Miracle-dz/UniFAR-FTUs huggingface dataset:
An Evaluation of Feature Selection Technique for Dendrite Cell Algorithm

Dendrite cell algorithm needs appropriates feature to represents its specific input signals. Although there are many feature selection algorithms have been used in identifying appropriate features for dendrite cell signals, there are algorithms that never been investigated and limited work to compare performance among them. In this study, six feature selection algorithms namely Information Gain, Gain Ratio, Symmetrical Uncertainties, Chi Square, Support Vector Machine, and Rough Set with Genetic Algorithm Reduct are examined and their effectiveness to represent dendrite cell signal are evaluated. Eight universal datasets are chosen and assessing their performance according to sensitivity, specificity, and accuracy. From the experiment, the Rough Set Genetic Algorithm reduct is found to be the most effect feature selection for dendrite cell algorithm when it generates a consistent result for all evaluation metrics. In single evaluation metrics, the chi square technique has the best competence in term of sensitiveness while the rough set genetic algorithm reduct is good at specificity and accuracy. In the next step, further analysis will be conducted on complex dataset such as time series data set.
Simplifying and Isolating Failure-Inducing Input

Given some test case, a program fails. Which circumstances of the test case are responsible for the particular failure? The delta debugging algorithm generalizes and simplifies the failing test case to a minimal test case that still produces the failure. It also isolates the difference between a passing and a failing test case. In a case study, the Mozilla Web browser crashed after 95 user actions. Our prototype implementation automatically simplified the input to three relevant user actions. Likewise, it simplified 896 lines of HTML to the single line that caused the failure. The case study required 139 automated test runs or 35 minutes on a 500 MHz PC.
Insula and Striatum Mediate the Default Bias

Humans are creatures of routine and habit. When faced with situations in which a default option is available, people show a consistent tendency to stick with the default. Why this occurs is unclear. To elucidate its neural basis, we used a novel gambling task in conjunction with functional magnetic resonance imaging. Behavioral results revealed that participants were more likely to choose the default card and felt enhanced emotional responses to outcomes after making the decision to switch. We show that increased tendency to switch away from the default during the decision phase was associated with decreased activity in the anterior insula; activation in this same area in reaction to “switching away from the default and losing” was positively related with experienced frustration. In contrast, decisions to choose the default engaged the ventral striatum, the same reward area as seen in winning. Our findings highlight aversive processes in the insula as underlying the default bias and suggest that choosing the default may be rewarding in itself.
Maternal Residence Near Agricultural Pesticide Applications and Autism Spectrum Disorders among Children in the California Central Valley

Background Ambient levels of pesticides (“pesticide drift”) are detectable at residences near agricultural field sites. Objective Our goal was to evaluate the hypothesis that maternal residence near agricultural pesticide applications during key periods of gestation could be associated with the development of autism spectrum disorders (ASD) in children. Methods We identified 465 children with ASD born during 1996–1998 using the California Department of Developmental Services electronic files, and matched them by maternal date of last menstrual period to 6,975 live-born, normal-birth-weight, term infants as controls. We determined proximity to pesticide applications using California Department of Pesticide Regulation records refined using Department of Water Resources land use polygons. A staged analytic design applying a priori criteria to the results of conditional logistic regressions was employed to exclude associations likely due to multiple testing error. Results Of 249 unique hypotheses, four that described organochlorine pesticide applications—specifically those of dicofol and endosulfan—occurring during the period immediately before and concurrent with central nervous system embryogenesis (clinical weeks 1 through 8) met a priori criteria and were unlikely to be a result of multiple testing. Multivariate a posteriori models comparing children of mothers living within 500 m of field sites with the highest nonzero quartile of organochlorine poundage to those with mothers not living near field sites suggested an odds ratio for ASD of 6.1 (95% confidence interval, 2.4–15.3). ASD risk increased with the poundage of organochlorine applied and decreased with distance from field sites. Conclusions The association between residential proximity to organochlorine pesticide applications during gestation and ASD among children should be further studied.
Cellular Mechanisms of Artificial Peptides Binding to HLA

On the basis of the consideration that cell-free models cannot precisely mimic the complexity of the intracellular environment, we used a system to investigate the mechanisms that enable antigen-presenting cells (APC) to bind exogenous peptides through their human leukocyte antigen (HLA) molecules. We evaluated the uptake of the radiolabeled peptide 17-29-Tyr of influenza virus matrix protein by B-EBV cell lines, under various conditions. The results can be summarized as follows: a) the kinetics of peptide binding and release are very fast in living, fully competent cells; b) the peptide-HLA complexes are short-living and the DR molecules continuously undergo peptidic exchange; c) using glutaraldehyde-fixed cells, the kinetics of the two phenomena are slow, closely resembling those observed with the same peptide and purified, immobilized DR molecules. The data suggest that in APC, cellular mechanisms are operative that increase the efficiency of both loading and unloading of Class II HLA with exogenous peptides. This is likely to be related to the recycling of Class II molecules to intracellular compartments, were binding takes place. The observation that the HLA-peptide complex is a dynamic structure, suggests the possibility of replacing natural peptides with synthetic ones at this level, in order to regulate the immune response.
Laser-based People Tracking

— In this paper, we describe a method for real-time tracking of objects with multiple laser range-finders covering a workspace in a parallel and distributed fashion. Tracking people is a popular problem in machine vision. Here we adapt the methods used in vision to pla-nar laser scanners. We group range measurements into entities like blobs and objects. With the help of a Kalman Filter (KF), the tracker smooths object paths and estimates its path even when the underlying object is occluded from all the lasers. We finally evaluate the tracker's performance through four experiments.
DisVis: Visualizing Discussion Threads in Online Health Communities

An increasing number of individuals turn to online health communities (OHC) for information, advice and support about their health condition or disease. As a result of users' active participation, these forums store overwhelming volumes of information, which can make access to this information challenging and frustrating. To help overcome this problem we designed a discussion visualization tool DisVis. DisVis includes features for overviewing, browsing and finding particular information in a discussion. In a between subjects study, we tested the impact of DisVis on individuals' ability to provide an overview of a discussion, find topics of interest and summarize opinions. The study showed that after using the tool, the accuracy of participants' answers increased by 68% (p-value = 0.023) while at the same time exhibiting trends for reducing the time to answer by 38% with no statistical significance (p-value = 0.082). Qualitative interviews showed general enthusiasm regarding tools for improving browsing and searching for information within discussion forums, suggested different usage scenarios, highlighted opportunities for improving the design of DisVis, and outlined new directions for visualizing user-generated content within OHCs.
Implementation of Local Fourier Burst Accumulation for Video Deblurring

This article presents Local Fourier Burst Accumulation, a recent motion deblurring method. This method processes image bursts and can be naturally extended to video deblurring. The algorithm ﬁrst registers the frame to its neighboring frames by consistency-controlled optical ﬂow and then fuses the frames temporally by a weighted average in the Fourier domain. As the method does not require the estimation of the blur kernel, it is less sensitive to common deblurring issues such as ringing. The algorithm is detailed and comparison with the results of the original authors are performed
Synthesis and optimization of reversible circuits—a survey

Reversible logic circuits have been historically motivated by theoretical research in low-power electronics as well as practical improvement of bit manipulation transforms in cryptography and computer graphics. Recently, reversible circuits have attracted interest as components of quantum algorithms, as well as in photonic and nano-computing technologies where some switching devices offer no signal gain. Research in generating reversible logic distinguishes between circuit synthesis, postsynthesis optimization, and technology mapping. In this survey, we review algorithmic paradigms—search based, cycle based, transformation based, and BDD based—as well as specific algorithms for reversible synthesis, both exact and heuristic. We conclude the survey by outlining key open challenges in synthesis of reversible and quantum logic, as well as most common misconceptions.
A Novel Reinforcement Learning Architecture for Continuous State and Action Spaces

We introduce a reinforcement learning architecture designed for problems with an infinite number of states, where each state can be seen as a vector of real numbers and with a finite number of actions, where each action requires a vector of real numbers as parameters. The main objective of this architecture is to distribute in two actors the work required to learn the final policy. One actor decideswhat actionmust be performed;meanwhile, a second actor determines the right parameters for the selected action.We tested our architecture and one algorithmbased on it solving the robot dribbling problem, a challenging robot control problem taken from the RoboCup competitions. Our experimental work with three different function approximators provides enough evidence to prove that the proposed architecture can be used to implement fast, robust, and reliable reinforcement learning algorithms.
Mechanosensing by the nucleus: From pathways to scaling relationships

The nucleus is linked mechanically to the extracellular matrix via multiple polymers that transmit forces to the nuclear envelope and into the nuclear interior. Here, we review some of the emerging mechanisms of nuclear mechanosensing, which range from changes in protein conformation and transcription factor localization to chromosome reorganization and membrane dilation up to rupture. Nuclear mechanosensing encompasses biophysically complex pathways that often converge on the main structural proteins of the nucleus, the lamins. We also perform meta-analyses of public transcriptomics and proteomics data, which indicate that some of the mechanosensing pathways relaying signals from the collagen matrix to the nucleus apply to a broad range of species, tissues, and diseases.
Enhancing Multicultural Awareness through the Storybook Reading Experience.

The purpose of this study was to examine the effects of combining home and classroom reading experiences of multicultural storybooks on the awareness and attitudes of kindergarten, second grade, and fourth-grade students towards individuals representing other cultures, circumstances, or lifestyles. Two classrooms of students at each of the three grade levels participated in the study with one classroom at each grade level randomly specified as the Storybook Reading Group; the other served as the Control Group. The following question guided the study : Are pupils' attitudes toward multicultural diversity enhanced by exposure to multicultural literature ? At the beginning and at the end of the study, all participants responded to a survey which examined their attitudes towards aspects of diversity. Administration of the instrument at posttest time indicated that positive gains occurred in the Storybook Reading Groups at Grades 2 and 4. For kindergartners, positive gains occurred on six of the nine survey items. A different, and surprising pattern occurred in the control groups where there was overall negative change at all three grade levels. These findings suggest that without a diversity program children's appreciation of diversity may actually decrease across the school year
Integrating semantics and narrative world generation

Implementation of a narrative world is often laborious and remains fairly independent from working directly with the narrative itself. Currently, there are few tools able to simplify this process. The aim of our research is to support this process by developing a declarative approach for generating narrative worlds. A set of narrative semantics will be used to discover and further generate appropriate content. The declarative approach and semantics will be initially implemented and validated in a virtual therapy tool for patients with post-traumatic stress disorder. The project will evolve towards the creation of a more general narrative creation tool
The Malaria Secretome: From Algorithms to Essential Function in Blood Stage Infection

The malaria agent Plasmodium falciparum is predicted to export a “secretome” of several hundred proteins to remodel the host erythrocyte. Prediction of protein export is based on the presence of an ER-type signal sequence and a downstream Host-Targeting (HT) motif (which is similar to, but distinct from, the closely related Plasmodium Export Element [PEXEL]). Previous attempts to determine the entire secretome, using either the HT-motif or the PEXEL, have yielded large sets of proteins, which have not been comprehensively tested. We present here an expanded secretome that is optimized for both P. falciparum signal sequences and the HT-motif. From the most conservative of these three secretome predictions, we identify 11 proteins that are preserved across human- and rodent-infecting Plasmodium species. The conservation of these proteins likely indicates that they perform important functions in the interaction with and remodeling of the host erythrocyte important for all Plasmodium parasites. Using the piggyBac transposition system, we validate their export and find a positive prediction rate of ∼70%. Even for proteins identified by all secretomes, the positive prediction rate is not likely to exceed ∼75%. Attempted deletions of the genes encoding the conserved exported proteins were not successful, but additional functional analyses revealed the first conserved secretome function. This gave new insight into mechanisms for the assembly of the parasite-induced tubovesicular network needed for import of nutrients into the infected erythrocyte. Thus, genomic screens combined with functional assays provide unexpected and fundamental insights into host remodeling by this major human pathogen.
BaseVISor: A Triples-Based Inference Engine Outfitted to Process RuleML and R-Entailment Rules

BaseVISor is a forward-chaining inference engine based on a Rete network optimized for the processing of RDF triples. A clause within the body and head of a rule either represents an RDF triple or invokes a procedural attachment (either built-in or user defined). This paper describes how BaseVISor has been outfitted to process RuleML and R-Entailment rules. In the case of RuleML, n-ary predicates are automatically translated into binary predicates and reified statements that encapsulate the n-ary predicates' arguments. For R-Entailment rules, the appropriate R-Entailment axioms, axiomatic triples and consistency rules are automatically imported into the engine and then used to derive all triples entailed by any set of triples asserted into the fact base. Operation of the system is illustrated using sample rule sets for both RuleML and R-Entailment and instructions are provided on how to obtain the BaseVISor beta release and process the examples
Interval-based Temporal Reasoning with General TBoxes

Aus der Motivation: Description Logics (DLs) are a family of formalisms well-suited for the representation of and reasoning about knowledge. Whereas most Description Logics represent only static aspects of the application domain, recent research resulted in the exploration of various Description Logics that allow to, additionally, represent temporal information, see [4] for an overview. The approaches to integrate time differ in at least two important aspects: First, the basic temporal entity may be a time point or a time interval. Second, the temporal structure may be part of the semantics (yielding a multi-dimensional semantics) or it may be integrated as a so-called concrete domain. Examples for multi-dimensional point-based logics can be find in, e.g., [21;29], while multi-dimensional interval-based logics are used in, e.g., [23;2]. The concrete domain approach needs some more explanation. Concrete domains have been proposed by Baader and Hanschke as an extension of Description Logics that allows reasoning about 'concrete qualities' of the entities of the application domain such as sizes, length, or weights of real-worlds objects [5]. Description Logics with concrete domains do usually not use a fixed concrete domain; instead the concrete domain can be thought of as a parameter to the logic. As was first described in [16], if a 'temporal' concrete domain is employed, then concrete domains may be point-based, interval-based, or both.
Investigating outcomes of online engagement

So far, digital divide research and policy was primarily engaged with access to computers and the Internet. The results of having access to these digital media were neglected. This article focuses on the tangible outcomes of online access and activity. There have been few attempts to measure such outcomes. With respect to digital inclusion, the most interesting question is who actually benefits from being online. This article answers this question by the results of a representative survey of the Dutch population in 2013. Internet outcomes and benefits are framed in concepts of participation in several domains of society: economic, social, educational, political and institutional. The results show that the same social categories having more access to the Internet also have more outcomes or benefits from Internet use: people with high education and income and young people. Outcomes in fact are the essence or stake of the digital divide. This study shows that some categories of the Dutch population benefit substantially more than others by using the Internet in finding a job, lower prices of products and services, better opportunities of education, a political party to vote for, new friends, a partner in dating and other outcomes.
Expression Analysis of WRKY Transcription Factor Genes in Response to Abiotic Stresses in Horsegram (Macrotyloma uniflorum (Lam.) Verdc.)

Drought and salt stress are two major environmental constraints that limit the productivity of agriculture crops worldwide. WRKY transcription factors are the plant-specific transcription factors that regulate several developmental events and stress responses in plants. The WRKY domain is defined by a 60-amino acid conserved sequence named WRKYGQK at N-terminal and a Zinc Finger-like motif at the C-terminal. WRKY genes are known to respond several stresses which may act as negative or positive regulators. The function of most of the WRKY transcription factors from non-model plants remains poorly understood. This investigation shows the expression levels of eight WRKY transcription factor genes from horsegram plant under drought and salt stress conditions. The increase in mRNA transcript levels of WRKY transcription factor genes was found to be high in drought stressed plants compared to salt-stressed plants. The levels of MDA which indicates the lipid peroxidation were less in drought stress. More ROS is produced in salt stress conditions compared to drought. The results show that the expression of WRKY transcription factors in drought stress conditions is reducing the adverse effect of stress on plants. These results also suggest that, during abiotic stress conditions such as drought and salt stress, WRKY transcription factors are regulated at the transcription level.
Effects of Annealing Treatments on the Properties of Al/Ti/p-GaN Interfaces for Normally OFF p-GaN HEMTs

This paper reports on the behavior of Al/Ti/ p-GaN interfaces as gate contacts for p-GaN/AlGaN/GaN normally off high electron mobility transistor (HEMTs), highlighting the impact of the thermal budget on the metal gate on the device characteristics. In fact, while the devices subjected to an annealing at 800°C show a considerable high leakage current, those with nonannealed Al/Ti gate contacts exhibit a normally off behavior, with a pinch-off voltage Vpo = +1.1 V and an on/off current ratio of 3 × 108. Temperature-dependent electrical measurements on back-to-back Schottky diodes allowed to determine a Schottky barrier height ΦB of 2.08 and 1.60 eV, for the nonannealed and 800°C annealed gate contacts, respectively. Hence, the increase in the leakage current observed upon annealing at 800°C was attributed to the lowering of the Schottky barrier height ΦB of the metal gate. The interfacial structural characterization explained the barrier lowering induced by the annealing. This scenario was discussed through the simulated band diagram of the heterostructures, considering the experimental values of ΦB. These results provide useful information for the device makers to optimize the fabrication flow of normally off HEMTs with p-GaN gate.
A 0.1-25.5-GHz Differential Cascaded-Distributed Amplifier in 0.18- μm CMOS Technology

A differential distributed amplifier employs a loss-compensation L section to increase the bandwidth of the interstage by a factor of 3.5. To demonstrate the proposed circuit, a cascaded distributed amplifier with five stages is presented. It has been fabricated in a 0.18um CMOS process and achieves a gain of better than 15 dB and a pass bandwidth of 100 MHz to 25.5 GHz while consuming 171 mW from a 1.9-V supply
Reinforcement Learning Memory

This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage(,x) learning and directed exploration can solve non-Markovian tasks with long-term dependencies between relevant events. This is demonstrated in a T-maze task, as well as in a difficult variation of the pole balancing task.
The Prediction of Frequency of Illness from the Response to Seperation: A Preliminary Study and Replication Attempt

&NA; We attempted to investigate the hypothesis that object loss, if poorly resolved, may be a possible determinant in the development of somatic illness.4 Two groups of student nurses were studied to determine whether frequency of illness during the freshman year could be predicted from the degree of adjustment six weeks after separation from home. Girls who had adjusted poorly at the 6‐week mark were ill most often during the rest of the school year. Illness seemed most frequent where the level of depressive affects was highest.