Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influences of Emotion on Learning and Memory

Emotion has a substantial influence on the cognitive processes in humans, including perception, attention, learning, memory, reasoning, and problem solving. Emotion has a particularly strong influence on attention, especially modulating the selectivity of attention as well as motivating action and behavior. This attentional and executive control is intimately linked to learning processes, as intrinsically limited attentional capacities are better focused on relevant information. Emotion also facilitates encoding and helps retrieval of information efficiently. However, the effects of emotion on learning and memory are not always univalent, as studies have reported that emotion either enhances or impairs learning and long-term memory (LTM) retention, depending on a range of factors. Recent neuroimaging findings have indicated that the amygdala and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex mediating memory encoding and formation; and (iii) the hippocampus for successful learning and LTM retention. We also review the nested hierarchies of circular emotional control and cognitive regulation (bottom-up and top-down influences) within the brain to achieve optimal integration of emotional and cognitive processing. This review highlights a basic evolutionary approach to emotion to understand the effects of emotion on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional processing. We also summarize the current state of knowledge on the impact of emotion on memory and map implications for educational settings. In addition to elucidating the memory-enhancing effects of emotion, neuroimaging findings extend our understanding of emotional influences on learning and memory processes; this knowledge may be useful for the design of effective educational curricula to provide a conducive learning environment for both traditional “live” learning in classrooms and “virtual” learning through online-based educational technologies.
Security enforcement using PKI in Semantic Web

The communication technology is developing in internet to use WWW through wired and wireless networks. The electronic authentication system based on PKI (public key infrastructure) was developed in order to guarantee the stability of client-server type of applications. The efficiency decreases when some of user node becomes mobile terminal, making this capacity, and speeds of internet communication have gone to degrade. In this paper, we propose the PKI security system to authenticate Semantic Web service providers as well as Web service consumers. We consider a secure PKI infrastructure that has four main components, they are Certification Authority, Registration authority, certificate revocation list and certificate validation authority. Each component has specified functionalities to use XML based message to multi purpose communication. Mobile nature of user's authentication requires a distributed PKI server to authenticate requesting application on internet. Mobility attains different security issues in wireless PKI communication for remote users. We can not assume secure communication of user on internet in open environment till all basic components of PKI system is not in safe condition. CRL (certificate revocation list), and OCSP (online certificate status protocol) are common method to check status of a certificate online. Digital certificate validation resolves problem of security by making real-time verification possible. We have addressed here it for dependability aspects for the semantic web as well as data quality, integrity real-time processing and security for the semantic web. We need to ensure that our work on semantic web is a subject to unauthorized / intrusions and malicious web applications during key exchange.
An evolutionary approach for the tuning of a chess evaluation function using population dynamics

Using the game of chess, we propose an approach for the tuning of evaluation function parameters based on evolutionary algorithms. We introduce an iterative method for population member selection and show how the resulting win, loss, or draw information from competition can be used in conjunction with the statistical analysis of the population to develop evaluation function parameter values. A population of evaluation function candidates are randomly generated and exposed to the proposed learning techniques. An analysis to the success of learning is given and the undeveloped and developed players are examined through competition against a commercial chess program.
Novel diagnostic method for a single phase pole-mount transformer using two-port measurement

Diagnosis and maintenance of a power transformer are important because it deals with high power in high voltage, and any failure of previous detection of the malfunction in transformer would cause a disaster in the household customers as well as in the industry. To diagnose a power transformer, Sweep Frequency Response Analyzer (SFRA) has been widely used and been studied for the past years. The SFRA measures the change of a transfer function characteristics of a transformer with some specific terminal conditions, and has been used to check the state of the transformer which could be caused due to aging or to any damage before and after moving, and so on. It, however, uses just one port of the transformer to check the impedance, so the information from the SFRA measurement is limited in principle. This paper suggests a novel way to measure two ports of a power transformer to get the inside information of a transformer. To prove the validity of the proposed method, two-port S-parameters were measured using Vector Network Analyzer (VNA), and the measured S-parameters were converted into the transfer function using proper equations for the comparison of the two measurement data. The comparison of two showed good matching in the range of 20Hz to 2MHz. It suggests that the proposed method could be used to effectively diagnose the power transformers.
On cross spectral periocular recognition

This paper introduces the challenge of cross spectral periocular matching. The proposed algorithm utilizes neural network for learning the variabilities caused by two different spectrums. Two neural networks are first trained on each spectrum individually and then combined such that, by using the cross spectral training data, they jointly learn the cross spectral variability. To evaluate the performance, a cross spectral periocular database is prepared that contains images pertaining to visible night vision and near infrared spectrums. The proposed combined neural network architecture, on the cross spectral database, shows improved performance compared to existing feature descriptors and cross domain algorithms.
A Phase I Trial to Determine the Safety, Tolerability, and Maximum Tolerated Dose of Deforolimus in Patients with Advanced Malignancies

Purpose: This was a phase I trial to determine the maximum tolerated dose and toxicity of deforolimus (AP23573, MK-8669), an inhibitor of mammalian target of rapamycin (mTOR). The pharmacokinetics, pharmacodynamics, and antineoplastic effects were also studied. Experimental Design: Deforolimus was administered intravenously over 30 min every 7 days according to a flat dosing schedule. Dose was escalated according to an accelerated titration design. Patients remained on study until disease progression as long as they tolerated the drug without significant toxicities. Results: Forty-six patients were enrolled on the study. Common side effects included fatigue, anorexia, and mucositis. The maximum tolerated dose was 75 mg and mucositis was the dose-limiting toxicity. Similar to other mTOR inhibitors, deforolimus exhibited nonlinear pharmacokinetics and a prolonged half-life. Among 34 patients evaluable for response, 1 patient had a partial response, 21 patients had stable disease, and 12 had progressed. Percent change in tumor size was significantly associated with AUC (P = 0.015). A significant association was also detected for maximum change in cholesterol within the first two cycles of therapy and change in tumor size (r = −0.38; P = 0.029). Conclusions: Deforolimus was well tolerated on the schedule tested in this trial with toxicity and pharmacokinetic profiles that were similar to that of other mTOR inhibitors. Additional phase II studies are needed to determine if deforolimus is superior to other mTOR inhibitors in terms of efficacy. The change in serum cholesterol as a potential biomarker of activity should be studied further.
Differential Alteration in Expression of Striatal GABAAR Subunits in Mouse Models of Huntington’s Disease

Huntington’s disease (HD) is a neurodegenerative disorder characterized by progressive motor symptoms that are preceded by cognitive deficits and is considered as a disorder that primarily affects forebrain striatal neurons. To gain a better understanding of the molecular and cellular mechanisms associated with disease progression, we analyzed the expression of proteins involved in GABAergic neurotransmission in the striatum of the R6/1 transgenic mouse model. Western blot, quantitative PCR and immunohistochemical analyses were conducted on male R6/1 mice and age-matched wild type littermates. Analyses were performed on 2 and 6 month-old animals, respectively, before and after the onset of motor symptoms. Expression of GAD 67, GAD 65, NL2, or gephyrin proteins, involved in GABA synthesis or synapse formation did not display major changes. In contrast, expression of α1, α3 and α5 GABAAR subunits was increased while the expression of δ was decreased, suggesting a change in tonic- and phasic inhibitory transmission. Western blot analysis of the striatum from 8 month-old Hdh Q111, a knock-in mouse model of HD with mild deficits, confirmed the α1 subunit increased expression. From immunohistochemical analyses, we also found that α1 subunit expression is increased in medium-sized spiny projection neurons (MSN) and decreased in parvalbumin (PV)-expressing interneurons at 2 and 6 months in R6/1 mice. Moreover, α2 subunit labeling on the PV and MSN cell membranes was increased at 2 months and decreased at 6 months. Alteration of gene expression in the striatum and modification of GABAA receptor subtypes in both interneurons and projection neurons suggested that HD mutation has a profound effect on synaptic plasticity at an early stage, before the onset of motor symptoms. These results also indicate that cognitive and other behavioral deficits may be associated with changes in GABAergic neurotransmission that consequently could be a relevant target for early therapeutic treatment.
Sex Differences in Detecting Sexual Infidelity Results of a Maximum Likelihood Method for Analyzing the Sensitivity of Sex Differences to Underreporting

Despite the importance of extrapair copulation (EPC) in human evolution, almost nothing is known about the design features of EPC detection mechanisms. We tested for sex differences in EPC inference-making mechanisms in a sample of 203 young couples. Men made more accurate inferences (8 men =0.66, 8 women =0.46), and the ratio of positive errors to negative errors was higher for men than for women (1.22 vs. 0.18). Since some may have been reluctant to admit EPC behavior, we modeled how underreporting could have influenced these results. These analyses indicated that it would take highly sex-differentiated levels of underreporting by subjects with trusting partners for there to be no real sex difference. Further analyses indicated that men may be less willing to harbor unresolved suspicions about their partners' EPC behavior, which may explain the sex difference in accuracy. Finally, we estimated that women underreported their own EPC behavior (10%) more than men (0%).
Partial Enteral Nutrition Preserves Elements of Gut Barrier Function, Including Innate Immunity, Intestinal Alkaline Phosphatase (IAP) Level, and Intestinal Microbiota in Mice

Lack of enteral nutrition (EN) during parenteral nutrition (PN) leads to higher incidence of infection because of gut barrier dysfunction. However, the effects of partial EN on intestina linnate immunity, intestinal alkaline phosphatase (IAP) and microbiota remain unclear. The mice were randomized into six groups to receive either standard chow or isocaloric and isonitrogenous nutritional support with variable partial EN to PN ratios. Five days later, the mice were sacrificed and tissue samples were collected. Bacterial translocation, the levels of lysozyme, mucin 2 (MUC2), and IAP were analyzed. The composition of intestinal microbiota was analyzed by 16S rRNA pyrosequencing. Compared with chow, total parenteral nutrition (TPN) resulted in a dysfunctional mucosal barrier, as evidenced by increased bacterial translocation (p < 0.05), loss of lysozyme, MUC2, and IAP, and changes in the gut microbiota (p < 0.001). Administration of 20% EN supplemented with PN significantly increased the concentrations of lysozyme, MUC2, IAP, and the mRNA levels of lysozyme and MUC2 (p < 0.001). The percentages of Bacteroidetes and Tenericutes were significantly lower in the 20% EN group than in the TPN group (p < 0.001). These changes were accompanied by maintained barrier function in bacterial culture (p < 0.05). Supplementation of PN with 20% EN preserves gut barrier function, by way of maintaining innate immunity, IAP and intestinal microbiota.
Leaf phenology in 22 North American tree species during the 21st century

Recent shifts in phenology are the best documented biological response to current anthropogenic climate change, yet remain poorly understood from a functional point of view. Prevailing analyses are phenomenological and approximate, only correlating temperature records to imprecise records of phenological events. To advance our understanding of phenological responses to climate change, we developed, calibrated, and validated process‐based models of leaf unfolding for 22 North American tree species. Using daily meteorological data predicted by two scenarios (A2: +3.2 °C and B2: +1 °C) from the HadCM3 GCM, we predicted and compared range‐wide shifts of leaf unfolding in the 20th and 21st centuries for each species. Model predictions suggest that climate change will affect leaf phenology in almost all species studied, with an average advancement during the 21st century of 5.0 days in the A2 scenario and 9.2 days in the B2 scenario. Our model also suggests that lack of sufficient chilling temperatures to break bud dormancy will decrease the rate of advancement in leaf unfolding date during the 21st century for many species. Some temperate species may even have years with abnormal budburst due to insufficient chilling. Species fell into two groups based on their sensitivity to climate change: (1) species that consistently had a greater advance in their leaf unfolding date with increasing latitude and (2) species in which the advance in leaf unfolding differed from the center to the northern vs. southern margins of their range. At the interspecific level, we predicted that early‐leafing species tended to show a greater advance in leaf unfolding date than late‐leafing species; and that species with larger ranges tend to show stronger phenological changes. These predicted changes in phenology have significant implications for the frost susceptibility of species, their interspecific relationships, and their distributional shifts.
Cardiac p300 Is Involved in Myocyte Growth with Decompensated Heart Failure

ABSTRACT A variety of stresses on the heart initiate a number of subcellular signaling pathways, which finally reach the nuclei of cardiac myocytes and cause myocyte hypertrophy with heart failure. However, common nuclear pathways that lead to this state are unknown. A zinc finger protein, GATA-4, is one of the transcription factors that mediate changes in gene expression during myocardial-cell hypertrophy. p300 not only acts as a transcriptional coactivator of GATA-4, but also possesses an intrinsic histone acetyltransferase activity. In primary cardiac myocytes derived from neonatal rats, we show that stimulation with phenylephrine increased an acetylated form of GATA-4 and its DNA-binding activity, as well as expression of p300. A dominant-negative mutant of p300 suppressed phenylephrine-induced nuclear acetylation, activation of GATA-4-dependent endothelin-1 promoters, and hypertrophic responses, such as increase in cell size and sarcomere organization. In sharp contrast to the activation of cardiac MEK-1, which phosphorylates GATA-4 and causes compensated hypertrophy in vivo, p300-mediated acetylation of mouse cardiac nuclear proteins, including GATA-4, results in marked eccentric dilatation and systolic dysfunction. These findings suggest that p300-mediated nuclear acetylation plays a critical role in the development of myocyte hypertrophy and represents a pathway that leads to decompensated heart failure.
Lack of ifenprodil anxiolytic activity after its multiple treatment in chronically ethanol-treated rats.

AIMS The purpose of this study was to assess the anxiolytic activity of ifenprodil in Warsaw high-preferring (WHP) and low-preferring (WLP) rats after chronic ethanol treatment. METHODS WHP and WLP animals, their paired-ethanol-naive groups and control Wistar rats were treated with ifenprodil (1.0 mg/kg, intraperitoneally) for 21 consecutive days. Anxiolytic activity was evaluated by using the two-compartment exploratory test. In addition, the locomotor activity paradigm was also assessed. RESULTS Ifenprodil did not affect this paradigm in all investigated groups. The ethanol treatment led to lowering of anxiolytic scores in WHP rats. Multiple ifenprodil administration showed an anxiogenic-like activity in both WHP- and WLP-ethanol-treated groups. CONCLUSIONS Our results suggest that, under some conditions, the role of ifenprodil in the treatment of alcoholism may be insufficient to support its use.
Combining Clustering techniques and Formal Concept Analysis to characterize Interestingness Measures

Formal Concept Analysis "FCA" is a data analysis method which enables to discover hidden knowledge existing in data. A kind of hidden knowledge extracted from data is association rules. Different quality measures were reported in the literature to extract only relevant association rules. Given a dataset, the choice of a good quality measure remains a challenging task for a user. Given a quality measures evaluation matrix according to semantic properties, this paper describes how FCA can highlight quality measures with similar behavior in order to help the user during his choice. The aim of this article is the discovery of Interestingness Measures "IM" clusters, able to validate those found due to the hierarchical and partitioning clustering methods "AHC" and "k-means". Then, based on the theoretical study of sixty one interestingness measures according to nineteen properties, proposed in a recent study, "FCA" describes several groups of measures.
Vaginal bacterial microflora modifications during the growth of healthy cows

The aim of this work was first, to determine the predominant groups capable of colonizing the vagina and maintaining high numbers with time. The normal microbial flora of the cow's vagina and its evolution from weaning to service was then studied using standard microbiological methods. The results show that the most dominant bacteria belong to the streptococci, followed by the staphylococci, with similar levels during the whole study period. Enterobacteriaceae and lactobacilli were present at very low levels, the latter increasing during the cow's growth, suggesting some kind of hormonal influence. The results will allow the selection of micro‐organisms with probiotic characteristics, classified as GRAS (Generally Regarded as Safe), to be used in the prevention of infections in the vaginal tract of cows, such as metritis, which produces delayed periods between partum and conception, and consequent economic losses.
Evaluating the word-expert approach for Named-Entity Disambiguation

Named Entity Disambiguation (NED) is the task of linking a named-entity mention to an instance in a knowledge-base, typically Wikipedia. This task is closely related to word-sense disambiguation (WSD), where the supervised word-expert approach has prevailed. In this work we present the results of the word-expert approach to NED, where one classifier is built for each target entity mention string. The resources necessary to build the system, a dictionary and a set of training instances, have been automatically derived from Wikipedia. We provide empirical evidence of the value of this approach, as well as a study of the differences between WSD and NED, including ambiguity and synonymy statistics.
Is Visual Search Really like Foraging?

The visual-search paradigm provides a controlled and easy to implement experimental situation in which to study the search process. However, little work has been carried out in humans to investigate the extent to which traditional visual-search tasks are similar to more general search or foraging. Here we report results from a task in which search involves walking around a room and leaning down to inspect individual locations. Consistent with more traditional search tasks, search time increases linearly with display size, and the target-present to target-absent search slope is 1:2. However, although rechecking of locations did occur, compared to more traditional search it was relatively rare, suggesting an increased role for memory.
A PVT-variation tolerant fully integrated 60 GHz transceiver for IEEE 802.11ad

A PVT tolerant fully integrated 60 GHz transceiver for IEEE 802.11ad is presented. By introducing a newly proposed self-sensing LDO, the transceiver adjusts bias currents and the LDO output voltage for the PA to minimize the output power variation while relaxing the hot carrier injection (HCI) degradation. The measurement shows excellent robustness against PVT variations, demonstrating only 5 dB output power variation over -20 °C to 85 °C across process corners.
Improving the emergency department performance using simulation and MCDM methods

The main purpose of this paper is to introduce a new framework to more efficiently investigate the patient flow of the Emergency Department (ED) of a governmental hospital in Tehran, Iran, in order to find out improving scenarios for reducing waiting times of patients. The proposed framework integrates the simulation model of patients flow process with the group AHP and TOPSIS decision models in order to evaluate and rank scenarios based upon desired performance measures. TOPSIS decision model takes the weights of performance measures from the group AHP and the values of performance measures from simulation model, and ranks the improving scenarios. The results analysis indicates that the average waiting time of non-fast-track patients by taking new policies with reasonable expenditure can be reduced by 42.3%.