Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and Safety of Telaprevir , Pegylated Interferon α2 b and Ribavirin Triple Therapy in Japanese Patients Infected with Hepatitis C Virus Genotype 1 b

Objective This study evaluated the efficacy and safety of triple therapy with telaprevir (TVR), pegylated interferon α-2b (PegIFN-α-2b) and ribavirin (RBV) in Japanese patients chronically infected with hepatitis C virus (HCV) genotype 1b in real-world clinical practice. Methods A total of 106 consecutive patients with HCV genotype 1b were treated with triple therapy for 12 weeks followed by dual therapy with PegIFN-α-2b and RBV for 12 weeks. The primary end point was sustained virological response (SVR), defined as undetectable serum HCV RNA at 24 weeks after the end of treatment. Results The overall SVR rate was 87.7% (93/106 patients). Age and body weight (BW) differed significantly between patients with and patients without SVR. Multivariate analysis showed that age <67 years [odds ratio (OR) 5.03, p=0.014] and BW 55 kg (OR 5.87, p=0.008) were independent pretreatment factors predictive of SVR. When posttreatment factors were included, age <67 years (OR 7.30, p=0.041), rapid virological response (OR 10.60, p=0.019) and continuation of therapy (OR 14.45, p=0.012) were each independently associated with SVR. Body weight <55 kg (OR 5.96, p=0.015) and TVR initial dose 41 mg/kg/ day (OR 5.19, p=0.017) were each independently associated with discontinuation of therapy. Discontinuation rates decreased in inverse proportion to the percentage of patients with an initial TVR dose of 1,500 mg/day. Conclusion For TVR-based triple therapy, continuation of therapy is the most important predictor of SVR. Patients who are likely intolerant of standard-dose TVR should receive reduced initial doses of TVR to avoid discontinuation of therapy.
Safe operating area of a 0.15µm GaAs PHEMT in overdrive operating conditions

We present an evaluation of the safe operating area of a 0.15 μm GaAs PHEMT operating under overdrive conditions. The approach, used to delimit the device safe operating area, consists on performing on-state and off-state accelerated DC step stresses for bias conditions included in the device breakdown region. The accelerated DC stresses have induced weak degradations of the device electrical parameters attributed to trap effects.
SUSTAINABLE FACTORS IN THE HUMAN ASSETS OF DANA HOTEL AS A HERITAGE HOTEL IN SOLO, INDONESIA

This research aims to study what sustainable factors of Dana Hotel in the human assets; and also find out what the status of Dana Hotel, using VRIN analysis (Value, Rarity, Imperfect Imitability, and Non-Subs­ti­tu­ta­bility) from Natural Language Data of observation and in-depth interviews in a descriptive qua­litative study. In results, in order to achieve sustainability, Dana Hotel has valuable, rare, imperfectly imitable, and non-subs­titutable factors in the human assets. As the human assets are valuable, rare, im­perfectly imitable, and non-subs­titutable, the status of Dana Hotel is sustainable in the context of hu­man resources. It is concluded that following the success of Dana Hotel, organizations that have those fac­tors or even more, tend to have big opportunities to survive.
Registered Replication Report on Mazar, Amir, and Ariely (2008)

The self-concept maintenance theory holds that many people will cheat in order to maximize self-profit, but only to the extent that they can do so while maintaining a positive self-concept. Mazar, Amir, and Ariely (2008, Experiment 1) gave participants an opportunity and incentive to cheat on a problem-solving task. Prior to that task, participants either recalled the Ten Commandments (a moral reminder) or recalled 10 books they had read in high school (a neutral task). Results were consistent with the self-concept maintenance theory. When given the opportunity to cheat, participants given the moral-reminder priming task reported solving 1.45 fewer matrices than did those given a neutral prime (Cohen’s d = 0.48); moral reminders reduced cheating. Mazar et al.’s article is among the most cited in deception research, but their Experiment 1 has not been replicated directly. This Registered Replication Report describes the aggregated result of 25 direct replications (total N = 5,786), all of which followed the same preregistered protocol. In the primary meta-analysis (19 replications, total n = 4,674), participants who were given an opportunity to cheat reported solving 0.11 more matrices if they were given a moral reminder than if they were given a neutral reminder (95% confidence interval = [−0.09, 0.31]). This small effect was numerically in the opposite direction of the effect observed in the original study (Cohen’s d = −0.04).
SoCo: a social network aided context-aware recommender system

Contexts and social network information have been proven to be valuable information for building accurate recommender system. However, to the best of our knowledge, no existing works systematically combine diverse types of such information to further improve recommendation quality. In this paper, we propose SoCo, a novel context-aware recommender system incorporating elaborately processed social network information. We handle contextual information by applying random decision trees to partition the original user-item-rating matrix such that the ratings with similar contexts are grouped. Matrix factorization is then employed to predict missing preference of a user for an item using the partitioned matrix. In order to incorporate social network information, we introduce an additional social regularization term to the matrix factorization objective function to infer a user's preference for an item by learning opinions from his/her friends who are expected to share similar tastes. A context-aware version of Pearson Correlation Coefficient is proposed to measure user similarity. Real datasets based experiments show that SoCo improves the performance (in terms of root mean square error) of the state-of-the-art context-aware recommender system and social recommendation model by 15.7% and 12.2% respectively.
Scale for Measuring Transformational Leadership in Public Sector Organizations in Sri Lanka: With Special Reference to Ministries of Western Provincial Council

The most accepted Multifactor Leadership Questionnaire (MLQ) is heavily applied to measure the transformational leadership in private sector and central government organizations than provincial council organizations in Sri Lanka. Thus this paper describes the development of a 21 item instrument for assessing transformational leadership in provincial council organizations in Sri Lanka with special reference to the western provincial council. To do so, both qualitative and quantitative methods were applied in three fundamental stages recommended by Churchill (1979). Initially a qualitative research was undertaken in five ministries in the western provincial council within Colombo district through interviews with 15 senior and middle level administrative officers from different back grounds which produced 21 items with four factors emerged. These 21 -items were included in a questionnaire and quantitative study was undertaken with the same respondents who were currently involved in the service in the Western Provincial Council. 60 questionnaires were distributed and 56 questionnaires were returned and found to be useful 56, which represents a 93% response rate. More than half (52) of the respondents were female between the age of 40-55. To ensure the reliability and validity of the measures of transformational leadership construct, mainly reliability test, factor analysis, was used. Finally, 21 items were deducted into 10 items and a new scale was developed to measure the transformational leadership in public sector organizations with three dimensions idealized influence, inspirational motivation, intellectual stimulation and. Regarding the limitations of the study in this respect, only the senior and middle level managers were considered. The sample size was 60 and it was selected only from the western provincial council with the use of purposive sampling technique. Further studies with large sample size which covers the all provincial councils using newly developed scale to measure the transformational leadership and replication studies with other organizations would be useful for further generalizations of the newly developed scale.
Effects of multiple interventions

The purpose of this chapter is (i) to describe some currently available analytical methods for using individual level epidemiological data to estimate the impact of multiple risk factor interventions on health and (ii) to carefully review the conditions under which these methods deliver unbiased estimates of impact. The chapter is organized as follows. In sections 2 and 3, we discuss estimation of effects of short-term, timeindependent interventions. Specifically, we discuss estimating the effect of a single risk factor intervention on life expectancy or quality-adjusted life expectancy over a specified period of follow-up in a single population, when essentially ideal epidemiologic data are available. That is, we assume a random sample of the population is randomly assigned to different levels of the risk factor and followed prospectively for a fixed time period. Second, we consider the same study design, except now we are interested in the joint effect of an intervention on several risk factors. Third, we consider the problem of extrapolation of the results to longer periods of follow-up and to other populations for which no primary epidemiologic data are available. Sections 2 and 3 serve to indicate the possibilities and limitations of even ideal epidemiologic data for estimating the effects of multiple time-independent risk factor interventions. In sections 4 and 5 we turn to the main topic of this chapter: the estimation of the effect of multiple time-dependent interventions from observational data, possibly plagued by confounding, selection bias, measurement error, information bias and ill-defined interventions. In sections 6 to 8, we illustrate our methods by attempting to estimate the effects of various time-varying interventions on subjects entered in the Framingham Offspring cohort study. Finally, in section 9 we offer some conclusions. Chapter 28
Global Grids and Cloud Toolkits

In the past few years, many overlying concepts of distributed computing eminently cluster, grid and cloud computing have appeared. In recent years, extensive researches have been conducted in the area of simulation to model large complex systems and understand their behavior, especially in parallel and distributed systems. Distributed computing combines multiple computers, geographically dispersed in a cost effective way and presents a single unified resource to the end user with huge storage and computational power. Due to their complexity, grid computing and cloud computing applications need to be tested before running on an appropriate infrastructure. However, access to such infrastructures is not feasible or available to everyone. Therefore, various simulation tools were developed to ease the cost and complexity of testing these applications. Therefore, the aim of this paper is to analyze and compare various simulation tools for some distributed systems such as grid computing and cloud computing.
Hedge Fund Politics and Portfolios

Consistent with the well-documented relation between political orientation and psychological traits, hedge funds’ political orientations are related to their portfolio decisions. Relative to politically conservative hedge funds, politically liberal hedge funds exhibit a preference for smaller stocks, less mature companies, volatile stocks, unprofitable companies, non-dividend paying companies, and lottery-type securities. Politically liberal hedge funds are also more likely to enter new positions or fully exit existing positions, and make larger adjustments to their U.S. equity market exposure. Our results suggest that psychological characteristics can influence the portfolio decisions of even those at the very top of the financial sophistication ladder.
Real-Time Anomaly Detection from Edge to HPC-Cloud

Telemetry data plays an important role in many areas such as motor racing, meteorology, agriculture, transportation, manufacturing processes and energy monitoring to name a few. There lies a direct intersection between embedded computing and big data analysis. In the domain of motor racing, telemetry data is very widely used for analyzing or improving the performance of the racing cars and monitoring the effects of racing towards the physical status of the race car drivers. A large number of sensors, in the number of 100s, are fixed on the racing car. There are on-board and off-board electronic systems that transmit the sensor readings to teams on the pit and electromechanical systems that control the fuel utilization, throttling, etc. The generated sensor readings are then analyzed using several big data analysis methods, with detecting anomaly events at edge and conducting correlation analysis for high dimensional data on HPC and Cloud.
Isolation, expression and characterization of a minor allergen from Penicillium crustosum.

A ribosomal P1 protein, Pen b 26 from Penicillium brevicompactum, was previously identified as a major allergen. A homolog protein was isolated and characterized from Penicillium crustosum which is not known to be allergenic mold. A cDNA library of P. crustosum was constructed and screened using a probe based on the DNA sequence of Pen b 26. A positive clone was isolated, expressed in Escherichia coli, purified and characterized by comparing its immunological and physical properties to Pen b 26. It was designated as Pen cr 26 and had a 321 nt ORF corresponding to 107 amino acids with a MW of 11 kDa. Pen cr 26 had strong sequence homology to Pen b 26 (92% for nucleotides and 86% for amino acids) and its physical and predicted structural properties were similar to the latter. The level of expression of Pen cr 26 was much lower than that of Pen b 26 in the same expression vector. Both proteins were recognized equally well by the IgG class specific antibodies, but Pen cr 26 was poorly recognized by Penicillium-sensitive atopic sera (IgE), suggesting striking antigenic difference in IgE epitopes, i.e., 87% were positive for Pen b 26 while only 23% were positive for Pen cr 26. The allergenicity of Pen cr 26 seems to be minor in nature and it could be a hypoallergenic variant of Pen b 26.
GrandLand Traffic Data Processing Platform

Recent years have seen an increasing number of traffic surveillance cameras deployed on the main roads and intersections of metropolitan areas. For large and ediumsized cities, these cameras generate an enormous amount of data. Existing solutions based relational database systems cannot effectively manage and process such large volume of data, nor can they provide support for efficient and scalable support for either analytical tasks or tasks requiring response in real-time. To address these challenges, we have developed the GrandLand Traffic Data Processing Platform (GLPlatform) to provide distributed, scalable processing of traffic surveillance data.
Bayesian Foundations of Constant-Gain Learning

Constant-gain learning (CGL) models replace the assumption of model-consistent expectations by a near-rational expectation formation mechanism in which the agents estimate over time the coe¢ cients of a perceived law of motion for economic variables. A crucial parameter under CGL is the gain coe¢ cient, which governs the rate at which agents discount past information when forming expectations. In this paper, we provide a microfoundation for the use of CGL based on Bayesian theory. In particular, we demonstrate how, under certain conditions, CGL expectations can approximate the average beliefs of heterogeneous …nitelylived agents who “learn from experience”. That is, individuals update their expectations by Bayesian methods based on observations from their own lifetimes. In this case, the constant gain coe¢ cient is a function of the average life-expectancy and of the precision of the priors. We study the example of a Lucas-tree asset-pricing model where individuals learn from experience about stock prices and dividends. In this model, the above approximation is valid and the stock price expectations display stochastic ‡uctuations around the rational expectations solution due to waves of optimism and pessimism loosely related to fundamentals.
Loneliness in Children With High Functioning Pervasive Developmental Disorders

Although children with high-functioning pervasive developmental disorders (HFPDD) may notice that they are di‹erent from other children, they may not su›ciently understand what is speci⁄cally di‹erent about them, which may increase their feeling of loneliness. The present article examined developmental and qualitative di‹erences in feelings of loneliness of children with HFPDD and children who are typically developed by investigating the relationship between competence and loneliness. Children with HFPDD (n=45) and children who are typically developed (n=281) who were at various stages of development completed a loneliness and competence scale. The results suggested that after the higher grades of elementary school, the children with HFPDD were lonelier than the children who are typically developed. The loneliness and competence scores were independent of each other among the children with HFPDD, whereas those scores were signi⁄cantly negatively correlated in the children who are typically developed. Loneliness in children with HFPDD may be unlike that experienced by children who are typically developed; their loneliness may not be related to psychological conditions, such as appreciating interactions with friends, but rather directly related to physical conditions, such as a lower number of acquaintances. Therefore, both subjective and objective aspects of loneliness must be considered.
Seahorses of the Hippocampus coronatus complex: taxonomic revision, and description of Hippocampus haema, a new species from Korea and Japan (Teleostei, Syngnathidae)

Abstract Morphological and molecular analyses were conducted on 182 specimens belonging to the Hippocampus coronatus complex (H. coronatus sensu lato), collected in Korea and Japan 1933–2015, in order to clarify the taxonomic status of the species within this complex. Three species are recognized based on the shape of the coronet, the number of trunk rings (TrR) and tail rings (TaR), and presence or absence of a wing-tip spine (WS) at the dorsal fin base. Hippocampus coronatus Temminck & Schlegel, 1850 (H. coronatus sensu stricto), is diagnosed by 10 TrR, 37–40 TaR, an extremely high coronet (55.7–79.0 % head length) with four tips on the corona flat (CoT), and one WS. Hippocampus sindonis Jordan & Snyder, 1901 is diagnosed by 10 TrR, 35–38 TaR, a moderately high coronet (36.3–55.4 % HL) with five CoT, and no WS. A new species, H. haema is described on the basis of 140 specimens, characterized by 10 TrR, 35–38 TaR, a moderately high coronet (34.1–54.9 % head length) with four CoT, and two WS. Hippocampus haema is only known from the Korea Strait, western Kyushu, and East/Japan Sea. Recognition of the three species is supported by differences in mitochondrial DNA fragments (cytochrome b, 16S rRNA, and 12S rRNA).
Implementation and evaluation of a large-scale object detection system

In this report, we give detailed information about implementation and evaluation efforts that were undertaken w.r. t. the system described in [1]. Particular emphasis is given to system-level learning of contextual dependencies, and in particular to the computation of visual features used by the employed learning algorithms. Another important issue treated here concerns the evaluation of the system: we give details about the evaluation procedures and the HRI RoadTraffic dataset which is the basis of the evaluation efforts. As a last point, we compare the HRI RoadTraffic dataset to other publicly available, annotated datasets for road traffic and present arguments why the HRI RoadTraffic dataset constitutes a suitable reference dataset for future benchmarking efforts.
Measuring the relative performance of schema matchers

Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by human experts, to automatic matching, using various heuristics (schema matchers). In this work, we consider the problem of linearly combining the results of a set of schema matchers. We propose the use of machine learning algorithms to learn the optimal weight assignments, given a set of schema matchers. We also suggest the use of genetic algorithms to improve the process efficiency.
Creating virtual walkthrough environment from vertical panoramic mosaic

In this paper, a novel algorithm for creating virtual indoor environments is described. First, a panoramic mosaic is generated from a series of photos taken with a camera rotates along a horizontal axis. Then, from the panoramic mosaic image, a nonfixed viewing point virtual walkthrough system can be created by defining manually the corners in the vertical panoramic mosaic. The side ratio of the virtual walkthrough system can be obtained from the panning angle subsequently. By applying the cylindrical projection technique, the texture for the sides of the virtual walkthrough environment can be projected in a more realistic way. Real images have been used to verify our proposed algorithm with satisfactory results.
Towards the development of conceptual dictionary for narrative generation system

This paper describes the structure and function of conceptual dictionary positioning in our integrated narrative generation system architecture. It provides knowledge of verb concepts and noun concepts associated with an event concept that is a basic constitutional unit in narrative. This dictionary is developing now with the integrated narrative generation system. In this paper, we report the current developmental process to consider future expansion and plan. Current version of verb concept dictionary has 5337 case frames and modified 300 constraints, and noun concept dictionary contains 142168 noun concepts including 5770 intermediate concepts. After we explain the structure, we introduce the role and function in narrative generation process using two application systems.
Real Time Dynamic Image Retargeting Based on a Dynamic Visual Attention Model

With the constantly growing number of multimedia devices, images can now be viewed on a broad range of display of tremendously varying size. However, perceiving all the details of a multimedia content is difficult on smaller mobile devices. To solve this problem, saliency based image re-targeting algorithms have been proposed in order to generate more perceptually efficient thumbnails. In this article, we propose a new real-time visual attention based image re-targeting method which differs from previous works in that it generates dynamic (i.e. time changing) thumbnails. This unique behavior is made possible by the use of a dynamic computational model of visual attention. By exploiting the singular characteristics of this model, we are able to dynamically re-target large and complex images in order to efficiently script their discovery on large and small displays. We achieved such re-targeting by integrating simulated attentional focuses over a fixed time window into a temporal heat-map. By segmenting this heat-map at each time step, we can generate the region of interest that will be displayed as dynamic preview. In order to validate that every salient location of the image has been displayed, we compare the regions shown in the preview with mean observers eye fixations obtained during a free viewing experiment.