Miracle-dz/UniFAR-FTUs huggingface dataset:
COLA: Decentralized Linear Learning

Decentralized machine learning is a promising emerging paradigm in view of global challenges of data ownership and privacy. We consider learning of linear classification and regression models, in the setting where the training data is decentralized over many user devices, and the learning algorithm must run on-device, on an arbitrary communication network, without a central coordinator. We propose COLA, a new decentralized training algorithm with strong theoretical guarantees and superior practical performance. Our framework overcomes many limitations of existing methods, and achieves communication efficiency, scalability, elasticity as well as resilience to changes in data and allows for unreliable and heterogeneous participating devices.
Performance Analysis of Large Intelligent Surfaces (LISs): Asymptotic Data Rate and Channel Hardening Effects

The concept of a large intelligent surface (LIS) has recently emerged as a promising wireless communication paradigm that can exploit the entire surface of man-made structures for transmitting and receiving information. An LIS is expected to go beyond massive multiple-input multiple-output (MIMO) system, insofar as the desired channel can be modeled as a perfect line-of-sight. To understand the fundamental performance benefits, it is imperative to analyze its achievable data rate, under practical LIS environments and limitations. In this paper, an asymptotic analysis of the uplink data rate in an LIS-based large antenna-array system is presented. In particular, the asymptotic LIS rate is derived in a practical wireless environment where the estimated channel on LIS is subject to estimation errors, interference channels are spatially correlated Rician fading channels, and the LIS experiences hardware impairments. Moreover, the occurrence of the channel hardening effect is analyzed and the performance bound is asymptotically derived for the considered LIS system. The analytical asymptotic results are then shown to be in close agreement with the exact mutual information as the number of antennas and devices increase without bounds. Moreover, the derived ergodic rates show that hardware impairments, noise, and interference from estimation errors and the non-line-of-sight path become negligible as the number of antennas increases. Simulation results show that an LIS can achieve a performance that is comparable to conventional massive MIMO with improved reliability and a significantly reduced area for antenna deployment.
Multiobjective self‐optimization of the cellular architecture for green 5G networks

Cellular architecture, energy efficiency, and self‐optimizing network are key features to meet the forecast requirements of the fifth‐generation networks. Frequently, the major optimization focus is on maximizing the data rate, but many other objectives are considered ahead to be optimized in the standardization of green fifth‐generation networks such as ubiquitous coverage, cost, availability, latency, automation, energy efficiency, load balancing, mobility, and awareness, which are often conflicting objectives. In this paper, we propose a multiobjective evolutionary framework using a real traffic profile and three‐dimensional beamforming to ensure green self‐optimization of the network cellular layouts. The framework is based on a genetic algorithm (GA) handling conflicting objectives: coverage, capacity, energy efficiency, load balancing, and mobility. The simulation results show a dynamic and automated design of the network layouts following the spatial and temporal fluctuation of the traffic. The sectors are switched‐on, shaped, and switched‐off only where and when required for both macro and virtual small cell layers.
A Novel Integrated Way for Deciphering the Glycan Code for the FimH Lectin

The fimbrial lectin FimH from uro- and enteropathogenic Escherichia coli binds with nanomolar affinity to oligomannose glycans exposing Manα1,3Man dimannosides at their non-reducing end, but only with micromolar affinities to Manα1,2Man dimannosides. These two dimannoses play a significantly distinct role in infection by E. coli. Manα1,2Man has been described early on as shielding the (Manα1,3Man) glycan that is more relevant to strong bacterial adhesion and invasion. We quantified the binding of the two dimannoses (Manα1,2Man and Manα1,3Man to FimH using ELLSA and isothermal microcalorimetry and calculated probabilities of binding modes using molecular dynamics simulations. Our experimentally and computationally determined binding energies confirm a higher affinity of FimH towards the dimannose Manα1,3Man. Manα1,2Man displays a much lower binding enthalpy combined with a high entropic gain. Most remarkably, our molecular dynamics simulations indicate that Manα1,2Man cannot easily take its major conformer from water into the FimH binding site and that FimH is interacting with two very different conformers of Manα1,2Man that occupy 42% and 28% respectively of conformational space. The finding that Manα1,2Man binding to FimH is unstable agrees with the earlier suggestion that E. coli may use the Manα1,2Man epitope for transient tethering along cell surfaces in order to enhance dispersion of the infection.
“R U Mad?”: Computerized text analysis of affect in social media relates to stress and substance use among ethnic minority emerging adult males

ABSTRACT Objective: This study examined the interactive role of affectivity and stress in substance use severity among ethnic minority, emerging adult males, using linguistic indicators of affect obtained through social media. Method: Participants were 119 emerging adult, ethnic minority males (ages 18–25) who provided access to their mobile phone text messaging and Facebook activity for 6-months. Computerized text analysis (LIWC2015) was used to obtain linguistic indices of positive and negative affect from texts and Facebook posts. The Perceived Stress Scale was used to measure stress, and items from the Drug Abuse Screening Test were used to measure substance use severity. Results: Generalized estimating equations showed that higher negative affect in texts was associated with greater substance use severity. Stress moderated the relationship between positive affect expressed in Facebook posts and substance use such that higher positive affect in Facebook posts was associated with less substance use at higher stress and greater substance use at lower stress. Conclusions: Findings highlight the complexities of interactions between stress and affectivity. Findings could inform development of substance use interventions for young males that employ social technologies.
Letter: association between proton pump inhibitors and the risk of hepatocellular carcinoma—authors’ reply

strains of Helicobacter pylori in patients with hepatocellular carcinoma. J Oncol Res Ther. 2017;3:1‐7. 9. Hatakeyama M. Oncogenic mechanisms of the Helicobacter pylori CagA protein. Nat Rev Cancer. 2004;4:688‐694. 10. Ward JM, Fox JG, Anver MR, et al. Chronic active hepatitis and associated liver tumors in mice caused by a persistent bacterial infection with a novel Helicobacter species. J Natl Cancer Inst. 1994;86:1222‐1227.
Ancient DNA: The quest for the best

It is the dream of all researchers working with ancient DNA to identify prior to DNA extraction from bone the specimens or specific zones within them that contain the highest proportion of endogenous DNA. As it impacts the sacrifice of precious ancient specimens and the financial support needed for the analyses, the question is of high importance to the scientific field of palaeogenomics. The “Holy Grail” of palaeogenomics was reached when Cristina Gamba et al. ( ) discovered that it was in the petrosal part of the temporal bone, the densest part of the mammalian skeleton, where DNA is exceptionally well preserved. As a consequence, osteological collections experienced a rush from palaeogenomicists to “harvest” these precious bone parts. In this issue of Molecular Ecology Resources, Alberti et al. ( ) describe the discovery of another promising source of relatively well‐preserved endogenous DNA, that they had identified through computed tomography (CT scans), the outermost layer of cortical bone. These bones being larger and more abundant than petrous bones, this discovery increases markedly the source material for high‐quality palaeogenomic studies and releases the pressure on osteological collections.
Examining the STEM Awareness and Entrepreneurship Levels of Pre-Service Science Teachers

The scientific and technological developments in today's world require countries to raise entrepreneurial, productive, critical, problem-solving, and entrepreneurial individuals. Therefore, STEM (Science, Technology, Engineering, and Mathematics) education has gained importance today. STEM education is defined as an approach that takes an interdisciplinary relationship and takes a holistic approach to science, technology, engineering, and mathematics. STEM education includes the activities that will increase the students' interest and orientations towards science, technology, engineering, and mathematics fields using the skills that should be possessed today. The aim of this study was to examine the STEM awareness and entrepreneurship levels of pre-service science teachers. The sample of the study consisted of 93 female and 20 male students studying in the Science Education Department at Afyon Kocatepe University. As a quantitative research type, survey method was used in this study. “STEM Awareness Scale” (SAS) developed by Buyruk and Korkmaz (2016) and “Entrepreneurship Scale for Teacher Candidates” developed by Deveci and Cepni (2015) were used as data collection tools. As a result of analyses, it was seen that science teachers' attitudes towards STEM education were positive. Females’ STEM awareness was significantly higher than males’ in both positive and negative sub-factors. STEM awareness of the first grade students was significantly lower than the other classes in the positive sub-factor, and significant differences were found between the first grade and second grade, and the second grade and the fourth grade in the negative sub-factor. There were no significant differences of entrepreneurship levels in terms of gender. Also, the entrepreneurship characteristics of the second grade were significantly higher than the other grade levels.
Magnetic resonance imaging correlates of neuro‐axonal pathology in the MS spinal cord

In people with multiple sclerosis (MS), the spinal cord is the structure most commonly affected by clinically detectable pathology at presentation, and a key part of the central nervous system involved in chronic disease deterioration. Indices, such as the spinal cord cross‐sectional area at the level C2 have been developed as tools to predict future disability, and—by inference—axonal loss. However, this and other histo‐pathological correlates of spinal cord magnetic resonance imaging (MRI) changes in MS remain incompletely understood. In recent years, there has been a surge of interest in developing quantitative MRI tools to measure specific tissue features, including axonal density, myelin content, neurite density, and orientation, among others, with an emphasis on the spinal cord. Quantitative MRI techniques including T1 and T2, magnetization transfer and a number of diffusion‐derived indices have all been applied to MS spinal cord. Particularly diffusion‐based MRI techniques combined with microscopic resolution achievable using high magnetic field scanners enable a new level of anatomical detail and quantification of indices that are clinically meaningful.
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models

Recent work has shown that it is possible to train deep neural networks that are provably robust to norm-bounded adversarial perturbations. Most of these methods are based on minimizing an upper bound on the worst-case loss over all possible adversarial perturbations. While these techniques show promise, they often result in difficult optimization procedures that remain hard to scale to larger networks. Through a comprehensive analysis, we show how a simple bounding technique, interval bound propagation (IBP), can be exploited to train large provably robust neural networks that beat the state-of-the-art in verified accuracy. While the upper bound computed by IBP can be quite weak for general networks, we demonstrate that an appropriate loss and clever hyper-parameter schedule allow the network to adapt such that the IBP bound is tight. This results in a fast and stable learning algorithm that outperforms more sophisticated methods and achieves state-of-the-art results on MNIST, CIFAR-10 and SVHN. It also allows us to train the largest model to be verified beyond vacuous bounds on a downscaled version of ImageNet.
A Heuristic for the Bounded Diameter Minimum Spanning Tree Problem

Given a connected, edge-weighted and undirected complete graph G(V,E,w), the bounded diameter minimum spanning tree (BDMST) problem deals with finding a spanning tree T of minimum cost in such a way that the diameter of T should not exceed D ≥ 2, where D is a given positive integer. This problem is NP-hard for 4 ≤ D < |V | - 1. In this paper, we present a problem-specific heuristic (Heu_BDMST) for the BD-MST problem. Heu_BDMST is a greedy approach that combines the concept of the Kruskal algorithm and the shortest path algorithm. On a set of benchmark Euclidean and non-Euclidean instances, Heu_BDMST is effective in comparison to well-known problem-specific heuristics in the literature.
Genomic Profiling of Parathyroid Carcinoma Reveals Genomic Alterations Suggesting Benefit from Therapy.

BACKGROUND Parathyroid carcinoma (PC) is a rare endocrine malignancy that can cause life-threatening hypercalcemia. We queried whether comprehensive genomic profiling (CGP) of PC might identify genomic alterations (GAs), which would suggest benefit from rationally matched therapeutics. METHODS We performed hybrid-capture-based CGP to identify GAs and tumor mutational burden (TMB) in tumors from patients with this malignancy. RESULTS There were 85 total GAs in 16 cases (5.3 GAs per case), and the median TMB was 1.7 mutations per megabase (m/Mb), with three cases having >20 m/Mb (18.7%). The genes most frequently harboring GA were CDC73 (38%), TP53 (38%), and MEN1 (31%). All MEN1-mutated cases also had loss of heterozygosity at that locus, but in contrast all CDC73-mutated cases retained heterozygosity. GAs suggesting potential benefit from matched targeted therapy were identified in 11 patients (69%) and most frequently found in PTEN (25%), NF1 (12.5%), KDR (12.5%), PIK3CA (12.5%), and TSC2 (12.5%). A patient whose tumor harbored KDR T668 K and who was treated with cabozantinib experienced a > 50% drop in parathyroid hormone level and radiographic partial response of 5.4 months with duration limited by toxicity. CONCLUSION CGP identified GAs in PC that suggest benefit from targeted therapy, as supported by an index case of response to a matched tyrosine kinase inhibitor. Moreover, the unexpectedly high frequency of high TMB (>20 m/Mb) suggests a subset of PC may benefit from immune checkpoint inhibitors. IMPLICATIONS FOR PRACTICE Parathyroid carcinoma (PC) is a rare endocrine malignancy that can cause life-threatening hypercalcemia. However, its molecular characteristics remain unclear, with few systemic therapeutic options available for this tumor. Hybrid-capture-based comprehensive genomic profiling of 16 primary cancers demonstrated presence of potentially actionable genomic alterations, including PTEN, NF1, KDR, PIK3CA, and TSC2, and a subset of hypermutated cancers with more than 20 mutations per megabase, the latter of which could benefit from immune checkpoint inhibitor therapy. A case benefiting from rationally matched targeted therapy for activating KDR mutation is also presented. These findings should be further investigated for their therapeutic potential.
Mitochondrial Respiratory Function in Peripheral Blood Cells from Huntington's Disease Patients

Patients with Huntington's disease display symptoms from both the central nervous system and peripheral tissues. Mitochondrial dysfunction has been implicated as part of the pathogenesis of the disease and has been reported in brain tissue and extracerebral tissues, such as muscle and blood cells, but the results are inconsistent. Therefore, the authors performed a refined evaluation of mitochondrial function in 2 types of peripheral blood cells from 14 patients with Huntington's disease and 21 control subjects. Several hypotheses were predefined, including impaired mitochondrial complex II function (primary), complex I function (secondary), and maximum oxidative phosphorylation capacity (secondary) in patient cells.
Quasi-hyperbolic momentum and Adam for deep learning

Momentum-based acceleration of stochastic gradient descent (SGD) is widely used in deep learning. We propose the quasi-hyperbolic momentum algorithm (QHM) as an extremely simple alteration of momentum SGD, averaging a plain SGD step with a momentum step. We describe numerous connections to and identities with other algorithms, and we characterize the set of two-state optimization algorithms that QHM can recover. Finally, we propose a QH variant of Adam called QHAdam, and we empirically demonstrate that our algorithms lead to significantly improved training in a variety of settings, including a new state-of-the-art result on WMT16 EN-DE. We hope that these empirical results, combined with the conceptual and practical simplicity of QHM and QHAdam, will spur interest from both practitioners and researchers. Code is immediately available.
Emerging therapeutic strategies for minimal change disease and focal and segmental glomerulosclerosis

ABSTRACT Introduction: Minimal change disease (MCD) and Focal and segmental glomerulosclerosis (FSGS) are two of the major causes of nephrotic syndrome (NS) in children and adults. According to KDIGO (Kidney Disease: Improving Global Outcomes) guidelines, the treatment of adult primary MCD and FSGS should be based on immunosuppressants and antiproteinuric drugs. Recently, Rituximab, a humanized monoclonal antibody (mAb) has emerged as a potential treatment for steroid or calcineurin inhibitor-dependent patients; it has however demonstrated lower efficacy in those with nephrotic syndrome that is resistant to the above indicated drugs. Area covered: Analysis of ongoing and already completed clinical trials, retrieved from clinicaltrials.gov, clinicaltrialsregister.eu and PubMed involving new therapies for nephrotic syndrome secondary to MCD and FSGS. Expert opinion: The most promising drugs under investigation for MCD and FSGS are mAbs. We are hopeful that new therapeutic options to treat multi-drug resistant MCD and FSGS will emerge from currently ongoing studies. What appears certain is the difficulty in enrolling patients affected by orphan renal diseases and the selection of valid endpoints in clinical trials, such as kidney failure.
Cognitive Behavioral Therapy in Movement Disorders: A Review

In addition to motor symptoms, patients with movement disorders often complain of psychiatric disturbances, including mood, anxiety, and impulse‐control disorders and psychosis. These abnormalities are often misdiagnosed and left untreated, thus resulting in a worse prognosis and lower quality of life. Besides the use of standard pharmacological treatments, psychiatric abnormalities can be treated by means of nonpharmacological approaches. These approaches include various types of psychological therapies, the most widely used being cognitive behavioral therapy (CBT). We reviewed all articles, conducted until 2014, that contained primary data derived from clinical trials and case reports on the effect of CBT in the most common movement disorders. One randomized, controlled study and several uncontrolled studies on the efficacy of CBT in Parkinson's disease (PD) have shown a short‐term benefit of depression and anxiety. In Tourette's syndrome (TS), CBT has been assessed in a number of large controlled clinical trials that have demonstrated an improvement in psychiatric disturbances and tics. There are no controlled studies on the efficacy of CBT in other types of movement disorders, such as dystonia, Huntington's disease, and essential tremor. Only a limited number of studies have evaluated the efficacy of CBT in the management of psychiatric disorders in movement disorders. The evidence available suggests that CBT is useful in TS and probably useful in PD. We recommend the planning of randomized, controlled clinical trials to investigate the effects of CBT and group CBT in the treatment of psychiatric disturbances in movement disorders.
Faster Matrix Completion Using Randomized SVD

Matrix completion is a widely used technique for image inpainting and personalized recommender system, etc. In this work, we focus on accelerating the matrix completion using faster randomized singular value decomposition (rSVD). Firstly, two fast randomized algorithms (rSVD-PI and rSVDBKI) are proposed for handling sparse matrix. They make use of an eigSVD procedure and several accelerating skills. Then, with the rSVD-BKI algorithm and a new subspace recycling technique, we accelerate the singular value thresholding (SVT) method in [1] to realize faster matrix completion. Experiments show that the proposed rSVD algorithms can be 6X faster than the basic rSVD algorithm [2] while keeping same accuracy. For image inpainting and movie-rating estimation problems, the proposed accelerated SVT algorithm consumes 15X and 8X less CPU time than the methods using svds and lansvd respectively, without loss of accuracy.
Increased surfactant protein‐D levels in the airways of preterm neonates with sepsis indicated responses to infectious challenges

Sepsis is multifactorial and potentially devastating for preterm neonates. Changes in surfactant protein‐D (SP‐D), phosphatidylcholine (PC) and PC molecular species during infection may indicate innate immunity or inflammation during sepsis. We aimed to compare these important pulmonary molecules in ventilated neonates without or with sepsis.
Pediatric HIV Infection and Decreased Prevalence of OPV Point Mutations Linked to Vaccine-associated Paralytic Poliomyelitis

Abstract Background Mutations associated with prolonged replication of the attenuated polioviruses found in oral poliovirus vaccine (OPV) can lead to vaccine-derived poliovirus (VDPV) and cause paralysis indistinguishable from that caused by wild poliovirus. In response, the World Health Organization has initiated the transition to exclusive use of inactivated poliovirus vaccine (IPV), with OPV administration in cases of outbreak. However, it is currently unclear how IPV-only vaccination, well known to provide humoral but not mucosal immunity, will impact the development of paralysis causing OPV variants. Children infected with human immunodeficiency virus (HIV) have been documented to show decreased mucosal immunity following OPV vaccination. Thus, HIV-infected children vaccinated with OPV may serve as proxy for children with IPV-only vaccination. Methods We conducted a prospective study of Zimbabwean infants receiving OPV as part of their routine vaccination schedule. Stool samples collected from OPV-vaccinated children serially until age 24 months were tested for OPV serotypes using a real-time polymerase chain reaction protocol that quantifies the amount of mutant OPV variants found in each sample. Results Out of 2130 stool samples collected from 402 infants 365 stool samples were OPV positive: 313 from 212 HIV-noninfected (HIV−) infants and 52 from 34 HIV-infected (HIV+) infants. HIV− infants showed significantly higher proportions of OPV mutants when compared to HIV+ infants. Conclusions HIV infection is associated with a reduced proportion of OPV vaccine associated paralytic polio mutants. These results suggest that OPV administered to individuals previously vaccinated only with IPV will show decreased propensity for OPV mutations.