Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-Range Regulatory Polymorphisms Affecting a GABA Receptor Constitute a Quantitative Trait Locus (QTL) for Social Behavior in Caenorhabditis elegans

Aggregation is a social behavior that varies between and within species, providing a model to study the genetic basis of behavioral diversity. In the nematode Caenorhabditis elegans, aggregation is regulated by environmental context and by two neuromodulatory pathways, one dependent on the neuropeptide receptor NPR-1 and one dependent on the TGF-β family protein DAF-7. To gain further insight into the genetic regulation of aggregation, we characterize natural variation underlying behavioral differences between two wild-type C. elegans strains, N2 and CB4856. Using quantitative genetic techniques, including a survey of chromosome substitution strains and QTL analysis of recombinant inbred lines, we identify three new QTLs affecting aggregation in addition to the two known N2 mutations in npr-1 and glb-5. Fine-mapping with near-isogenic lines localized one QTL, accounting for 5%–8% of the behavioral variance between N2 and CB4856, 3′ to the transcript of the GABA neurotransmitter receptor gene exp-1. Quantitative complementation tests demonstrated that this QTL affects exp-1, identifying exp-1 and GABA signaling as new regulators of aggregation. exp-1 interacts genetically with the daf-7 TGF-β pathway, which integrates food availability and population density, and exp-1 mutations affect the level of daf-7 expression. Our results add to growing evidence that genetic variation affecting neurotransmitter receptor genes is a source of natural behavioral variation.
Image Based Search System Using Hierarchical Object Category Recognition Technique

In this paper, we present the information search system using object category recognition, which is queried by image from mobile phone camera or from photo sharing service on internet. In such system, processing speed is an important requirement. We adopted “Standard Model” proposed by T. Serre in 2005, and improved processing speed by replacing Gabor filter to Haar wavelet, vector quantization of feature patch, and restriction of calculation area. In addition, by retaining the information of each feature’s position, it compensates the accuracy which is a little reduced in exchange of processing speed. We implemented this method to server system, and proved this system can work in practical processing time. Through the experiment for Caltech-101 image database, we confirmed value of this system.
Characterization of Left Ventricular Diastolic Function by Tissue Doppler Imaging and Clinical Status in Children With Hypertrophic Cardiomyopathy

Background—Conventional transmitral Doppler indices are unreliable in assessing clinical status in patients with hypertrophic cardiomyopathy (HCM) because they are affected by loading conditions. This study sought to determine whether tissue Doppler velocities are predictive of adverse clinical outcomes including death, cardiac arrest, ventricular tachycardia (VT), significant cardiac symptoms, and exercise capacity in children with HCM. Methods and Results—We studied 80 consecutive children (median age 12 years, median follow-up 26 months) evaluated at 1 hospital from January 1999 to August 2003 compared with 80 age- and gender-matched controls. Patients underwent echocardiography, ambulatory Holter monitoring, and upright exercise testing. Children with HCM had significantly decreased early diastolic tissue Doppler velocities at the lateral mitral (13.2 versus 19.3 cm/s), tricuspid (13.3 versus 16.3 cm/s), and septal (9.4 versus 13.5 cm/s) annuli compared with controls (P <0.001 for each comparison). By forward stepwise regression analysis, early transmitral left ventricular filling velocity (E)/septal Ea ratio predicted death, cardiac arrest, or VT (r =0.610, R2 =0.37, P <0.001). Peak oxygen consumption (&OV0312;O2) was most predictive of children who developed symptoms (r =0.427, R2 =0.182, P <0.001). Peak &OV0312;O2 correlated inversely with E/Ea septal ratio (r =−0.740, P <0.01). Conclusions—Transmitral E/septal Ea ratio predicts children with HCM who are at risk of adverse clinical outcomes including death, cardiac arrest, VT, and significant cardiac symptoms. Peak &OV0312;O2 correlated with peak exercise capacity in HCM patients.
Evaluation of Novel Design Strategies for Developing Zinc Finger Nucleases Tools for Treating Human Diseases

Zinc finger nucleases (ZFNs) are associated with cell death and apoptosis by binding at countless undesired locations. This cytotoxicity is associated with the binding ability of engineered zinc finger domains to bind dissimilar DNA sequences with high affinity. In general, binding preferences of transcription factors are associated with significant degenerated diversity and complexity which convolutes the design and engineering of precise DNA binding domains. Evolutionary success of natural zinc finger proteins, however, evinces that nature created specific evolutionary traits and strategies, such as modularity and rank-specific recognition to cope with binding complexity that are critical for creating clinical viable tools to precisely modify the human genome. Our findings indicate preservation of general modularity and significant alteration of the rank-specific binding preferences of the three-finger binding domain of transcription factor SP1 when exchanging amino acids in the 2nd finger.
Aggression and Affiliation during Social Conflict in Pigs

Social conflict is mostly studied in relation to aggression. A more integral approach, including aggressive and affiliative behaviour as well as physiology, may however give a better understanding of the animals' experience during social conflict. The experience of social conflict may also be reflected in the spatial distribution between conspecifics. The objective was to assess the relationship between behaviour, physiology, and spatial integration in pigs (Sus scrofa) during social conflict. Hereto, 64 groups of pigs (9 wk of age) were studied in a 24 h regrouping test whereby pairs of familiar pigs were grouped with 2 unfamiliar pairs, in either barren or straw-enriched housing. Data on aggressive and affiliative behaviour, skin lesions, body weight, and haptoglobin could be summarized into three principal component analysis factors. These three factors were analysed in relation to spatial integration, i.e. inter-individual distances and lying in body contact. Pigs stayed up to 24 h after encounter in closer proximity to the familiar pig than to unfamiliar pigs. Pigs with a high factor 1 score were more inactive, gave little social nosing, had many skin lesions and a high body weight. They tended to space further away from the familiar pig (b = 1.9 cm; P = 0.08) and unfamiliar ones (b = 0.7 cm; P = 0.05). Pigs that were involved in much aggression (factor 2), and that had a strong increase in haptoglobin (factor 3), tended to be relatively most far away from unfamiliar pigs (b = 0.03 times further; P = 0.08). Results on lying in body contact were coherent with results on distances. Pigs in enriched housing spaced further apart than pigs in barren housing (P<0.001). The combined analysis of measures revealed animals that may either promote or slow down group cohesion, which may not have become clear from single parameters. This emphasizes the importance of an integral approach to social conflict.
Optimization spectrum decision parameters in CR using autonomously search algorithm

In order to solve the contradiction between wireless communication service demand and spectrum resource shortage and enhance the utilization rate of spectrum, Cognitive Radio technology is necessary. Firstly, this paper presents a cognitive engine framework structure, and then the concept of bio-inspired and its application in CR computing were emphatically introduced. Finally, in order to solve spectrum parameters problem, this paper proposed based on autonomously search algorithm. Based on population evolution, ASA algorithm employs the foraging, reproduction, selection and mutation operators, and was tested under the multicarrier simulation environment. The experiment results show that ASA algorithm can better adjust each subcarrier communication parameters according to the requirement of cognitive engine parameters optimization, which include transmitted power, modulation mode, and bit-error-rate and so on, and finally satisfy the channel condition and the dynamic changes of the user service.
Arteriolar Diameter and Tissue Oxygen Tension During Muscle Contraction in Hypertensive Rats

This study evaluated the possibility that hi hypertension, mechanisms that maintain near normal arteriolar diameters at elevated arteriolar pressures limit the ability of skeletal muscle arterioles to dilate hi response to an increase hi tissue metabolism. The spinotrapezius muscles of 16- to 20-week-old spontaneously hypertensive rats (SHR) and Wistar-Kyoto rats (WKY) were contracted at frequencies of 1, 2, 4, and 8 Hz. The inner diameters of first-order through third-order arterioles were measured at rest and following 3 minutes of contractions. Tissue oxygen tension (PO2) at the venous end of capillaries was monitored during 8-Hz contractions. At rest, following contractions, and after nurrimnm dilation with adenosine, the inner diameters of arterioles of equivalent branch order were not significantly different hi SHR and WKY. Opening of closed arterioles during musde contraction and adenosine application occurred hi less than 5% of the observations hi both groups. The resting tissue Po2 was 25.5 ± 1.3 mm Hg hi normal rats and 26.1 ± 2.1 mm Hg hi SHR. At nearly maximum vasodilation during 8-Hz stimulation, tissue PO2] recovered to 81.9 ± 12.7% of control In WKY but only to 41.2 ± 13.0% of control hi SHR. These observations indicate that the expression of local regulatory mechanisms related to tissue metabolism is virtually normal In the spinotrapezius muscle vasculature of SHR in the context of arteriolar dilation. However, at near maTinwni performance, factors other than absolute arteriolar diameter preclude the normal preservation of tissue PO2 in the spinotrapezius musde of SHR.
Pay is not everything: Differential effects of monetary and non-monetary rewards on employees’ attitudes and behaviours

Purpose Monetary and non-monetary rewards have rarely been considered together under the HRM perspective. Despite the vast literature on HRM, there is still a lack of studies that explicitly discuss the link between the adoption of a total reward system (TRS) and employee-related outcomes. The purpose of this paper is to investigate this important issue in order to provide insights that can help organisations devise compensation strategies that are effective in sustaining employees’ positive attitudes and behaviours. Design/methodology/approach Using a survey of 1,092 employees, the authors examine the effect of the overall TRS on three outcome variables (i.e. job satisfaction, affective commitment, and innovative behaviour at work). Furthermore, the authors examine the impact that each component of the TRS (i.e. base pay, training and development opportunities, and positive work environment) has on the dependent variables. Findings The results confirm that the adoption of a TRS exerts a positive influence on the aforementioned outcomes. However, interesting differences emerged when looking at the individual components in the overall sample. Originality/value This paper provides original insights into the complex relationship between TRS and the employee-related outcomes of job satisfaction, affective commitment, and innovative behaviour at work.
A Human-Aided Machine Translation System for Japanese-English Patent Translation

The approach presented here enables Japanese users with no knowledge of English or legal English to generate patent claims in English from a Japanese-only interface. It exploits the highly determined structure of patent claims and merges Natural Language Generation (NLG) and Machine Translation (MT) techniques and resources as realized in the AutoPat and PC-Transfer applications. Due to its tuned MT engine, the approach can be seen as a human-aided machine translation (HAMT) system circumventing major obstacles in full-scale Japanese-English MT. The approach is fully implemented on a large scale and will be commercially released in autumn 2005.
Unc5B associates with LARG to mediate the action of repulsive guidance molecule

Neuronal axons are guided by attractive and repulsive cues in their local environment. Because the repulsive guidance molecule A (RGMa) was originally identified as an axon repellent in the visual system, diverse functions in the developing and adult central nervous system have been ascribed to it. RGMa binding to its receptor neogenin induces RhoA activation, leading to inhibitory/repulsive behavior and collapse of the neuronal growth cone. However, the precise mechanisms that regulate RhoA activation are poorly understood. In this study, we show that Unc5B, a member of the netrin receptor family, interacts with neogenin as a coreceptor for RGMa. Moreover, leukemia-associated guanine nucleotide exchange factor (LARG) associates with Unc5B to transduce the RhoA signal. Focal adhesion kinase (FAK) is involved in RGMa-induced tyrosine phosphorylation of LARG as well as RhoA activation. These findings uncover the molecular basis for diverse functions mediated by RGMa.
Graph Searching Algorithms for Semantic-Social Recommendation

In this paper we present two recommendation algorithms, called Node-Edge-Based and Node-Based recommendation algorithms. These algorithms are designed to recommend items to users connected via social network. Our algorithms are based on three main features: a social network analysis measure (degree centrality), the graph searching algorithm (Depth First Search algorithm), and the semantic similarity measure (which measures the closeness between the input item and users). We apply these algorithms to a real dataset (Amazon dataset) and we compare them with item-based collaborative filtering and hybrid recommendation algorithms. Our results show good precision as well as in a good performance in terms of runtime. Moreover, Node-Edge-Based and Node-Based algorithms search a small part of the dataset, compared to item-based and hybrid recommendation algorithms.
Sphingosine-1-Phosphate, a Platelet-Derived Lysophospholipid Mediator, Negatively Regulates Cellular Rac Activity and Cell Migration in Vascular Smooth Muscle Cells

Previous studies demonstrated that sphingosine-1-phosphate (S1P) induced migration of human umbilical vein endothelial cells (HUVECs) whereas it inhibited that of vascular smooth muscle cells (SMCs). This study explored the molecular mechanisms underlying the contrasting S1P actions on vascular cell motility. In rat and human aortic SMCs, the chemoattractant platelet-derived growth factor B-chain (PDGF) induced rapid 5- to 6-fold increases in the cellular amount of GTP-bound, active form of Rac. S1P did not affect PDGF-stimulated tyrosine phosphorylation of PDGF-&bgr; receptor, but strongly inhibited PDGF-induced Rac activation, with a dose-response relationship similar to that for inhibition of PDGF-elicited chemotaxis. Dihydrosphingosine-1-phosphate, which is a weaker agonist for the S1P receptors, but not an inactive ligand sphingosine, also inhibited PDGF-stimulated chemotaxis and Rac activation although to lesser extents compared with S1P, suggesting that negative regulation by S1P of both chemotaxis and Rac was a receptor-mediated process. In contrast, S1P by itself stimulated Rac activity in HUVECs. Among the five S1P receptor isoforms, SMCs prominently expressed Edg-5 mRNA, whereas HUVECs expressed abundant Edg-1 mRNA but lacked detectable expression of Edg-5 mRNA. Adenovirus-mediated expression of a dominant-negative form of either Rac or Cdc42, but not RhoA, markedly attenuated chemotaxis of SMCs and HUVECs toward PDGF and S1P, respectively. Overexpression of Edg-1 in SMCs and Edg-5 in HUVECs reduced S1P-induced inhibition and stimulation, respectively, of Rac activity and migration. These results together indicate that Edg isoform-specific, negative or positive regulation of cellular Rac activity is critically involved in S1P-mediated bimodal regulation of cell motility in SMCs and HUVECs.
Output-coherent image-space LIC for surface flow visualization

Image-space line integral convolution (LIC) is a popular approach for visualizing surface vector fields due to its simplicity and high efficiency. To avoid inconsistencies or color blur during the user interactions in the image-space approach, some methods use surface parameterization or 3D volume texture for the effect of smooth transition, which often require expensive computational or memory cost. Furthermore, those methods cannot achieve consistent LIC results in both granularity and color distribution on different scales. This paper introduces a novel image-space LIC for surface flows that preserves the texture coherence during user interactions. To make the noise textures under different viewpoints coherent, we propose a simple texture mapping technique that is local, robust and effective. Meanwhile, our approach pre-computes a sequence of mipmap noise textures in a coarse-to-fine manner, leading to consistent transition when the model is zoomed. Prior to perform LIC in the image space, the mipmap noise textures are mapped onto each triangle with randomly assigned texture coordinates. Then, a standard image-space LIC based on the projected vector fields is performed to generate the flow texture. The proposed approach is simple and very suitable for GPU acceleration. Our implementation demonstrates consistent and highly efficient LIC visualization on a variety of datasets.
Textual Demand Analysis: Detection of Users’ Wants and Needs from Opinions

This paper tackles textual demand analysis, the task of capturing what people want or need, rather than identifying what they like or dislike, on which much conventional work has focused. It exploits syntactic patterns as clues to detect previously unknown demands, and requires domaindependent knowledge to get high recall. To build such patterns we created an unsupervised pattern induction method relying on the hypothesis that there are commonly desired aspects throughout a domain corpus. Experimental results show that the proposed method detects twice to four times as many demand expressions in Japanese discussion forums compared to a baseline method.
Smart and Secure: Preserving Privacy in Untrusted Home Routers

Recently, wireless home routers increasingly become smart. While these smart routers provide rich functionalities to users, they also raise security concerns. Since a smart home router may process and store personal data for users, once compromised, these sensitive information will be exposed. Unfortunately, current operating systems on home routers are far from secure. As a consequence, users are facing a difficult tradeoff between functionality and privacy risks. This paper attacks this dilemma with a novel SEAL architecture for home routers. SEAL leverages the ARM TrustZone technology to divide a conventional router OS (i.e., Linux) in a non-secure/normal world. All sensitive user data are shielded from the normal world using encryption. Modules (called applets) that process the sensitive data are located in a secure world and confined in secure sandboxes provided by a tiny secure OS. We report the system design of SEAL and our preliminary implementation and evaluation results.
Orientation-aware indoor localization using affinity propagation and compressive sensing

The sparse nature of location finding makes it desirable to exploit the theory of compressive sensing for indoor localization. In this paper, we propose a received signal strength (RSS)-based localization scheme in Wireless Local Area Networks (WLANs) using the theory of compressive sensing (CS), which offers accurate recovery of sparse signals from a small number of measurements by solving an l1-minimization problem. In order to mitigate the effects of RSS variations due to channel impediments and mobile device orientation, a two-step localization scheme is proposed by exploiting affinity propagation for coarse localization followed by a CS-based fine localization to further improve the accuracy. We implement the localization algorithm on a WiFi-integrated mobile device to evaluate the performance. Experimental results indicate that the proposed system leads to substantial improvements on localization accuracy and complexity over the widely used traditional fingerprinting methods.
Adaptive Web document classification with MCRDR

With the explosive increase in Web based information, the need for an intelligent agent for automatic classification has also been increased resulting in many research discoveries in this area. Machine learning (ML) based document classification is now the prevalent approach. However, classification by ML may not keep the same performance because the knowledge generated from the training set may not be appropriate for certain types of Web information. People are often concerned more about the newly uploaded information such as Web based online news than information already available. This explains why it is not widely used in real applications. However, the manual classification method, by the domain users, cannot be a solution either until the knowledge acquisition bottleneck issue is resolved. Multiple classification ripple down rules, an incremental knowledge acquisition method, is suggested to overcome this problem with fast learning and low cost maintenance.
Scene Categorization from Tiny Images

Scene categorization can play a crucial role in applications such as image retrieval and object recognition. It seems reasonable that scene category labels like indoor, outdoor, kitchen, or beach can be assigned to images at lower spatial and radiometric resolution than may be required for categorization and localization of objects in the scenes. This paper presents a systematic investigation of resolution requirements for scene categorization. We introduce a novel, challenging database of tiny images for 20 dierent scene categories, present experimental results on human categorization performance, as well as an algorithm to eciently learn and perform scene categorization. Our model’s best recall rate of 46% significantly outperforms human recall of 30% on 32 ◊ 32 images. These results should encourage future research in the use of categorization on low resolution thumbnails as an important preprocessing step to model context in categorization, recognition and localization.