Miracle-dz/UniFAR-FTUs huggingface dataset:
A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems

In this work we propose an energy-efficient, implantable, real-time, blind Adaptive Stimulation Artifact Rejection (ASAR) engine. This enables concurrent neural stimulation and recording for state-of-the-art closed-loop neuromodulation systems. Two engines, implemented in 40nm CMOS, achieve convergence of <42µs for Spike ASAR and <167µs for LFP ASAR, and can attenuate artifacts up to 100mVp-p by 49.2dB, without any prior knowledge of the stimulation pulse. The LFP and Spike ASAR designs occupy an area of 0.197mm2 and 0.209mm2, and consume 1. 73µW and 3. 02µW, respectively at 0.644V.
Effect of melatonin treatment on the developmental potential of parthenogenetic and somatic cell nuclear-transferred porcine oocytes in vitro

Summary Melatonin secreted from the mammalian pineal gland is a free-radical scavenger that protects tissues from cell damage. The present study examined the effects of addition of melatonin to the culture medium on the developmental potential of parthenogenetic and somatic cell nuclear-transferred (SCNT) porcine oocytes. Supplementation of the maturation medium with melatonin did not increase the maturation rate, the proportion of oocytes that cleaved and developed into blastocysts after parthenogenetic activation, or the blastocyst cell number compared to controls. When 10−7 M melatonin was added to the culture medium, the proportion of parthenogenetic oocytes that developed to the 2-cell and 4-cell stages was significantly higher than that of controls. The potential of melatonin-treated oocytes to develop into blastocysts was high but not significantly different from that of controls. The addition of 10−7 M melatonin to the culture medium did not increase the preimplantation development of SCNT oocytes. Melatonin treatment significantly reduced the levels of reactive oxygen species in 4-cell parthenogenetic and SCNT embryos, but did not reduce the proportion of apoptotic cells in parthenogenetic and SCNT blastocysts. Although the results indicated that parthenogenetic and SCNT melatonin -treated embryos had significantly lower levels of reactive oxygen species than controls, the potential of melatonin-treated embryos to develop into blastocysts was not significantly higher than that of controls, in contrast to previous reports. The beneficial effects of melatonin on the developmental potential of oocytes might depend on the culture conditions.
Edinburgh Research Explorer Towards Effective Tutorial Feedback for Explanation Questions : A Dataset and Baselines

We propose a new shared task on grading student answers with the goal of enabling welltargeted and flexible feedback in a tutorial dialogue setting. We provide an annotated corpus designed for the purpose, a precise specification for a prediction task and an associated evaluation methodology. The task is feasible but non-trivial, which is demonstrated by creating and comparing three alternative baseline systems. We believe that this corpus will be of interest to the researchers working in textual entailment and will stimulate new developments both in natural language processing in tutorial dialogue systems and textual entailment, contradiction detection and other techniques of interest for a variety of computational linguistics tasks.
Social Media Use and Online Political Participation Among College Students During the US Election 2012

A total of 4,556 US college students were surveyed immediately after Election 2012 to investigate what social media–related psychological and behavioral factors predicted their online political participation. Structural equation modeling and hierarchical multiple regression results showed that online social capital, political self-efficacy, and Facebook group participation were positive predictors of online political participation, while social trust did not directly influence online political participation. General political use of Facebook and Twitter was a positive predictor of online political participation; however, extensive Facebook and Twitter use was a negative predictor. Implications for research and political practice are discussed.
Fast particle filters for multi-rate sensors

Computational complexity is a major concern for practical use of the versatile particle filter (PF) for nonlinear filtering applications. Previous work to mitigate the inherent complexity includes the marginalized particle filter (MPF), with the fastSLAM algorithm as one important case. MPF utilizes a linear Gaussian sub-structure in the problem, where the Kalman filter (KF) can be applied. While this reduces the state dimension in the PF, the present work aims at reducing the sampling rate of the PF. The algorithm is derived for a class of models with linear Gaussian dynamic model and two multi-rate sensors, with different sampling rates, one slow with a nonlinear and/or non-Gaussian measurement relation and one fast with a linear Gaussian measurement relation. For this case, the KF is used to process the information from the fast sensor and the information from the slow sensor is processed using the PF. The problem formulation covers the important special case of fast dynamics and one slow sensor, which appears in many navigation and tracking problems.
CSI estimation method based on random beamforming for massive number of transmit antenna systems

Beamforming techniques offer array gain and spatial multiplexing gain in multiple input multiple output (MIMO) systems. Wireless systems with massive numbers of transmit antennas (Massive MIMO) are attractive to increase the channel capacity and/or energy efficiency. However, the downlink channel state information (CSI) estimation sequence suffers increased loss in terms of lower MAC efficiency and calculation complexity. This paper proposes a CSI feedback scheme based random beamforming weights for massive MIMO when the number of users is small. In the proposed scheme, the CSI estimation beams are randomly determined and the number of beams for CSI estimation is limited. By iteratively revising the random beamforming weight, the access point can obtain the CSI of the signal space of all transmit antennas. Simulation results show that the achievable bit rate of the proposed method approaches that of the full antenna CSI.
Genetic Determinants for n-Butanol Tolerance in Evolved Escherichia coli Mutants: Cross Adaptation and Antagonistic Pleiotropy between n-Butanol and Other Stressors

ABSTRACT Cross-tolerance and antagonistic pleiotropy have been observed between different complex phenotypes in microbial systems. These relationships between adaptive landscapes are important for the design of industrially relevant strains, which are generally subjected to multiple stressors. In our previous work, we evolved Escherichia coli for enhanced tolerance to the biofuel n-butanol and discovered a molecular mechanism of n-butanol tolerance that also conferred tolerance to the cationic antimicrobial peptide polymyxin B in one specific lineage (green fluorescent protein [GFP] labeled) in the evolved population. In this work, we aim to identify additional mechanisms of n-butanol tolerance in an independent lineage (yellow fluorescent protein [YFP] labeled) from the same evolved population and to further explore potential cross-tolerance and antagonistic pleiotropy between n-butanol tolerance and other industrially relevant stressors. Analysis of the transcriptome data of the YFP-labeled mutants allowed us to discover additional membrane-related and osmotic stress-related genes that confer n-butanol tolerance in E. coli. Interestingly, the n-butanol resistance mechanisms conferred by the membrane-related genes appear to be specific to n-butanol and are in many cases antagonistic with isobutanol and ethanol. Furthermore, the YFP-labeled mutants showed cross-tolerance between n-butanol and osmotic stress, while the GFP-labeled mutants showed antagonistic pleiotropy between n-butanol and osmotic stress tolerance.
Catabolite inactivation of heterologous fructose-1,6-bisphosphatases and fructose-1,6-bisphosphatase-beta-galactosidase fusion proteins in Saccharomyces cerevisiae.

Fructose-1,6-bisphosphatase (FruP2ase) from Saccharomyces cerevisiae is rapidly inactivated upon addition of glucose to a culture growing on non-sugar carbon sources. Under the same conditions the FruP2ases from Schizosaccharomyces pombe or Escherichia coli expressed in S. cerevisiae were not affected. A chimaeric protein containing the first 178 amino acids from the N-terminal half of S. cerevisiae FruP2ase fused to E. coli beta-galactosidase was susceptible to catabolite inactivation. Elimination of a putative destruction box, RAELVNLVG . KK . K. , beginning at amino acid 60 did not prevent catabolite inactivation. Similarly a change of the vacuole-targeting sequence QKKLD, amino acids 80-84, to QKNSD did not affect significantly the course of inactivation of beta-galactosidase. A fusion protein carrying only the first 138 amino acids from FruP2ase was inactivated at a higher rate than the one carrying the first 178, suggesting the existence of a protective region between amino acids 138 and 178. A fusion protein carrying the first 81 amino acids from FruP2ase was inactivated by glucose at a similar rate to the one carrying the 178 amino acids, but one with only the first 18 amino acids was resistant to catabolite inactivation. Inactivation of FruP2ase in mutants ubr1 that lack a protein required for ubiquitin-dependent proteolysis, or pra1 that lack vacuolar protease A, proceeded as in a wild type. Our results suggest that at least two domains of FruP2ase may mark beta-galactosidase for catabolite inactivation and that FruP2ase can be inactivated by a mechanism independent of transfer to the vacuole.
Regular Multivitamin Supplement Use, Single Nucleotide Polymorphisms in ATIC, SHMT2, and SLC46A1, and Risk of Ovarian Carcinoma

ATIC, SHMT2, and SLC46A1 have essential roles in one-carbon (1-C) transfer. The authors examined whether associations between ovarian carcinoma and 15 variants in these genes are modified by regular multivitamin use, a source of 1-C donors, among Caucasian participants from two US case–control studies. Using a phased study design, variant-by-multivitamin interactions were tested, and associations between variants and ovarian carcinoma were reported stratified by multivitamin supplement use. Per-allele risk associations were modified by multivitamin use at six variants among 655 cases and 920 controls (Phase 1). In a larger sample of 968 cases and 1,265 controls (Phases 1 and 2), interactions were significant (P ≤ 0.03) for two variants, particularly among regular multivitamin users: ATIC rs7586969 [odds ratio (OR) = 0.7, 95% confidence interval (CI) = 0.6–0.9] and ATIC rs16853834 (OR = 1.5, 95% CI = 1.1–2.0). The two ATIC single nucleotide polymorphisms (SNPs) did not share the same haplotype; however, the haplotypes they comprised mirrored their SNP risk associations among regular multivitamin supplement users. A multi-variant analysis was also performed by comparing the observed likelihood ratio test statistic from adjusted models with and without the two ATIC variant-by-multivitamin interaction terms with a null distribution of test statistics generated by permuting case status 10,000 times. The corresponding observed P value of 0.001 was more extreme than the permutation-derived P value of 0.009, suggesting rejection of the null hypothesis of no association. In summary, there is little statistical evidence that the 15 variants are independently associated with risk of ovarian carcinoma. However, the statistical interaction of ATIC variants with regular multivitamin intake, when evaluated at both the SNP and gene level, may support these findings as relevant to ovarian health and disease processes.
Rule Anomalies Detecting and Resolving for Software Defined Networks

Software Defined Network (SDN) is facilitating rapid innovation of network by providing a programmable network infrastructure. However, managing SDN flow rules, especially among multiple modules and administrators, has become complex and error-prone. Different controller modules with diverse objectives may be installed on the SDN controller, which can lead to anomalies among policies and rules. In this paper, we propose ADRS(Anomaly Detecting and Resolving for SDN) to solve this problem. Firstly, we analyse the rule-level anomalies that may occur in SDN based on OpenFlow protocol. Then we present an interval tree model for rapid rule scanning and a share model for network privilege allocating. By applying these models, we provide an automatic algorithm to detect and resolve the anomalies among SDN modules. Moreover, a rule-recovery mechanism is presented to avoid modification faults. We also implement and evaluate our system in the OpenDayLight controller.
Implementation of smart infrastructure and non-invasive wearable for real time tracking and early identification of diseases in cattle farming using IoT

The major objective of this system is to make infrastructure of cattle farming smarter and to implement a noninvasive wearable to track physiological and biological activities of cattle using Internet of Things alias IoT. Each cattle is tagged with a wearable device. The wearable device and sink node is designed based on architecture of device to cloud. The wearable device is for early detection of illness, abnormalities detection, emergency handling, location tracking, calving time intimation and determine disease before visual signs. The sink node is responsible for smart lighting, smart ventilation, smart watering and smoke detection along with sprinkler actuation to make infrastructure smarter and safer. All sensor readings will be forwarded to thingspeak cloud to enable remote access. Through thingspeak cloud real time health characteristics of individual cattle, smoke level in farm, daily water and electricity usage will be displayed in line graph. All data along with time and date can be extracted as an excel sheet for further analysis. As a result overall cattle health and milk production will be improved by reducing cattle health inspection costs ensuring small size, low cost, high consistency and reliability.
P2X Receptors: Epithelial Ion Channels and Regulators of Salt and Water Transport

When the results from electrophysiological studies of renal epithelial cells are combined with data from in vivo tubule microperfusion experiments and immunohistochemical surveys of the nephron, the accumulated evidence suggests that ATP-gated ion channels, P2X receptors, play a specialized role in the regulation of ion and water movement across the renal tubule and are integral to electrolyte and fluid homeostasis. In this short review, we discuss the concept of P2X receptors as regulators of salt and water salvage pathways, as well as acknowledging their accepted role as ATP-gated ion channels.
Contrasting Effects of Two Kinds of Boredom on Alcohol Use

Despite its prominence among common sense explanations of alcohol use and drinking problems, the phenomenon of boredom has received remarkably little attention among alcohol researchers. This study focuses on two distinctive kinds of boredom identified in an earlier survey and relates them to drinking behavior in a student sample. A scale of Existential Boredom (e.g., frequency of boredom, a lack of purpose in life) was found in multiple regression analyses to have a strong, positive relationship to frequency of alcohol use among males. A scale measuring Interpersonal Boredom (e.g., boredom with “small talk” versus feelings of “happiness with people”) was inversely related to quantity of alcohol consumed by both males and females. These and other findings suggest that the mundane situational experience of boredom has important consequences that are worthy of further sociological investigation.
Global Transcriptome Analysis of the Scorpion Centruroides noxius: New Toxin Families and Evolutionary Insights from an Ancestral Scorpion Species

Scorpion venoms have been studied for decades, leading to the identification of hundreds of different toxins with medical and pharmacological implications. However, little emphasis has been given to the description of these arthropods from cellular and evolutionary perspectives. In this report, we describe a transcriptomic analysis of the Mexican scorpion Centruroides noxius Hoffmann, performed with a pyrosequencing platform. Three independent sequencing experiments were carried out, each including three different cDNA libraries constructed from RNA extracted from the whole body of the scorpion after telson removal, and from the venom gland before and after venom extraction. Over three million reads were obtained and assembled in almost 19000 isogroups. Within the telson-specific sequences, 72 isogroups (0.4% of total unique transcripts) were found to be similar to toxins previously reported in other scorpion species, spiders and sea anemones. The annotation pipeline also revealed the presence of important elements of the small non-coding RNA processing machinery, as well as microRNA candidates. A phylogenomic analysis of concatenated essential genes evidenced differential evolution rates in this species, particularly in ribosomal proteins and proteasome components. Additionally, statistical comparison of transcript abundance before and after venom extraction showed that 3% and 2% of the assembled isogroups had higher expression levels in the active and replenishing gland, respectively. Thus, our sequencing and annotation strategies provide a general view of the cellular and molecular processes that take place in these arthropods, allowed the discovery of new pharmacological and biotechnological targets and uncovered several regulatory and metabolic responses behind the assembly of the scorpion venom. The results obtained in this report represent the first high-throughput study that thoroughly describes the universe of genes that are expressed in the scorpion Centruroides noxius Hoffmann, a highly relevant organism from medical and evolutionary perspectives.
Denoising Autoencoders for Fast Combinatorial Black Box Optimization

We integrate a Denoising Autoencoder (DAE) into an Estimation of Distribution Algorithm (EDA) and evaluate the performance of DAE-EDA on several combinatorial optimization problems. We asses the number of fitness evaluations and the required CPU times. Compared to the state-of-the-art Bayesian Optimization Algorithm (BOA), DAE-EDA needs more fitness evaluations, but is considerably faster, sometimes by orders of magnitude. These results show that DAEs can be useful tools for problems with low but non-negligible fitness evaluation costs.
Rainfall runoff modelling – Modellers Guide

How do I begin with hydrological modeling of a regional basin? Whether I shall go for continuous stream flow simulation model or distributed event based model? How do I reduce number of parameters to make my model parsimonious? What is the role of GIS in hydrological modeling? How do I carry out calibration, validation, and sensitivity analysis and uncertainty estimation for my model? There are many such questions arising in the modeler’s mind and he is supposed to find answers for all such questions to progress in his modeling studies. This paper is intended to serve as a source of information that beginners in rainfallrunoff modeling are often looking for.
Motor Primitives and Rehabilitation

To generate movements the CNS must handle the large number of degrees of freedom of the musculo-skeletal apparatus. Our results show the CNS solves this problem with an architecture based on the utilization of discrete building blocks to construct a variety of movements. The experimental evidence indicates that a small number of building blocks can explain a large fraction of the variation in the muscle pattern. The results represent a remarkable simplification in view of the high dimensionality of the space of all possible muscle pattern.
EMOTION RECOGNITION FROM MADARIN SPEECH SIGNALS

In this paper, a Mandarin speech based emotion cl assification method is presented. Five primary human emotions including anger, boredom, happiness, neutral and sadness are investigated. In emotion classification of speech signals, conventional features are statistics of fundamental frequency, loudness, duration and voice quality. However, the recognition accuracy of systems employing these features degrades substantially when more than two valence emotion categories are invoked. For speech emotion recognition, we select 16 LPC coefficients, 12 LPCC components, 16 LFPC components, 16 PLP coefficients, 20 MFCC components and jitter as the basic features to form the feature vector. A Mandarin corpus recorded by 12 non-professional speakers is employed. The recognizer presented in this paper is based on three recognition techniques: LDA, K-NN, and HMMs. Experimental results show that the selected features are robust and effective for the emotion recognition not only in the arousal dimension but also in the valence dimension.
An Empirical Assessment of Optimal Monetary Policy in the Euro Area

We estimate a New Keynesian DSGE model for the Euro area under alternative descriptions of monetary policy (discretion, commitment or a simple rule) after allowing for Markov switching in policy maker preferences and shock volatilities. This reveals that there have been several changes in Euro area policy making, with a strengthening of the anti-inflation stance in the early years of the ERM, which was then lost around the time of German reunification and only recovered following the turnoil in the ERM in 1992. The ECB does not appear to have been as conservative as aggregate Euro-area policy was under Bundesbank leadership, and its response to the financial crisis has been muted. The estimates also suggest that the most appropriate description of policy is that of discretion, with no evidence of commitment in the Euro-area. As a result although both ‘good luck’ and ‘good policy’ played a role in the moderation of inflation and output volatility in the Euro-area, the welfare gains would have been substantially higher had policy makers been able to commit. We consider a range of delegation schemes as devices to improve upon the discretionary outcome, and conclude that price level targeting would have achieved welfare levels close to those attained under commitment, even after accounting for the existence of the Zero Lower Bound on nominal interest rates.