Miracle-dz/UniFAR-FTUs huggingface dataset:
Topic-Adaptive Sentiment Analysis on Tweets via Learning from Multi-sources Data

Twitter sentiment analysis model trained from data of one topic may per-forms worse on another topic. While tweets have diverse topics, and the topic of target data of sentiment analysis task is change with the application requirement, which makes it hard to get a good performance. We also notice that one model cannot performs well on every topic, and tweets have no sentiment label to train the model. On the other hand, there are plenty of available text data with sentiment label and topic information such as online movie and product reviews. So we propose a method based on transfer learning, which use topic information and term distribution as a bridge between target tweets and texts from other sources. It could quickly find appropriate in-stances from other sources, and then use them to train a model adapting to target tweets of specific topic for getting better performance. The experiment result shows the effectiveness of the proposed method.
On-Line Cursive Handwriting Recognition Using Hidden Markov Models and Statistical Grammars

The BYBLOS continuous speech recognition system is applied to on-line cursive handwriting recognition. By exploiting similarities between on-line cursive handwriting and continuous speech recognition, we can use the same base system adapted to handwriting feature vectors instead of speech. The use of hidden Markov models obviates the need for segmentation of the handwritten script sentences before recognition. To test our system, we collected handwritten sentences using text from the ARPA Airline Travel Information Service (ATIS) and the ARPA Wall Street Journal (WSJ) corpora. In an initial experiment on the ATIS data, a word error rate of 1.1% was achieved with a 3050-word lexicon, 52-character set, collected from one writer. In a subsequent writer-dependent test on the WSJ data, error rates ranging between 2%-5% were obtained with a 25,595-word lexicon, 86-character set, collected from six different writers. Details of the recognition system, the data collection process, and analysis of the experiments are presented.
Multispectral Palmprint Recognition Using Score-Level Fusion

With the increasing demand of highly accurate and robust authentication system, palm print has widely been used in personal identification. Multispectral palm print has been proposed to get more distinguishing feature information and improve resistance to spoof. The vivid texture information of palm print presenting at different resolutions offers abundant prospects in personal recognition. So this paper describes a method to authenticate individuals based on multi-scale and multi-resolution palm print recognition. First, we extract palm print feature based on NSCT (nonsubsampled Contour transform), and store the feature using a hash table. Then the scores generated from each set of palm print image under red, green, blue and NIR spectrum, are combined using score level fusion method. This method use SUM and MAX operators. Comparatively low values of equal error rate and high recognition rate have been obtained for all fusion techniques. Multispectral palm print verification results on the ROI image libraries of PolyU demonstrate the effectiveness and accuracy of the proposed method.
A Progressive Rendering Algorithm Using an Adaptive Perceptually Based Image Metric

In this paper, we propose to solve the global illumination problem through a progressive rendering method relying on an adaptive sampling of the image space. The refinement of this sample scheme is driven by an image metric based on a powerful vision model. A Delaunay triangulation of the sampled points is followed by a classification of these triangles into three classes. By interpolating each triangle according to the class it belongs to, we can obtain a high quality image by computing only a fraction of all the pixels and thus saving computation time.
Deep Representations and Codes for Image Auto-Annotation

The task of image auto-annotation, namely assigning a set of relevant tags to an image, is challenging due to the size and variability of tag vocabularies. Consequently, most existing algorithms focus on tag assignment and fix an often large number of hand-crafted features to describe image characteristics. In this paper we introduce a hierarchical model for learning representations of standard sized color images from the pixel level, removing the need for engineered feature representations and subsequent feature selection for annotation. We benchmark our model on the STL-10 recognition dataset, achieving state-of-the-art performance. When our features are combined with TagProp (Guillaumin et al.), we compete with or outperform existing annotation approaches that use over a dozen distinct handcrafted image descriptors. Furthermore, using 256-bit codes and Hamming distance for training TagProp, we exchange only a small reduction in performance for efficient storage and fast comparisons. Self-taught learning is used in all of our experiments and deeper architectures always outperform shallow ones.
Shallow Semantics for Relation Extraction

This paper presents a new method for extracting meaningful relations from unstructured natural language sources. The method is based on information made available by shallow semantic parsers. Semantic information was used (1) to enhance a dependency tree kernel; and (2) to build semantic dependency structures used for enhanced relation extraction for several semantic classifiers. In our experiments the quality of the extracted relations surpassed the results of kernel-based models employing only semantic class information.
Dictionary learning for sparse decomposition: A new criterion and algorithm

During the last decade, there has been a growing interest toward the problem of sparse decomposition. A very important task in this field is dictionary learning, which is designing a suitable dictionary that can sparsely represent a group of training signals. In most dictionary learning algorithms, the cost function to determine the the optimum dictionary is the ℓ0 norm of the matrix of decomposition coefficients of the training signals. However, we believe that this cost function fails to fully express the goal of dictionary learning, because it only sparsifies the whole set of coefficients for all training signals, rather than the coefficients for each training signal individually. Thus, in this paper we present a new criterion for dictionary learning. We then propose a new dictionary learning algorithm that solves our proposed optimization problem for the case of complete dictionaries. The proposed algorithm follows the idea of smoothed ℓ0 (SL0) algorithm for sparse recovery. Simulation results emphasize the efficiency of the proposed cost function and algorithm.
Design of intelligent network disk storage system

Faced with mass storage demand in the area of high performance computing, video monitoring, IPTV and multimedia, storage technology have no choice but to be developed rapidly on the basis of current conditions. Network cluster storage technology founded on cluster storage system is most popular storage method to solve mass storage problem at present. Intelligent network disk (IND) is a novel idea of storage system architecture. IND cluster is a new way for mass storage. In order to realize IND storage function and reflect its characteristics such as mass, speed, security, scalability and low-price, some of key techniques, i.e. self-bootload, linux kernel portability and start, file management, disk mounting, intelligent control routine, fault tolerance and recovery and IND combination pattern are described in the paper.
Release of Endothelium‐Derived Relaxing Factor From Freshly Harvested Porcine Endothelial Cells

Vascular relaxation in rabbit aortic preparations induced by acetylcholine is endothelium-dependent. The nature of the endothelium-derived relaxing factor (EDRF) has not been ascertained because it is very labile (reported half-life 6–50 seconds). To obtain a stable source of EDRF, a system was developed in which the relaxing factor was continuously produced by freshly harvested porcine endothelial cells. Endothelial cells were collected from aortas by exposing the endothelial lining to collagenase 0.1%. Cells were washed and concentrated by repeated centrifugation to obtain a high cell count (7.2 × 106 cells/ml). Endothelium-deprived aortic strips from rabbits were incubated in these cells suspended in tissue culture medium and fetal calf serum. The strips were precontracted with histamine. Acetylcholine was added to induce EDRF release. Significant relaxation of endothelium- deprived aortic strips was observed. Superoxide dismutase, an enzyme known to protect EDRF against inactivation, caused further relaxation, which was inhibited by the addition of hemoglobin, an agent known to inhibit the relaxing action of EDRF. Even without the addition of acetylcholine, hemoglobin caused contraction of the denuded aortic strips in suspension of porcine endothelial cells, demonstrating spontaneous EDRF release. Hemoglobin had no effect in cell-free medium. Endothelial-cell-dependent relaxation occurred without attachment of endothelial cells to the endothelium-deprived aortic strips: when the cell suspension was replaced by cell-free medium, relaxation did not occur after acetylcholine. Scanning electron microscopy showed no attachment of endothelial cells to the subendothelial layer. It can be concluded that freshly harvested endothelial cells produce endothelium-derived relaxing factor with and without stimulation by acetylchollne.
Imaging dispersion curves of surface waves on multi-channel record

Summary Real and synthetic data verifies the wavefield transformation method described here converts surface waves on a shot gather directly into images of multi-mode dispersion curves. Pre-existing multi-channel processing methods require preparation of a shot gather with exceptionally large number of traces that cover wide range of source-to-receiver offsets for a reliable separation of different modes. This method constructs high-resolution images of dispersion curves with relatively small number of traces. The method is best suited for near-surface engineering project where surface coverage of a shot gather is often limited to near-source locations and higher-mode surface waves can be often generated with significant amount of energy.
Reduction of HIV-1 Infectivity through Endoplasmic Reticulum-Associated Degradation-Mediated Env Depletion

ABSTRACT During the HIV-1 replicative cycle, the gp160 envelope is processed in the secretory pathway to mature into the gp41 and gp120 subunits. Misfolded proteins located within the endoplasmic reticulum (ER) are proteasomally degraded through the ER-associated degradation (ERAD) pathway, a quality control system operating in this compartment. Here, we exploited the ERAD pathway to induce the degradation of gp160 during viral production, thus leading to the release of gp120-depleted viral particles.
The design and implementation of TCP hardwiring and offloading engine

This paper described the design and implementation procedure of Transmission Control Protocol (TCP) hardwiring and TCP offloading engine based on Field Programmable Gate Array (FPGA). The design consists of several modules, and the connection among modules is implemented by buses. The result shows that some functions are realized in this design. The most contribution of this paper is that the design founds the base of Transmission Control Protocol/Internet Protocol (TCP/IP) hardwiring and offloading engine.
Expression levels and genetic polymorphisms of interleukin-2 and interleukin-10 as biomarkers of Graves’ disease

The aim of the present study was to determine whether the expression levels of interleukin (IL)-2 and IL-10 may be used as biological markers in Graves’ disease (GD) patients. A total of 256 individuals, including 118 GD patients and 138 healthy individuals, were enrolled into the study. Blood samples were collected from each patient and healthy individual, which were then subjected to enzyme-linked immunosorbent assay (ELISA). Total RNA and total proteins were determined using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot analysis, respectively. In addition, restriction fragment length polymorphism (RFLP) analysis was performed to detect the presence of genetic polymorphisms. The ELISA results indicated that the IL-2 and IL-10 serum levels in the GD patients were increased by ~5.2 and ~7-fold when compared with the levels in the healthy controls. The results of RT-qPCR indicated that the mRNA expression levels of IL-2 and IL-10 were upregulated in the GD patients when compared with the healthy controls. Furthermore, the western blot analysis results revealed that the protein expression levels of IL-2 and IL-10 were significantly increased in the GD patients. RFLP analysis indicated that the increased number of GG single nucleotide polymorphisms (SNPs) in the GD group were detected in the −330 locus of the IL-2 promoter and the −1082 locus of the IL-10 promoter. In addition, the results indicated that the relatively high rates of homozygous GG SNPs (IL-2 −330T/G and IL-10 −1082A/G polymorphisms) on the alleles may be associated with the incidence of GD. The serum, mRNA and protein expression levels of IL-2 and IL-10 were significantly increased in GD patients when compared with the levels in the healthy controls. In conclusion, the expression levels and genetic polymorphisms of IL-2 and IL-10 may be potential biomarkers for the incidence of Graves’ disease in the population studied.
Reflections on Distressed Couples Contemplating Divorce

Abstract Considerable research has been published in the area of clinical treatment interventions concerning divorce and separation. Despite this fact, the American divorce rate today is more than twice that of 1960, although it has declined slightly since hitting the highest point in our history in the early 1980s (Whitehead & Popenoe, 2001). Whichever way one looks at it, dissolution of marriage is a common occurrence in our society and will continue to be so for many years to come. Family therapists in their work with couples and families are faced with this issue and are searching for ways to make this transition as healthy as possible for those dealing with the challenge. This clinical study examines one treatment approach, the Structured Marital Separation (SMS), proposed by Granvold and Tarrant in two 1983 articles in the Journal of Marital & Family Therapy. Thirty-six married couples, primarily of white, middle class backgrounds, were followed up to determine their reactions to the collaborative use of this intervention during marital treatment. Further, five therapists were asked about their experiences with the process. The authors discuss the clinical study, the SMS treatment process, results of the follow-up, and some suggestions for futurework.
Handbook of polygraph testing.

Chapter 1 The Comparison Question Test Raskin & Honts Chapter 2 Practical Use of the Concealed Information Test for Criminal Investigation in Japan Nakayama Chapter 3 The Guilty Knowledge Test (GKT) as an Application of Psychophysiology: Future Prospects and Obstacles Ben-Shakar & Elaad Chapter 4 A Critical Review of the Control Questions Test (CQT) Ben-Shakar Chapter 5 Physiological Detection of Deception in Psychological Perspectives Kleiner Chapter 6 The Pretest Interview: A Preliminary Framework Mitchell Chapter 7 The Polygraph in Personnel Screening Krapohl Chapter 8 Post-conviction Sex Offender Testing and the American Polygraph Association Consigli Chapter 9 Countermeasures Honts & Amato Chapter 10 Event-related Potentials in Detection of Deception, Malingering and False Memories Rosenfield Chapter 11 Computer Methods for the Psychophysiological Detection of Deception Kircher & Raskin Chapter 12 Legal Aspects of Polygraph Admissibility in the United States Daniels
16α‐Hydroxycleroda‐3,13 (14)Z‐dien‐15,16‐olide from Polyalthia longifolia: a safe and orally active antileishmanial agent

Background and purpose: New antileishmanials from natural products are urgently needed due to the emergence of drug resistance complicated by severe cytotoxic effects. 16α‐Hydroxycleroda‐3,13 (14)Z‐dien‐15,16‐olide (Compound 1) from Polyalthia longifolia was found to be a potential antileishmanial and non‐cytotoxic, as evidenced by long‐term survival (>6 months) of treated animals. This prompted us to determine its target and, using molecular modelling, identify the interactions responsible for its specific antileishmanial activity.
Deformation-based loop closure for large scale dense RGB-D SLAM

In this paper we present a system for capturing large scale dense maps in an online setting with a low cost RGB-D sensor. Central to this work is the use of an “as-rigid-as-possible” space deformation for efficient dense map correction in a pose graph optimisation framework. By combining pose graph optimisation with non-rigid deformation of a dense map we are able to obtain highly accurate dense maps over large scale trajectories that are both locally and globally consistent. With low latency in mind we derive an incremental method for deformation graph construction, allowing multi-million point maps to be captured over hundreds of metres in real-time. We provide benchmark results on a well established RGB-D SLAM dataset demonstrating the accuracy of the system and also provide a number of our own datasets which cover a wide range of environments, both indoors, outdoors and across multiple floors.
PhyloPat: an updated version of the phylogenetic pattern database contains gene neighborhood

Phylogenetic patterns show the presence or absence of certain genes in a set of full genomes derived from different species. They can also be used to determine sets of genes that occur only in certain evolutionary branches. Previously, we presented a database named PhyloPat which allows the complete Ensembl gene database to be queried using phylogenetic patterns. Here, we describe an updated version of PhyloPat which can be queried by an improved web server. We used a single linkage clustering algorithm to create 241 697 phylogenetic lineages, using all the orthologies provided by Ensembl v49. PhyloPat offers the possibility of querying with binary phylogenetic patterns or regular expressions, or through a phylogenetic tree of the 39 included species. Users can also input a list of Ensembl, EMBL, EntrezGene or HGNC IDs to check which phylogenetic lineage any gene belongs to. A link to the FatiGO web interface has been incorporated in the HTML output. For each gene, the surrounding genes on the chromosome, color coded according to their phylogenetic lineage can be viewed, as well as FASTA files of the peptide sequences of each lineage. Furthermore, lists of omnipresent, polypresent, oligopresent and anticorrelating genes have been included. PhyloPat is freely available at http://www.cmbi. ru.nl/phylopat.
Human Body Scents: Do they Influence our Behavior?

Pheromonal communication in the animal world has been of great research interest for a long time. While extraordinary discoveries in this field have been made, the importance of the human sense of smell was of far lower interest. Humans are seen as poor smellers and therefore research about human olfaction remains quite sparse compared with other animals. Nevertheless amazing achievements have been made during the past 15 years. This is a collection of available data on this topic and a controversial discussion on the role of putative human pheromones in our modern way of living. While the focus was definitely put on behavioral changes evoked by putative human pheromones this article also includes other important aspects such as the possible existence of a human vomeronasal organ. If pheromones do have an influence on human behavior there has to be a receptor organ. How are human body scents secreted and turned into odorous substances? And how can con-specifics detect those very odors and transmit them to the brain? Apart from that the most likely candidates for human pheromones are taken on account and their impact on human behavior is shown in various detail.
Integration of continuous speech recognition and information retrieval for mutually optimal performance

Traditionally, indexing and searching of speech content in multimedia databases have been achieved through a combination of separately constructed speech recognition and information retrieval engines. Although each technology has a legacy of research, only recently have efforts been made to study the potential suboptimality of this strategy, and none of these efforts specifically addresses the presence of uncertainty in automatically generated transcriptions. This research develops a refinement of the most common information retrieval relevance formula, TFIDF, to incorporate uncertainty as a retrieval feature, along with a set of techniques to acquire this uncertainty from multiple hypotheses produced by existing speech recognition data structures. In the process a greater amount of evidence is extracted than is available in the most likely transcription hypothesis, and overall retrieval precision and recall are improved. The term weighting scheme known as the inverse document frequency is shown to be a special case of the mutual information between the document set and the term, the former requiring a Boolean characterization of term occurrence information and the latter permitting fractional probabilities. The relevance between a query and document from speech recognition is then modelled as a random variable arising from the statistical nature of the speech recognition system. The statistics of this model are then derived from the word lattices and the N-Best lists from the output of the recognizer. In analyzing the word lattices, the path probabilities for each node are summed. The relative rankings of competing terms of these summed probabilities are shown to be indicative of the probability of term occurrence. A model of this relationship is used to predict term presence and term count, reducing the degradation in retrieval quality due to speech recognition by 24%. In a separate model, the Top-N distinct text-processed hypotheses from the word lattices are used to estimate the term probability and term count. This strategy reduces the degradation in retrieval quality due to speech recognition by 63%. Experiments were performed on a standardized test of broadcast news stories that had been transcribed manually and judged against a set of natural language queries.
Aspects of Epstein-Barr virus infection in childhood

Antibodies to Epstein-Barr (EB) virus capsid antigen and EB virus complement fixing antibodies were estimated in sera from 23 children and 27 young adults with infectious mononucleosis, and in 79 control patients. Complement fixing antibodies, but not those to virus capsid antigen, were much lower in patients tested during acute infectious mononucleosis than in controls. It is suggested that this disparity could form the basis of a diagnostic test. Anomalous results, in which the EB virus antibody pattern suggested active infection though heterophile antibodies and/or abnormal white blood cells were absent, were observed in sera from patients of all ages but the majority were aged 5 years or less. The proportion of sera with EB virus antibodies increased throughout childhood, suggesting that infection with this virus is relatively frequent in this age group and may often be unrecognized.