identifies the synoptic systems that would favor to produce the desired smoke plumes for the Fire and Smoke Model Evaluation Experiment (FASMEE). Daysmoke and PB-Piedmont (PB-P) models are used to simulate smoke plume evolution during the day time and smoke drainage and fog formation during the nighttime for hypothetical prescribed burns on 5–8 February 2011 at the Stewart Army Base in the southeastern United States. Daysmoke simulation is evaluated using the measured smoke plume heights of two historical prescribed burns at the Eglin Air Force Base. The simulation results of the hypothetical prescribed burns show that the smoke plume is not fully developed with low plume height during the daytime on 5 February when the burn site is under the warm, moist, and windy conditions connected to a shallow cyclonic system and a cold front. However, smoke drainage and fog are formed during the nighttime. Well-developed smoke plumes, which rise mainly vertically, extend to a majority portion of the planetary boundary layer, and have steady clear boundaries, appear on both 6 and 7 February when the air is cool but dry and calm during a transition between two low-pressure systems. The plume rises higher on the second day, mainly due to lighter winds. The smoke on 8 February shows a loose structure of large horizontal dispersion and low height after passage of a deep low-pressure system with strong cool and dry winds. Smoke drainage and fog formation are rare for the nights during 5–8 February. It is concluded that prescribed burns conducted during a period between two low-pressure systems would likely generate the desired plumes for FASMEE measurement during daytime. Meanwhile, as the fire smolders into the night, the burns would likely lead to fog formation when the burn site is located in the warm and moist section of a low-pressure system or a cold front.
Language Model Supervision for Handwriting Recognition Model Adaptation

Not all languages and domains of handwriting have large labeled datasets available for training handwriting recognition (HWR) models. One way to address this problem is to leverage high resource languages to help train models for low resource languages. In this work, we adapt HWR models trained on a source language to a target language that uses the same writing script. We do so using only labeled data in the source language, unlabeled data in the target language, and a language model in the target language. The language model is used to produce target transcriptions to allow regular example based training. Using this approach we demonstrate improved transferability among French, English, and Spanish languages using both historical and modern handwriting datasets.
Optimal voltage for nanoparticle detection with thin nanopores

The resistive-pulse technique provides a fast and label-free method for nanoparticle detection. To achieve higher sensitivity, thin nanopores such as silicon nitride nanopores are usually considered. In this study, nanoparticle detection has been mimicked with simulations. We found that the surface charges of particles can significantly affect current blockade in short pores, particularly under high electric fields. For particles with surface charge densities higher than -0.02 C m-2, current blockade ratios depend closely on the applied voltage. From our simulation results, an optimal voltage can be found for particle detection, at which the current blockade ratio does not depend on the surface charge density of the particle. This optimal voltage was obtained from the balance of current increase and decrease caused by cations and anions, respectively, due to negative surface charges of the particles. From this systematic study, the optimal voltage was found to represent a property of the system that only depends on the electrolyte type. We think our findings can provide some help for accurate particle detection in experiments.
The Sequential Scale-Up of an Evidence-Based Intervention: A Case Study

Policy makers face dilemmas when choosing a policy, program, or practice to implement. Researchers in education, public health, and other fields have proposed a sequential approach to identifying interventions worthy of broader adoption, involving pilot, efficacy, effectiveness, and scale-up studies. In this article, we examine a scale-up of an early math intervention to the state level, using a cluster randomized controlled trial. The intervention, Pre-K Mathematics, has produced robust positive effects on children’s math ability in prior pilot, efficacy, and effectiveness studies. In the current study, we ask if it remains effective at a larger scale in a heterogeneous collection of pre-K programs that plausibly represent all low-income families with a child of pre-K age who live in California. We find that Pre-K Mathematics remains effective at the state level, with positive and statistically significant effects (effect size on the Early Childhood Longitudinal Study, Birth Cohort Mathematics Assessment...
Gaps in the Heart Failure Guidelines

There are still many aspects of heart failure care for which gaps remain in the evidence base, resulting in gaps in the guidelines. We aim to highlight these guideline gaps including areas that warrant further research and other areas where new data are forthcoming.
The Quantum Gravity Dynamics of Near Extremal Black Holes

We study the quantum effects of Near-Extremal black holes near their horizons. The gravitational dynamics in such backgrounds are closely connected to a particle in AdS2 with constant electric field. We use this picture to solve the theory exactly. We will give a formula to calculate all correlation functions with quantum gravity backreactions as well as the exact Wheeler-DeWitt wavefunction. Using the WdW wavefunction, we investigate the complexity growth in quantum gravity.
The Economic Consequences of Audit Firms’ Quality Control System Deficiencies

This study seeks to determine the role of audit firms’ quality control (QC) system deficiencies, as measured by the Public Company Accounting Oversight Board (PCAOB) inspection program, on audit qu...
Optimal Transmission Using a Self-Sustained Relay in a Full-Duplex MIMO System

This paper investigates wireless information and power transfer in a full-duplex MIMO relay channel where the self-sustained relay harvests energy from both source transmit signal and self-interference signal to decode and forward source information to a destination. We formulate a new problem to jointly optimize power splitting at the relay and precoding design for both the source and relay transmissions. Using duality theory, we establish closed-form optimal primal solutions in terms of the dual variables, based on which we then design a customized and efficient primal-dual algorithm to maximize the achievable throughput. Numerical results demonstrate the rate gains from using multiple transmit and receive antennas in both information decoding and energy harvesting, and the significant benefit of harvesting energy from self-interference signals. We also extend our analysis to the case when channel state information is only available at receiving nodes and show how our algorithm can optimize the power splitting at the relay for it to remain self-sustained. Through analysis and simulation, we demonstrate that an optimal combination of non-uniform power splitting, variable power allocation, and self-interference power harvesting can effectively exploit a full-duplex MIMO system to achieve significant performance gains over existing uniform power splitting and half-duplex transmissions.
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms

Alternating direction method of multiplier (ADMM) is a powerful method to solve decentralized convex optimization problems. In distributed settings, each node performs computation with its local data and the local results are exchanged among neighboring nodes in an iterative fashion. During this iterative process the leakage of data privacy arises and can accumulate significantly over many iterations, making it difficult to balance the privacy-utility tradeoff. In this study we propose Recycled ADMM (R-ADMM), where a linear approximation is applied to every even iteration, its solution directly calculated using only results from the previous, odd iteration. It turns out that under such a scheme, half of the updates incur no privacy loss and require much less computation compared to the conventional ADMM. We obtain a sufficient condition for the convergence of R-ADMM and provide the privacy analysis based on objective perturbation.
Sparsemax and Relaxed Wasserstein for Topic Sparsity

Topic sparsity refers to the observation that individual documents usually focus on several salient topics instead of covering a wide variety of topics, and a real topic adopts a narrow range of terms instead of a wide coverage of the vocabulary. Understanding this topic sparsity is especially important for analyzing user-generated web content and social media, which are featured in the form of extremely short posts and discussions. As topic sparsity of individual documents in online social media increases, so does the difficulty of analyzing the online text sources using traditional methods. In this paper, we propose two novel neural models by providing sparse posterior distributions over topics based on the Gaussian sparsemax construction, enabling efficient training by stochastic backpropagation. We construct an inference network conditioned on the input data and infer the variational distribution with the relaxed Wasserstein (RW) divergence. Unlike existing works based on Gaussian softmax construction and Kullback-Leibler (KL) divergence, our approaches can identify latent topic sparsity with training stability, predictive performance, and topic coherence. Experiments on different genres of large text corpora have demonstrated the effectiveness of our models as they outperform both probabilistic and neural methods.
Do share-of-income limits on tax-deductibility of charitable contributions affect giving?

Abstract The 2017 Tax Cut and Jobs Act increased the limitation on the tax deductibility of charitable contributions from 50 to 60 percent of adjusted gross income. This note estimates the effect of the share-of-income limitation on giving for the first time. Patterns in giving over time and across charities coincide with earlier changes in the share-of-income limit, consistent with a substantial policy effect. I estimate that the 2017 limit increase will boost aggregate household giving on the order of $10 billion.
Persistent 1-Cycles: Definition, Computation, and Its Application

Persistence diagrams, which summarize the birth and death of homological features extracted from data, are employed as stable signatures for applications in image analysis and other areas. Besides simply considering the multiset of intervals included in a persistence diagram, some applications need to find representative cycles for the intervals. In this paper, we address the problem of computing these representative cycles, termed as persistent 1-cycles. The definition of persistent cycles is based on the interval module decomposition of persistence modules, which reveals the structure of persistent homology. After showing that the computation of the optimal persistent 1-cycles is NP-hard, we propose an alternative set of meaningful persistent 1-cycles that can be computed with an efficient polynomial time algorithm. We also inspect the stability issues of the optimal persistent 1-cycles and the persistent 1-cycles computed by our algorithm with the observation that the perturbations of both cannot be properly bounded. We design a software which applies our algorithm to various datasets. Experiments on 3D point clouds, mineral structures, and images show the effectiveness of our algorithm in practice.
Fusion of DARPin to Aldolase Enables Visualization of Small Protein by Cryo-EM.

Summary Solving protein structures by single-particle cryoelectron microscopy (cryo-EM) has become a crucial tool in structural biology. While exciting progress is being made toward the visualization of small macromolecules, the median protein size in both eukaryotes and bacteria is still beyond the reach of cryo-EM. To overcome this problem, we implemented a platform strategy in which a small protein target was rigidly attached to a large, symmetric base via a selectable adapter. Of our seven designs, the best construct used a designed ankyrin repeat protein (DARPin) rigidly fused to tetrameric rabbit muscle aldolase through a helical linker. The DARPin retained its ability to bind its target: GFP. We solved the structure of this complex to 3.0 A resolution overall, with 5–8 A resolution in the GFP region. As flexibility in the DARPin position limited the overall resolution of the target, we describe strategies to rigidify this element.
Rapid geometric feature signaling in the simulated spiking activity of a complete population of tactile nerve fibers

The dexterous manipulation of objects relies on the rapid and accurate extraction of the objects’ geometric features by the sense of touch. Here we simulate the responses of all the nerve fibers th...
A Lagrangian sphere which is not a vanishing cycle

We give examples of Calabi–Yau threefolds containing Lagrangian spheres which are not vanishing cycles of nodal degenerations, answering a question of Donaldson in the negative.
The Role of Free Tissue Transfer in the Management of Chronic Frontal Sinus Osteomyelitis.

Objectives/hypothesis Chronic frontal sinus infection is managed with a combination of medical and surgical interventions. Frontal bone osteomyelitis due to recurrent infection following trauma or prior open surgery may require more significant debridement. Free tissue transfer may allow for extensive debridement with replacement of tissue, and definitive eradication of osteomyelitis. Study design Retrospective chart review. Methods Patients undergoing free flap obliteration of the frontal sinus for frontal bone osteomyelitis at a single institution were included in the study. Clinical, radiologic, and surgical data were collected. Surgeries before and after free flap obliteration were compared by Wilcoxon signed rank test. Results Fifteen patients were identified; however, one patient had less than 6 months of follow-up and was excluded from analysis. Of the remaining 14 patients, mean follow-up duration was 26 months (range, 6-120 months). Mean number of surgeries prior to free flap was 3.7 (range, 1-8 surgeries). Free flap obliteration resolved chronic frontal sinusitis in all patients. Two patients experienced postoperative infection, and the overall complication rate was 29%. Eight patients underwent cranioplasty (six immediate, two delayed) without complication. All patients received planned courses of postoperative antibiotics. A statistically significant decrease in the number of surgeries after free flap obliteration was observed P ≤ .01). Conclusions Extensive debridement followed by free tissue transfer and antibiotics offers a definitive treatment for complicated, recurrent frontal osteomyelitis. Simultaneous cranioplasty provides immediate protective and aesthetic benefit without complication. Consideration should be given for free tissue transfer and cranioplasty earlier in the algorithm for treatment of refractory frontal sinus osteomyelitis. Level of evidence 4 Laryngoscope, 129:1497-1504, 2019.
Evaluation of three classification models to predict risk class of cattle cohorts developing bovine respiratory disease within the first 14 days on feed using on-arrival and/or pre-arrival information

Abstract Bovine respiratory disease (BRD) remains the leading cause of morbidity and mortality in feedlot cattle. At feedlot arrival, classification of cattle groups into high- or low-risk based on their expected level of BRD is common, highly variable, and based on many subjective criteria. An accurate objective classification methodology would provide a tool to more efficiently allocate resources and promote judicious use of antimicrobial therapy. The objective of this research was to evaluate the diagnostic performance of three classification algorithms to classify cattle into risk classes based on the expected BRD morbidity in the first 14 days on feed (DOF) and to evaluate if data collected at the sale barn would provide information useful to increase classification performance. Data from 141 lots representing 618 purchase groups and 35,027 animals were used to predict the BRD risk class of cattle groups on arrival at the first management location (lot) following purchase. Sale barn, lot-level, and weather variables at each location were used to determine the combination of data most beneficial to diagnostic performance. Three classification algorithms were evaluated for their diagnostic performance (accuracy, sensitivity, specificity) in classifying cattle groups into risk classes based on three BRD morbidity cutoffs (2%, 4%, 6%) within the first 14 DOF. Bootstrapping methods were applied to estimate confidence intervals around the diagnostic performance point estimates. The predictive performance of individual algorithms varied by different cutoffs in BRD morbidity within the first 14 DOF and the predictors provided to the algorithms. The median morbidity within the first 14 DOF was 2.1% and using a 2% cutoff to classify cattle groups into high- or low-risk, using only lot level information provided the highest accuracy and specificity and was as good as the same model trained with additional lot and sale barn information with respect to sensitivity. At the 4% cutoff, the lot level dataset also provided the highest accuracy and sensitivity and the same level of specificity as using the full dataset. With a limited dataset, using cutoffs in BRD morbidity within the first 14 DOF of 2% and 4%, we found collecting sale barn data did not provide any additional benefit over collecting only on-arrival data with respect to classifying lots of cattle into high- or low-risk. A 6% cutoff was not useful due to the highly imbalanced dataset that is created with respect to our outcome of interest.
Surface Deposition of Molecular Contaminants in the Mars 2020 Rover Wake

Abstract The Mars 2020 rover has very strict contamination control requirements as it will cache samples on the surface of Mars for possible future return. It is known that the rover will outgas a minor amount of molecular contaminant on the surface of Mars, and numerical simulations using STAR-CCM+ are performed in order to predict the magnitude of the contaminant deposition to the Martian surface in the vicinity of the rover. Outgassing from the Rover Warm Electronics Bay (WEB) is predicted to be the dominant source of contamination for this scenario, and is therefore considered in this work. A flat terrain (i.e., no local topography) and a nominal rover orientation (i.e., no rocks under rover wheels, etc.) is also assumed. This analysis is performed in order to determine whether or not the M2020 rover WEB could self-contaminate a potential sampling site if the rover were to remain in the same location for an extended period of time. Simulations are performed under a variety of surface wind conditions, and it is determined that the predicted level of molecular contaminant deposition to the surface near the rover due to WEB outgassing and the model considered could be a maximum of 9 ng of organic contaminant in one specific location near the rover if the rover were to remain stationary for 100 sols.
“Left Behind?” Financialization and Income Inequality Between the Affluent, Middle Class, and The Poor

There is increasing scholarly evidence that financialization has contributed to rising income inequality, especially by concentrating income among the affluent and rich. There is less empirical research examining who is losing out to the affluent. This paper fills this gap by examining how three measures of financialization (finance, insurance and real estate or FIRE employment; credit expansion; and financial crises) affect upper-tail (measured as the ratio between the 90th and 50th income percentiles) and lower-tail (measured as the ratio between the 50th and 10th income percentiles) income inequality. Using concepts from economic sociology and the social stratification literature, I develop a perspective that links financialization to income inequality by creating more unequal market incomes while simultaneously reducing redistribution and social transfers. I analyze disposable household income data (after taxes and transfers) from the Luxembourg Income Study (LIS) and other public sources like the OECD from 16 affluent nations between the years 1980 to 2010, and I use an unbalanced panel design due to LIS data coverage. I find that both the middle class and poor are hurt by financialization (strongest evidence tied to FIRE employment); however, incomes of the poor are most sensitive to financialization.
Geologic Constraints on Early Mars Climate

Early Mars climate research has well-defined goals (MEPAG 2018). Achieving these goals requires geologists and climate modelers to coordinate. Coordination is easier if results are expressed in terms of well-defined parameters. Key parameters include the following quantitative geologic constraints. (1) Cumulative post-3.4 Ga precipitation-sourced water runoff in some places exceeded $1~\mbox{km}$ column. (2) There is no single Early Mars climate problem: the traces of ≥2 river-forming periods are seen. Relative to rivers that formed earlier in Mars history, rivers that formed later in Mars history are found preferentially at lower elevations, and show a stronger dependence on latitude. (3) The duration of the longest individual river-forming climate was ${>}(10^{2}\mbox{--}10^{3})~\mbox{yr}$ , based on paleolake hydrology. (4) Peak runoff production was ${>}0.1~\mbox{mm}/\mbox{hr}$ . However, (5) peak runoff production was intermittent, sustained (in a given catchment) for only <10% of the duration of river-forming climates. (6) The cumulative number of wet years during the valley-network-forming period was ${>}10^{5}~\mbox{yr}$ . (7) Post-Noachian light-toned, layered sedimentary rocks took ${>}10^{7}~\mbox{yr}$ to accumulate. However, (8) an “average” place on Mars saw water for ${<}10^{7}~\mbox{yr}$ after the Noachian, suggesting that the river-forming climates were interspersed with long globally-dry intervals. (9) Geologic proxies for Early Mars atmospheric pressure indicate pressure was not less than 0.012 bar but not much more than 1 bar. A truth table of these geologic constraints versus currently published climate models shows that the late persistence of river-forming climates, combined with the long duration of individual lake-forming climates, is a challenge for most models.
Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?

We build a game-theoretic model to examine how better demand forecasting resulting from algorithms, machine learning, and artificial intelligence affects the sustainability of collusion in an indus...
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling

Linear encoding of sparse vectors is widely popular, but is commonly data-independent -- missing any possible extra (but a priori unknown) structure beyond sparsity. In this paper we present a new method to learn linear encoders that adapt to data, while still performing well with the widely used $\ell_1$ decoder. The convex $\ell_1$ decoder prevents gradient propagation as needed in standard gradient-based training. Our method is based on the insight that unrolling the convex decoder into $T$ projected subgradient steps can address this issue. Our method can be seen as a data-driven way to learn a compressed sensing measurement matrix. We compare the empirical performance of 10 algorithms over 6 sparse datasets (3 synthetic and 3 real). Our experiments show that there is indeed additional structure beyond sparsity in the real datasets; our method is able to discover it and exploit it to create excellent reconstructions with fewer measurements (by a factor of 1.1-3x) compared to the previous state-of-the-art methods. We illustrate an application of our method in learning label embeddings for extreme multi-label classification, and empirically show that our method is able to match or outperform the precision scores of SLEEC, which is one of the state-of-the-art embedding-based approaches.
High-Frequency Transmission Lines

Transmission lines are used to guide electromagnetic waves from one place to another. They are used for many types of applications; the most common application in high-frequencies is transmission of signals, either digital or analog. In this case, high-frequency transmission lines are often designed to maximize the operable frequency bandwidth and minimize the attenuation of the signals. The former preserves the quality of the signal being transmitted, while the latter increases the maximum possible distance of transmission. Examples of high-frequency transmission lines include coaxial cables, optical fibers, microstrip lines, and hollow waveguides. Transmission of signals is not always limited to physically long lines. Some high-frequency transmission lines are also used for short-distance transmission as, for example, those used to transmit signals within a computer or to feed an antenna from its source. This article discusses various types of high-frequency transmission lines used in RF and microwave applications and the various propagation mechanisms behind their operation. Keywords: transmission lines; waveguides; cables; propagation; signal transmission
News Spillovers in the Sovereign Debt Market

Abstract We study the effect of a sovereign credit rating change of one country on the sovereign credit spreads of other countries from 1991 to 2000. We find evidence of spillover effects; that is, a ratings change in one country has a significant effect on sovereign credit spreads of other countries. This effect is asymmetric: positive ratings events abroad have no discernable impact on sovereign spreads, whereas negative ratings events are associated with an increase in spreads. On average, a one-notch downgrade of a sovereign bond is associated with a 12 basis point increase in spreads of sovereign bonds of other countries. The magnitude of the spillover effect following a negative ratings change is amplified by recent ratings changes in other countries. We distinguish between common information and differential components of spillovers. While common information spillovers imply that sovereign spreads move in tandem, differential spillovers are expected to result in opposite effects of ratings events across countries. Despite the predominance of common information spillovers, we also find evidence of differential spillovers among countries with highly negatively correlated capital flows or trade flows vis-a-vis the United States. That is, spreads in these countries generally fall in response to a downgrade of a country with highly negatively correlated capital or trade flows. Variables proxying for cultural or institutional linkages (e.g., common language, formal trade blocs, common law legal systems), physical proximity, and rule of law traditions across countries do not seem to affect estimated spillover effects.
Supercritical water gasification: practical design strategies and operational challenges for lab-scale, continuous flow reactors.

Abstract Optimizing an industrial-scale supercritical water gasification process requires detailed knowledge of chemical reaction pathways, rates, and product yields. Laboratory-scale reactors are employed to develop this knowledge base. The rationale behind designs and component selection of continuous flow, laboratory-scale supercritical water gasification reactors is analyzed. Some design challenges have standard solutions, such as pressurization and preheating, but issues with solid precipitation and feedstock pretreatment still present open questions. Strategies for reactant mixing must be evaluated on a system-by-system basis, depending on feedstock and experimental goals, as mixing can affect product yields, char formation, and reaction pathways. In-situ Raman spectroscopic monitoring of reaction chemistry promises to further fundamental knowledge of gasification and decrease experimentation time. High-temperature, high-pressure spectroscopy in supercritical water conditions is performed, however, long-term operation flow cell operation is challenging. Comparison of Raman spectra for decomposition of formic acid in the supercritical region and cold section of the reactor demonstrates the difficulty in performing quantitative spectroscopy in the hot zone. Future designs and optimization of continuous supercritical water gasification reactors should consider well-established solutions for pressurization, heating, and process monitoring, and effective strategies for mixing and solids handling for long-term reactor operation and data collection.
Age prediction using a large chest x-ray dataset

Age prediction based on appearances of different anatomies in medical images has been clinically explored for many decades. In this paper, we used deep learning to predict a person’s age on Chest X-Rays. Specifically, we trained a CNN in regression fashion on a large publicly available dataset. Moreover, for interpretability, we explored activation maps to identify which areas of a CXR image are important for the machine (i.e. CNN) to predict a patient’s age, offering insight. Overall, amongst correctly predicted CXRs, we see areas near the clavicles, shoulders, spine and mediastinum being most activated for age prediction, as one would expect biologically. As CXR is the most commonly requested imaging exam, a potential use case for estimating age may be found in the preventative counselling of patient health status compared to their age-expected average, particularly when there is a large discrepancy between predicted age and the real patient age.
How effective are early grade reading interventions? A review of the evidence

It is imperative that students learn to read in the early grades, yet many fail to do so in developing countries. Early grade reading interventions have emerged as a common means to attempt to address this problem. This paper presents a definition of early grade reading interventions as interventions that employ a combination of five components: at a minimum, they must train teachers to teach reading using simplified instructional techniques and evidence-based curricula. In addition, they typically include in-class coaching and the provision of instructional guidelines, instructional materials, or tools for student assessment. To develop a better understanding of the effectiveness of the interventions, the paper summarizes evidence from 18 early grade reading interventions, occurring across a large variety of contexts, including four World Bank regions and three World Bank income groups. The study finds that early grade reading interventions are consistently effective, although not infallible. The large majority had highly significant impacts on at least one reading subtask. However, only for a few interventions were effect sizes large enough to equate to more than a year's worth of schooling or create fluent readers on average. The cost of implementation varied widely, but some programs were highly cost-effective. Some programs failed to achieve impact altogether, although these programs were in the minority. In short, early grade reading interventions are not a guaranteed means to improve reading, and they rarely lead to fluency over a short span of time, but they are a mostly reliable means to make significant improvements in literacy over a short period of time.
Development of a Microfluidic Platform for Trace Lipid Analysis

The inherent trace quantity of primary fatty acid amides found in biological systems presents challenges for analytical analysis and quantitation, requiring a highly sensitive detection system. The use of microfluidics provides a green sample preparation and analysis technique through small-volume fluidic flow through micron-sized channels embedded in a polydimethylsiloxane (PDMS) device. Microfluidics provides the potential of having a micro total analysis system where chromatographic separation, fluorescent tagging reactions, and detection are accomplished with no added sample handling. This study describes the development and the optimization of a microfluidic-laser induced fluorescence (LIF) analysis and detection system that can be used for the detection of ultra-trace levels of fluorescently tagged primary fatty acid amines. A PDMS microfluidic device was designed and fabricated to incorporate droplet-based flow. Droplet microfluidics have enabled on-chip fluorescent tagging reactions to be performed quickly and efficiently, with no additional sample handling. An optimized LIF optical detection system provided fluorescently tagged primary fatty acid amine detection at sub-fmol levels (436 amol). The use of this LIF detection provides unparalleled sensitivity, with detection limits several orders of magnitude lower than currently employed LC-MS techniques, and might be easily adapted for use as a complementary quantification platform for parallel MS-based omics studies.