Miracle-dz/UniFAR-FTUs huggingface dataset:
UV-FIR SED modeling of AGN in IR-luminous galaxies up to z∼2.5: Understanding the effects of torus models

UV-FIR SED modeling is an effective way to disentangle emission between star formation (SF) and active galactic nuclei (AGN) in galaxies; however, this approach becomes uncertain for composite AGN/SF galaxies that comprise 50-70% of IR-samples. Cosmic X-ray background (XRB) models require a large fraction of obscured AGN to reproduce the observed XRB peak, motivating reliable SED analyses in objects where the AGN may be “buried” in the galaxy and in the mid-IR to far-IR SED. In this paper, we study a 24μm-selected (S24 > 100μJy) sample of 95 galaxies with $0 \% < f_{MIR,AGN} < 100 \%$, 0.4 < z < 2.7, and 1011L⊙ < LIR < 1013L⊙. We test the performance of AGN models ranging in torus optical depth via SED fitting, comparing results with Spitzer MIR spectroscopy and X-ray observations. Best-fit torus optical depth can shed light on whether these galaxies host a luminous obscured AGN population. We find that permitting a broader AGN SED parameter space results in improved fit quality with higher optical depths, higher FIR AGN contributions, and higher LBol, impacting the bright-end of the LBol luminosity function. Our results suggest there may be a population of dust-obscured composites that are bolometrically significant but have their AGN mostly hidden in the mid-IR SED. If so, literature applications of SED fitting that often simplify AGN models or omit optically thick torrii may largely underestimate AGN contribution from composite sources, as these sources are both numerous and have solutions sensitive to the assumed range of AGN models.
Bayesian hidden Markov models for latent variable labeling assignments in conflict research: application to the role ceasefires play in conflict dynamics

A crucial challenge for solving problems in conflict research is in leveraging the semi-supervised nature of the data that arise. Observed response data such as counts of battle deaths over time indicate latent processes of interest such as intensity and duration of conflicts, but defining and labeling instances of these unobserved processes requires nuance and imprecision. The availability of such labels, however, would make it possible to study the effect of intervention-related predictors - such as ceasefires - directly on conflict dynamics (e.g., latent intensity) rather than through an intermediate proxy like observed counts of battle deaths. Motivated by this problem and the new availability of the ETH-PRIO Civil Conflict Ceasefires data set, we propose a Bayesian autoregressive (AR) hidden Markov model (HMM) framework as a sufficiently flexible machine learning approach for semi-supervised regime labeling with uncertainty quantification. We motivate our approach by illustrating the way it can be used to study the role that ceasefires play in shaping conflict dynamics. This ceasefires data set is the first systematic and globally comprehensive data on ceasefires, and our work is the first to analyze this new data and to explore the effect of ceasefires on conflict dynamics in a comprehensive and cross-country manner.
Existence of solutions to gas expansion problem through a sharp corner for 2‐D Euler equations with general equation of state

In this article, we study the gas expansion problem by turning a sharp corner into a vacuum for the two‐dimensional (2‐D) pseudosteady compressible Euler equations with a convex equation of state. This problem can be considered as the interaction of a centered simple wave with a planar rarefaction wave. To obtain the global existence of a solution up to the vacuum boundary of the corresponding 2‐D Riemann problem, we consider several Goursat‐type boundary value problems for 2‐D self‐similar Euler equations and use the ideas of characteristic decomposition and bootstrap method. Further, we formulate 2‐D‐modified shallow water equations newly and solve a dam‐break‐type problem for them as an application of this work. Moreover, we also recover the results from the available literature for certain equations of states that provide a check that the results obtained in this article are actually correct.
A Review and Some New Results on Probabilistic Control

In probabilistic control a controller is designed by matching the closed-loop system behaviour with some desired one. In this work we review and extend several productive approaches to measure proximity and connect the resulting solutions to conventional optimal control theory. Our main result is to show that the resulting problems majorize conventional optimal control objectives which leads to the deﬁnition of (probabilistic) ﬁxed point iterations that collapse onto the deterministic optimal control
Metal–superconductor transition in low-dimensional superconducting clusters embedded in two-dimensional electron systems

Motivated by recent experimental data on thin film superconductors and oxide interfaces, we propose a random-resistor network apt to describe the occurrence of a metal–superconductor transition in a two-dimensional electron system with disorder on the mesoscopic scale. We consider low-dimensional (e.g. filamentary) structures of a superconducting cluster embedded in the two-dimensional network and we explore the separate effects and the interplay of the superconducting structure and of the statistical distribution of local critical temperatures. The thermal evolution of the resistivity is determined by a numerical calculation of the random-resistor network and, for comparison, a mean-field approach called effective medium theory (EMT). Our calculations reveal the relevance of the distribution of critical temperatures for clusters with low connectivity. In addition, we show that the presence of spatial correlations requires a modification of standard EMT to give qualitative agreement with the numerical results. Applying the present approach to an LaTiO3/SrTiO3 oxide interface, we find that the measured resistivity curves are compatible with a network of spatially dense but loosely connected superconducting islands.
Experimental Study of Multiple Scattering in X-Ray-Absorption Near-Edge Structure

Mise en evidence de deux types de diffusion multiple: 1) des atomes diffusants sont a peu pres colineaires avec l'atome central; 2) les atomes diffusants sont loin d'etre colineaires. Importance du type 1 au voisinage de la structure fine d'absorption de rayons X, et du type 2 au-dessus de la limite d'absorption quand les distances de liaison sont inferieures a ∼1,6 A. Exemples pour KMnO 4 et K 3 Mn(CN) 6
A simplified noise-predictive partial response maximum likelihood detection using M-algorithm for perpendicular magnetic recording channels

We propose a simplified noise-predictive partial response maximum likelihood (NPML) system in conjunction with M-algorithm for dual-layered perpendicular magnetic recording channels. The complexity, which is increased by the construction of noise prediction filter, can be reduced through the M-algorithm. Despite the complexity of the proposed scheme (M=4) is decreased to 1/4 than one of the full NP(12321)ML system, two systems maintain almost the same bit-error rate and the detection performance of the noise-predictive maximum likelihood is better than that of the conventional PRML.
An Improved Internal Consistency Reliability Estimate

Kuder-Richardson Formula 20 was derived on the assumption that the average covariance between items on different forms is the same as the average covariance on the same form. This formula is considered an underestimate of the parallel form reliability because the average covariance of items with identical difficulty is expected to be higher than the average covariance of items of different difficulty. The proposed coefficient is derived by assuming instead that the average Goodman-Kruskal gamma between items of identical difficulty would be the same as the average for items of different difficulty. Given the average gamma for the present items, this permits an estimate of the covariance between items of identical difficulty. This leads directly to an estimate of the correlation between scores on the present test and those on a form that had an identical distribution of difficulty. Some examples are given.
Pride and Prejudice: Same-Sex Marriage Legalization Announcements and Hate Crimes

In this paper, we examine whether same-sex marriage legalization announcements impact the occurrence of hate crimes against lesbian, gay, bisexual, and transgender (LGBT) people. Using a difference-in-differences design, we exploit the variation in the timing of same-sex marriage legalization announcements across states. On average, a same-sex marriage legalization announcement reduces the anti-LGBT hate crime rate by . 112 per 100,000 people, although some additional analyses have weaker results. Decreases are mostly driven by reductions in violent crimes. Event-study estimates show that results fade after 1 year and provide evidence that reductions are not due to changes in social trends before an announcement. Our results demonstrate that salient, progressive LGBT policy announcements may, by themselves, effectively reduce anti-LGBT hate crimes.
Maternal Rumen Bacteriota Shapes the Offspring Rumen Bacteriota, Affecting the Development of Young Ruminants

Using a study design that enabled direct comparison of the rumen microbiota between sheep dams and their lambs, between littermates, and between sheep dams and lambs from other mothers, we identified the heritable subsets of rumen bacteriota in Hu sheep, some of which may play important roles in affecting the growth traits of young lambs. Some maternal rumen bacteria could help predict the growth traits of the young offspring, and they may assist in breeding of and selection for high-performance sheep. ABSTRACT The maternal rumen microbiota can affect the infantile rumen microbiota and likely offspring growth, and some rumen microbes are heritable and are associated with host traits. However, little is known about the heritable microbes of the maternal rumen microbiota and their role in and effect on the growth of young ruminants. From analyzing the ruminal bacteriota from 128 Hu sheep dams and their 179 offspring lambs, we identified the potential heritable rumen bacteria and developed random forest prediction models to predict birth weight, weaning weight, and preweaning gain of the young ruminants using rumen bacteria as predictors. We showed that the dams tended to shape the bacteriota of the offspring. About 4.0% of the prevalent amplicon sequence variants (ASVs) of rumen bacteria were heritable (h2 > 0.2 and P < 0.05), and together they accounted for 4.8% and 31.5% of the rumen bacteria in relative abundance in the dams and the lambs, respectively. Heritable bacteria classified to Prevotellaceae appeared to play a key role in the rumen niche and contribute to rumen fermentation and the growth performance of lambs. Lamb growth traits could be successfully predicted using some maternal ASVs, and the accuracy of the predictive models was improved when some ASVs from both dams and their offspring were included. IMPORTANCE Using a study design that enabled direct comparison of the rumen microbiota between sheep dams and their lambs, between littermates, and between sheep dams and lambs from other mothers, we identified the heritable subsets of rumen bacteriota in Hu sheep, some of which may play important roles in affecting the growth traits of young lambs. Some maternal rumen bacteria could help predict the growth traits of the young offspring, and they may assist in breeding of and selection for high-performance sheep.
Medical Parasitology Taxonomy Update, June 2020–June 2022

The taxonomy of medically important parasites continues to evolve. This minireview provides an update of additions and updates in the field of human parasitology from June 2020 through June 2022. A list of previously reported nomenclatural changes that have not been broadly adapted by the medical community is also included. ABSTRACT The taxonomy of medically important parasites continues to evolve. This minireview provides an update of additions and updates in the field of human parasitology from June 2020 through June 2022. A list of previously reported nomenclatural changes that have not been broadly adapted by the medical community is also included.
PHYSICS-BASED BALANCING DOMAIN DECOMPOSITION BY CONSTRAINTS FOR HETEROGENEOUS PROBLEMS

In this work, we present a novel balancing domain decomposition by constraints preconditioner that is robust for multi-material and heterogeneous problems. We start with a well-balanced subdomain partition and, based on an aggregation of elements according to their physical coefficients, we end up with a finer physics-based (PB) subdomain partition. Next, we define geometrical objects (corners, edges, and faces) for this PB partition, and select some of them to enforce subdomain continuity (primal objects). When the physical coefficient in each PB subdomain is constant and the primal objects satisfy a mild condition on the existence of acceptable paths, we can show both theoretically and numerically that the condition number does not depend on the contrast of the coefficient. The constant coefficient condition is computationally feasible for multi-material problems. However, for highly heterogeneous problems, such restriction might result into a large coarse problem. In this case, we propose a relaxed version of the method where we only require that the maximal contrast of the physical coefficient in each PB subdomain is smaller than a predefined threshold. The threshold can be chosen so that the condition number is reasonably small while the size of the coarse problem is not too large. An extensive set of numerical experiments is provided to support our findings. In particular, we show a robustness and a weak scalability analysis up to 8000 cores of the new preconditioner when applied to a 3D heterogeneous problem with more than 260 million degrees of freedom. For the scalability analysis, we have exploited a highly scalable advanced inter-level overlapped implementation of the preconditioner that deals very efficiently with the coarse problem computation.
Ribavirin Treatment Failure-Associated Mutation, Y1320H, in the RNA-Dependent RNA Polymerase of Genotype 3 Hepatitis E Virus (HEV) Enhances Virus Replication in a Rabbit HEV Infection Model

HEV-3 causes chronic hepatitis E that requires antiviral therapy in immunosuppressed individuals. RBV is the main therapeutic option for chronic hepatitis E as an off-label use. ABSTRACT Chronic hepatitis E virus (HEV) infection has become a significant clinical problem that requires treatment in immunocompromised individuals. In the absence of an HEV-specific antiviral, ribavirin (RBV) has been used off-label, but treatment failure may occur due to mutations in the viral RNA-dependent RNA polymerase (RdRp), including Y1320H, K1383N, and G1634R. Chronic hepatitis E is mostly caused by zoonotic genotype 3 HEV (HEV-3), and HEV variants from rabbits (HEV-3ra) are closely related to human HEV-3. Here, we explored whether HEV-3ra, along with its cognate host, can serve as a model to study RBV treatment failure-associated mutations observed in human HEV-3-infected patients. By utilizing the HEV-3ra infectious clone and indicator replicon, we generated multiple single mutants (Y1320H, K1383N, K1634G, and K1634R) and a double mutant (Y1320H/K1383N) and assessed the role of mutations on replication and antiviral activity of HEV-3ra in cell culture. Furthermore, we also compared the replication of the Y1320H mutant with the wild-type HEV-3ra in experimentally infected rabbits. Our in vitro analyses revealed that the effects of these mutations on rabbit HEV-3ra are altogether highly consistent with those on human HEV-3. Importantly, we found that the Y1320H enhances virus replication during the acute stage of HEV-3ra infection in rabbits, which corroborated our in vitro results showing an enhanced viral replication of Y1320H. Taken together, our data suggest that HEV-3ra and its cognate host is a useful and relevant naturally occurring homologous animal model to study the clinical relevance of antiviral-resistant mutations observed in human HEV-3 chronically-infected patients. IMPORTANCE HEV-3 causes chronic hepatitis E that requires antiviral therapy in immunosuppressed individuals. RBV is the main therapeutic option for chronic hepatitis E as an off-label use. Several amino acid changes, including Y1320H, K1383N, and G1634R, in the RdRp of human HEV-3 have reportedly been associated with RBV treatment failure in chronic hepatitis E patients. In this study, we utilized an HEV-3ra from rabbit and its cognate host to investigate the effect of these RBV treatment failure-associated HEV-3 RdRp mutations on viral replication efficiency and antiviral susceptibility. The in vitro data using rabbit HEV-3ra was highly comparable to those from human HEV-3. We demonstrated that the Y1320H mutation significantly enhanced HEV-3ra replication in cell culture and enhanced virus replication during the acute stage of HEV-3ra infection in rabbits. The rabbit HEV-3ra infection model should be useful in delineating the role of human HEV-3 RBV treatment failure-associated mutations in antiviral resistance.
Identification of Small-Molecule Inhibitors of the Salmonella FraB Deglycase Using a Live-Cell Assay

Nontyphoidal salmonellosis is a serious threat in the United States and globally. We have recently identified an enzyme, FraB, that when mutated renders Salmonella growth defective in vitro and unfit in mouse models of gastroenteritis. ABSTRACT Nontyphoidal salmonellosis is one of the most significant foodborne diseases in the United States and globally. There are no vaccines available for human use to prevent this disease, and only broad-spectrum antibiotics are available to treat complicated cases of the disease. However, antibiotic resistance is on the rise and new therapeutics are needed. We previously identified the Salmonella fraB gene, that mutation of causes attenuation of fitness in the murine gastrointestinal tract. The FraB gene product is encoded in an operon responsible for the uptake and utilization of fructose-asparagine (F-Asn), an Amadori product found in several human foods. Mutations in fraB cause an accumulation of the FraB substrate, 6-phosphofructose-aspartate (6-P-F-Asp), which is toxic to Salmonella. The F-Asn catabolic pathway is found only in the nontyphoidal Salmonella serovars, a few Citrobacter and Klebsiella isolates, and a few species of Clostridium; it is not found in humans. Thus, targeting FraB with novel antimicrobials is expected to be Salmonella specific, leaving the normal microbiota largely intact and having no effect on the host. We performed high-throughput screening (HTS) to identify small-molecule inhibitors of FraB using growth-based assays comparing a wild-type Salmonella and a Δfra island mutant control. We screened 224,009 compounds in duplicate. After hit triage and validation, we found three compounds that inhibit Salmonella in an fra-dependent manner, with 50% inhibitory concentration (IC50) values ranging from 89 to 150 μM. Testing these compounds with recombinant FraB and synthetic 6-P-F-Asp confirmed that they are uncompetitive inhibitors of FraB with Ki′ (inhibitor constant) values ranging from 26 to 116 μM. IMPORTANCE Nontyphoidal salmonellosis is a serious threat in the United States and globally. We have recently identified an enzyme, FraB, that when mutated renders Salmonella growth defective in vitro and unfit in mouse models of gastroenteritis. FraB is quite rare in bacteria and is not found in humans or other animals. Here, we have identified small-molecule inhibitors of FraB that inhibit the growth of Salmonella. These could provide the foundation for a therapeutic to reduce the duration and severity of Salmonella infections.
On the control of uncertain impulsive systems: approximate stabilization and controlled invariance

The problems of stabilization and controlled invariance of a fairly wide class of uncertain hybrid systems is considered. Uncertainty enters in the form of a disturbance input that can affect both the continuous and the discrete dynamics. A method for designing piecewise constant, feedback controllers for this class of systems is developed. In the case of controlled invariance, the controller ensures that the state of the system remains arbitrarily close to a desired set over an arbitrarily long time horizon. In the case of stabilization, the controller ensures approximate exponential convergence of the runs of the closed loop system to the zero level set of a Lyapunov function.
High-spatial-resolution, near-infrared observations of ARP 220

High-spatial-resolution slit scans of the nucleus of Arp 220 are presented along with near-infrared photometry of the nuclear region. A single nucleus is found coincident with the strongest radio peak. The core is resolved to be on the order of 1" (370 pc) in diameter. The photometry of the central region shows a minimum near 3.7 µm which is inconsistent with the near-infrared source being a "classical" nonthermal source, such as 3C 273, embedded in a dust cloud.
Children's rates of BMI change during pre‐pandemic and two COVID‐19 pandemic periods, IQVIA Ambulatory Electronic Medical Record, January 2018 Through November 2021

Many US youth experienced accelerated weight gain during the early COVID‐19 pandemic. Using an ambulatory electronic health record data set, the authors compared children's rates of BMI change in three periods: pre‐pandemic (January 2018‐February 2020), early pandemic (March‐December 2020), and later pandemic (January‐November 2021).
2PLSF: Two-Phase Locking with Starvation-Freedom

Invented more than 40 years ago, the two-phase locking concurrency control (2PL) is capable of providing opaque transactions over multiple records. However, classic 2PL can suffer from live-lock and its scalability is low when applied to workloads with a high number of non-disjoint read accesses. In this paper we propose a new 2PL algorithm (2PLSF) which, by utilizing a novel reader-writer lock, provides highly scalable transactions with starvation-freedom guarantees. Our 2PLSF concurrency control can be applied to records, metadata and to indexing data structures used in database management systems (DBMS). In our experiments we show that 2PLSF is often superior to classical 2PL and can surpass concurrency controls with optimistic reads, simultaneously providing high throughput and low latency for disjoint and non-disjoint workloads.
Towards Automated Analysis of Rhetorical Categories in Students Essay Writings using Bloom’s Taxonomy

Essay writing has become one of the most common learning tasks assigned to students enrolled in various courses at different educational levels, owing to the growing demand for future professionals to effectively communicate information to an audience and develop a written product (i.e. essay). Evaluating a written product requires scorers who manually examine the existence of rhetorical categories, which is a time-consuming task. Machine Learning (ML) approaches have the potential to alleviate this challenge. As a result, several attempts have been made in the literature to automate the identification of rhetorical categories using Rhetorical Structure Theory (RST). However, RST do not provide information regarding students’ cognitive level, which motivates the use of Bloom’s Taxonomy. Therefore, in this research we propose to: i) investigate the extent to which classification of rhetorical categories can be automated based on Bloom’s taxonomy by comparing the traditional ML classifiers with the pre-trained language model BERT, ii) explore the associations between rhetorical categories and writing performance. Our results showed that BERT model outperformed the traditional ML-based classifiers with 18% better accuracy, indicating it can be used in future analytics tool. Moreover, we found a statistical difference between the associations of rhetorical categories in low-achiever, medium-achiever and high-achiever groups which implies that rhetorical categories can be predictive of writing performance.