Miracle-dz/UniFAR-FTUs huggingface dataset:
Connecting QAs to Show Intent underlying Web Query

People want to ask something to find relevant answer following their information needs. Discovering intents behind Web query is helpful for users to find useful Web search results or recognize search objectives. In this paper, we try to discover structured intents of Web query using Community Question-Answer (CQA) information following the assumption that QAs concerned with query keywords represent practical intents of the query. Through syntactic and structural analysis of CQA contents, we extract candidate features of intent which form intent expressions and measure relations of answers toward questions by using QA similarities and differences. Finally we connect QAs using intent expressions and answer question relations. Experimental results show that QA connections are useful as fragments of knowledge to understand Web query intents and their changes.
Association between Vascular Endothelial Growth Factor Gene Polymorphisms and Pre-Eclampsia Susceptibility: An Updated Meta-Analysis

ABSTRACT Objectives: The aim of this study was to assess the genetic association between vascular endothelial growth factor (VEGF) gene polymorphisms and the risk of pre-eclampsia (PE). Methods: A systematic literature search of several databases (PubMed, Embase, and the China National Knowledge Infrastructure (CNKI)) was conducted for case–control trials comparing VEGF polymorphisms (+936C/T, −634G/C, −2578C/A, and −1154G/A) with the risk of PE. Meta-analysis was performed using the Stata 12.0 software. Results: Twenty-three case–control studies on a total of 2597 PE patients and 3075 controls were included in our meta-analysis. The +936C/T polymorphism was observed to be associated with the risk of PE in the overall population (T vs. C: odds ratios (OR) = 1.434, 95% confidence interval (CI) = 1.120–1.836, P = . 004). However, the −634G/C, −2578C/A, and −1154G/A polymorphisms showed no association with the risk of PE. A subgroup analysis based on ethnicity found that the +936C/T polymorphism was associated with the risk of PE in both Europeans and Asians. Furthermore, the −634G/C polymorphism was found to be associated with the risk of PE in Europeans (C vs. G: OR = 1.428, 95% CI = 1.141–1.778, P = .002). The polymorphisms at other loci were not associated with the risk of PE. Conclusion: This meta-analysis suggests that VEGF +936C/T polymorphism, rather than −634G/C, −2578C/A, or −1154G/A polymorphisms, is associated with the risk of PE in the overall study population. However, the −634G/C polymorphism may be associated with the risk of developing PE in Europeans.
Neural Network and Genetic Algorithm Based ECG Beat Classification

This paper proposes a potential cascaded neural network algorithm for ECG Holter system beat classification. The system works in real time and is capable of recognizing up to 20 artificial QRS templates. The parallelism of neural network increases the efficiency of computations. An error signal derived from differences between predictor and testing signal is used in the classification. A neural network is used to generate linear predictions for signals. Another neural network generates error signals measured between predictions taken from the first neural network and testing signal. A fifth neural network does the classifications utilizing the error signals instead of complex raw signal. Three Hermite functions are used in generating testing signals with and without noise. Proper thresholding for the error signals is essential for classifier immunity. The result is a compact, online, efficient, and hardware realizable signals classifier that uses minimal compressed error signal.
Dynamic Image Based Visual Servoing with Unmanned Aerial Vehicles

In recent years rotary-wing unmanned aerial vehicles (UAVs) are seeing more uses in applications such as transmission line inspection, event filming, parcel delivery, and search-and-rescue missions. Recent improvements in embedded systems have lead to more research for improving unmanned aerial vehicle (UAV) autonomy. Traditionally for outdoor use, the inertial measurement unit (IMU) with magnetometer, barometer, or global positioning system (GPS) can be used for pose estimation, where the pose estimate is used for motion control. However, in GPS denied environments, such as indoors, other sensors need to be used for acquiring pose of the UAV in the environment. One method to solve for the vehicle’s pose is visual servoing, which uses a camera to collect information about the environment, and estimates the UAV’s pose for control. This thesis implements the proposed dynamic image-based visual servoing (DIBVS) controller in Fink et al. [1] using a newer experimental platform to improve the performance. This new platform utilizes the Robot Operating System (ROS) running on an on-board Nvidia Jetson TX1 (TX1) mini computer with a FLIR Chameleon 3 camera for the computer vision (CV) system. ROS is chosen to create a simple framework that would handle necessary components for the UAV, such as image capture and data transfer, while allowing for minimal software changes to test different algorithms. Using this framework, future research projects using the platform can save time troubleshooting issues testing hardware, and instead focus on problems related to the algorithms being tested. Also, future upgrades to the platform would need minimal changes to the software so long as the new system is able to run ROS. For the experiments, the CV system uses color to identify visual features used to compute image moments
Triglycine-Based Approach for Identifying the Substrate Recognition Site of an Enzyme

Various peptides or non-structural amino acids are recognized by their specific target proteins, and perform a biological role in various pathways in vivo. Understanding the interactions between target protein and peptides (or non-structural amino acids) provides key information on the molecular interactions, which can be potentially translated to the development of novel drugs. However, it is experimentally challenging to determine the crystal structure of protein–peptide complexes. To obtain structural information on the substrate recognition of the peptide-recognizing enzyme, X-ray crystallographic studies were performed using triglycine (Gly-Gly-Gly) as the main-chain of the peptide. The crystal structure of Parengyodontium album Proteinase K in complex with triglcyine was determined at a 1.4 Å resolution. Two different bound conformations of triglycine were observed at the substrate recognition site. The triglycine backbone forms stable interactions with β5-α4 and α5-β6 loops of the main-chain. One of the triglycine-binding conformations was identical to the binding mode of a peptide-based inhibitor from a previously reported crystal structure of Proteinase K. Triglycine has potential application in X-ray crystallography in order to identify the substrate recognition sites in the peptide binding enzymes.
Physico-Phyto and Chromato Graphic Analysis of Aviccinia alba and Laguncularia racemosa Leaves

To investigate the physicochemical analysis, preliminary phytochemicals screening, along with TLC analysis and antibacterial activities of mangrove plants leaves of Aviccinia alba and Laguncularia racemosa. A. alba crude drug were showed the Physicochemical characteristic such as; extractive value (5.00%), water soluble extractive value (7.20%), loss on drying weight (12.43%), total ash value (14.00%), acid insoluble ash value (3.10%) and water soluble extractive value (3.90%). Similarly, physicochemical values in L. racemosa 8.50% extractive value, 6.45 % water soluble extractive value, 8.45 % of loss on drying weight, 16.22% total ash value, 3.40 % acid insoluble ash value and 3.40 % water soluble extractive values. Phytochemical analysis of methanol extracts of A. alba (AME) and L. racemosa (LME) revealed the presence high amount of tannins and phenolic compounds. TLC analysis revealed five clear distinct bands or spots by AME showed with their Rf values range from 0.2 to 0.75. Whereas LME showed seven unclear compound spots with varying Rf values range from 0.2 to 0.80. Methanol extracts of both plants were strongly inhibited against with Staphylococcus aureus, Streptococcus pyogenes as gram negative bacteria and a much broader spectrum of action than Pseudomonas aeruginosa and E. coli as gram positive bacteria. These studies will help in setting down Pharmacopoeia standardisation and determining the quality and purity of bioactive compounds. Further investigation is being advocated for the identification of lead molecule with pharmacological significance.
Examining criterion-oriented validity of the Repetitive Behavior Scales for Early Childhood (RBS-EC) and the Video-Referenced Rating of Reciprocal Social Behavior (vrRSB)

Abstract Improved characterization of quantitative traits and dimensionally distributed complex behaviors during toddlerhood may improve early identification of autism spectrum disorder and related neurodevelopmental disorders. Parents of 205 community-ascertained toddlers (age: mean = 20.2, SD = 2.6 months) completed the Repetitive Behavior Scales for Early Childhood (RBS-EC) and the Video-Referenced Rating of Reciprocal Social Behavior (vrRSB), with longitudinal follow-up of behavioral assessments and/or another round of parent-report questionnaires. Criterion validity was examined both concurrently and longitudinally using the Infant Toddler Social Emotional Assessment (ITSEA) as a criterion anchor. Reciprocal social behavior as measured by the vrRSB was significantly associated with social competence as measured by the ITSEA, longitudinally and concurrently. Reciprocal social behavior was not associated with the externalizing subscale on the ITSEA, providing evidence of discriminant validity. Higher-order repetitive behaviors (restricted interests; rituals and routines) as measured by RBS-EC subscales were associated with the dysregulation and internalizing subscales of the ITSEA, longitudinally and concurrently. All RBS-EC subscales (excepting repetitive motor) were associated concurrently and longitudinally with the dysregulation subscale of the ITSEA. We report evidence of criterion-oriented and discriminant validity for the constructs/domains captured by the RBS-EC and vrRSB. These instruments may be particularly useful in characterizing dimensional variability across the typical-to-atypical continuum.
Rule Extraction Based on Data Dimensionality Reduction Using RBF Neural Networks

Compact rules is desirable in the task of rule extraction. Since there are often redundant or irrelevant attributes in data sets, removing the redundant or irrelevant attributes from the data sets can lead to more compact rules. In this paper, firstly, a novel method, a separability-correlation measure (SCM), is used to rank the importance of attributes, and an RBF classifier is used to evaluate the best subset of attributes to be retained. Secondly, large overlaps between clusters of the same class are allowed in order to reduce the number of hidden units in the RBF network. Thirdly, rule extraction is carried out based on the retained subset of attributes used as the input to the RBF neural network. Simulations show that this procedure lead to more compact rules.
Transient Hypoxemia Disrupts Anatomical and Functional Maturation of Preterm Fetal Ovine CA1 Pyramidal Neurons

Children who survive premature birth often exhibit reductions in hippocampal volumes and deficits in working memory. However, it is unclear whether synaptic plasticity and cellular mechanisms of learning and memory can be elicited or disrupted in the preterm fetal hippocampus. CA1 hippocampal neurons were exposed to two common insults to preterm brain: transient hypoxia-ischemia (HI) and hypoxia (Hx). We used a preterm fetal sheep model using both sexes in twin 0.65 gestation fetuses that reproduces the spectrum of injury and abnormal growth in preterm infants. Using Cavalieri measurements, hippocampal volumes were reduced in both Hx and HI fetuses compared with controls. This volume loss was not the result of neuronal cell death. Instead, morphometrics revealed alterations in both basal and apical dendritic arborization that were significantly associated with the level of systemic hypoxemia and metabolic stress regardless of etiology. Anatomical alterations of CA1 neurons were accompanied by reductions in probability of presynaptic glutamate release, long-term synaptic plasticity and intrinsic excitability. The reduction in intrinsic excitability was in part due to increased activity of the channels underlying the fast and slow component of the afterhyperpolarization in Hx and HI. Our studies suggest that even a single brief episode of hypoxemia can markedly disrupt hippocampal maturation. Hypoxemia may contribute to long-term working memory disturbances in preterm survivors by disrupting neuronal maturation with resultant functional disturbances in hippocampal action potential throughput. Strategies directed at limiting the duration or severity of hypoxemia during brain development may mitigate disturbances in hippocampal maturation. SIGNIFICANCE STATEMENT Premature infants commonly sustain hypoxia-ischemia, which results in reduced hippocampal growth and life-long disturbances in learning and memory. We demonstrate that the circuitry related to synaptic plasticity and cellular mechanisms of learning and memory (LTP) are already functional in the fetal hippocampus. Unlike adults, the fetal hippocampus is surprisingly resistant to cell death from hypoxia-ischemia. However, the hippocampus sustains robust structural and functional disturbances in the dendritic maturation of CA1 neurons that are significantly associated with the magnitude of a brief hypoxic stress. Since transient hypoxic episodes occur commonly in preterm survivors, our findings suggest that the learning problems that ensue may be related to the unique susceptibility of the hippocampus to brief episodes of hypoxemia.
Effect of ethanolic extract of Melia dubia leaves on full‐thickness cutaneous wounds in Wistar rats

In recent years, the therapeutic effects of phyto‐principles have been appreciated for their promising effects on wound healing. Melia dubia (Malabar neem) possesses anti‐cancer, anti‐diabetic, anti‐tumor, anti‐inflammatory, antioxidant, antibacterial, and fungicidal properties. Here, we studied the wound healing efficacy of ethanolic extract of M. dubia leaves on cutaneous wound healing for the first time. The ethanolic extract of M. dubia was applied topically on the wounds of the experimental rats until the wounds heal completely. Wounds of the control rats were treated with PBS. Granulation tissues formed on wound surfaces of the excision wound were harvested on days 4 and 8 and analyzed to determine the total collagen and hexosamine content. Total collagen and hexosamine were significantly (p < .001) higher in M. dubia treated rats compared to control. The rate of wound closure was significantly higher (p < .001) and period of epithelialization was shorter in M. dubia treated rats. Incision wound tissue was used for the tensile strength measurement. Tensile strength was improved in M. dubia treated wound tissues. Results concluded that the topical application of ethanolic extracts of M. dubia improved the rate of wound contraction and tensile strength by increased synthesis of collagen.
An exploration of alternative representations for Generative-ComponentsTM Symbolic View

In this paper we explore graph models used to illustrate the relationships between elements of designs in computer-aided design (CAD) systems. we discuss common limitations and ways to make such representations more usable and interactive. In order to study common problems of symbolic representations in CAD systems, we conducted a survey of a number of CAD applications that employ graph representations in their interface and provided comparative analysis of the properties of graph representations in these systems. As a case study we used bentley GenerativeComponentstM (GC) system a parametric CAD application that uses graph (“symbolic”) view to visualize the structure of design. we conducted series of interviews with expert GC users that revealed many limitations of the GC symbolic view. to address these limitations, we developed alternative representations of symbolic view that aim at enhancing user experience with the system and reviewed these with expert GC users. As a result of our study, we developed a set of interactive prototypes using SHriMP1 visualization tool and Processing programming language. these provide improved ways of user interaction with symbolic representation, including better readability of the graph and, as a result, an improved support for design model analysis.
IMPROVED APPROACH TO IRIS SEGMENTATION BASED ON BRIGHTNESS CORRECTION FOR IRIS RECOGNITION

With the increasing need for security systems, security and the authentication of individuals become nowadays more than ever an asset of great significance in almost every field. Iris recognition system provides identification and verification of an individual automatically based on characteristics and the unique features in iris structure. The correct iris recognition system based on the iris segmentation method and how controlled the inner and outer boundaries of iris that can be damaged by irrelevant parts such as eyelashes and eyelid. To achieve this aim, in this paper basically explains the proposed segmentation method [Iris Segmentation Based on Brightness Correction ISBC] by addition two brightness FB(First Brightness) and SB(Second Brightness), which applied on an eye image passed through preprocessing operations to implement this algorithm in C# Programming Language, with a new modifications in iris segmentation stage. The proposed approach testing conducted on the iris CASIA (Chinese Academy of Science and Institute of Automation) dataset (CASIA v1.0 and CASIA v4.0 interval ) iris image database and the results indicated that proposed approach has 100% accuracy rates with (CASIA v1.0) and 100% accuracy rates with (CASIA v4.0 interval).
Social Identity and Social FreeRiding

We model individual identification choice as a strategic group formation problem. When choosing a social group to identify with, individuals appreciate high social status and a group stereotype to which they have a small social distance. A group’s social status and stereotype are shaped by the (exogenous) individual attributes of its members and hence endogenous to individuals’ choices. Unless disutility from social distance is strong enough, this creates a strategic tension as individuals with attributes that contribute little to group status would like to join high-status groups, thereby diluting the latters’ status and changing stereotypes. Such social free-riding motivates the use of soft exclusion technologies in high-status groups, which provides a unifying rationale for phenomena such as hazing rituals, charitable activities or status symbols that is not taste-based or follows a standard signaling mechanism.
Modified Carrier Based PWM for Quasi-Z-Source Inverter-Based Grid-Tie Single-Phase Photovoltaic Power System

In single-phase photovoltaic (PV) system, there is double-frequency power mismatch existed between the dc input and ac output. The double-frequency ripple (DFR) energy needs to be buffered by passive network. Otherwise, the ripple energy will flow into the input side and adversely affect the PV energy harvest. In a conventional PV system, electrolytic capacitors are usually used for this purpose due to their high capacitance. However, electrolytic capacitors are considered to be one of the most failure prone components in a PV inverter. In this paper, a capacitance reduction control strategy is proposed to buffer the DFR energy in single-phase Z-source/quasiZ-source inverter applications.This paper also presents an effective control method, including system-level control and Carrier based pulse width modulation for quasi-Z-source inverter (qZSI) based grid-tie photovoltaic (PV) power system. A new method carrier PWM strategies is also proposed and compared with different conventional carrier PWM technique. Reduction of total harmonics distortion (THD) and improvement of the harmonic spectrum of inverter output voltage are some advantages of the proposed control method. The simulation results based on the MATLAB/SIMULINK software are presented to validate the capabilities of the proposed modulation method.
Flower Pollen Extract and its Effect on Metabolic Adaptation of Muscles Preventation of muscle soreness by pretreatment with antioxidants

A free radical-scavenging preparation (pollen extract) or the corresponding placebo was given to 50 volunteers over a period of 4 weeks to test the hypothesis that muscle soreness is associated with the generation of free radicals. The increase in malonyldialdehyde and lactate immediately after exercise both in blood and in muscle tissue was significantly lower after treatment with the scavenging preparation. The same was true for the prolonged post-exercise increase in creatine kinase over a 5-day period. The postexercise glycogen content of muscle was higher in the pollen extract group, as were the subjective feelings of pain, oedema, discomfort and tension in the working muscle. We conclude that the beneficial preventive effect of pollen extract on post-exercise muscle soreness and lowering of the concentration of lipid peroxides indicate that free radicals are probably involved in the development of muscle soreness.
Network congestion control algorithm based on Actor-Critic reinforcement learning model

Aiming at the network congestion control problem, a congestion control algorithm based on Actor-Critic reinforcement learning model is designed. Through the genetic algorithm in the congestion control strategy, the network congestion problems can be better found and prevented. According to Actor-Critic reinforcement learning, the simulation experiment of network congestion control algorithm is designed. The simulation experiments verify that the AQM controller can predict the dynamic characteristics of the network system. Moreover, the learning strategy is adopted to optimize the network performance, and the dropping probability of packets is adaptively adjusted so as to improve the network performance and avoid congestion. Based on the above finding, it is concluded that the network congestion control algorithm based on Actor-Critic reinforcement learning model can effectively avoid the occurrence of TCP network congestion.
The Twelfth East Asia-Pacific Conference on Structural Engineering and Construction Cyclic Shear Resistance of Expanded Beam-Column Joint

This paper presents the strengthening technique for interior reinforced concrete beam-column joint based on joint expansion concept. The beam-column joint is expanded two-dimensionally by cast-in-situ concrete around the corners of the joint. Experiment has been conducted on interior beam-column specimens with expanded joint zone. Experimental results demonstrate a good performance of this method to upgrade the joint shear strength, energy dissipation and ductility. It has been found that by increasing the joint size, the joint shear failure can be prevented. The joint expansion is shown to reduce the joint shear stress. This method is effective to change failure mode from brittle joint shear failure to flexural failure in beams. © 2011 Published by Elsevier Ltd.