Miracle-dz/UniFAR-FTUs huggingface dataset:
Sampling Requirements and Accelerated Schemes for Sparse Linear Regression with Orthogonal Least-Squares

We study the problem of inferring a sparse vector from random linear combinations of its components. We propose the Accelerated Orthogonal Least-Squares (AOLS) algorithm that improves performance of the well-known Orthogonal Least-Squares (OLS) algorithm while requiring significantly lower computational costs. While OLS greedily selects columns of the coefficient matrix that correspond to non-zero components of the sparse vector, AOLS employs a novel computationally efficient procedure that speeds up the search by anticipating future selections via choosing $L$ columns in each step, where $L$ is an adjustable hyper-parameter. We analyze the performance of AOLS and establish lower bounds on the probability of exact recovery for both noiseless and noisy random linear measurements. In the noiseless scenario, it is shown that when the coefficients are samples from a Gaussian distribution, AOLS with high probability recovers a $k$-sparse $m$-dimensional sparse vector using ${\cal O}(k\log \frac{m}{k+L-1})$ measurements. Similar result is established for the bounded-noise scenario where an additional condition on the smallest nonzero element of the unknown vector is required. The asymptotic sampling complexity of AOLS is lower than the asymptotic sampling complexity of the existing sparse reconstruction algorithms. In simulations, AOLS is compared to state-of-the-art sparse recovery techniques and shown to provide better performance in terms of accuracy, running time, or both. Finally, we consider an application of AOLS to clustering high-dimensional data lying on the union of low-dimensional subspaces and demonstrate its superiority over existing methods.
Equidistribution and counting for orbits of geometrically finite hyperbolic groups

Let G be the identity component of SO(n,1), acting linearly on a finite dimensional real vector space V. Consider a vector w_0 in V such that the stabilizer of w_0 is a symmetric subgroup of G or the stabilizer of the line Rw_0 is a parabolic subgroup of G. For any non-elementary discrete subgroup Gamma of G with w_0Gamma discrete, we compute an asymptotic formula for the number of points in w_0Gamma of norm at most T, provided that the Bowen-Margulis-Sullivan measure on the associated hyperbolic manifold and the Gamma skinning size of w_0 are finite. The main ergodic ingredient in our approach is the description for the limiting distribution of the orthogonal translates of a totally geodesically immersed closed submanifold of Gamma\H^n. We also give a criterion on the finiteness of the Gamma skinning size of w_0 for Gamma geometrically finite.
Inflammatory bone loss associated with MFG‐E8 deficiency is rescued by teriparatide

A prolonged increase in proinflammatory cytokines is associated with osteoporotic and autoimmune bone loss and, conversely, anti‐inflammatory pathways are associated with protection against bone loss. Milk fat globule‐epidermal growth factor (MFG‐E)‐8 is a glycoprotein that is proresolving, regulates apoptotic cell clearance, and has been linked to autoimmune disease and skeletal homeostasis. The role of MFG‐E8 in the young vs. adult skeleton was determined in mice deficient in MFG‐E8 (KO). In vivo, trabecular bone was similar in MFG‐E8KO and wild‐type (WT) mice at 6 and 16 wk, whereas 22 wk adult MFG‐E8KO mice displayed significantly reduced trabecular BV/TV. The number of osteoclasts per bone surface was increased in 22‐wk MFG‐E8 KO vs. WT mice, and recombinant murine MFG‐E8 decreased the number and size of osteoclasts in vitro. Adult MFG‐E8KO spleen weight:body weight was increased compared with WT, and flow cytometric analysis showed significantly increased myeloid‐derived suppressor cells (CD11bhiGR‐1+) and neutrophils (CD11bhiLy6G+) in MFG‐E8KO bone marrow, suggesting an inflammatory phenotype. PTH‐treated MFG‐E8KO mice showed a greater anabolic response (+124% BV/TV) than observed in PTH‐treated WT mice (+64% BV/TV). These data give insight into the role of MFG‐E8 in the adult skeleton and suggest that anabolic PTH may be a valuable therapeutic approach for autoimmune‐associated skeletal disease. —Michalski, M. N. , Seydel, A. L. , Siismets, E. M. , Zweifler, L. E. , Koh, A. J., Sinder, B. P., Aguirre, J. I. , Atabai, K. , Roca, H. , McCauley, L. K. Inflammatory bone loss associated with MFG‐E8 deficiency is rescued by teriparatide. FASEB J. 32, 3730–3741 (2018). www.fasebj. org
Perceived Depriving Parental Rearing and Depression

Four groups of depressed patients 47 unipolars, 21 bipolars, 34 with neurotic-reactive depression, and 39 with unspecified depressive disorder completed, after recovery, the EMBU, a Swedish instrument aimed at assessing the experience of parental rearing practices. The results for three factors: “rejection”, “emotional warmth” and “over-protection” and the global judgement scores of “severity” and “consistency” in rearing attitudes were compared with those obtained from 205 healthy individuals. Depressed patients, particularly in the unipolar unspecified groups rated both parents lower than the controls on emotional warmth. Patients tended also to rate their parents as less consistent in their rearing attitudes. The variables emotional warmth and overprotection allowed 64% of the patients and 72 of the unipolar depressives to be classified correctly. These results, like those of previous studies, support the hypothesis that deprivation of love during childhood represents an important psychological risk factor in the background of depressive disorders.
Late gestation undernutrition can predispose for visceral adiposity by altering fat distribution patterns and increasing the preference for a high-fat diet in early postnatal life

We have developed a sheep model to facilitate studies of the fetal programming effects of mismatched perinatal and postnatal nutrition. During the last trimester of gestation, twenty-one twin-bearing ewes were fed a normal diet fulfilling norms for energy and protein (NORM) or 50 % of a normal diet (LOW). From day 3 postpartum to 6 months (around puberty) of age, one twin lamb was fed a conventional (CONV) diet and the other a high-carbohydrate–high-fat (HCHF) diet, resulting in four groups of offspring: NORM-CONV; NORM-HCHF; LOW-CONV; LOW-HCHF. At 6 months of age, half of the lambs (all males and three females) were slaughtered for further examination and the other half (females only) were transferred to a moderate sheep diet until slaughtered at 24 months of age (adulthood). Maternal undernutrition during late gestation reduced the birth weight of LOW offspring (P< 0·05), and its long-term effects were increased adrenal size in male lambs and adult females (P< 0·05), increased neonatal appetite for fat-(P= 0·004) rather than carbohydrate-rich feeds (P< 0·001) and reduced deposition of subcutaneous fat in both sexes (P< 0·05). Furthermore, LOW-HCHF female lambs had markedly higher visceral:subcutaneous fat ratios compared with the other groups (P< 0·001). Postnatal overfeeding (HCHF) resulted in obesity (>30 % fat in soft tissue) and widespread ectopic lipid deposition. In conclusion, our sheep model revealed strong pre- and postnatal impacts on growth, food preferences and fat deposition patterns. The present findings support a role for subcutaneous adipose tissue in the development of visceral adiposity, which in humans is known to precede the development of the metabolic syndrome in human adults.
On the Chemical Composition of Sepiolite and Palygorskite

Many studies of the chemical composition of sepiolite and palygorskite have been carried out using analytical electron microscopy (AEM). According to the literature, a compositional gap exists between sepiolites and palygorskites, but the results presented here show that they may all be intermediate compositions between two extremes. The results of >1000 AEM analyses and structural formulae have been obtained for the samples studied (22 samples of sepiolite and 21 samples of palygorskite) and indicate that no compositional gap exists between sepiolite and palygorskite. Sepiolite occupies the most magnesic and trioctahedral extreme and palygorskite the most aluminic-magnesic and dioctahedral extreme. Sepiolite and palygorskite with intermediate compositions exist between the two pure extremes: (1) sepiolite with a small proportion of octahedral substitution; (2) palygorskite with a very wide range of substitution (the pure dioctahedral extreme is unusual); and (3) intermediate forms, Al-sepiolite and Mg-palygorskite with similar or the same chemical composition. The chemical compositions of the intermediate forms can be so similar that a certain degree of polymorphism exists between Al-sepiolite and Mg-palygorskite.
Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies

Over the past quarter of a century, there has been rapid development in structural biology, which now can provide solid evidence for understanding the functions of proteins. Concurrently, computational approaches with particular relevance to the chemical biology and drug design (CBDD) field have also incrementally and steadily improved. Today, these methods help elucidate detailed working mechanisms and accelerate the discovery of new chemical modulators of proteins. In recent years, integrating computational simulations and predictions with experimental validation has allowed for more effective explorations of the structure, function and modulation of important therapeutic targets. In this review, we summarize the main advancements in computational methodology development, which are then illustrated by several successful applications in CBDD. Finally, we conclude with a discussion of the current major challenges and future directions in the field.
Identifying Links Between Sexual Violence and Youth Violence Perpetration: New Opportunities for Sexual Violence Prevention.

Objective One promising opportunity for advancing sexual violence (SV) research and identifying new avenues for prevention involves examining other forms of violence that may share risk factors with SV. Youth violence (YV) is ideal for consideration given evidence of overlap in SV and YV risk factors, a large set of established YV risk factors across the social ecology, and the number of evidence-based YV prevention strategies available. The current paper identifies shared and unique risk factors for SV and YV and highlights evidence-based YV prevention strategies that impact these shared risk factors. Conclusions Researchers and program developers should consider adapting and evaluating evidence-based YV prevention strategies to prevent SV. Modifying these programs to address SV's unique risk factors may maximize their potential effectiveness. In addition, expanding SV research at the outer levels of the social ecology is critical to developing community-level prevention strategies. The YV literature suggests several potential risk factors at these levels in need of research for SV, including school connectedness, social disorganization, and availability of alcohol and drugs. Using the YV literature as a starting point for expanding SV research leverages prior investments in YV research, may help identify new SV prevention strategies at a limited cost, and moves the field more quickly toward implementation of cost-effective, multidomain violence prevention strategies in communities.
Genetic and epigenetic insights into uveal melanoma

Uveal melanoma (UM) is the most frequent primary intraocular tumor in Caucasian adults and is potentially fatal if metastases develop. While several prognostic genetic changes have been identified in UM, epigenetic influences are now getting closer attention. Recent technological advances have allowed to exam the human genome to a greater extent and have improved our understanding of several diseases including malignant tumors. In this context, there has been tremendous progress in the field of UM pathogenesis. Herein, we review the literature with emphasis on genetic alterations, epigenetic modifications and signaling pathways as well as possible biomarkers in UM. In addition, different research models for UM are discussed. New insights and major challenges are outlined in order to evaluate the current status for this potentially devastating disease.
Analysis of Secular Ground Motions in Istanbul from a Long-Term InSAR Time-Series (1992-2017)

The identification and measurement of ground deformations in urban areas is of great importance for determining the vulnerable parts of the cities that are prone to geohazards, which is a crucial element of both sustainable urban planning and hazard mitigation. Interferometric synthetic aperture radar (InSAR) time series analysis is a very powerful tool for the operational mapping of ground deformation related to urban subsidence and landslide phenomena. With an analysis spanning almost 25 years of satellite radar observations, we compute an InSAR time series of data from multiple satellites (European Remote Sensing satellites ERS-1 and ERS-2, Envisat, Sentinel-1A, and its twin sensor Sentinel-1B) in order to investigate the spatial extent and rate of ground deformation in the megacity of Istanbul. By combining the various multi-track InSAR datasets (291 images in total) and analysing persistent scatterers (PS-InSAR), we present mean velocity maps of ground surface displacement in selected areas of Istanbul. We identify several sites along the terrestrial and coastal regions of Istanbul that underwent vertical ground subsidence at varying rates, from 5 ± 1.2 mm/yr to 15 ± 2.1 mm/yr. The results reveal that the most distinctive subsidence patterns are associated with both anthropogenic factors and relatively weak lithologies along the Haramirede valley in particular, where the observed subsidence is up to 10 ± 2 mm/yr. We show that subsidence has been occurring along the Ayamama river stream at a rate of up to 10 ± 1.8 mm/yr since 1992, and has also been slowing down over time following the restoration of the river and stream system. We also identify subsidence at a rate of 8 ± 1.2 mm/yr along the coastal region of Istanbul, which we associate with land reclamation, as well as a very localised subsidence at a rate of 15 ± 2.3 mm/yr starting in 2016 around one of the highest skyscrapers of Istanbul, which was built in 2010.
The unreasonable effectiveness of the forget gate

Given the success of the gated recurrent unit, a natural question is whether all the gates of the long short-term memory (LSTM) network are necessary. Previous research has shown that the forget gate is one of the most important gates in the LSTM. Here we show that a forget-gate-only version of the LSTM with chrono-initialized biases, not only provides computational savings but outperforms the standard LSTM on multiple benchmark datasets and competes with some of the best contemporary models. Our proposed network, the JANET, achieves accuracies of 99% and 92.5% on the MNIST and pMNIST datasets, outperforming the standard LSTM which yields accuracies of 98.5% and 91%.
Distributed Task Allocation of Multiple Robots: A Control Perspective

The problem of dynamic task allocation in a distributed network of redundant robot manipulators for path-tracking with limited communications is investigated in this paper, where <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> fittest ones in a group of <inline-formula> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> redundant robot manipulators with <inline-formula> <tex-math notation="LaTeX">${n>k}$ </tex-math></inline-formula> are allocated to execute an object tracking task. The problem is essentially challenging in view of the interplay of manipulator kinematics and the dynamic competition for activation among manipulators. To handle such an intricate problem, a distributed coordination control law is developed for the dynamic task allocation among multiple redundant robot manipulators with limited communications and with the aid of a consensus filter. In addition, a theorem and its proof are presented for guaranteeing the convergence and stability of the proposed distributed control law. Finally, an illustrative example is provided and analyzed to substantiate the efficacy of the proposed control law.
ISI: Integrate Sensor Networks to Internet With ICN

Internet of Things (IoT) is a growing topic of interest. Billions of IoT devices are expected to connect to the Internet in the near future. These devices differ from the traditional devices operated in the Internet. In this paper, we argue that an information-centric networking (ICN), a new networking paradigm, is a more suitable architecture for the IoT compared to the currently prevailing IP-based network. We observe that recent works that propose to use ICN for IoT, either do not cover the need to integrate sensor networks with the Internet to realize IoT or do so inefficiently. There is a need to understand effective ways to integrate the various heterogeneous sensor networks with the Internet without affecting their current mode of operation. In this paper, we study the essential requirements for integrating sensor networks to the Internet. We provide an architecture with gateways for paving a way for the sensor networks to become a part of the IoT family. We further provide a naming schema for efficient operation of the resource constrained sensor networks, discuss mobility, security, communication patterns, and propose the most suitable choices for IoT networks.
Cascaded Random Forest for Hyperspectral Image Classification

This paper proposes a Cascaded Random Forest (CRF) method, which can improve the classification performance by means of combining two different enhancements into the Random Forest (RF) algorithm. In detail, on the one hand, a neighborhood rough sets based Hierarchical Random Subspace Method is designed for feature selection, which can improve the strength of base classifiers and increase the diversity between each two of the base classifiers; and on the other hand, Boosting is introduced into RF. As the minimization of the training error for updating the weights of samples in Boosting often leads to overfitting, we added out-of-bag error to update the sample weights in CRF. Different from the existing Boosting strategy that only one base classifier is generated at each iteration, the proposed CRF trains several base classifiers at each iteration. To evaluate the performance of our method, CRF is compared with other related RF methods and support vector machine on three benchmark hyperspectral datasets, and experimental results show that CRF can provide competitive solutions for hyperspectral image classification.
Electroconvulsive Therapy at a Veterans Health Administration Medical Center

Objectives Little epidemiologic research has examined the practice of electroconvulsive therapy (ECT). We investigated sociodemographic and clinical characteristics, service use, and psychotropic medication prescription patterns associated with ECT use at a Veterans Health Administration Medical Center. Methods Among veterans receiving specialty mental health services, we compared those who received ECT with those who did not using bivariate &khgr;2 and t tests and multivariate logistic regression. Results In fiscal year 2012, 11,117 veterans received specialty mental health services, of whom 50 received ECT (0.45%) in FY2012 or FY2013. Those who received ECT were more likely to be diagnosed with major depressive or bipolar disorders and had substantially higher levels of mental health service usage (Cohen d > 0.75) and psychotropic prescription fills, including antidepressants (Cohen d = 2.66), antipsychotics (Cohen d = 2.15), lithium (Cohen d = 1.34), mood stabilizers (Cohen d = 1.30), and anxiolytic/sedative/hypnotics (Cohen d = 1.34). Conclusions Our findings suggest that ECT is used as a treatment of last resort, although available evidence and guidelines recommend wider use.
Hyperspectral Imagery Semantic Interpretation Based on Adaptive Constrained Band Selection and Knowledge Extraction Techniques

In this paper, we propose a novel adaptive band selection approach for hyperspectral image semantic interpretation. This approach is based on constrained band selection (CBS) method and extracted knowledge coming from tensor locality preserving projection. The extracted knowledge is presented as a set of rules which are used to evaluate the importance of spectral bands for classes discrimination. Based on these extracted rules and the CBS approach, relevant bands are selected to enhance the hyperspectral image semantic interpretation. The main advantage of the proposed adaptive band selection approach is to allow the automatic selection of discriminant, distinctive and informative spectral bands, and improve the semantic interpretation of hyperspectral images. Experimental results on real images show that the proposed band selection approach reaches competitive good performances, in terms of classification accuracy.
Wearable Platform for Real-time Monitoring of Sodium in Sweat.

A fully integrated and wearable platform for harvesting and analysing sweat sodium concentration in real time during exercise has been developed and tested. The platform was largely produced using 3D printing, which greatly simplifies fabrication and operation compared to previous versions generated with traditional production techniques. The 3D printed platform doubles the capacity of the sample storage reservoir to about 1.3 ml, reduces the assembly time and provides simple and precise component alignment and contact of the integrated solid-state ion-selective and reference electrodes with the sorbent material. The sampling flowrate in the device can be controlled by introducing threads to enhance wicking of sweat from the skin, across the electrodes to the storage area. The platform was characterised in the lab and in exercise trials over a period of about 60 minutes continuous monitoring. Sweat sodium concentration was found to rise initially to approximately 17 mM and decline gradually over the period of the trial to about 11-12 mM.
An In Vitro Model of the Blood–Brain Barrier: Naegleria fowleri Affects the Tight Junction Proteins and Activates the Microvascular Endothelial Cells

Naegleria fowleri causes a fatal disease known as primary amoebic meningoencephalitis. This condition is characterized by an acute inflammation that originates from the free passage of peripheral blood cells to the central nervous system through the alteration of the blood–brain barrier. In this work, we established models of the infection in rats and in a primary culture of endothelial cells from rat brains with the aim of evaluating the activation and the alterations of these cells by N. fowleri. We proved that the rat develops the infection similar to the mouse model. We also found that amoebic cysteine proteases produced by the trophozoites and the conditioned medium induced cytopathic effect in the endothelial cells. In addition, N. fowleri can decrease the transendothelial electrical resistance by triggering the destabilization of the tight junction proteins claudin‐5, occludin, and ZO‐1 in a time‐dependent manner. Furthermore, N. fowleri induced the expression of VCAM‐1 and ICAM‐1 and the production of IL‐8, IL‐1β, TNF‐α, and IL‐6 as well as nitric oxide. We conclude that N. fowleri damaged the blood–brain barrier model by disrupting the intercellular junctions and induced the presence of inflammatory mediators by allowing the access of inflammatory cells to the olfactory bulbs.