Miracle-dz/UniFAR-FTUs huggingface dataset:
Electronic structure of Pr2MnNiO6 from x-ray photoemission, absorption and density functional theory

The electronic structure of double perovskite Pr2MnNiO6 was studied using core x-ray photoelectron spectroscopy and x-ray absorption spectroscopy. The 2p x-ray absorption spectra show that Mn and Ni are in 4+ and 2+ states respectively. Based on charge transfer multiplet analysis of the 2p XPS spectra of both ions, we find charge transfer energies of 3.5 and 2.5 eV for Ni and Mn respectively. The ground state of Ni2+ and Mn4+ ions reveal a higher d electron count of 8.21 and 3.38 respectively as compared to the ionic values. The partial density of states clearly show a charge transfer character of the system for U − J 2 eV. The O 1s edge absorption spectra reveal a band gap of 0.9 eV, which is close to the value estimated from analysis of Ni and Mn 2p photoemission and absorption spectra. The combined analysis of nature of spectroscopic data and first principles calculations reveal that the material is a p − d type charge transfer insulator with an intermediate covalent character according to the Zannen–Sawatzy–Allen phase diagram.
State-of-the-art of microbubble-assisted blood-brain barrier disruption

Focused ultrasound with microbubbles promises unprecedented advantages for blood-brain barrier disruption over existing intracranial drug delivery methods, as well as a significant number of tunable parameters that affect its safety and efficacy. This review provides an engineering perspective on the state-of-the-art of the technology, considering the mechanism of action, effects of microbubble properties, ultrasound parameters and physiological variables, as well as safety and potential therapeutic applications. Emphasis is placed on the use of unified parameters, such as microbubble volume dose (MVD) and ultrasound mechanical index, to optimize the procedure and establish safety limits. It is concluded that, while efficacy has been demonstrated in several animal models with a wide range of payloads, acceptable measures of safety should be adopted to accelerate collaboration and improve understanding and clinical relevance.
Submodular Secretary Problem with Shortlists

In submodular $k$-secretary problem, the goal is to select $k$ items in a randomly ordered input so as to maximize the expected value of a given monotone submodular function on the set of selected items. In this paper, we introduce a relaxation of this problem, which we refer to as submodular $k$-secretary problem with shortlists. In the proposed problem setting, the algorithm is allowed to choose more than $k$ items as part of a shortlist. Then, after seeing the entire input, the algorithm can choose a subset of size $k$ from the bigger set of items in the shortlist. We are interested in understanding to what extent this relaxation can improve the achievable competitive ratio for the submodular $k$-secretary problem. In particular, using an $O(k)$ shortlist, can an online algorithm achieve a competitive ratio close to the best achievable online approximation factor for this problem? We answer this question affirmatively by giving a polynomial time algorithm that achieves a $1-1/e-\epsilon -O(k^{-1})$ competitive ratio for any constant $\epsilon > 0$, using a shortlist of size $\eta_\epsilon(k) = O(k)$. Also, for the special case of m-submodular functions, we demonstrate an algorithm that achieves a $1-\epsilon$ competitive ratio for any constant $\epsilon > 0$, using an $O(1)$ shortlist. Finally, we show that our algorithm can be implemented in the streaming setting using a memory buffer of size $\eta_\epsilon(k) = O(k)$ to achieve a $1 - 1/e - \epsilon-O(k^{-1})$ approximation for submodular function maximization in the random order streaming model. This substantially improves upon the previously best known approximation factor of $1/2 + 8 \times 10^{-14}$ [Norouzi-Fard et al. 2018] that used a memory buffer of size $O(k \log k)$.
Identifying Brain Networks at Multiple Time Scales via Deep Recurrent Neural Network

For decades, task functional magnetic resonance imaging has been a powerful noninvasive tool to explore the organizational architecture of human brain function. Researchers have developed a variety of brain network analysis methods for task fMRI data, including the general linear model, independent component analysis, and sparse representation methods. However, these shallow models are limited in faithful reconstruction and modeling of the hierarchical and temporal structures of brain networks, as demonstrated in more and more studies. Recently, recurrent neural networks (RNNs) exhibit great ability of modeling hierarchical and temporal dependence features in the machine learning field, which might be suitable for task fMRI data modeling. To explore such possible advantages of RNNs for task fMRI data, we propose a novel framework of a deep recurrent neural network (DRNN) to model the functional brain networks from task fMRI data. Experimental results on the motor task fMRI data of Human Connectome Project 900 subjects release demonstrated that the proposed DRNN can not only faithfully reconstruct functional brain networks, but also identify more meaningful brain networks with multiple time scales which are overlooked by traditional shallow models. In general, this work provides an effective and powerful approach to identifying functional brain networks at multiple time scales from task fMRI data.
Urban Image Stitching using Planar Perspective Guidance

Image stitching methods with spatially-varying homographies have been proposed to overcome partial misalignments caused by global perspective projection; however, local warp operators often fracture the coherence of linear structures, resulting in an inconsistent perspective. In this paper, we propose an image stitching method that warps a source image to a target image by local projective warps using planar perspective guidance. We first detect line structures that converge into three vanishing points, yielding line-cluster probability functions for each vanishing point. Then we estimate local homographies that account for planar perspective guidance from the joint probability of planar guidance, in addition to spatial coherence. This allows us to enhance linear perspective structures while warping multiple urban images with grid-like structures. Our results validate the effectiveness of our method over state-of-the-art projective warp methods in terms of planar perspective.
Type 2 Diabetes and Glycemic Variability: Various Parameters in Clinical Practice

It has become possible to measure blood glucose levels continuously from 24 h to approximately 2 weeks due to the recent development of relevant devices such as continuous glucose monitoring and flash glucose monitoring systems. This has enabled not only medical professionals but also patients to monitor details of glycemic variability (GV) which was not possible in the past. Details of GV for both short and intermediate periods can now be obtained, and it is important in patient care to appropriately evaluate the data obtained. Types of GV in terms of time frame vary from short-term to long-term. Several studies reported that long-term GV was related to micro- and macro-angiopathies in patients with type 2 diabetes mellitus (T2DM). However, there are still unknown aspects regarding the relationships of various durations of GV with prognosis. Further clinical trials are required to examine the mechanism of GV and to evaluate whether GV can be a valuable therapeutic target in treatment of patients with T2DM.
Patch-based Interferometric Phase Estimation via Mixture of Gaussian Density Modelling & Non-local Averaging in the Complex Domain

This paper addresses interferometric phase (InPhase) image denoising, i.e., the denoising of phase modulo-2p images from sinusoidal 2p-periodic and noisy observations. The wrapping discontinuities present in the InPhase images, which are to be preserved carefully, make InPhase denoising a challenging inverse problem. We propose a novel two-step algorithm to tackle this problem by exploiting the non-local self-similarity of the InPhase images. In the first step, the patches of the phase images are modelled using Mixture of Gaussian (MoG) densities in the complex domain. An Expectation Maximization(EM) algorithm is formulated to learn the parameters of the MoG from the noisy data. The learned MoG is used as a prior for estimating the InPhase images from the noisy images using Minimum Mean Square Error (MMSE) estimation. In the second step, an additional exploitation of non-local self-similarity is done by performing a type of non-local mean filtering. Experiments conducted on simulated and real (MRI and InSAR) datasets show results which are competitive with the state-of-the-art techniques.
Working in Chains: African Informal Workers and Global Value Chains

This article examines how global value chains alter the processes of value creation by reshaping the institutional systems that govern the livelihoods of poor rural workers in contemporary Africa. In connecting rural workers to distant markets, global value chains reconfigure local modes of organization and resource use, translating and redistributing value in unexpected ways. The capacity of global linkages to resolve problems of rural poverty and disaffection is explored in the context of informal workers in horticultural farms in South Africa and precarious women producers of exotic oil in the Argan forests of south-western Morocco. Particular attention is focused on the mechanisms through which global linkages reconfigure institutional systems in the creation of transnational value chains, realigning labor regimes, livelihoods, and local commercial systems, followed by a consideration of the social tensions created by the economic and organizational realignment needed to make global value chains work.
Combined Internal and External Category-Specific Image Denoising

In this paper, we present a category-specific image denoising algorithm that exploits patch similarity within the input image and between the input image and an external dataset. We rely on standard internal denoising for smooth regions while consulting external images in the same category as the input to denoise textured regions. The external denoising component estimates the latent patches using the statistics, i.e. means and covariance matrices, of external patches, subject to a low-rank constraint. In the final stage, we aggregate results of internal and external denoising using a weighting rule based on the patch SNR measure. Our experimental results on five datasets confirms that the proposed algorithm produces superior results compared with state-of-the-art denoising methods both qualitatively and quantitatively.
Executive (dys)function after traumatic brain injury: special considerations for behavioral pharmacology

Executive function is an umbrella term that includes cognitive processes such as decision-making, impulse control, attention, behavioral flexibility, and working memory. Each of these processes depends largely upon monoaminergic (dopaminergic, serotonergic, and noradrenergic) neurotransmission in the frontal cortex, striatum, and hippocampus, among other brain areas. Traumatic brain injury (TBI) induces disruptions in monoaminergic signaling along several steps in the neurotransmission process – synthesis, distribution, and breakdown – and in turn, produces long-lasting deficits in several executive function domains. Understanding how TBI alters monoamingeric neurotransmission and executive function will advance basic knowledge of the underlying principles that govern executive function and potentially further treatment of cognitive deficits following such injury. In this review, we examine the influence of TBI on the following measures of executive function – impulsivity, behavioral flexibility, and working memory. We also describe monoaminergic-systems changes following TBI. Given that TBI patients experience alterations in monoaminergic signaling following injury, they may represent a unique population with regard to pharmacotherapy. We conclude this review by discussing some considerations for pharmacotherapy in the field of TBI.
Whole genome sequencing of Neisseria meningitidis W isolates from the Czech Republic recovered in 1984–2017

Introduction The study presents the analysis of whole genome sequence (WGS) data for Neisseria meningitidis serogroup W isolates recovered in the Czech Republic in 1984 – 2017 and their comparison with WGS data from other countries. Material and Methods Thirty-one Czech N. meningitidis W isolates, 22 from invasive meningococcal disease (IMD) and nine from healthy carriers were analysed. The 33-year study period was divided into three periods: 1984-1999, 2000-2009, and 2010-2017. Results Most study isolates from IMD and healthy carriers were assigned to clonal complex cc22 (n = 10) in all study periods. The second leading clonal complex was cc865 (n = 8) presented by IMD (n = 7) and carriage (n = 1) isolates that emerged in the last study period, 2010 – 2017. The third clonal complex was cc11 (n = 4) including IMD isolates from the first (1984 – 1999) and third (2010 – 2017) study periods. The following clonal complex was cc174 (n = 3) presented by IMD isolates from the first two study periods, i.e. 1984 – 1999 and 2000 – 2009. One isolate of each cc41/44 and cc1136 originated from healthy carriers from the second study period, 2000 - 2009. The comparison of WGS data for N. meningitidis W isolates recovered in the Czech Republic in the study period 1984 – 2017 and for isolates from other countries recovered in the same period showed that clonal complex cc865, ST-3342 is unique to the Czech Republic since 2010. Moreover, the comparison shows that cc11 in the Czech Republic does not comprise novel hypervirulent lineages reported from both European and non-European countries. WGS data for Czech serogroup W meningococci point to the presence of MenB vaccine antigen genes and confirm the hypothesis about the MenB vaccine potential against N. meningitidis serogroup W. All 31 study isolates were assigned to Bexsero® Antigen Sequence Types (BAST), and seven of them were of newly described BASTs. Conclusions WGS analysis contributed considerably to a more detailed molecular characterization of N. meningitidis W isolates recovered in the Czech Republic over a 33-year period and allowed for a spatial and temporal comparison of these characteristics between isolates from the Czech Republic and other countries. In addition, the WGS data precised the base for the update of the recommendation for vaccination in the Czech Republic.
Do Superstitious Traders Lose Money?

Do superstitious traders lose money? We answer this question in the context of trading in the Taiwan Futures Exchange, where we exploit the Chinese superstition that the number “8” is lucky and the number “4” is unlucky. We find that individual investors, but not institutional investors, submit disproportionately more limit orders at “8” than at “4. ” This imbalance, defined as “superstition index” for each investor, is positively correlated with trading losses. Superstitious investors lose money mainly because of their bad market timing and stale orders. Nevertheless, the reliance on number superstition for limit order submissions does decrease with trading experience.
Effects of the Endocrine-Disrupting Chemicals, Vinclozolin and Polychlorinated Biphenyls, on Physiological and Sociosexual Phenotypes in F2 Generation Sprague-Dawley Rats

Background: Exposure to endocrine-disrupting chemicals (EDCs) during gestation influences development of the F1 generation offspring and can result in disease and dysfunction in adulthood. Limited evidence suggests consequences on the F2 generation, exposed as germ cells within the F1 fetus. These F2s provide a unique window into the programming effects of EDCs. Objective: This study assessed intergenerational effects of EDC exposure on adult physiology and behavior in Sprague-Dawley rats. Methods: Pregnant rats were exposed to either a polychlorinated biphenyl (PCB) mixture, Aroclor 1,221 (A1221), the fungicide vinclozolin (VIN), or the vehicle (VEH) (6% dimethylsulfoxide in sesame oil) alone. A1221 is weakly estrogenic, while VIN is antiandrogenic, enabling us to compare different classes of EDCs. The F1 male and female offspring were bred to generate the paternal- and maternal-lineage F2 generation. This F2 generation was assessed for physiological outcomes, ultrasonic vocalizations (USVs), and sexual behavior in adulthood. Results: Each EDC caused phenotypic effects in a sex- and lineage-dependent manner. The most robustly affected group was the paternal-lineage males. F2 VIN paternal male descendants had increased body weight throughout the lifespan, lower concentrations of circulating estradiol, and lower adrenal and testicular indices. Both VIN and A1221 paternal-lineage males also exhibited the greatest number of changes in the characteristics of USVs in response to an opposite-sex animal and changes in sexual behaviors in a mating test. Conclusion: Exposure of rats to EDCs at the germ cell stage led to differences in the physiological and behavioral phenotype later in life, especially in males. This finding has implications for multigenerational physiological and reproductive health in wildlife and humans. https://doi.org/10.1289/EHP3550
Primary Structure Analysis of Antifungal Peptides from Cultivated and Wild Cereals

Cereal-derived bioactive peptides with antimicrobial activity have been poorly explored compared to those from dicotyledonous plants. Furthermore, there are a few reports addressing the structural differences between antimicrobial peptides (AMPs) from cultivated and wild cereals, which may shed light on significant varieties in the range and level of their antimicrobial activity. We performed a primary structure analysis of some antimicrobial peptides from wild and cultivated cereals to find out the features that are associated with the much higher antimicrobial resistance characteristic of wild plants. In this review, we identified and analyzed the main parameters determining significant antifungal activity. They relate to a high variability level in the sequences of C-terminal fragments and a high content of hydrophobic amino acid residues in the biologically active defensins in wild cereals, in contrast to AMPs from cultivated forms that usually exhibit weak, if any, activity. We analyzed the similarity of various physicochemical parameters between thionins and defensins. The presence of a high divergence on a fixed part of any polypeptide that is close to defensins could be a determining factor. For all of the currently known hevein-like peptides of cereals, we can say that the determining factor in this regard is the structure of the chitin-binding domain, and in particular, amino acid residues that are not directly involved in intermolecular interaction with chitin. The analysis of amino acid sequences of alpha-hairpinins (hairpin-like peptides) demonstrated much higher antifungal activity and more specificity of the peptides from wild cereals compared with those from wheat and corn, which may be associated with the presence of a mini cluster of positively charged amino acid residues. In addition, at least one hydrophobic residue may be responsible for binding to the components of fungal cell membranes.
Hypertension in Sudanese individuals and associated risk factors: the critical intersection between salt and sugar intake.

Background Hypertension is common problem across the globe. The aim of this study was to assess the prevalence of hypertension and impact of salt and sugar intake in Sudanese population. Methods A descriptive cross sectional study, included 323 of participants in Khartoum state. The data collection was performed to gather demographic information, physical activity and dietary habits. In addition to measurement of blood pressure (BP), weight and height measurement for calculation of body mass index (BMI). Results Among the 323 respondents (males were 171), 29 (9%) are known hypertensive, 60 (18.6%) are diagnosed to be hypertensive. Therefore, the prevalence of hypertension is 27.6%. Hypertension was significantly associated with male sex, increasing age, obesity, low physical activity, salt and sugar intake. Logistic regression analysis showed that increasing age, obesity and high sugar intake are absolute predictors for hypertension in Sudanese population. Conclusions The prevalence of hypertension was 27.6%. Hypertension in Sudanese individuals was associated with high sugar and salt intake, obesity and increase in age. Therefore, decreasing sugar and salt intake should be advocated by health authorities and the public in Sudan.
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation

Transferring representations from large supervised tasks to downstream tasks has shown promising results in AI fields such as Computer Vision and Natural Language Processing (NLP). In parallel, the recent progress in Machine Translation (MT) has enabled one to train multilingual Neural MT (NMT) systems that can translate between multiple languages and are also capable of performing zero-shot translation. However, little attention has been paid to leveraging representations learned by a multilingual NMT system to enable zero-shot multilinguality in other NLP tasks. In this paper, we demonstrate a simple framework, a multilingual Encoder-Classifier, for cross-lingual transfer learning by reusing the encoder from a multilingual NMT system and stitching it with a task-specific classifier component. Our proposed model achieves significant improvements in the English setup on three benchmark tasks - Amazon Reviews, SST and SNLI. Further, our system can perform classification in a new language for which no classification data was seen during training, showing that zero-shot classification is possible and remarkably competitive. In order to understand the underlying factors contributing to this finding, we conducted a series of analyses on the effect of the shared vocabulary, the training data type for NMT, classifier complexity, encoder representation power, and model generalization on zero-shot performance. Our results provide strong evidence that the representations learned from multilingual NMT systems are widely applicable across languages and tasks.
IL-23 inhibitors for moderate-to-severe psoriasis

Since the identification of high levels of interleukin 23 (IL-23) in psoriasis lesional skin, as well as finding that IL-23 was the most important source of the p40 subunit shared by IL-12 and IL-23, significant effort has been made in identifying potential new drugs that specifically block the unique IL-23 p19 subunit. At this time, 2 inhibitors of IL-23 p19 have been approved by the United States Food and Drug Administration, guselkumab and tildrakizumab. Two other agents, risankizumab and mirikizumab, have completed phase 3 and phase 2 of development, respectively. Pivotal trials in the development of these agents and clinical use of the approved agents are discussed. Thus far, this class of medications seems to provide a high level of efficacy, along with infrequent dosing and very favorable safety results.