Miracle-dz/UniFAR-FTUs huggingface dataset:
Abbott–Deser–Tekin like conserved quantities in Lanczos–Lovelock gravity: beyond Killing diffeomorphisms

We obtain the conserved Abbott–Deser–Tekin (ADT)- like current for the Lanczos–Lovelock gravity for a diffeomorphism vector, which defines the horizon of a spacetime and, importantly, is not necessarily a Killing vector. As the original ADT current is defined only for the presence of a background Killing vector, one cannot use it extensively for the thermodynamic description of the wide classes of non-Killing horizons which appear in gravity. On the other hand, this general approach can be utilized for those horizons. Here, the conserved current can be written as the derivative of the two-rank anti-symmetric potential, the connection of which is apparent with the conserved Noether potential from our analysis. If one assumes the diffeomorphism vector as the Killing one, the results match to the ADT case, whereas non-trivial result comes for the conformal Killing vectors and other horizon defining vectors.
Diaphanosoma macedonicum Korovchinsky et 2014 (Crustacea: Cladocera: Sididae) in Lake Ohrid Diaphanosoma Korovchinsky

The endemic Balkan species Diaphanosoma macedonicum 2014 is found in ancient Lake Ohrid, previously lack-ing the representatives of the genus, for the first time. Their morphological features are briefly described and compared with those of other populations of the species inhabiting the neighbouring lakes Large Prespa and Dojran. The recent invasion of the representatives of the genus in Lake Ohrid probably was possible due to its ongoing eutrophication, especially in areas of high human activity. 19 females, three juveniles, and four deformed specimens. Only 17 adults suitable for morphometric measurements Specimens were examined under a dissecting micro- scope MBS-20 and a compound microscope Olympus BX-41 with camera lucida. Measurements of bodies and body parts were made according to Korovchinsky [2004]. Abbreviations: AnL — antennal length, BL — body length, DE — diameter of eye, HH — head height, HL — head length, UB — length of the upper antennal branch.
Abstractive Summarization Guided by Latent Hierarchical Document Structure

Sequential abstractive neural summarizers often do not use the underlying structure in the input article or dependencies between the input sentences. This structure is essential to integrate and consolidate information from different parts of the text. To address this shortcoming, we propose a hierarchy-aware graph neural network (HierGNN) which captures such dependencies through three main steps: 1) learning a hierarchical document structure through a latent structure tree learned by a sparse matrix-tree computation; 2) propagating sentence information over this structure using a novel message-passing node propagation mechanism to identify salient information; 3) using graph-level attention to concentrate the decoder on salient information. Experiments confirm HierGNN improves strong sequence models such as BART, with a 0.55 and 0.75 margin in average ROUGE-1/2/L for CNN/DM and XSum. Further human evaluation demonstrates that summaries produced by our model are more relevant and less redundant than the baselines, into which HierGNN is incorporated. We also find HierGNN synthesizes summaries by fusing multiple source sentences more, rather than compressing a single source sentence, and that it processes long inputs more effectively.
Affine Monads and Lazy Structures for Bayesian Programming

We show that streams and lazy data structures are a natural idiom for programming with infinite-dimensional Bayesian methods such as Poisson processes, Gaussian processes, jump processes, Dirichlet processes, and Beta processes. The crucial semantic idea, inspired by developments in synthetic probability theory, is to work with two separate monads: an affine monad of probability, which supports laziness, and a commutative, non-affine monad of measures, which does not. (Affine means that T(1)≅ 1. ) We show that the separation is important from a decidability perspective, and that the recent model of quasi-Borel spaces supports these two monads. To perform Bayesian inference with these examples, we introduce new inference methods that are specially adapted to laziness; they are proven correct by reference to the Metropolis-Hastings-Green method. Our theoretical development is implemented as a Haskell library, LazyPPL.
Complete analysis of spin structure function g₁ of ³He

We present a comprehensive analysis of the nuclear effects important in DIS on polarized He-3 over a wide range of Bjorken x, 10^{-4} \leq x \leq 0.8. Effects relevant for the extraction of the neutron spin structure function, g1^n, from the He-3 data are emphasized.
Measuring diffuse interstellar bands with cool stars - Improved line lists to model background stellar spectra

Context. Diffuse stellar bands (DIBs) are ubiquitous in stellar spectra. Traditionally, they have been studied through their extraction from hot (early-type) stars because of their smooth continuum. In an era in which there are several ongoing or planned massive Galactic surveys using multi-object spectrographs, cool (late-type) stars constitute an appealing set of targets. However, from the technical point of view, the extraction of DIBs in their spectra is more challenging because of the complexity of the continuum. Aims. In this contribution we provide the community with an improved set of stellar lines in the spectral regions associated with the strong DIBs at λ 6196.0, λ 6269.8, λ 6283.8, and λ 6379.3. These lines allow for the creation of better stellar synthetic spectra, reproducing the background emission and a more accurate extraction of the magnitudes associated with a given DIB (e.g., equivalent width, radial velocity). Methods. The Sun and Arcturus were used as representative examples of dwarf and giant stars, respectively. A high quality spectrum for each of them was modeled using TURBOSPECTRUM and the Vienna Atomic Line Database (VALD) stellar line list. The oscillator strength log ( gf ) and wavelength of specific lines were modified to create synthetic spectra in which the residuals in both the Sun and Arcturus were minimized. Results. The TURBOSPECTRUM synthetic spectra, based on improved line lists, reproduce the observed spectra for the Sun and Arcturus in the mentioned spectral ranges with greater accuracy. Residuals between the synthetic and observed spectra are always \hbox{$\lsim$}10%, which is much better than residuals with previously existing options. We tested the new line lists with some characteristic spectra from a variety of stars, including both giant and dwarf stars, and under different degrees of extinction. As occurred with the Sun and Arcturus, residuals in the fits used to extract the DIB information are smaller when using synthetic spectra made with the updated line lists. Tables with the updated parameters are provided to the community.
X-ray reflection from the inner disc of the AGN Ton S180

We analyse a long archival XMM-Newton observation of the narrow-line Seyfert 1 galaxy Ton S180, using the latest reflection models to explore the high quality X-ray spectrum. We find that the iron line is relatively narrow and sharp, and the soft excess is extremely smooth. We cannot find an acceptable reflection model that describes both components, and conclude that the soft excess cannot be produced by relativistic reflection. Fitting the 3-10 keV band with relativistic reflection to model the iron line strongly prefers low spin values (< 0.4), with the exact value depending on the model and not well constrained. We then model the broad- band spectrum with a two-component Comptonization continuum plus relativistic reflection. This gives a much better fit than a pure reflection model, which again prefers a low spin value. The photon index of the reflection component is intermediate between the two Comptoniza- tion components, suggesting that both illuminate the disk a similar amount and therefore both contribute to the reflection.
OARRR_A_347797 7..16

Psoriatic arthritis (PsA) is a well-known inflammatory disorder with a wide variety of phenotypes that extend beyond the joints. It has been defined as an immune-mediated disorder in which Th-1 and Th-17 cells play a key role. It has been associated with an elevated risk of metabolic syndrome (MetS), which is characterized by abdominal obesity, hypertension, hyperglycemia, and hyperlipidemia. While the exact pathophysiology of the link between PsA and MetS has yet to be precisely determined, persistence of inflammatory abnormalities, with overexpression of pro-inflammatory cytokines, might be the cause. Studies have consistently emphasized the strong association between elevated risk of developing cardiovascular disease and MetS in individuals with underlying PsA. The literature has also shown an association between the increased PsA severity and the increased frequency of MetS components. This association has important clinical consequences when treating patients with PsA. Therefore, screening programs should be implemented for PsA patients to evaluate whether they have MetS, and appropriate treatment should be given to manage cardiometabolic risk factors. Patients should also be closely monitored for potential adverse treatment effects on co-morbidities. This article summarizes the evidence of associations between several components of MetS and PsA and analyzes the impact of treatment on
Submanifolds in Carnot Groups

Preface. - 1. Carnot groups. - 2. Measure of submanifolds on Carnot groups. - 3. Elements of Geometric Measure Theory in the Heisenberg group. - 4. Intrinsic parametrization of H-regular surfaces. - 5. The Bernstein problem in Heisenberg groups and calibrations.
Semantic Integration in Biomedicine 2003) 2003:156-157.

In 1986, the National Library of Medicine (NLM) initiated a terminology integration project – the Unified Medical Language System ® (UMLS) – as “an effort to overcome two significant barriers to effective retrieval of machine-readable information”: the variety of names used to express the same concept and the absence of a standard format for distributing terminologies. By integrating more than 60 families of biomedical vocabularies, the UMLS Metathesaurus ® currently provides not only an extensive list of names (2.5 million) for its 900,551 concepts, but also over 12 million relations among these concepts. Its scope is broader and its granularity finer than that of any of its source vocabularies.
K-Band Imaging of 52 B3-VLA Quasars: Nucleus and Host Properties

We present K-band imaging and photometry of a sample of 52 radio-loud quasars (RQs) selected from the B3 survey with flux densities greater than 0.5 Jy at 408 MHz. The optical completeness of the sample is 90%, and the quasars cover the redshift range 0.4–2.3. For ∼57% of the sources for which the quality of the images allowed a detailed morphological study (16/28), resolved extended emission was detected around the QSO, and its K flux was measured. Interpreting this "fuzz" as starlight emission from the host galaxy, its location on the K-z plane at z < 1 is consistent with radio quasars being hosted by galaxies similar to radio galaxies (RGs) or giant ellipticals (gE's). At higher redshifts the detected host galaxies of RQs are more luminous than are typical RGs and gE's, although some weak detections or upper limits are consistent with a similar fraction of RQs being hosted by galaxies with the expected luminosities for RGs or gE's. The study of the B - K color distribution of the QSO nuclei, after removing the contribution of K emission from the host galaxy, confirm that these sources are not reddened by large amounts of dust, with an estimated extinction AV < 1.0 mag at z ≃ 1. We find a significant correlation between radio power and nuclear infrared luminosity, indicating a direct link between the radio synchrotron emission and the nuclear emission in K. This correlation is more tight for the steep-spectrum sources (99.97% significance). In addition, a trend is found between radio power and infrared luminosity of the host galaxy (or mass), in the sense that the most powerful quasars inhabit the most luminous galaxies. The similarity of this tendency with that found for powerful FR II radio galaxies is consistent with the unification model for radio sources.
lilGym: Natural Language Visual Reasoning with Reinforcement Learning

We present lilGym, a new benchmark for language-conditioned reinforcement learning in visual environments. lilGym is based on 2,661 highly-compositional human-written natural language statements grounded in an interactive visual environment. We introduce a new approach for exact reward computation in every possible world state by annotating all statements with executable Python programs. Each statement is paired with multiple start states and reward functions to form thousands of distinct Markov Decision Processes of varying difficulty. We experiment with lilGym with different models and learning regimes. Our results and analysis show that while existing methods are able to achieve non-trivial performance, lilGym forms a challenging open problem. lilGym is available at https://lil.nlp. cornell.edu/lilgym/.
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing

Modern deep neural networks tend to be evaluated on static test sets. One shortcoming of this is the fact that these deep neural networks cannot be easily evaluated for robustness issues with respect to specific scene variations. For example, it is hard to study the robustness of these networks to variations of object scale, object pose, scene lighting and 3D occlusions. The main reason is that collecting real datasets with fine-grained naturalistic variations of sufficient scale can be extremely time-consuming and expensive. In this work, we present Counterfactual Simulation Testing, a counterfactual framework that allows us to study the robustness of neural networks with respect to some of these naturalistic variations by building realistic synthetic scenes that allow us to ask counterfactual questions to the models, ultimately providing answers to questions such as"Would your classification still be correct if the object were viewed from the top? "or"Would your classification still be correct if the object were partially occluded by another object? ". Our method allows for a fair comparison of the robustness of recently released, state-of-the-art Convolutional Neural Networks and Vision Transformers, with respect to these naturalistic variations. We find evidence that ConvNext is more robust to pose and scale variations than Swin, that ConvNext generalizes better to our simulated domain and that Swin handles partial occlusion better than ConvNext. We also find that robustness for all networks improves with network scale and with data scale and variety. We release the Naturalistic Variation Object Dataset (NVD), a large simulated dataset of 272k images of everyday objects with naturalistic variations such as object pose, scale, viewpoint, lighting and occlusions. Project page: https://counterfactualsimulation.github. io
Array Signal Processing Algorithms for Beamforming and Direction Finding

Array processing is an area of study devoted to processing the signals received from an antenna array and extracting information of interest. It has played an important role in widespread applications like radar, sonar, and wireless communications. Numerous adaptive array processing algorithms have been reported in the literature in the last several decades. These algorithms, in a general view, exhibit a trade-off between performance and required computational complexity. In this thesis, we focus on the development of array processing algorithms in the application of beamforming and direction of arrival (DOA) estimation. In the beamformer design, we employ the constrained minimum variance (CMV) and the constrained constant modulus (CCM) criteria to propose full-rank and reduced-rank adaptive algorithms. Specifically, for the full-rank algorithms, we present two low-complexity adaptive step size mechanisms with the CCM criterion for the step size adaptation of the stochastic gradient (SG) algorithms. The convergence and steady-state properties are analysed. Then, the full-rank constrained conjugate gradient (CG) adaptive filtering algorithms are proposed according to the CMV and CCM criteria. We introduce a CG based weight vector to incorporate the constraint in the design criteria for solving the system of equations that arises from each design problem. The proposed algorithms avoid the covariance matrix inversion and provide a trade-off between the complexity and performance. In reduced-rank array processing, we present CMV and CCM reduced-rank schemes based on joint iterative optimization (JIO) of adaptive filters. This scheme consists a bank of full-rank adaptive filters that forms the transformation matrix, and an adaptive reduced-rank filter that operates at the output of the bank of filters. The transformation matrix and the reduced-rank weight vector are jointly optimized according to the CMV or CCM criteria. For the application of beamforming, we describe the JIO scheme for both the direct-form processor (DFP) and the generalized sidelobe canceller (GSC) structures. For each structure, we derive SG and recursive least squares (RLS) type algorithms to iteratively compute the transformation matrix and the reduced-rank weight vector for the reduced-rank scheme. An auxiliary vector filtering (AVF) algorithm based on the CCM design for robust beamforming is presented. The proposed beamformer decomposes the adaptive filter into a constrained (reference vector filter) and an unconstrained (auxiliary vector filter) component. The weight vector is iterated by subtracting the scaling auxiliary vector from the reference vector. For the DOA estimation, the reduced-rank scheme with the minimum variance (MV) power spectral evaluation is introduced. A spatial smoothing (SS) technique is employed in the proposed method to improve the resolution. The proposed DOA estimation algorithms are suitable for large arrays and to deal with direction finding for a small number of snapshots, a large number of users, and without the exact information of the number of sources.
Unchanged thermopower enhancement at the semiconductor-metal transition in correlated FeSb2−xTex

Substitution of Sb in FeSb2 by less than 0.5% of Te induces a transition from a correlated semiconductor to an unconventional metal with large effective charge carrier mass m∗. Spanning the entire range of the semiconductor-metal crossover, we observed an almost constant enhancement of the measured thermopower compared to that estimated by the classical theory of electron diffusion. Using the latter for a quantitative description one has to employ an enhancement factor of 10–30. Our observations point to the importance of electron-electron correlations in the thermal transport of FeSb2, and suggest a route to design thermoelectric materials for cryogenic applications.
Full title: Impact of postnatal depression on neonatal outcomes: an exploratory study in Kisumu County, western Kenya Short title: Postnatal depression and neonatal outcomes

Corresponding author: Catherine Gribbin E-mail: catmac57@gmail.com (CG) . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted October 27, 2022. ; https://doi.org/10.1101/2022.10. 25.22281500 doi: medRxiv preprint
Numerical Study on the Effect of ZrS2 on CZTSSe Photovoltaic Device Using SCAPS 1-D

CZTSSe based photovoltaic devices are gaining attention recently. They have many favorable properties like less costly and simple manufacturing processes, comparably nontoxic and easily available constituent components, and most importantly, excellent optoelectronic properties. Herein, we propose a CZTSSe based solar cell and aim to report for the first time a new material for the buffer layer: Zirconium Sulphide (ZrS2). The suggested device here is Al-doped ZnO(AZO)/ZrS2/CZTSSe/Mo. Here we use a numerical simulation package called Solar Cell Capacitance Simulator or SCAPS 1-D to analyze the output of the device with varying input parameters. To explore the impact of the ZrS2 layer on the functioning of the suggested device,its donor density was changed from 1012 cm−3 to 1016 cm−3. The simulations indicate that the donor density doesn’t particularly affect the output parameters of the device within the tested range. Besides the influence of the ZrS2 layer, a study was also carried out to find the role of operating temperature and the intrinsic layer on the proposed device. Most of the parameters declined rapidly with the increase in temperature while they remain constant with the change in ZnO thickness. Efficiency dropped to 9% at 500K from 23 % at 300K and the efficiency of the device remained 23% with the variation of intrinsic layer thickness. As per the simulation results, we can conclude that ZrS2 is an appropriate material as buffer layer for photovoltaic devices with a CZTSSe absorber layer.
Fast radio burst search: cross spectrum vs. auto spectrum method

The search for fast radio bursts (FRBs) is a hot topic in current radio astronomy studies. In this work, we carry out a single pulse search with a very long baseline interferometry (VLBI) pulsar observation data set using both auto spectrum and cross spectrum search methods. The cross spectrum method, first proposed in Liu et al., maximizes the signal power by fully utilizing the fringe phase information of the baseline cross spectrum. The auto spectrum search method is based on the popular pulsar software package PRESTO, which extracts single pulses from the auto spectrum of each station. According to our comparison, the cross spectrum method is able to enhance the signal power and therefore extract single pulses from data contaminated by high levels of radio frequency interference (RFI), which makes it possible to carry out a search for FRBs in regular VLBI observations when RFI is present.
PV Powered Neural Network Based SEPIC Converter Fed BLDC for Consumer Application

The goal of this study is to investigate the utilization of a SEPIC in PV array-fed consumer applications. In order to run a centrifugal pump, a BLDC motor must be employed. It is possible to soften the start of a BLDC motor by using the INC-MPPT approach, which uses the SEPIC for management. As an added advantage, the SEPIC can adjust the input voltage level at its output when used as a DC-DC buck-boost converter. An SPV array may be optimised at any voltage level, independent of the voltage level being utilised, thanks to this feature. Through the use of simulated results created in the MATLAB programme, the dynamic and steady state performance of a BLDC motor linked to a centrifugal water pump powered by a PV array-SEPIC is analysed and confirmed in this study.