Miracle-dz/UniFAR-FTUs huggingface dataset:
Response inhibition, preattentive processing, and sex difference in young children: an event-related potential study

Response inhibition and preattentive processing are two important cognitive abilities for child development, and the current study adopted both behavioral and electrophysiological protocols to examine whether young children’s response inhibition correlated with their preattentive processing. A Go/Nogo task was used to explore young children’s response inhibition performances and an Oddball task with event-related potential recordings was used to measure their preattentive processing. The behavioral results showed that girls committed significantly fewer commission error rates, which showed that girls had stronger inhibition control abilities than boys. Girls also achieved higher d′ scores in the Go/Nogo task, which indicated that they were more sensitive to the stimulus signals than boys. Although the electrophysiological results of preattentive processing did not show any sex differences, the correlation patterns between children’s response inhibition and preattentive processing were different between these two groups: the neural response speed of preattentive processing (mismatch negativity peak latency) negatively correlated with girls’ commission error rates and positively correlated with boys’ correct hit rates. The current findings supported that the preattentive processing correlated with human inhibition control performances, and further showed that girls’ better inhibition responses might be because of the influence of their preattentive processing.
Isolation of Probiotic Lactobacilli from Human Infants’ Stool Samples Exhibiting Antimicrobial Activity Against Pathogenic Microorganisms

Emergence of drug resistance amongst bacterial isolates has forced the scientific community to develop new and natural alternatives to prevent and treat diseases. One such alternative is the use of probiotics. The present study was undertaken to isolate probiotic lactobacilli from stool samples of 30 healthy breast fed infants (1-3 months old) to control gastrointestinal diseases in infants and children. Out of 50 isolates, three exhibited superior probiotic attributes like tolerance to lysozyme, low pH and bile salts and strong adhesion to intestinal epithelial Caco-2 cells. Two isolates were identified as Lactobacillus pentosus and third one as L. plantarum . All three lactobacilli inhibited the growth of common microbial gut pathogens ( Shigella dysenteriae, Escherichia coli , Salmonella thyphimurium, Staphylococcus aureus, Proteus vulgaris and Kleibseilla pneumoniae ). They successfully coaggregated pathogens mentioned above (15-55%) and competitively inhibited adherence of pathogens (8-48%) on intestinal epithelial Caco-2 cells. Moreover, these lactobacilli were completely biocompatible to each other and sensitive to commonly used antibiotics (amikacin, amoxicillin-clavulanic acid, cefoperazone, ciprofloxacin, cotrimoxazole, nalidixic acid). In conclusion, three lactobacilli isolates identified as L. pentosus strains and L. plantarum have the strong potential to be exploited for prophylactic and therapeutic control of gastrointestinal infections.
CBTune: Contextual Bandit Tuning for Logic Synthesis

—Logic synthesis pre-optimization involves applying a sequence of transformations called synthesis ﬂow to reduce the circuit’s Boolean logic graph, like AIG. However, the challenge lies in selecting and arranging these transformations due to the exponentially expanding solution space. In this work, we propose CBTune, a novel online learning framework that utilizes a contextual bandit algorithm to explore the solution space and generate synthesis ﬂows efﬁciently. We develop the Syn-LinUCB algorithm as the agent, which incorporates circuit characteristics and leverages long-term payoffs to guide decision-making, thus effectively preventing getting trapped in local optima. Experimental results show that our framework achieves the optimal synthesis ﬂow with a lower time cost, substantially reducing the number of AIG nodes and 6-LUTs compared to SOTA approaches.
AKT2/3 Subunits Render Guard Cell K+ Channels Ca2+ Sensitive

Inward-rectifying K+ channels serve as a major pathway for Ca2+-sensitive K+ influx into guard cells. Arabidopsis thaliana guard cell inward-rectifying K+ channels are assembled from multiple K+ channel subunits. Following the recent isolation and characterization of an akt2/3-1 knockout mutant, we examined whether the AKT2/3 subunit carries the Ca2+ sensitivity of the guard cell inward rectifier. Quantification of RT-PCR products showed that despite the absence of AKT2 transcripts in guard cells of the knockout plant, expression levels of the other K+ channel subunits (KAT1, KAT2, AKT1, and AtKC1) remained largely unaffected. Patch-clamp experiments with guard cell protoplasts from wild type and akt2/3-1 mutant, however, revealed pronounced differences in Ca2+ sensitivity of the K+ inward rectifier. Wild-type channels were blocked by extracellular Ca2+ in a concentration- and voltage-dependent manner. Akt2/3-1 mutants lacked the voltage-dependent Ca2+ block, characteristic for the K+ inward rectifier. To confirm the akt2/3-1 phenotype, two independent knockout mutants, akt2-1 and akt2::En-1 were tested, demonstrating that the loss of AKT2/3 indeed affects the Ca2+ dependence of guard cell inward rectifier. In contrast to AKT2 knockout plants, AKT1, AtKC1, and KAT1 loss-of-function mutants retained Ca2+ block of the guard cell inward rectifier. When expressed in HEK293 cells, AKT2 channel displayed a pronounced susceptibility toward extracellular Ca2+, while the dominant guard cell K+ channel KAT2 was Ca2+ insensitive. Thus, we conclude that the AKT2/3 subunit constitutes the Ca2+ sensitivity of the guard cell K+ uptake channel.
Comprehensive pan-cancer analysis of cfDNA methylation marks in tumors reveals complex epigenetic regulatory circuits and diagnostic biomarkers

DNA methylation is an extensively studied, stable, and fundamental epigenetic alteration in most cancer types 1 . Single-base-pair resolution analyses of DNA methylation is currently feasible 2 . Analysis of DNA methylation, in liquid biopsies hold practice-changing potentials 3-6 . Despite undeniable progress, clinical translation lags behind, mainly due to:
Efﬁcient Multi-View Multi-Target Tracking Using a Distributed Camera Network

— In this paper, we propose a multi-target tracking method using a distributed camera network, which can effectively handle the occlusion and reidenﬁcation problems by combining advanced deep learning and distributed information fusion. The targets are ﬁrst detected using a fast object detection method based on deep learning. We then combine the deep visual feature information and spatial trajectory information in the Hungarian algorithm for robust targets association. The deep visual feature information is extracted from a convolutional neural network, which is pre-trained using a large-scale person reidentiﬁcation dataset. The spatial trajectories of multiple targets in our framework are derived from a multiple view information fusion method, which employs an information weighted consensus ﬁlter for fusion and tracking. In addition, we also propose an efﬁcient track processing method for ID assignment using multiple view information. The experiments on public datasets show that the proposed method is robust to solve the occlusion problem and reidentiﬁcation problem, and can achieve superior performance compared to the state of the art methods.
NOTES AND

The parameterization of geostrophic eddies represents a large sink of energy in most ocean models, yet the ultimate fate of this eddy energy in the ocean remains unclear. The authors conjecture that a significant fraction of the eddy energy may be transferred to internal lee waves and oscillations over rough bottom topography, leading to bottom-enhanced diapycnal mixing. A range of circumstantial evidence in support of this conjecture is presented and discussed. The authors further propose a modification to the Gent and McWilliams eddy parameterization to account for the bottom-enhanced diapycnal mixing.
Stability of Bose condensed atomic 7Li.

We study the stability of a Bose condensate of atomic 7Li in a (harmonic oscillator) magnetic trap at nonzero temperatures. In analogy to the stability criterion for a neutron star, we conjecture that the gas becomes unstable if the free energy as a function of the central density of the cloud has a local extremum which conserves the number of particles. Moreover, we show that the number of condensate particles at the point of instability decreases with increasing temperature, and that for the temperature interval considered, the normal part of the gas is stable against density fluctuations at this point.
Stochastic Polynomial-Chaos-Based Average Modeling of Power Electronic Systems

With the introduction of variable-frequency generators in next-generation more-electric aircraft, both voltage and frequency are to reveal significant tolerance levels. In this study, a method based on the combination of polynomial chaos and nodal analysis is developed to identify and quantify the impact of such tolerance in ac/dc diode rectifiers and dc/dc switch-mode converters. The resulting stochastic average models track the transients of the tolerance limits and related information in the time domain both accurately and efficiently. The relative merits of the method are substantiated through a comparative analysis with the Monte Carlo and root-sum-square methods.
UvA-DARE (

Measurements of longitudinal ﬂow correlations are presented for charged particles in the pseudorapidity range | η | < 2 . 4 using 7 µ b − 1 and 470 µ b − 1 of Pb+Pb collisions at √ s NN = 2 . 76 and 5.02 TeV, respectively, recorded by the ATLAS detector at the LHC. It is found that the correlation between the harmonic ﬂow coefﬁcients v n measured in two separated η intervals does not factorise into the product of single-particle coefﬁcients, and this breaking of factorisation, or ﬂow decorrelation, increases linearly with the η separation between the intervals. The ﬂow decorrelation is stronger at 2.76 TeV than at 5.02 TeV. Higher-order moments of the correlations are also measured, and the corresponding linear coefﬁcients for the k th-moment of the v n are found to be proportional to k for v 3 , but not for v 2 . The decorrelation effect is separated into contributions from the magnitude of v n and the event-plane orientation, each as a function of η . These two contributions are found to be comparable. The longitudinal ﬂow correlations are also measured between v n of different order in n . The decorrelations of v 2 and v 3 are found to be independent of each other, while the decorrela-tions of v 4 and v 5 are found to be driven by the nonlinear contribution from v 22 and v 2 v 3 , respectively.
Memory and complexity reduction in parahermitian matrix manipulations of PEVD algorithms

A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and will diagonalise a parahermitian matrix via paraunitary operations. This paper addresses savings - both computationally and in terms of memory use - that exploit the parahermitian structure of the matrix being decomposed, and also suggests an implicit trimming approach to efficiently curb the polynomial order growth usually observed during iterations of the PEVD algorithms. We demonstrate that with the proposed techniques, both storage and computations can be significantly reduced, impacting on a number of broadband multichannel problems.
On some functionals of the ﬁrst passage times in jump models of stochastic volatility

We compute some functionals related to the generalised joint Laplace transforms of the ﬁrst times at which two-dimensional jump processes exit half strips. It is assumed that the state space components are driven by Cox processes with both independent and common (positive) exponential jump components. The method of proof is based on the solutions of the equivalent partial integro-diﬀerential boundary-value problems for the associated value functions. The results are illustrated on several two-dimensional jump models of stochastic volatility which are based on non-aﬃne analogues of certain mean-reverting or diverting diﬀusion processes representing closed-form solutions of the appropriate stochastic diﬀerential equations.
Topic Review : Multimedia over Wireless Review : An Experimental Study of Multimedia Traffic Performance in Mesh Networks

Review: An Experimental Study of Multimedia Traffic Performance in Mesh Networks This paper was published in 2005 in the proceedings of the International Workshop on Wireless Traffic Measurements and Modeling (WitMeMo), collocated with MobiSys. This workshop is “intended to serve as a forum for scientists and engineers in academia and industry to exchange and discuss their experiences and research results . that report on experiences obtained from operational wireless experiments in testbeds or the field. ” This paper is well aligned with the goals of the WitMeMo workshop, and though it does not offer new methodologies or solutions to address the limitations of wireless multimedia networking, it does present experimental data that reveal new insights into the issues encountered transmitting multimedia streams over wireless mesh networks in various configurations.
The Power of information Age Concepts and Technologies An Empirical Assessment of the Impact of Requirements Uncertainty on Development Quality Performance

System requirements are recognized as a critical step in the development of quality software (SW) systems and an important area of research. Being the first step in the process of software engineering, the effort has potential to shape the direction for all subsequent project activity. The main purpose of this research is to examine the impact of requirements uncertainty and task uncertainty on outcomes in software development projects, limiting the attention to process and product quality. Some of those examined projects are defense-related and aerospace-command and control systems. A cross-sectional survey of 123 participants work in software development in 34 U.S organizations was employed to prove my research model. Analyzed data provided evidence of a significant negative association between requirements uncertainty and development quality factors: process and product. Moreover, the analyzed data showed that there is a significance positive association between requirements and task uncertainty. In addition, the data provided evidence of a negative significant association between task uncertainty and process and product quality. My study pointed to areas where there was negative impact on the developed system quality. In particular, my research focused on the uncertainty regarding user requirements, because I believed that this had the most influenced. Findings from this research can provide the basis on which project managers and software practitioners can design concrete strategies that would enhance the performance of software development to high quality ends.
A four-step pre-analytical conceptual study towards a reliable smart mobile e-health monitoring system design

In the development of general system design approaches the main concern is whether the approach meets the proposed system's specifications and the ability of the system to operate for a specified period of time within those specifications. However, with the expansion in the field of sensitive systems e.g. e-health monitoring systems, a great emphasis is put on the period of time that the system will keep meeting its design requirements (i.e. System Reliability). However, there are no clear conclusions that can be drawn from the prior work in this field to clarify the mechanism of integrating the reliability concept and requirements in a smart mobile e-health monitoring system. In our belief, the full understanding of the term reliability and the concepts behind it with the requirements and specifications of the system is an important element in order for us to propose and create new special reliability mechanisms that fully match the system's objectives and enhance its reliability. This paper aims to propose a four-step pre-analytical conceptual study of the concept of reliability in relation to a smart mobile e-health monitoring system. Our approach aims to contribute toward the expansion of techniques for integrating the physical layer components' characteristics with the application layer objectives to optimize the best design of a reliable smart mobile e-health monitoring system, with respect to the patients' needs as performance requirements.
Subacute pathobiological response following chronic repetitive mild traumatic brain injury in an aged preclinical model of amyloid pathogenesis

Repetitive mild traumatic brain injury (r-mTBI) is a high risk factor for Alzheimer’s disease (AD). The precise nature of how r-mTBI leads to, or precipitates, AD pathogenesis remains unclear. In this study we explore subacute effects of chronic r-mTBI (12-impacts) administered over 1-month in aged-PS1/APP mice and littermate controls. We investigate specific mechanisms that may elucidate the molecular link between AD and r-mTBI, focusing primarily on amyloid and tau pathology, amyloid processing, glial activation states and associated clearance mechanisms. Herein, we demonstrate r-mTBI in aged PS1/APP mice does not augment, glial activation, amyloid burden, or tau pathology (with exception of pS202+Tau) 1-month after exposure to the last-injury. However, we observed a decrease in brain soluble A 𝛽 42 levels without any appreciable change in peripheral soluble A 𝛽 42 levels--this was accompanied by an increase in brain insoluble to soluble A 𝛽 42 ratio in injured PS1/APP mice compared to sham-injury. A parallel reduction in phagocytic receptor, TREM-2, was also observed. This study demonstrates very subtle subacute effects of rmTBI on a pre-existing amyloid pathology background, which may be on a continuum towards a slow and worsening neurodegenerative outcome compared to sham-injury, and, therefore, have many implications, especially in the elderly population exposed to TBI.
Metal-Free Polymethyl Methacrylate (PMMA) Nanoparticles by Enamine “Click” Chemistry at Room Temperature

Click" chemistry has become an efficient avenue to unimolecular polymeric nanoparticles through the self-crosslinking of individual polymer chains containing appropriate functional groups. Herein we report the synthesis of ultra-small (7 nm in size) polymethyl methacrylate (PMMA) nanoparticles (NPs) by the "metal-free" cross-linking of PMMA-precursor chains prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization containing β-ketoester functional groups. Intramolecular collapse was performed by the one-pot reaction of β-ketoester moieties with alkyl diamines in tetrahydrofurane at r.t. (i.e., by enamine formation). The collapsing process was followed by size exclusion chromatography and by nuclear magnetic resonance spectroscopy. The size of the resulting PMMA-NPs was determined by dynamic light scattering. Enamine "click" chemistry increases the synthetic toolbox for the efficient synthesis of metal-free, ultra-small polymeric NPs.
Cascade-based multi-scale AI approach for modeling rainfall-runoff process

In this paper, runoff time series of the sub-basins in a cascade form were decomposed by Wavelet Transform (WT) to extract their dynamical and multi-scale features for modeling Multi-Station (MS) Rainfall-Runoff (R-R) process of the Little River Watershed (LRW) in USA. A Self-Organizing Map (SOM) clustering technique was also employed to find homogeneous extracted sub-series9 clusters. As a complementary feature, extraction criterion of Mutual Information (MI) was utilized for proper cluster agent choice to impose to the Artificial Intelligence (AI) models (Feed Forward Neural Network, FFNN; Extreme Learning Machine, ELM; and Least Square Support Vector Machine, LSSVM) to predict the runoff of the LRW sub-basins. The performance of wavelet-based runoff prediction was compared to the Markovian-based MS model. The proposed method not only considers the prediction of the outlet runoff but also covers predictions of interior sub-basins behavior. The outcomes showed that the proposed AI-models combined with the SOM and MI tools enhanced the MS runoff prediction efficiency up to 23% in comparison with the Markovian-based models. Nevertheless, benefit of the seasonality of the process along with reduction of dimension of the inputs could help the AI-models to consume pure information of the recorded data.
Design and Realization of Precise Indoor Localization Mechanism for Wi-Fi Devices

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.
Adaptive Selective Compensation for Variable Frequency Active Power Filters in More Electrical Aircraft

The work presented here investigates an adaptive current controller for active power filters for aircrafts power networks, which compensate selected load current harmonics. The attention is focused on the load current harmonic compensation when the fundamental frequency varies over a wide range (typically between 360 Hz and 800 Hz as in new generation aircrafts) and the harmonics produced by distorting loads (such as the 5th and the 7th) are above the achievable current loop bandwidth. Compared with previously reported resonant controllers, this work proposes an adaptive leading angle compensation in the resonant filter, which-by compensating the variable process delay-is potentially able to guarantee the theoretical current control stability when the selected frequency is up to the Nyquist frequency. However, the presence of intermodulation, i.e., distortion introduced due to the compensation of frequencies approaching the Nyquist limit, introduces an additional distortion, which limits the maximum compensation frequency. Experimental results are presented to demonstrate the effectiveness of the proposed system.