Miracle-dz/UniFAR-FTUs huggingface dataset:
Domestic and Foreign Incomes and Trade Balance - A Case of South Asian Economies

The persistent trade deficit is one of the common issues of South Asia specifically, Bangladesh, India and Pakistan. While an increase in domestic income can help in the movement from import based economy to the economy with export capacity (quadratic effect), but quadratic effect of the world income must also be evaluated as it creates demand for exports. This study has adapted Kuznets curve hypothesis to propose U shaped and inverted U shaped relationship of domestic income and world income respectively on the trade balance. By estimating Panel ARDL model using the data for three selected economies, this study has confirmed the U shaped and inverted U shaped relationship with respect to domestic income and world income respectively. Further policymakers can moderate domestic income effect to minimize trade deficit by boosting terms of trade and FDI.
The Influence of Channel Aspect Ratio on Performance of Optimized Thermal-Fluid Structures

This paper presents a parametric geometry study of a thermal-fluid structure for single phase liquid cooling applications. Topology optimization results for an example two-dimensional system are first presented. The results of numerical experiments examining the influence of channel aspect ratio, i.e. height over width, on the thermal-fluid performance of a derived branching channel cold plate are then explained. These results are compared with those for a similarly sized straight microchannel cold plate. The optimized structure is found to exhibit moderately higher thermal resistance in addition to significantly lower pressure drop when compared with the traditional straight channel system. The study highlights an analysis and design method that combines optimization techniques with further design refinement via automated geometry parameter sweeps.
Using Feedback to Conduct Crowd Control

Crowd Control is a function generally associated with the police more than the military. However, the Canadian Forces are occasionally asked to intervene in riot situations either in Canada, in support to Federal, Provincial and Municipal Governments, or overseas, during Coalition operations. Thus, there is a need to understand crowd behaviour and to determine optimal intervention strategies for crowd control. Arguably the most famous recent event involving the Canadian Forces was the Oka Crisis in 1990 in which Mohawk Warriors carried out a 76 day standoff and the Quebec Provincial Police were unable to handle the situation. Another example of situations concerning governments around the world are unruly protests during visits of foreign dignitaries, such as the Vancouver APEC Protest, in 1997. Although, the Canadian Forces have not been employed in these events, they have skills and resources that might be called upon if a situation gets out of control and must be prepared to deploy on short notice. A model has been developed that can be used to understand these events in the time dimension both inside the event and from event to event. The model has been developed theoretically and “face validated” using data from two case studies. The model is required to evaluate appropriate tactics such as the employment of non-lethal weapons, and as a training simulator for strategic and tactical commanders.
Coupling of Arm Movements during Human-Robot Interaction: the handover case

Collaboration involves understanding the action of others, as well as acting in a way that can be understood by others. One of those tasks is the handover. In this paper, we study the behaviour of humans during the handover and design the mechanisms allowing a robot to learn from that behaviour.We analyse and model the arm movements of humans while handing over objects to one another. The contributions of this paper are the following: (i) a computational model that captures the behaviour of the “giver” and “receiver” of the object, by coupling the arm motion; (ii) discuss this approach amidst a previous coupling strategy; and (iii) embedded the model in the iCub robot for human to robot handovers.Our results show that: (i) the robot can coordinate with the human to timely and safely receive the object; (ii) the robot behaves in a “human-like” manner while receiving the object; and (iii) our approach has significant advantages to the previous approach.
Nonparametric Hypothesis Testing for Isotonic Survival Models with Clustering

A nonparametric test for clustering in survival data based on the bootstrap method is proposed. The survival model used considers the isotonic property of the covariates in the estimation via the backfitting algorithm. Assuming a model that incorporates the clustering effect into the piecewise proportional hazards model, simulation studies indicate that the procedure is correctly-sized and powerful in a reasonably wide range of scenarios. The test procedure for the presence of clustering over time is also robust to model misspecification.
3D Mapping and Navigation for Autonomous Quadrotor Aircraft

Autonomous navigation is a challenging problem in GPS-denied environments. For small flying robots and quadrotors, inherent limitations such as limited sensor payload and small system time-constant add another layer of challenge to the problem. This paper presents a solution for autonomous navigation of a quadrotor by performing autonomous behaviors, such as exploration, returning home, or following waypoints. The solution relies on accurate localization, mapping, and navigation between waypoints. A 3D mapping algorithm is proposed that enables the fast moving quadrotor to make a reliable 3D model. One of the contributions of the paper is the 3D mapping algorithm which is built upon a 2D mapping algorithm and IMU information. Compared with state-of-the-art algorithms, the proposed 3D mapping allows the quadrotor to generate more accurate models with low-bandwidth channels. Additionally, the algorithm allows the quadrotor to have aggressive changes in rotation and translation that occur frequently due to the fast dynamics of the quadrotor. Also 2D and 3D maps are displayed on multiple remote devices, such as tablets. Multiple tests were performed in simulated and real-world environments to show the effectiveness of the proposed solution.
13/75 Managing faecal incontinence in people with advanced dementia 1 Managing Faecal Incontinence in people with advanced dementia resident in Care Homes

Background and Rationale: Faecal incontinence (FI) is the involuntary loss of liquid or solid stool that is a social or hygienic problem. The prevalence of faecal incontinence in care homes is high. Older people with dementia with FI have a reduced quality of life and are at risk of developing further serious health problems. Faecal incontinence is not an inevitable consequence of old age or advanced dementia and its causes are multi-factorial. There is good evidence on risk factors and associations, but very few intervention studies. The effectiveness of programmes to address the known problems of faecal incontinence in care homes is contingent not only on specific bowelfocused interventions, but also on contextually situated decision making. There is therefore a need to draw on a range of evidence sources to capture this to understand how, why and in what circumstances, particular programmes to reduce FI work (or not) for people with advanced dementia in care homes.
Microbiological quality control of probiotic products

Microbiological quality control of probiotic products such as Imunele, Dannon, Pomogayka showed that they contain living cultures of the Lactobacillus Bifidobacterium genus in the amount of 107 CFU/ml, which corresponds to the number indicated on the label of products. It is identified that the survival rate of test-strains cultured with pasteurized products does not exceed 10%. The cell concentration of target-microorganisms was reduced by 20-45% after the interaction with living probiotic bacteria. Thus, the yogurt Activia has the most antagonistic activity. © 2014 The Authors. Published by Elsevier B.V. Peer-review under responsibility of Tomsk Polytechnic University.
Dyadic Coping in Foster and Biological Parents and Its Relation to Child Psychopathology

Abstract. This study investigated whether foster parents’ reports of their dyadic coping competencies differ from biological parents, whether there are differences with regard to the temporal associations between maternal and paternal dyadic coping in the two samples, and whether parental dyadic coping competencies predict future mental health problems in children. A total of 94 foster children and 157 children living in their biological families, both samples aged 2–7 years, as well as their (foster) parents were assessed three times over a 12-month period. The mothers’ and fathers’ dyadic coping competencies were assessed using the Dyadic Coping Inventory (DCI). Child psychopathology was assessed using the Child Behavior Checklist (CBCL) and a standardized clinical interview (Kinder-DIPS), both mainly based on maternal report. Foster parents reported better dyadic coping competencies across the three assessments than did biological parents. There were no significant differences with regard to the temporal associations between mothers’ and fathers’ report over time between the two samples. Cross-lagged panel models yielded a high within person stability across the three assessments for both, mothers and fathers (actor effects), as well as some significant interpersonal effects primarily from paternal to maternal dyadic coping (partner effects). In contrast to the expectation, mothers’ and fathers’ dyadic coping did not predict child mental health problems at the third assessment. The results make an important contribution to the research on dyadic coping and on how child mental health problems affect parental dyadic coping competencies and vice versa.
Secession with Natural Resources

We look at the formation of new Indian states in 2001 to uncover the effects of political secession on the comparative economic performance of natural resource rich and natural resource poor areas. Resource rich constituencies fared comparatively worse within new states that inherited a relatively larger proportion of natural resources. We argue that these patterns reflect how political reorganisation affected the quality of state governance of natural resources. We describe a model of collusion between state politicians and resource rent recipients that can account for the relationships we see in the data between natural resource abundance and post-break-up local outcomes.
A Review of Wearable Sensor for Stroke Patients

Worldwide, stroke is a serious and life-threatening problems. Without warning, stroke can bring dramatic and unexpected changes in human’s lives. Paralysis, communication problems, difficulty controlling of the body and balance are the most common effects after a stroke. The rapidly developing loss of brain functions after the brain stops receiving blood flow are frequently left with a long term disability and needs medical attention for recovery. To make rehabilitation more efficient for stroke patients, the entire progress and detections of how well they have improved are required to monitor. As a powerful and practical instrument in health monitoring research and modern technology, wearable sensors have been widely accepted in the last decade especially in clinical rehabilitation. It is constantly increasing with the major effort in various fields of therapy, for example, Parkinson’s disease, Alzheimer’s disease and furthermore in stroke recovery. Numerous wearable devices have been used for analyzing, monitoring, and assessment in therapeutic treatment nowadays. This review aimed to examine the available literature of wearable sensor-based device establishment in sensor types, locations and range of functions of the clinical application in people after stroke. We address and report about studies that have already investigated in clinical testing of stroke population. We, moreover, discuss their boundaries and present a range of recommendation for the future research.
Hardware Acceleration of Computer Vision and Deep Learning Algorithms on the Edge using OpenCL

Machine vision using CNN is a key application in Industrial automation environment, enabling real time as well as offline analytics. A lot of processing is required in real time, and in high speed environment variable latency of data transfer makes a cloud solution unreliable. There is a need for application specific hardware acceleration to process CNNs and traditional computer vision algorithms. Cost and time-to-market are critical factors in the fast moving Industrial automation segment which makes RTL based custom hardware accelerators infeasible. This work proposes a low-cost, scalable, compute-at-the-edge solution using FPGA and OpenCL. The paper proposes a methodology that can be used to accelerate traditional as well as machine learning based computer vision algorithms.
Criminal Network Community Detection Using Graphical Analytic Methods: A Survey

Criminal networks analysis has attracted several numbers of researchers as network analysis gained its popularity among professionals and researchers. In this study, we have presented a comprehensive review of community detection methods based on graph analysis. The concept of community was vividly discussed as well as the algorithms for detecting communities within a network. Broad categorization of community detection algorithms was also discussed as well as a thorough review of detection algorithms which has been developed, implemented and evaluated by several authors in social network analysis. Most importantly, a strict review of researches based on the detection of community in a criminal network was carried out revealing the strength and limitations of criminal network community detection methods. Thus, it becomes obvious through this study that more research activities is necessary and expected in order to further grow this research area.
Traditional Icon Culinary as Indonesia Gastro Brand Irwansyah Irwansyah

Indonesia foods have been initiated and developed as nation brand. However, there is no specific food or beverage of Indonesia became an icon of gastro brand although Indonesia decided to have 30 icons of traditional culinary as a part of soft diplomacy. This study surveyed the culinary icons at hotels that have restaurants which served breakfast for local and foreign guests who stayed at. As a guideline, this study constructs the working definition of gastro brand by elaborating previous concepts such as gastro, gastronomy and brand. In addition, this study used parallel mix-method to identify and confirm Indonesia gastro brand. This study found that fried rice could be identified as a main icon of Indonesia gastro brand based on its popularity and availability. The study also confirms previous research that fried rice is not only traditional, omnipresent and ubiquitous’ culinary but also as a part of nation brand.
Placental Vesicles and their miRNAs in Preeclampsia and Normal Pregnancies – Uptake and Function

The present thesis focuses on the pregnancy associated syndrome preeclampsia (PE), a potentially fatal syndrome with acute as well as long-term consequences for both mother and child. There is no cure except termination of the pregnancy, no certain way to predict the disorder and only symptomatic treatment. PE develops in two stages. In the first stage, the placenta is inadequately implanted, leading to oxidative stress and release of placental factors into the maternal circulation. In the second stage, the released factors cause endothelial dysfunction and the clinical symptoms. Furthermore, there is growing evidence of long-term cardiovascular consequences after PE We and others have studied the possible links between the first and second stage. Central to this thesis is the placentally released syncytiotrophoblast extracellular vesicles (STBEVs), which like other extracellular vesicles carries miRNAs and can be taken up by recipient cells where they affect target cell gene expression. We focus specifically on the STBEV role in endothelial dysfunction. In paper I, we describe the interaction between specific miRNAs and trophoblast differentiation, as well as how these are affected by hypoxia. In paper II, the miRNA content of STBEVs is analysed, and how this is affected by foetal haemoglobin. In paper III, an analysis of placenta specific miRNAs in normal and PE STBEVs is performed, as well as studying the uptake of STBEVs and transfer of miRNAs to primary endothelial cells. In paper IV we further elucidate the specific uptake mechanisms of normal PE STBEVs into primary endothelial cells and study the effect on endothelial cell gene expression. In conclusion, in this thesis we describe molecular mechanisms involved in miRNA regulation of target genes, the release and uptake of placental STBEVs as well as their transfer of functional miRNAs to target cells. By isolating STBEVs from perfused placentas we have been able to study vesicles with a strong physiological resemblance to the in vivo environment.
Chinese Word Segment Based on Character Representation Learning

来斯惟,徐立恒,陈玉博,刘康,赵军 中国科学院自动化所模式识别国家重点实验室,北京,100190 E-mail: {swlai, lhxu, yubo.chen, kliu, jzhao}@nlpr.ia. ac.cn 摘 要:分词是中文自然语言处理中的一个关键基础技术。 通过基于字的统计机器学习方法学习判断词边 界是当前中文分词的主流做法。 然而,传统机器学习方法严重依赖人工设计的特征,而验证特征的有效性 需要不断的尝试和修改,是一项费时费力的工作。 随着基于神经网络的表示学习方法的兴起,使得自动学 习特征成为可能。 本文探索了一种基于表示学习的中文分词方法。 首先从大规模语料中无监督地学习中文 字的语义向量,然后将字的语义向量应用于基于神经网络的有监督中文分词。 实验表明,表示学习算法是 一种有效的中文分词方法,但是我们仍然发现,由于语料规模等的限制,表示学习方法尚不能完全取代传 统基于人工设计特征的有监督机器学习方法。 关键词:表示学习、中文分词
Gas Evolution Dynamics in Godunov-type Schemes and Analysis of Numerical Shock Instability

In this paper we are going to study the gas evolution dynamics of the exact and approximate Ricmann solvers, e.g., the Flux Vector Splitting (FVS) and the Flux Difference Splitting (FDS) schemes. Since the FVS scheme and the Kinetic Flux Vector Splitting (KFVS) scheme have the same physical mechanism and similar flux function, based on the analysis of the discretized KFVS scheme the weakness and advantage of the FVS scheme are clearly observed. The subtle dissipative mechanism of the Godunov method in the 2D case is also analyzed, and the physical reason for shock instability, i.e., carbuncle phenomena and odd-even decoupling, is presented.
Psychological factors and self-care behaviors as correlates of Medication Adherence among Insulin-taking Type 2 Diabetes patients

Although poor medication adherence (MA) is common in type 2 diabetes mellitus (T2DM) patients, little is known about psychological factors associated with this problem. In this context, we examined the relationship between MA and psychological factors namely depression (Becks Depression Inventory), diabetes related distress (Problem Areas in Diabetes scale), spiritual well-being (Spiritual Well-being Scale) and self-care behaviors (diet, physical activity) (Self Care Inventory). 172 insulin-naive T2DM patients were taken as sample of the study. Pearson’s Product Moment Correlation, Multiple Regression Analysis and T-test were used to analyze the data. Although MA was significantly correlated with depression, diabetes related distress, spiritual well-being and self-care behaviors (diet, physical activity). But among them only diabetes related distress and self care behaviours (diet, physical activity) significantly predicted MA. Depressive symptoms were found to be high in female patients and physical activity was found to be high in male patients. This research identified some psychological factors that influenced the medication adherence of adults with type 2 diabetes mellitus. Understanding of the self-care behaviour patterns of diabetic adults may assist primary care providers and educators to develop more individualized treatment plans throughout the course of the illness. Furthermore, recognizing and addressing individual emotional responses (depression and diabetes distress) to diabetes, in addition to providing medical care, may improve the patient’s self-efficacy and ability to manage their diabetes. This is important for clinical practice, where optimal management of diabetes requires effort from healthcare providers working collaboratively with the patient. In addition, knowing about the individual’s state of spiritual well-being will help health care professionals to frame their actions towards developing intervention techniques which will in turn help them to develop positivity among the chronically ill patients towards their lives.
Individual Learning Style and Systems Tool Preferences

Active Experimentation Abstract Conceptualization Concrete ExperienceConceptualization Concrete Experience Reflective Observation It is this final characteristic that serves as a key block of the foundation for the research conducted for this paper. It is proposed that people exhibit patterns of learning from experience that reflect the manifestation of certain proclivities to seek information, assign meaning, and attend to certain cues at the exclusion of others. These tendencies often mirror personal beliefs and intrinsic traits that differentiate people, yet whose origins are not well understand. Koestler (1945), for example, identifies leaders as holding worldviews that tend toward being belonging to a constellation of attributes which he describes as being either akin to that of a Yogi or a Commissar. In a similar way, other typologies distinguish between natural human tendencies to perceive the world, make sense, and learning in quite divergent ways that we often refer to as learning styles. Learning Styles In order to evaluate learning style, several inventories are available including those developed by Honey and Mumford (1995), Dechant and Marsick (1993), Murrell (1987) and Glacel (2001). However, the inventory selected for use in this study was Kolb’s KLSI (1991) which chosen based on the work Saeed (2003). The interpretation of scores is given as an orientation while combined orientations give a resulting learning style. The following is a summarization of the orientations developed from the Kolb learning style
Classification and Prediction of Suicidal Tendencies of the Youth in the Philippines: An Empirical Study

This paper investigates suicidal tendencies of youth in the Philippines based on the Young Adult Fertility and Sexuality Study (YAFS) 2002. The main goal of the paper is the classification and prediction of suicidal tendencies using classification algorithms. The different classification algorithms such as Classification and Regression Trees, random forests and conditional inference trees; and the logistic regression have consistent findings on the significant variables affecting suicidal tendencies. Due to the severely unbalanced classes of the response variable, the classification models have very poor predictive ability for the minority class although the overall classification rate is high. A classification algorithm is proposed which improves the predictive ability in terms of balancing out the correct classification in the two classes of the response variable.
Extracting Named Entities Using Named Entity Recognizer for Arabic News Articles

This paper describes how to extract, for the Arabic language, named entities and topics from news articles. Indeed, there is a lack of high quality tools for Named Entity Recognition (NER) for Arabic; therefore the authors have built an Arabic NER (RenA). NER involves extracting information and identifying types, such as name, organization, and location. For English language there are effective tools for NER, however these are not directly applicable to Arabic language. As a result, a new method and tool (i.e., RenA) have been developed. For NER evaluation purposes a baseline corpus was built for assessment and comparison with other methods and tools, with help from volunteer graduate students who understand Arabic. RenA produces good results, with accurate Name, Organization, and Location extraction from news articles collected from online resources. A comparison between the RenA results with a popular Arabic NER resulted in a noticeable enhancement.