Miracle-dz/UniFAR-FTUs huggingface dataset:
Chinese Herbal Medicine Qi Ju Di Huang Wan for the Treatment of Essential Hypertension: A Systematic Review of Randomized Controlled Trials

Background. Chinese herbs are potentially effective for hypertension. Qi Ju Di Huang Wan (QJDHW) is a commonly used Chinese herbal medicine as a monotherapy or in combination with other antihypertensive agents for the treatment of essential hypertension (EH). However, there is no critically appraised evidence such as systematic reviews or meta-analyses on the effectiveness and safety of QJDHW for EH. Methods and Findings. CENTRAL, PubMed, CBM, CNKI, VIP, and online clinical trial registry websites were searched for published and unpublished randomized controlled trials (RCTs) of QJDHW for essential hypertension up to January 2013 with no language restrictions. A total of 10 randomized trials involving 1024 patients were included. Meta-analysis showed that QJDHW combined with antihypertensive drugs was more effective in lowering blood pressure and improving TCM syndrome for the treatment of essential hypertension than antihypertensive drugs used alone. No trials reported severe adverse events related to QJDHW. Conclusions. Our review suggests that QJDHW combined with antihypertensive drugs might be an effective treatment for lowering blood pressure and improving symptoms in patients with essential hypertension. However, the finding should be interpreted with caution because of the poor methodological quality of included trials. There is an urgent need for well-designed, long-term studies to assess the effectiveness of QJDHW in the treatment of essential hypertension.
Organising Committee Program Committee Developing Self-regulated Learning in Ict-based Narrative Environments 32 Affect Detection and Metaphor in E- Drama: the First Stage Introduction and Relationship to Other Work 1. a Preliminary Approach to Affect Detection and Responding towards Improving Recal

3 Preface Narrative has been an important form to transmit knowledge across generations, and is innate to the human nature. Narrative is also a valuable vehicle to structure knowledge and to help us in the process of meaning making. Due to the explorative and complex nature of narrative, an intelligent learning environment (ILE) based on a narrative approach can promote several kinds of activities for learners: co-construction: participate in the construction of a narrative; exploration: engage in active exploration of the learning tasks, following a narrative approach and trying to understand and reason about an environment and its elements; reflection: engage in consequent analysis of what happened within the learning session. By applying a narrative approach in the development of an ILE, its is possible to attain an application that may help the learners to share ideas and points of view, to experience a particular situation by engaging in a role-playing, or even to post reflect on an action taken within such environment. The main goal of this workshop is to bring together researchers from different disciplines to discuss the creation of what we call narrative learning environments (NLE). In our view, narrative learning environments are a specific type of intelligent learning environments where narrative is approached and applied. The several applications of narrative and the several ways of conveying it within an ILE are an interesting topic to be addressed within this workshop. By analysing the variety of uses of narrative, it might be possible to devise a set of guidelines to be followed by other researchers when developing a NLE. The diverse ways in which NLE's have been developed and tested in the past few years (e.g. Puppet, POGO, Teatrix, Ghostwriter, etc.) suggest that the time has come to reflect on these practices and strive for an overview of principles and guidelines that have been applied. By trying to answer basic questions on the role of narrative in Intelligent Learning Environments, we aim to contribute to understanding more precisely and exploiting more effectively the potential of narrative in education. Abstract. We report work in progress on adding affect-detection to an existing e-drama program, a text-based software system for (human) dramatic improvisation in simple virtual scenarios, for use primarily in learning contexts. The system allows a human director to monitor improvisations and make interventions, for instance in reaction to excessive, insufficient or inappropriate emotions in the characters' speeches. Within …
Deception as a Conflict Management Technique Scale: A Preliminary Analysis

The current study was undertaken to develop a self-reporting scale on the perceptions and the uses of deception, both in general and as a conflict management technique. The study was initiated with Item Pool Generation followed by Data Collection which further leads towards Item Selection and finally the reliability and validity assessments. For data collection, a random sample of 408 individuals was drawn and administered with 50-item pool to carry out the item selection. For reliability assessment, a sample of 103 individuals on random basis were derived for the establishment of test-retest reliability. For validity assessment, 135 individuals’ random sample was extracted and administered with a battery of tests for ascertaining construct validity. The results of Item-total correlation was calculated and 35 items were selected at 0.05 level of significance. The internal consistency of Deception as Conflict Management Technique Scale (DCMTS) was calculated at 0.896 Cronbach alpha level. Exploratory factor analysis was carried out using varimax rotation. Psychometric reliability and validity assessments concluded that the 35-item scale has significant test-retest reliability and high correlation values are reported for both convergent and discriminant validity. The study further elaborated on the theoretical understanding and implementation of the DCMTS along with its limitations and implications.
Random partial paired comparison for subjective video quality assessment via hodgerank

Subjective visual quality evaluation provides the groundtruth and source of inspiration in building objective visual quality metrics. Paired comparison is expected to yield more reliable results; however, this is an expensive and timeconsuming process. In this paper, we propose a novel framework of HodgeRank on Random Graphs (HRRG) to achieve efficient and reliable subjective Video Quality Assessment (VQA). To address the challenge of a potentially large number of combinations of videos to be assessed, the proposed methodology does not require the participants to perform the complete comparison of all the paired videos. Instead, participants only need to perform a random sample of all possible paired comparisons, which saves a great amount of time and labor. In contrast to the traditional deterministic incomplete block designs, our random design is not only suitable for traditional laboratory and focus-group studies, but also fit for crowdsourcing experiments on Internet where the raters are distributive over Internet and it is hard to control with precise experimental designs. Our contribution in this work is three-fold: 1) a HRRG framework is proposed to quantify the quality of video; 2) a new random design principle is investigated to conduct paired comparison based on Erdos-Renyi random graph theory; 3) Hodge decomposition is introduced to derive, from incomplete and imbalanced data, quality scores of videos and inconsistency of participants'judgments. We demonstrate the effectiveness of the proposed framework on LIVE Database. Equipped with random graph theory and HodgeRank, our scheme has the following advantages over the traditional ones: 1) data collection is simple and easy to handle, and thus is more suitable for crowdsourcing on Internet; 2) workload on participants is lower and more flexible; 3) the rating procedure is efficient, labor-saving, and more importantly, without jeopardizing the accuracy of the results.
Self-determination and academic engagement of students with learning disabilities in a special education context

Policies that promote inclusive education have been adopted by provincial governments across Canada to provide students with disabilities access to the general education classroom, its curriculum, and interaction with their peers without disabilities. However, there is debate over the ability of general education classrooms to meet the learning needs of students with learning disabilities. The purpose of this study was to investigate student experiences within a self-contained special education classroom and address the primary research question: What is the lived experience of students with learning disabilities within the Literacy Development Program (LDP)? This research was guided by self-determination theory (SDT; Ryan & Deci, 2000), that posits human motivation, development, and well-being are impacted by social environments such as classrooms. SDT suggests that when students’ needs for relatedness, competence and autonomy are largely met, they will be self-motivated, curious and eager to succeed. Two sub-questions guided by SDT included: How does the implementation of the LDP support students’ needs for relatedness, competence and autonomy? and, How do supports for relatedness, competence and autonomy within the LDP impact student engagement? Case study methodology provided the opportunity for in-depth analysis of educational practices and student engagement within the classroom. Findings highlight numerous supports for students’ sense of relatedness to their classmates and the staff. Threats to students’ sense of competence through the process of “othering” that enrolment in a special education classroom entails are discussed. However, within the classroom there was considerable support for students’ sense of competence including minimizing otherness. Minimal supports for autonomy were observed within the LDP. As predicted by SDT, variation in academic engagement of three students selected for in-depth study was found. Implications for educational practice are discussed including ways that special education and regular education classroom contexts may minimize otherness for students with learning disabilities.
Defeating reverberation: Advanced dereverberation and recognition techniques for hands-free speech recognition

Automatic speech recognition is being used successfully in more and more products. However, current recognition systems usually require the use of close-talking microphones. This constraint limits the deployment of speech recognition for new applications. In hands-free situations, noise and reverberation cause a severe degradation of the recognition performance. The problem of noise robustness has attracted a great deal of attention and practical solutions have been proposed and evaluated with common benchmarks. In contrast, reverberation has long been considered an unsolvable problem. Recently, significant progress has been made in the field of reverberant speech recognition and this progress has been evaluated with the REVERB challenge 2014. In this paper, we describe the reverberant speech recognition system we proposed for the REVERB challenge that exhibited high recognition performance even under severe reverberation conditions. We compare our system with other proposed approaches to suggest potential future research directions in the field.
Movement pattern recognition through smartphone's accelerometer

Sensor-enabled smartphone's have become a mainstream platform for researchers due to their ability to collect and process large quantities of data, hence creating new opportunities for innovative applications. Yet, the limits in employing sensors to opportunistically detect human behaviors are not clear and deserve investigation. To this purpose, in this article, we discuss movement pattern recognition in day-by-day urban street behavior. As a case study, we restrict at recognizing situations when a pedestrian stops, crosses a street ruled by a traffic light; to do so we only use data coming from the accelerometer of the pedestrian's smartphone.
Robust Congestion Control for Multicast: Challenges and Opportunities

n Trust is the foundation of most congestion control protocols developed and deployed in the Inter- net today. Unfortunately, with the growth of the Inter- net, the assumption of universal trust is no longer ten- able. A communicating entity can misbehave to obtain a self-benecial bandwidth allocation. Thus, design of congestion control protocols that are robust to such mis- behavior has become an important research area. In this paper, we discuss the specic problem of designing ro- bust congestion control for multicast in the presence of untrusted hosts. We examine IP and peer-to-peer instan- tiations of the multicast service. For both cases, we show that protection against host misbehavior is harder than in unicast and poses new research challenges. We outline possible solutions for designing robust multicast conges- tion control protocols. Further, we argue that intrinsi- cally different design requirements imposed by untrusted environments point to the need for exploring an integra- tive alternative to the traditional layered network archi- tecture.
Collecting Trash : A Test of Purposive VisionR

The purposive approach to computer vision has been much discussed in recent years, but there have been few tests of the viability of the paradigm in a working vision system. We have tested the approach in the context of vision for a mobile robot performing tasks in a typical, unaltered o ce environment. In particular, we examine the approach in the context of a trash collection task; the task that was the subject of the 1994 AAAI Robot Competition. Our experience demonstrates that the approach is viable for solving such a task, and we show how our design for the visual system takes advantage of tight integration between the perception and action systems. In particular, we demonstrate that because of the constraints inherent in the task, it is possible to e ciently perform a search over the scene and over viewpoint for the object of interest. We address particular concerns with the purposive approach, such as how purposive systems can be adapted to new situations.
Filter-based Approximated Models for Discrete-time Systems . Application to Multirate Sampled LTI Systems

This paper deals with the task of obtaining approximated models of discrete-time systems by the use of parametrical identification algorithms. Firstly, a filter-based identification method used to obtain a parametric model from a series data of the impulse of the system based in Leverrier’s algorithm is revised. A second method based on least squares minimization that allows identifying the discrete system from input-output data is also presented. These techniques are of particular practical interest when treating discrete-time systems where the analytical resolution becomes very complex or even unfeasible. This is the case of the problem presented in the examples, where a multirate sampling technique is used to discretize the system under real sampling. This strategy yields a better description than that obtained using the traditional sampling method, but it involves a difficult treatment of parametrical model in terms of the poles and zeros due to the complexity of the resulting discrete transfer functions, but where a measured data series of the output is available. Key-Words: Modeling, Discrete-time systems, System identification, Multirate sampling, LTI (linear time invariant) systems.
The effect of rainfall on feature points extraction and image stitching

The aim of this paper is to investigate the effects of rainfall on image stitching by measuring the performance of the Harris corner detector, Scale-Invariant Feature Transform (SIFT) detector, and the Speeded Up Robust Feature (SURF) detector. A set of images were captured by using two cameras during light rain and during heavy rain. The number of detected features points was used as the performance measure. The results indicate that all the detectors are capable to extract a substantial amount of feature points. However, the rainfall does reduce the number of detected feature points by 48 and 67% when the Harris corner detector and the SURF detector were adopted respectively. At the end, the images were stitched together based on the feature points extracted by using the Harris corner detector. The results indicate that the effect of rainfall is negligible as long as there is a substantial amount of distinctive feature points.
Identifying a better measure of relatedness for mapping science

Measuring the relatedness between bibliometric units (journals, documents, authors or words) is a central task in bibliometric analysis. Relatedness measures are used for many different tasks, among them the generating of maps, or visual pictures, showing the relationship between all items from these data. Despite the importance of these tasks, there has been little written on how to quantitatively evaluate the accuracy of relatedness measures or the resulting maps. We propose a new framework for assessing the performance of relatedness measures and visualization algorithms that contains four factors: accuracy, coverage, scalability, and robustness. This method was applied to ten measures of journal-journal relatedness to determine the best measure. The ten relatedness measures were then used as inputs to a visualization algorithm to create an additional ten measures of journal-journal relatedness based on the distances between pairs of journals in two-dimensional space. This second step allows us to determine robustness (i.e., which measure remains best after dimension reduction). Results show that, for low coverage (under 50%), the Pearson correlation is the most accurate raw relatedness measure. However, the best overall measure, both at high coverage, and after dimension reduction, is the cosine index or a modified cosine index. Results also showed that the visualization algorithm increased local accuracy for most measures. Possible reasons for this counterintuitive finding are discussed.
SHelp: Automatic Self-Healing for Multiple Application Instances in a Virtual Machine Environment

When multiple instances of an application running on multiple virtual machines, an interesting problem is how to utilize the fault handling result from one application instance to heal the same fault occurred on other sibling instances, and hence to ensure high service availability in a cloud computing environment. This paper presents SHelp, a lightweight runtime system that can survive software failures in the framework of virtual machines. It applies weighted rescue points and error virtualization techniques to effectively make applications by-pass the faulty path. A two-level storage hierarchy is adopted in the rescue point database for applications running on different virtual machines to share error handling information to reduce the redundancy and to more effectively and quickly recover from future faults caused by the same bugs. A Linux prototype is implemented and evaluated using four web server applications that contain various types of bugs. Our experimental results show that SHelp can make server applications to recover from these bugs in just a few seconds with modest performance overhead.
Theology and Psychological Theory: Psychological Implications of Some Modern Theologies

In a sense, theologies are psychologies. They discuss the human condition, largely in terms of motivation and cognition, and suggest ways of organizing our thinking about human aspirations and goals. These considerations are nowhere more evident than in contemporary process, liberation, and feminist theologies. This article shows parallels among these perspectives relative to modern psychological research and theory, primarily in social psychology and more particularly relative to social cognition theory. The importance of the role of the self and needs for meaning, control, and self-esteem are stressed, indicating that theology can serve as psychological theory and that both psychology and theology might benefit from increased interaction between the disciplines.
Influence of Hypsometry in the Occupation of Semiarid Areas

This research aims with the help of geotechnologies to map the different uses and coverage of the earth by analyzing its effects in relation to the altitudinal gradient in semiarid regions. In order to do so, RapidEye images were acquired in the year 2014, after the organization of the database the digital processing of the acquired scenes was carried out which were performed contrast technique, segmentation, identified eight classes of use and land cover and submitted to Maximum Likelihood classification. The relationship between forest cover and different uses indicates that the most representative class was Agriculture and Livestock, as a consequence of the local economy being based on subsistence culture and the Lowland environment is the most affected. In addition, it is verified that there is a lower degree of anthropization in the tops evidencing that in the Plateau environment persists a greater density of native vegetation. This research confirms the hypothesis that the process of fragmentation of the native vegetation of the semi-arid region changes in relation to the altitudinal gradient, since the higher the altitude, the lower the degree of isolation and, consequently, the high forest coverage.
Vehicular Ad-Hoc Networks (VANETS) Security: Review and Challenges

Vehicular Ad-Hoc Network (VANET) has become a popular research area as it has tremendous capacity to improve vehicle and road safety, traffic management and convenience as well as comfort to both drivers and passengers. Vehicular Ad-hoc Networks (VANETs) are trying to find solution to avoid accidents and control traffic. It (VANET) is a piece of critical infrastructure that boosts traffic management efficiency and road safety. At present research efforts have placed a strong significance on novel VANET architectures and design implementations. A lot of VANET research works have focused on specific areas including broadcasting, navigation, Quality of Service (QoS), and security. This survey paper sheds some light on VANETs’ vulnerabilities and attacks. It surveys and examines some recent security problems and limitations of solutions. We observed that security is the key parameter for success of any VANET applications. There are still many critical challenges that should be taken into account such as privacy preservation, productivity, and usability. Therefore, the door for future research and efforts is open for more contributions in the field of Vehicular Ad-Hoc Networks VANET.
Macroeconomic Effects of Reallocation Shocks:A generalised impulse response function analysis for three European countries

We develop a generalised impulse response function (GIRF) approach to explore the different impacts of aggregate and sectoral shocks within a VAR-GARCH-M model. Using the outout of our GIRF analysis, we explore the behaviour of three European countries(Gremany, Spain and the UK). We analyse the aggregate and sectoral responses to discriminate among three different hypotheses of business cycle fluctuations. Links are established and explanations are provided within the still experimental charater of our exercise.