Miracle-dz/UniFAR-FTUs huggingface dataset:
A long way to go – Estimates of combined water, sanitation and hygiene coverage for 25 sub-Saharan African countries

Background Water, sanitation and hygiene (WASH) are essential for a healthy and dignified life. International targets to reduce inadequate WASH coverage were set under the Millennium Development Goals (MDGs, 1990–2015) and now the Sustainable Development Goals (SDGs, 2016–2030). The MDGs called for halving the proportion of the population without access to adequate water and sanitation, whereas the SDGs call for universal access, require the progressive reduction of inequalities, and include hygiene in addition to water and sanitation. Estimating access to complete WASH coverage provides a baseline for monitoring during the SDG period. Sub-Saharan Africa (SSA) has among the lowest rates of WASH coverage globally. Methods The most recent available Demographic Household Survey (DHS) or Multiple Indicator Cluster Survey (MICS) data for 25 countries in SSA were analysed to estimate national and regional coverage for combined water and sanitation (a combined MDG indicator for ‘improved’ access) and combined water with collection time within 30 minutes plus sanitation and hygiene (a combined SDG indicator for ‘basic’ access). Coverage rates were estimated separately for urban and rural populations and for wealth quintiles. Frequency ratios and percentage point differences for urban and rural coverage were calculated to give both relative and absolute measures of urban-rural inequality. Wealth inequalities were assessed by visual examination of coverage across wealth quintiles in urban and rural populations and by calculating concentration indices as standard measures of relative wealth related inequality that give an indication of how unevenly a health indicator is distributed across the wealth distribution. Results Combined MDG coverage in SSA was 20%, and combined basic SDG coverage was 4%; an estimated 921 million people lacked basic SDG coverage. Relative measures of inequality were higher for combined basic SDG coverage than combined MDG coverage, but absolute inequality was lower. Rural combined basic SDG coverage was close to zero in many countries. Conclusions Our estimates help to quantify the scale of progress required to achieve universal WASH access in low-income countries, as envisaged under the water and sanitation SDG. Monitoring and reporting changes in the proportion of the national population with access to water, sanitation and hygiene may be useful in focusing WASH policy and investments towards the areas of greatest need.
Biochemical properties of penicillin amidohydrolase from Micrococcus luteus

Some biochemical properties of whole-cell penicillin amidohydrolase from Micrococcus luteus have been studied. This whole-cell enzyme showed its maximal activity at 36 degrees C at pH 7.5. It was found that the activation energy of this enzyme was 8.03 kcal (ca. 33.6 kJ) per mol, and this amidohydrolase showed first-order decay at 36 degrees C. The penicillin amidohydrolase was deactivated rapidly at temperatures above 50 degrees C during storage or preincubation for 24 h. The Michaelis constant, Km, for penicillin G was determined as 2.26 mM, and the substrate inhibition constant, Kis, was 155 mM. The whole-cell penicillin amidohydrolase from M. luteus was capable of hydrolyzing penicillin G, penicillin V, ampicillin, and cephalexin, but not cephalosporin C and cloxacillin. This whole-cell enzyme also had synthetic activity for semisynthetic penicillins or cephalosporins from D-(--)-alpha-phenylglycine methyl ester and 6-alpha-aminopenicillanic acid or 7-amino-3-deacetoxycephalosporanic acid.
Triple-Mode Dielectric-Loaded Cylindrical Cavity Diplexer Using Novel Packaging Technique for LTE Base-Station Applications

This paper proposes a triple-mode dielectric-loaded cylindrical cavity diplexer by using a novel packaging technique for long term evolution (LTE) base station applications. Four metal cavities, loaded by a triple-mode dielectric resonator (DR), are designed to resonate at two different frequencies for the diplexer operation. In this context, three resonant modes of a single cavity are classified as a TM mode and a pair of hybrid degenerate modes (HE modes). The two degenerate modes in the same cavity are properly excited by employing an off-centered DR instead of a traditional corner-cut structure as a perturbation element. Finally, such a diplexer is designed and fabricated, and good agreement between measurement and simulation is achieved.
Role of imaging in the management of neuro-ophthalmic disorders

Advancements in physics, computers, and imaging science in the last century have seen neuro-imaging evolving from a plain X-ray to computed tomography, magnetic resonance imaging scans, noninvasive angiography, and special sequences such as fat suppression, fluid attenuation recovery and diffusion-weighted imaging. A prompt prescription of an appropriate imaging modality and the most suitable sequence can increase the diagnostic yield, and in many instances, it can be a sight-saving and even a life-saving decision. This article discusses basic principles of neuro-imaging, its common indications, and the appropriate application in an ophthalmology practice.
DIRECTIONAL CHANNEL MODELLING IN COST259 SWG 2.1

This paper summarizes the achievements of Subworkinggroup 2.1 (SWG2.1) of the COST259 initiative. A common approach for modelling the time-variant wideband angular-dispersive radio channel for link-level simulations is derived and the main parameters are described. The basic modelling philosophy is a stochastic signal description where deterministic a-priori information about the environment enters the model. The model is a generalization of the well-known COST207 models in three respects: (i) the directions of arrival both at the base station and the mobile station are included, (ii) not only macrocells, but also micro- and picocells are envisaged, (iii) large scale variations are modelled. To allow efficient simulations while still including large-scale variations, we have to distinguish between external, global, and local parameters. As part of the external parameters, a set of radio environments has been defined each of which is capable of generating several propagation scenarios. Global parameters tune the statistics of the local parameters and the actual realization. The relation between directional and non-directional models is touched by means of the wide-sense stationary uncorrelated-scattering (WSSUS) concept.
Nanoaggregate‐Embedded Beads as Novel Raman Labels for Biodetection

Novel Raman tags called nanoaggregate‐embedded beads (NAEBs) have been developed. NAEBs are silica‐coated, dye‐induced aggregates of a small number of metal nanoparticles. In this work, the Raman reporters used to induce aggregation of gold nanoparticles include strongly binding dyes such as XRITC, TRITC, and DTDC and weakly binding dyes such as R6G. Surface‐enhanced Raman scattering (SERS) signal from a single NAEB can be detected. This study also demonstrates that these SERS‐active beads can be used as Raman tags for bio‐detection.
Association Between the XRCC6 Polymorphisms and Cancer Risks

AbstractA number of studies have been carried out to investigate the association of X-ray repair complementing defective repair in Chinese hamster cells 6 (XRCC6) polymorphisms and cancer risks, and the results remained inconsistent and inconclusive.To assess the effect of XRCC6 polymorphisms on cancer susceptibility, we conducted a meta-analysis, up to May 23rd 2014, 6267 cases with different types of tumor and 7536 controls from 20 published case–control studies. Summary odds ratios and corresponding 95% confidence intervals for XRCC6 polymorphism and cancer risk were estimated using fixed- or random-effects models when appropriate. Heterogeneity was assessed by chi-squared-based Q-statistic test, and the sources of heterogeneity were explored by subgroup analyses, logistic meta-regression analyses and Galbraith plot. Publication bias was evaluated by Begg funnel plot and Egger test. Sensitivity analyses were also performed.The rs2267437 polymorphism was associated with a significant increase in risks of overall cancers, breast cancer, renal cell carcinoma and hepatocellular carcinoma, and it could increase the cancer risk in Asian population; the rs5751129 polymorphism could increase the cancer risk in overall cancers; the rs132770 polymorphism was associated with the increased renal cell carcinoma risk; furthermore, the rs132793 polymorphism could decrease breast cancer risk and increase risks in “other cancers”. Overall, the results provided evidences that the single nucleotide polymorphisms in XRCC6 promoter region might play different roles in various cancers, indicating different cancers have different tumorigenesis mechanisms. Our studies may perhaps supplement for the disease monitoring of cancers in the future, and additional studies to determine the exact molecular mechanism might provide us with interventions to protect the susceptible subgroups.
Quality Guarantees on k-Optimal Solutions for Distributed Constraint Optimization Problems

A distributed constraint optimization problem (DCOP) is a formalism that captures the rewards and costs of local interactions within a team of agents. Because complete algorithms to solve DCOPs are unsuitable for some dynamic or anytime domains, researchers have explored incomplete DCOP algorithms that result in locally optimal solutions. One type of categorization of such algorithms, and the solutions they produce, is k- optimality; a k-optimal solution is one that cannot be improved by any deviation by k or fewer agents. This paper presents the first known guarantees on solution quality for k-optimal solutions. The guarantees are independent of the costs and rewards in the DCOP, and once computed can be used for any DCOP of a given constraint graph structure.
Modular control of limit cycle locomotion over unperceived rough terrain

We present a general approach to design modular controllers for limit cycle locomotion over unperceived rough terrain. The control strategy uses a Central Pattern Generator (CPG) model implemented as coupled nonlinear oscillators as basis. Stumbling correction and leg extension reflexes are implemented as feedbacks for fast corrections, and model-based posture control mechanisms define feedbacks for continuous corrections. The control strategy is validated on a detailed physics-based simulated model of a compliant quadruped robot, the Oncilla robot. We demonstrate dynamic locomotion with a speed of more than 1.5 BodyLength/s over unperceived uneven terrains, steps, and slopes.
Analysis and Optimization of a Protocol for Mobile Element Discovery in Sensor Networks

Recent studies have demonstrated that mobile elements (MEs) are an efficient solution to help decrease dramatically energy consumption in wireless sensor networks (WSNs). However, in most of cases, sensors use duty cycle schemes to save energy, and unless the ME mobility pattern is deterministic, each sensor node has to discover the presence of the ME in the nearby area before starting to exchange data with it. Therefore, in such wireless sensor networks with mobile elements (in short, WSN-MEs), the definition and analysis of a protocol for efficient ME discovery becomes of fundamental importance. In this paper, we propose an extensive performance analysis of an easy-to-implement, hierarchical discovery protocol for WSN-MEs, called Dual Beacon Discovery (2BD) protocol, taking into account stochastic, multi-path, variable speed ME mobility patterns. We also derive the optimal parameter values that minimize the energy consumption of sensor nodes, while guaranteeing the minimum node throughput required by the applications under consideration. Finally, we compare the 2BD protocol with a classical solution based on Periodic Listening (PL). Our results show that 2BD can exploit its hierarchical mechanism and thus significantly increase lifetime, especially when the ME discovery phase is relatively long.
Evaluation of a Virtual Model Control for the selective support of gait functions using an exoskeleton

Robotic gait trainers are used all over the world for the rehabilitation of stroke patients, despite relatively little is known about how the robots should be controlled to achieve the optimal improvement. Most devices control complete joint trajectories and assume symmetry between both legs by either a position or an impedance control. However we believe that the control should not be on a joint level but on a subtask level (i.e. foot clearance, balance control). To this end we have chosen for virtual model control (VMC) to define a set of controllers that can assist in each of these tasks. Thus enabling the exoskeleton to offer selective support and evaluation of each substask during rehabilitation training. The bottleneck of the VMC performance is the ability to offer an end point impedance at the ankle as the arm between the joints is largest here. This endpoint impedance is evaluated in this paper to show the ability of our exoskeleton to offer the required moments to support all the gait functions defined in this paper. We have shown that it is possible to implement the VMCs necessary for selective support of gait functions using series elastic actuators with a non-linear transmission. For the vertical direction we measured an stiffness of 5 kN/m for all ranges at frequencies of up to 1 Hz as a near ideal spring. In the horizontal we measured op to 0.5 kN/m in the same frequency range. The crosstalk between the vertical and the horizontal directions has been shown to be small. This means that it is possible to selectively offer forces in either vertical or horizontal directions.
Stock Returns in Mergers and Acquisitions

This paper develops a real options framework to analyze the behavior of stock returns in mergers and acquisitions. In this framework, the timing and terms of takeovers are endogenous and result from value-maximizing decisions. The implications of the model for abnormal announcement returns are consistent with the available empirical evidence. In addition, the model generates new predictions regarding the dynamics of firm-level betas for the time period surrounding control transactions. Using a sample of 1090 takeovers of publicly traded US firms between 1985 and 2002, we present new evidence on the dynamics of firm-level betas, which is strongly supportive of the model's predictions.
Independent Delta/Theta Rhythms in the Human Hippocampus and Entorhinal Cortex

Theta oscillations in the medial temporal lobe (MTL) of mammals are involved in various functions such as spatial navigation, sensorimotor integration, and cognitive processing. While the theta rhythm was originally assumed to originate in the medial septum, more recent studies suggest autonomous theta generation in the MTL. Although coherence between entorhinal and hippocampal theta activity has been found to influence memory formation, it remains unclear whether these two structures can generate theta independently. In this study we analyzed intracranial electroencephalographic (EEG) recordings from 22 patients with unilateral hippocampal sclerosis undergoing presurgical evaluation prior to resection of the epileptic focus. Using a wavelet-based, frequency-band-specific measure of phase synchronization, we quantified synchrony between 10 different recording sites along the longitudinal axis of the hippocampal formation in the non-epileptic brain hemisphere. We compared EEG synchrony between adjacent recording sites (i) within the entorhinal cortex, (ii) within the hippocampus, and (iii) between the hippocampus and entorhinal cortex. We observed a significant interregional gap in synchrony for the delta and theta band, indicating the existence of independent delta/theta rhythms in different subregions of the human MTL. The interaction of these rhythms could represent the temporal basis for the information processing required for mnemonic encoding and retrieval.
Interactive Proof Search with Ludics : Short Abstract

Proof Theory and Computation. Recent developments in proof theory have led to major advances in the theory of programming languages. The modelling of computation using proofs impacted deeply the foundational studies of programming languages as well as many of their practical issues. Declarative programming languages have been related mainly in two ways to the mathematical theory of proofs: on the one hand, the “computation as proof normalization” paradigm provided a foundation for functional programming languages through the well-known Curry-Howard correspondence [9]. On the other hand the “computation as proof search” paradigm stands as a foundation for logic programming: the computation of a program is the search for a proof in some deductive system.
Hyper-Parameters Selection of LS-SVM Based on PSO Algorithm with Multi-Particles Sharing Strategy

To optimize the parameters of LS-SVM effectively, an improved Particle Swarm Optimization (PSO) algorithm is proposed to select the optimal parameters combination. For the improvement of the precocity in PSO algorithm, an multi-particles sharing strategy is introduced in simple PSO algorithm to enhance the convergence. The simulation indicates that the proposed PSO algorithm has a better selection on LS-SVM parameters.
Effect of maternal diabetes on gliogensis in neonatal rat hippocampus

Background: Diabetes in pregnancy is a common metabolic disorder associated with various adverse outcomes in the offspring including impairments in attention and memory and alterations in social behavior. Glial cells are proven to have a critical role in normal function of neurons, and alteration in their activity could contribute to disturbance in the brain function. The aim of this study was to investigate the effect of maternal diabetes on hippocampal mRNA expression and distribution pattern of glial fibrillary acidic protein (GFAP) immunoreactive glial cells in the dentate gyrus (DG) of rat neonate at postnatal day 14 (P14). Materials and Methods: Wistar female rats were randomly allocated in control, diabetic, and insulin-treated diabetic groups. Diabetes was induced by injection of streptozotocin from 4 weeks before gestation until parturition. After delivery, the male offspring was euthanized at P14. Results: Our results showed a significant higher level of hippocampal GFAP expression and an increase in the mean number of GFAP positive cells in the DG of diabetic group offspring (P < 0.05). We also found an insignificant up-regulation in the expression of GFAP and the mean number of positive cells in the insulin-treated diabetic group neonates as compared to control group (P > 0.05). Conclusion: The present study revealed that diabetes during pregnancy strongly increased the glial cells production in the developing rat hippocampus.
Exemplar Image Inpainting by Means of Curvature-Driven Method

We present a new image inpainting method based on exemplar-based image inpainting idea by Curvature-Driven Diffusion (CDD) model in this paper. This method improves effectiveness and the linear structure propagation by rational confidence and data computing method. Therefore, our method can effectively prevent the "garbage" from producing during the process of inpainting, which is a common problem faced in other methods. With this method, one can obtain more pleasurable vision results than those obtained by other similar methods.
Clustering-based gene-subnetwork biomarker identification using gene expression data

The identification of predictive biomarkers of complex disease with robustness and specificity is an ongoing challenge. Gene expressions provide information on how the cell reacts to a particular state and the relationship of genes may lead to novel information. A network-based approach integrating expression data with protein-protein interaction network can be used to identify gene-subnetwork biomarkers for a particular disease. However, cancer datasets are heterogeneous in nature containing unknown or undefined subtypes of cancers. In this study, we propose a gene-subnetwork biomarker identification approach by implementing an Expectation-Maximization (EM) clustering technique to homogenize the dataset. To validate our proposed method. Lung cancer expression datasets are used to identify gene-subnetwork biomarkers. The evaluation of gene-subnetwork biomarkers is done by 5-fold cross-validation on an independent dataset. The comparison between non-clustering and clustering-based gene-subnetwork identification showed that clustering produced improved classification performance at a statistically significant level. Furthermore, preliminary functional analysis results showed more significant subnetworks were identified using the proposed approach.
Genetic algorithms in crystallographic texture analysis

The method of genetic algorithms (GA) is a modern computer technique based on some ideas taken from biological evolution theory. GA is especially useful for a study of problems being not completely determined. They are, e. g. , problems having a few but not very different solutions or problems without a strict (exact) solution. In the last situation the GA application can be very useful if it is enough to find a good solution but not necessarily the best one. In GA approach it is not necessary to know a priori a general scheme of problem solution; however, it is important to have a procedure estimating the quality of a solution. This procedure is necessary to eliminate some solutions and to accept other ones. In last years the GA method was applied with success in different areas of science, e. g. , in: sociology, construction engineering, artificial intelligence and many others. The present work reports the first result (to the authors' knowledge) of GA application in crystallographic texture analysis: the orientation distribution function (ODF) is calculated from a set of pole figures (PFs); consequently, the GA method may be considered as an alternative method of texture analysis. It is possible, however, to apply GA to other practical problems in the field of crystallographic textures. One of such problems may be finding of the best texture giving required material properties. This may be, e.g., the research of a texture which optimises material proporties for a given application (e.g., drawability, electric or magnetic properties).
The Spite Motive and Equilibrium Behavior in Auctions

Abstract We study auctions where bidders have independent private values but attach a disutility to the surplus of rivals, and derive symmetric equilibria for first-price, second-price, English, and Dutch auctions. We find that equilibrium bidding is more aggressive than standard predictions. Indeed, in second-price auctions it is optimal to bid above one's valuation; that is, bidding "frenzies" can arise in equilibrium. Further, revenue equivalence between second-price and first-price auctions breaks down, with second-price outperforming first-price. We also find that strategic equivalence between second-price and English auctions no longer holds, although they remain revenue equivalent. We conclude that spiteful bidding rationalizes anomalies observed in laboratory experiments across the four auction forms better than the leading alternatives.