Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge Discovery in Scientific Literature

Digital libraries allow us to organize a vast amount of publications in a structured way and to extract information of user’s interest. In order to support customized use of digital libraries, we develop novel methods and techniques in the Knowledge Discovery in Scientific Literature (KDSL) research program of our graduate school. It comprises several sub-projects to handle specific problems in their own fields. The sub-projects are tightly connected by sharing expertise to arrive at an integrated system. To make consistent progress towards enriching digital libraries to aid users by automatic search and analysis engines, all methods developed in the program are applied to the same set of freely available scientific articles.
Looking for Opinion Leaders: Traditional Vs. Modern Measures in Traditional Societies

Since the introduction of the opinion leadership conceptualization, both practitioners and academics have been keenly interested in its applicability in modern society. Numerous studies have been conducted to identify potential opinion leaders, learn of the characteristics distinguishing them from their ‘followers,’ and understand how they exert their personal influence to change opinions and behaviors of the masses. Despite the growing research on opinion leadership, the identification of appropriate opinion leaders for practical purposes continues to be a challenge. Several methods were used to identify opinion leaders. The existence of numerous methods and their use in various societies, social settings and cultures and the variance across domains of opinion leadership raises questions on the applicability and validity of the modern, advanced measures when applied to other social settings. The present study is in fact a first attempt to apply the modern personality strength (PS) scale to a traditional community. The PS scale was found to be an efficient, valid, and useful instrument to identify opinion leaders in numerous studies. However, it was always used, tested, and validated in Western societies (e.g., Germany, USA, and Israel). When we applied the method in the Skukuza community, a small village in South Africa, the findings revealed the inapplicability of the scale in a traditional community. Several factors are suggested to explain the futility of the PS scale in a traditional society.
Immune responses in mice vaccinated with a DNA vaccine expressing serine protease-like protein from the new-born larval stage of Trichinella spiralis

SUMMARY Trichinella spiralis is a parasitic helminth that can infect almost all mammals, including humans. Trichinella spiralis infection elicits a typical type 2 immune responses, while suppresses type 1 immune responses, which is in favour of their parasitism. DNA vaccines have been shown to be capable of eliciting balanced CD4+ and CD8+ T cell responses as well as humoral immune responses in small-animal models, which will be advantage to induce protective immune response against helminth infection. In this study, serine protease (Ts-NBLsp) was encoded by a cDNA fragment of new-born T. spiralis larvae, and was inserted after CMV promoter to construct a DNA vaccine [pcDNA3·1(+)-Ts-NBLsp]. Ts-NBLsp expression was demonstrated by immunofluorescence. Sera samples were obtained from vaccinated mice, and they showed strong anti-Ts-NBLsp-specific IgG response. Mice immunized with the pcDNA3·1(+)-Ts-NBLsp DNA vaccine showed a 77·93% reduction in muscle larvae (ML) following challenge with T. spiralis ML. Our results demonstrate that the vaccination with pcDNA3·1(+)-Ts-NBLsp plasmid promoted the balance of type 1 and 2 immune responses and produced a significant protection against T. spiralis infection in mice.
MARGIE: Memory Analysis Response Generation, and Inference on English

A program is now running at the Stanford A r t i f i c i a l I n t e l I i gence P r o j e c t tha t analyzes na tu ra l language sentences i n t o an under ly ing language-free conceptual r e p r e s e n t a t i o n ; s to res t h i s represen ta t ion i n memory,estab l iahes re ferences and makes inferences] encodes the conceptua l r ep resen ta t i on in to an Engl ish s y n t a c t i c r e p r e s e n t a t i o n ; and then encodes the s y n t a c t i c r e p r e s e n t a t i o n i n t o an Engl ish s t r i n g . The program has two modes: PARAPHRASE and INFERENCE. In PARAPHRASE mode up to 150 semant ic paraphrases can be generated from an input sentence by read ing the conceptual rep resen ta t i on u n d e r l y i n g t ha t sentence using d i f f e r e n t words and concept comb ina t ione . 1n INFERENCE mode, most of the poss ib le i n f e r e n c e s t ha t can be made from an input sentence are produced as ou tpu t .
MAPPING CASE SERIES Utilizing 3 D NavX for Transseptal Puncture as an Additional Safeguard : A Case Series

Transseptal procedures can be associated with procedural related risk. We postulated that transseptal procedural risk and radiation exposure can be reduced utilizing the threedimensional (3D) NavX mapping system to guide the transseptal needle during the transseptal puncture. All patients less than 30 years old who underwent transseptal procedures with the assistance of 3D NavX between January 12 2011 and December 31 2014 were retrospectively evaluated. Data included patient demographics, type of arrhythmia, 3D guidance use, procedure time, fluoroscopy time, complications, and post-procedure outcome. Transesophageal echocardiography and intracardiac echocardiography were not used to assist with transseptal punctures in this study. Before attempting the transseptal puncture, a steerable catheter was used to probe for a patent foramen ovale (PFO) using the previously generated 3D model as a reference. If a PFO was present, it was marked on the 3D NavX model and used as the transseptal access site. If a transseptal puncture was required, an alligator clip was connected to the transseptal needle hub, which was connected to the 3D NavX to allow needle tip localization once the needle tip touched the blood pool during the transseptal puncture. Tracking the needle tip was utilized in addition to standard techniques to further evaluate needle location during the puncture. Echo imaging was not used. Fifty-one patients less than 30 years of age were evaluated. A PFO was present in 14 patients. The remaining 37 patients underwent a transseptal puncture guided by 3D NavX in addition to standard techniques. The median procedure time was 107 min (range 52–346 min) from lidocaine injection to time of catheter removal. The median fluoroscopic time for the full procedure was 1.3 min (range 0.00–19.2 min, mean 2.33 min). There were no transseptal procedure-related complications. Localization of the transseptal needle tip during the transseptal puncture is feasible, and reduces radiation exposure and may reduce procedural risk.
How anticipation for the sense of agency affects readiness potential

In recent Japanese society, we are facing a severe increase in the number of patients who suffer from motor paralysis and other dysfunctions. Establishing an effective rehabilitation system for them is important, and the key to attain this target is to clarify the mechanisms of one's body perception in the brain. The feeling of controlling our action and external event is an important aspect of body perception, and thus is a topic we have to investigate. This feeling is called the Sense of Agency (SoA), and in order to clarify the mechanism of the SoA, it is necessary to clarify neuro-physiological indices that reflect the arising of this feeling. Recent investigated the relationship between SoA and neural activity with event-related potential (ERP) but these studies focused only on the feedback processing after the action-feedback (e.g. N100, P300), while no study investigated the neural basis of the action-preceding part during SoA paradigm. In this research we focused on feedback-anticipation as an action-preceding factor of SoA, and the purpose of this research is to find a neuro-physiological indices which reflect this factor. We hypothesized that readiness potential (RP) would reflect this factor. In the Libet's clock task based experiment, two conditions which differed in the state of the anticipations for the feedback were prepared. In order to manipulate the anticipation, the probability of the tone occurrence was manipulated in each condition. Earlier and larger RP was observed when the feedback-anticipation was inconsistent in relative with the consistent condition, and additional experiment by increasing the sample size is needed. Our study is the first one that reveals the neural basis of the action-preceding factor of SoA, and we believe that our study will contribute to unravel the neural basis of the SoA.
Weighted-kernel Deterministic Annealing algorithm to shape clustering

Clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is a method of unsupervised learning to draw inferences from datasets consisting of input data without labeled responses. Clustering is used for exploratory data analysis to find hidden patterns or grouping in data. The clusters are modeled using a measure of similarity which is defined upon metrics such as Euclidean, pairwise or probabilistic distance. The problem is computationally difficult (NP-hard), and thus the common approach is to search only for approximate solutions. A particularly well known approximation method is Lloyd’s algorithm,[3] often actually referred to as “k-means algorithm". It does however only find a local optimum, and is commonly run multiple times with different random initializations. On the contrary, Rose in [1] proposed an annealing-based algorithm, well described in terms of laws such as minimum free energy principle in statistical physics literature, and showed that the solutions obtained using this approach are totally independent of the choice of initial configurations. The algorithm is referred as deterministic annealing (DA) algorithm and is aimed to provide high-quality solutions to a clustering problem with only marginal increase in computational complexity. The original DA algorithm by Rose aims to cluster a set of points X = {xi ∈D : 1 ≤ i ≤ N } in some bounded domain D in the Euclidean space, i.e., the points are separable in the Euclidean domain. However, a major drawback to DA algorithm is that it cannot separate clusters that are non-linearly separable in input space. On the other hand, the task of
Using dominant sets for data association in multi-camera tracking

This paper presents a novel approach to solve data association in multi-camera multi-target object tracking. The main novelty is represented by the first known use of dominant set framework for intra-camera and inter-camera data association. Thanks to the properties of dominant sets, we can treat the data association as a global clustering of the detections (people or other targets) obtained over the whole sequence of frames from all the cameras. In order to handle occlusions, splitting and merging of targets, an efficient out-of-sample extension to dominant sets has been introduced to perform data association between different cameras (inter-camera data association). Experiments carried out on PETS '09 public dataset showed promising performance in terms of accuracy (precision and recall, as well as MOTA) when compared with the state of the art.
rpoB Gene Sequencing for Identification of Corynebacterium Species

ABSTRACT The genus Corynebacterium is a heterogeneous group of species comprising human and animal pathogens and environmental bacteria. It is defined on the basis of several phenotypic characters and the results of DNA-DNA relatedness and, more recently, 16S rRNA gene sequencing. However, the 16S rRNA gene is not polymorphic enough to ensure reliable phylogenetic studies and needs to be completely sequenced for accurate identification. The almost complete rpoB sequences of 56 Corynebacterium species were determined by both PCR and genome walking methods. In all cases the percent similarities between different species were lower than those observed by 16S rRNA gene sequencing, even for those species with degrees of high similarity. Several clusters supported by high bootstrap values were identified. In order to propose a method for strain identification which does not require sequencing of the complete rpoB sequence (approximately 3,500 bp), we identified an area with a high degree of polymorphism, bordered by conserved sequences that can be used as universal primers for PCR amplification and sequencing. The sequence of this fragment (434 to 452 bp) allows accurate species identification and may be used in the future for routine sequence-based identification of Corynebacterium species.
2 INSIDE THE MNC : STRUCTURING OWNERSHIP OF FIRM-SPECIFIC ADVANTAGES

This study examines how multinational firms (MNCs) organize internal ownership of their firmspecific advantages (FSAs). In contrast to the assumption that FSAs are a public good within MNCs, we find that MNCs allocate economic ownership of their FSAs to affiliates and/or the parent within the firm. The MNC entities that own the FSAs contract or license them to other MNC entities. We draw on property rights theory to understand the decisions that MNCs make with regard to the internal ownership of FSAs, and we identify four different ways in which MNCs choose to structure internal FSA ownership. We argue that these structures are important in creating internal incentives and facilitating coordination. We find that MNCs with independent and easily codifiable FSAs, such as trademarks, are more likely to use ownership structures that provide market-like incentives. In contrast, MNCs with knowledge-intensive, tacit FSAs are more likely to use ownership structures that facilitate knowledge sharing and coordination within the firm.
Effects of Monodora myristica Seed on Lipid Profiles , and Mineral Concentrations of Male , Female , Pregnant and Lactating Albino Rats

Effects of Monodora myristica seed on lipid profiles, and mineral concentrations of male, female, pregnant and lactating albino rats. Lipid profile results revealed that cholesterol reduction in male and female rats become significantly (p<0.05) affected when compared with their controls after one weeks. Those of pregnant and lactating rats became significantly (p<0.05) affected against their control after two weeks. HDL-cholesterol and LDL-cholesterol were significantly (p<0.05) affected in all the status of rats used when compared to their controls. The levels of the mineral ions as observed in the present study were insignificantly (p>0.05) affected in all the status of rats used against their control. Hence Monodora myristica was not able to influence the levels of the mineral ions investigated in all the status of rats used. This study has shown the effects of Monodora myristica seed on lipid profiles and mineral concentrations of male, female, pregnant and lactating albino rats. (
Efficient Hidden Vector Encryptions and Its Applications 1

Predicate encryption is a new paradigm of public key encryption that enables searches on encrypted data. Using the predicate encryption, we can search keywords or attributes on encrypted data without decrypting the ciphertexts. In predicate encryption, a ciphertext is associated with attributes and a token corresponds to a predicate. The token that corresponds to a predicate f can decrypt the ciphertext associated with attributes x if and only if f (x) = 1. Hidden vector encryption (HVE) is a special kind of predicate encryption. HVE supports the evaluation of conjunctive equality, comparison, and subset operations between attributes in ciphertexts and attributes in tokens. Currently, several HVE schemes were proposed where the ciphertext size, the token size, and the decryption cost are proportional to the number of attributes in the ciphertext. In this thesis, we consider the efficiency, the generality, and the security of HVE schemes. The results of this thesis are described as follows. The first results of this thesis are efficient HVE schemes where the token consists of just four group elements and the decryption only requires four bilinear map computations, independent of the number of attributes in the ciphertext. The construction uses composite order bilinear groups and is selectively secure under the well-known assumptions. The second results are efficient HVE schemes that are secure under any kind of pairing types. To achieve our goals, we proposed a general framework that converts HVE schemes from composite order bilinear groups to prime order bilinear groups. Using the framework, we convert the previous HVE schemes from composite order bilinear groups to prime order bilinear groups. The third results are fully secure HVE schemes with short tokens. Previous HVE schemes were proven to be secure only in the selective security model where the capabilities of the adversaries are severely restricted. Using the dual system encryption techniques, we construct fully secure HVE schemes with match revealing property in composite order groups.
Employee Branding And Service Quality: The Moderating Effect Of Employees' Role Behavior

The purpose of this study is to identify relationship between employee branding and service quality as well as the moderating effect of employees’ role behavior on the employee branding-service quality relationship. It presents the findings from a questionnaire survey of 370 shoppers in one of the shopping complex located at Southern region of Malaysia. The results of hierarchical multiple regression analysis revealed that there is a significant moderating effect of employees’ role behavior on the employee branding-service quality relationship. The findings may be useful in designing customer retention strategies that are related to the retailing business. Implications, limitations of study and suggestions for future study are also explored.
The hydraulic condition analysis and optimal cross-section design of the “rectangle -v” shaped drainage canal of debris flow

The drainage canal is one of the most widely-used engineering measures in preventing debris flow. The cross- section shape and size are important parameters for designing the drainage canal of debris flow. While how to choose the optimal shape and size to make the drainage canal of debris flow have the best discharging ability is a problem few people have researched. The "Rectangle-V" shape is one of the widely-used cross-section shapes of debris flow drainage canal. This paper chooses it as a researching object, analyzes its optimal hydraulic condition, and discusses its optimal cross-section design. The cross-section configuration parameter (M) of "Rectangle-V" shaped debris flow drainage canal is defined as the ratio of wetted perimeter (P) to hydraulic radius(R). Based on the definition, the calculation formula of M is deduced under the optimal hydraulic condition. The formula indicates that M only relates with the bottom transverse slope coefficient under the optimal hydraulic condition. Assuming the discharge of debris flow (Q), the longitudinal gradient of debris flow drainage canal (I) and the gradation of debris flow grain size as known, we deduce the combinatorial calculating formulas of the cross- section size of "Rectangle-V" shaped debris flow drainage canal by using the simultaneous numerical solution method. On the basis of the analysis of the optimal hydraulic condition of "Rectangle-V" shaped debris flow drainage canal, this paper takes the Huoba Gully as an example for the optimal cross- section design of debris flow drainage canal.
Validating Black-Scholes Model in Pricing Indian Stock Call Options

Derivativesâ€™ trading was introduced in India during 2001, and the trade value of derivatives is almost three times that of cash market trade values. However, only about 20 percent of the options offered by the National Stock Exchange (NSE) are traded on an active basis. This is perhaps due to the lack of investor education about options and its pricing methodology. It is hoped that research on option pricing in India will enable investors to understand the mechanism of option pricing and its use as a tool to hedge risks. This empirical paper uses more than 95,000 call options to test the validity of the Black-Scholes (BS) model in pricing Indian Stock Options. The results show the robustness of the Black-Scholes model in pricing stock options in India and that pricing is further improved by incorporating implied volatility into the model.
The 22 nd Annual Conference of the Japanese Society for Artificial Intelligence , 2008-1-Classifying biomedical text abstracts using binary and multi-class Support Vector Machine

Text classification systems on biomedical literature aim to select relevant articles that match query keywords from large corpora. For this purpose, systems for finding relevant documents must be able to identify terms related to the search in the abstracts and also must distinguish between relevant and irrelevant results. Lately, many researchers attempt to find more applicable ways for classifying biomedical text articles in order to help users find relevant articles on the web. Due to this reason, our focus is on the problem of identifying relevant and irrelevant documents based on binary and multi-class classification in biomedical texts, especially for text biomedical abstracts. For our experiments, we have randomly downloaded and collected 400 paper abstracts of four diseases, including cancer, hepatitis, HIV/AIDS and thyroid from Medline database. Then, we have tested and compared the performance of binary classification and multi-class classification using LIBSVM. The results obtained in our experiments demonstrate that the accuracy of binary classification on the average 80.89% (with scaling) and 86.92% (without scaling), meanwhile multi-class classification on the average 75.73% (with scaling) and 85.25% (without scaling) for our biomedical text data with four categories of diseases. We observe that the choice of percentage for training and testing dataset has little influence on the classification accuracy.
Technical Background and Methodology for the Elsevier ’ s Artificial Intelligence Report

Abstract—In this paper we give the background of theIn this paper we give the background of the technical work conducted in the framework of preparing Elsevier’s AI report. It explains how we are using a corpusbased approach and keyword extraction and seeding to focus on articles that potentially represent the core of the field. We then utilize both supervised and unsupervised machine learning approaches to filter and analyze this corpus with the aim to understand its trends, subfields, the connections between them, as well as how they evolve over