Miracle-dz/UniFAR-FTUs huggingface dataset:
Clustering Words by Projection Entropy

We apply entropy agglomeration (EA), a recently introduced algorithm, to cluster the words of a literary text. EA is a greedy agglomerative procedure that minimizes projection entropy (PE), a function that can quantify the segmentedness of an element set. To apply it, the text is reduced to a feature allocation, a combinatorial object to represent the word occurences in the text's paragraphs. The experiment results demonstrate that EA, despite its reduction and simplicity, is useful in capturing significant relationships among the words in the text. This procedure was implemented in Python and published as a free software: REBUS.
A Portfolio of Japanese Equities Weighted by YKS Patent Values

Recently, the value of intangible assets has become increasingly important in estimating the value of an enterprise. In the practical business of asset management, however, compared to the analysis of financial statements, relatively few opportunities exist to quantify intangible assets and thus estimate the value of enterprises. In addition, few passive managers rely on value-weighted intangible assets. In this study, we propose an equities portfolio management method of weighting by patent values, which are calculated by the YKS method developed by Kudo and Associates. Importantly, the method presented here does not use market information or financial statements. The annualized excess return of the YK value-weighted portfolio is 6.1%, which significantly outperforms the market capitalization-weighted portfolio, and there is no extended period of negative underperformance in the periods examined in this study. Most investors are unaware that industries with overweight YK value-weighted portfolios have valuable patents, and that the market capitalization of these sectors may not include the value of these patents’. Our study shows that the annualized average growth rate of the weighted recurring profit of the YKP is higher than the growth rates of the market capitalization-weighted portfolio and a composite of the financial value-weighted portfolio.
Association of AGT (M268T) Gene Polymorphism in Diabetes and Nephropathy in Pakistan

Diabetes mellitus is considered as a group of metabolic disorders which have multiple etiologies. Pathogenesis of nephropathy in diabetes is presented by variations in genes encoding the significant components of renin angiotensin aldosterone system (RAAS) including angiotensin converting enzyme (ACE), angiotensin receptor, angiotensinogen (AGT) genes. The present study was conducted to explore the possible association of AG (M268T) polymorphism in diabetic patients with nephropathy in Pakistan. Study subjects included 100 controls, 260 diabetic patients without renal insufficiency and 190 diabetic nephropathy patients with persistent albuminuria. Fasting blood samples were collected from all the subjects after getting institutional ethical approval and informed consent. The biochemical estimations, PCR amplification and direct sequencing for the specific region of AGT gene was carried out. A significantly high frequency of genotype (TT) and allele (T) of AGT (M268T) was observed in diabetic nephropathy as compared to normal control subjects and diabetic patients without any known renal impairment. The genotype (TT) and allele (T) of AGT (M268T) polymorphism may be measured as a risk factor for the expansion and progression of renal impairment in diabetes. Further cross sectional population studies would be of help to establish and confirm the observed possible association of AGT gene variations with development of nephropathy in diabetes. KeywordsRAAS, AGT (M268T), Diabetes, Nephropathy.
The Nature of Regional Policy Work in Canada's Public Service

This paper compares rank-and-file policy-based Canadian federal government employees both in the National Capital Region and in the regions. Data was collected from an online survey, the results find a number of significant differences between the two groups in terms of demographics, tasks, and attitudes. We conclude that regional oriented policy tasks are carried out by a relatively few number of people and this group is, at best, on the margins of what could be considered to policy work. These differences may have a significant impact on the federal government’s overall policy capacity.
Combining cognition and emotion in virtual agents

Purpose The paper aims to explain the limitations of existing cognitive architectures and affective models, and propose a new cognitive-affective architecture that can be integrated in real intelligent agents to make them more realistic and believable. Design/methodology/approach The paper evaluates the state of the art, and describes the design and implementation of the cognitive-affective architecture in an agent. A brief evaluation of the agent is provided. Findings The paper clearly states that it is possible to use cognitive architectures to help, but there is a lack of architectures that address the problem of combining cognition and emotion in agents in a unified, simplified way. A cognitive-affective architecture is useful to make believable intelligent agents in an easier way. Research limitations/implications The paper does not explore a lot of possible future work that can be done to extend the emotional expressions of the agent, as well as including direct emotional-sensing capabilities in real time. Practical implications The paper argues about the need to include cognitive-affective architectures in modern intelligent agents. The architecture allows to influence and modify the behavior of the agent in real time, to achieve a more realistic and believable interaction with the user. Social implications The paper remarks the importance of a cognitive-affective architecture that makes intelligent agents able to help the users in different tasks and environments. Originality/value The paper describes a new cognitive-affective architecture and its utility for modern intelligent agents. This is proven by including it in a previous agent, which boosts its behavior and emotional expression possibilities and thus improves user experience.
Vertical coordination, rent distribution, and development

Vertical coordination has grown strongly in global supply chains. Local suppliers in developing countries engage in complex contracting with companies selling into high-income markets - either domestically or internationally. These contracts not only specify conditions for delivery and production processes, but also include the provision of inputs, technology, management advice etc. This paper analyzes how weak contract enforcement institutions and imperfect factor markets are affecting vertical coordination in development, and what the implications are for income creation and rent distribution.
Phospholipase C gamma 1: Mechanisms of Adhesion and Role in Migration and Metastasis

Abstract : Phospholipase C-gamma1 (PLC-gamma1) mediates cell adhesion and migration through an undefined mechanism. Here, we examine the role of PLC-gamma1 in cell-matrix adhesion in a hanging drop assay of cell aggregation. Plcg1 Null (-/-) mouse embryonic fibroblasts formed aggregates that were larger and significantly more resistant to dissociation than cells in which PLC-gamma1 is re-expressed (Null + cells). Aggregate formation could be disrupted by inhibition of fibronectin interaction with integrins, indicating that fibronectin assembly may mediate aggregate formation. Fibronectin assembly was mediated by integrin alpha5beta1 in both cell lines, while assays measuring fibronectin assembly revealed increased assembly in the Null cells. Null and Null + cells exhibited equivalent fibronectin mRNA levels and equivalent levels of fibronectin protein in pulse-labeling experiments. However, levels of secreted fibronectin in the conditioned medium were increased in Null cells. The data implicates a negative regulatory role for PLC-gamma1 in cell aggregation by controlling the secretion of fibronectin into the media and its assembly into fibrils.
Competitive location under proportional choice: 1-suboptimal points on networks

This paper is concerned with a competitive or voting location problem on networks under a proportional choice rule that has previously been introduced by Bauer et al. (1993). We refine a discretization result of the authors by proving convexity and concavity properties of related expected payoff functions. Furthermore, we answer the long time open question whether 1-suboptimal points are always vertices by providing a counterexample on a tree network.
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts

This paper is motivated by the automation of neuropsychological tests involving discourse analysis in the retellings of narratives by patients with potential cognitive impairment. In this scenario the task of sentence boundary detection in speech transcripts is important as discourse analysis involves the application of Natural Language Processing tools, such as taggers and parsers, which depend on the sentence as a processing unit. Our aim in this paper is to verify which embedding induction method works best for the sentence boundary detection task, specifically whether it be those which were proposed to capture semantic, syntactic or morphological similarities.
Dysplasia epiphysialis hemimelica; (tarso-epiphyseal aclasis).

DYSPLASIA EPIPHYSIALIS hemimelica is a rare epiphyseal dysplasia of the extremities which is readily recognizable roentgenographically. I t is the purpose of this communication to review the clinical and roentgen features of this disorder and to add a new case to the literature. This condition was originally reported by Mouchet and Belot in 1926 (l), but was first recognized and described as a definite entity in 1950 by Trevor (2), who collected 10 cases, to which he gave the name tarso-epiphyseal aclasis. Single cases have been published since that time by Ingelrans and Lacheretz (3), Donaldson et al. (4), and D'Angio et al. (5), and in 1956 Fairbank reported 14 additional examples, including 2 involving the upper extremity, which appear to fall into this group (6). Prior to the latter report, it was believed that this anomaly was confined to the lower limbs. Both D'Angio et al. and Fairbank have presented excellent reviews of this subject. The present paper will embody their data and a survey of the ent.
Cluster analysis of marketing data examining on-line shopping orientation: a comparison of k-means and rough clustering approaches

Cluster analysis is a common market segmentation technique, usually using k-means clustering. Techniques based on developments in computational intelligence are increasingly being used. One such technique is the theory of rough sets. However, previous applications have used rough sets techniques in classification problems, where prior group membership is known. This chapter introduces rough clustering, a technique based on a simple extension of rough sets theory to cluster analysis, and applicable where group membership is unknown. Rough clustering solutions allow multiple cluster membership of objects. The technique is demonstrated through the analysis of a data set containing scores on psychographic variables, obtained from a survey of shopping orientation and Web purchase intentions. The analysis compares k-means and rough clustering approaches. It is suggested that rough clustering can be
Quality of Life And Human Isolation: The Case of Rural Area of Puglia

The present research explores the socio-economic problems arising in a typical peripheral rural area - the Wide Area of Daunian Mountains (WADM)- in Southern Italy in order to analyse the concept of ‘well being’ through the analysis of the ‘quality of life’. For these purposes, we will develop an ‘Index of Human Isolation’ (UNDP, 1997), in order to take into account the multiple dimensions of isolation, that is a constant characteristic of rural areas, particularly the inter-generational, socio-structural, and geographical ones. This index will be employed to analyse the relationship between a set of variables representing the main economic, structural and social aspects of the area and the dynamics of the Value Added. The expected results are twofold; (a) the creation of VA should be decreasing at high levels of IHI; (b) the implementation of social-assistance network may actively contribute to the reduction of isolation.
Health-related quality of life of patients with juvenile idiopathic arthritis coming from 3 different geographic areas. The PRINTO multinational quality of life cohort study.

OBJECTIVES To compare health-related quality of life (HRQL) and to identify clinical determinants for poor HRQL of patients with juvenile idiopathic arthritis (JIA) coming from three geographic areas. METHODS The HRQL was assessed through the Child Health Questionnaire (CHQ). A total of 30 countries were included grouped in three geographic areas: 16 countries in Western Europe; 10 in Eastern Europe; and four in Latin America. Potential determinants of poor HRQL included demographic data, physician's and parent's global assessments, measures of joint inflammation, disability as measured by Childhood Health Assessment Questionnaire (CHAQ) and erythrocyte sedimentation rate. Poor HRQL was defined as a CHQ physical summary score (PhS) or psychosocial summary score (PsS) <2 S.D. from that of healthy children. RESULTS A total of 3167 patients with JIA, younger than 18 yrs, were included in this study. The most affected health concepts (<2 S.D. from healthy children) that differentiate the three geographic areas include physical functioning, bodily pain/discomfort, global health, general health perception, change in health with respect to the previous year, self-esteem and family cohesion. Determinants for poor HRQL were similar across geographic areas with physical well-being mostly affected by the level of disability while the psychosocial well-being by the intensity of pain. CONCLUSION We found that patients with JIA have a significant impairment of their HRQL compared with healthy peers, particularly in the physical domain. Disability and pain are the most important determinants of physical and psychosocial well-being irrespective of the geographic area of origin.
A novel approach to stroke rehabilitation

Objective: In patients with stroke, the authors tested whether additional sensorimotor training of the paralyzed or paretic upper limb delivered by a robotic device enhanced motor outcome. Methods: Fifty-six patients with stroke and hemiparesis or hemiplegia received standard poststroke multidisciplinary rehabilitation, and were randomly assigned either to receive robotic training (at least 25 hours) or exposure to the robotic device without training. Outcomes were assessed by the same masked raters, before treatment began and at the end of treatment, with the upper extremity component of the Fugl-Meyer Motor Assessment, the Motor Status score, the Motor Power score, and Functional Independence Measurement. Result: The robot treatment and control group had comparable clinical characteristics, lesion size, and pretreatment impairment scores. By the end of treatment, the robot-trained group demonstrated improvement in motor outcome for the trained shoulder and elbow (Motor Power score, p < 0.001; Motor Status score, p < 0.01) that did not generalize to untrained wrist and hand. The robot-treated group also demonstrated significantly improved functional outcome (Functional Independence Measurement–Motor, p < 0.01). Conclusion: Robot-delivered quantitative and reproducible sensorimotor training enhanced the motor performance of the exercised shoulder and elbow. The robot-treated group also demonstrated improved functional outcome. When added to standard multidisciplinary rehabilitation, robotics provides novel therapeutic strategies that focus on impairment reduction and improved motor performance.
Efficient Behavior Targeting Using SVM Ensemble Indexing

Behavior targeting (BT) is a promising tool for online advertising. The state-of-the-art BT methods, which are mainly based on regression models, have two limitations. First, learning regression models for behavior targeting is difficult since user clicks are typically several orders of magnitude fewer than views. Second, the user interests are not fixed, but often transient and influenced by media and pop culture. In this paper, we propose to formulate behavior targeting as a classification problem. Specifically, we propose to use an SVM ensemble for behavior prediction. The challenge of using ensemble SVM for BT stems from the computational complexity (it takes 53 minutes in our experiments to predict behavior for 32 million users, which is inadequate for online application). To this end, we propose a fast ensemble SVM prediction framework, which builds an indexing structure for SVM ensemble to achieve sub-linear prediction time complexity. Experimental results on real-world large scale behavior targeting data demonstrate that the proposed method is efficient and outperforms existing linear regression based BT models.
Choosing How to Pay: The Influence of Home Country Habits

Is having a foreign background a relevant factor in choosing between payment instruments in consumer point-of-sale transactions? We analyze this question using a unique diary survey in which both participants with a Dutch and a foreign background documented their daily purchases. Payment habits acquired in home countries continue to affect the mode of payment after migration. First generation migrants born in cash-oriented economies are more likely to use cash in point-of-sale transactions. However, the second-generation has similar payment habits as individuals with a Dutch background. This finding suggests that payment behaviour is not passed on from generation to generation, but moulded by host country payment habits. Finally, we suggest that special information campaigns to increase debit card usage will not have clear net social benefits.
In‐vitro dissolution methods for controlled release parenterals and their applicability to drug‐eluting stent testing

Objectives Dissolution testing is a powerful tool for the characterization of dosage form performance in vitro under standardized conditions. In spite of the increasing number of parenterally administered medicinal products, currently there are no compendial dissolution test methods designed especially for these types of dosage forms. In addition to classical drug delivery systems, drug/device combination products, such as drug‐eluting stents, are being used increasingly.
Bilinear map of filter-bank outputs for DNN-based speech recognition

Filter-bank outputs are extended into tensors to yield precise acoustic features for speech recognition using deep neural networks (DNNs). The ﬁlter-bank outputs with temporal contexts form a time-frequency pattern of speech and have been shown to be effective as a feature parameter for DNN-based acoustic models. We attempt to project the ﬁlter-bank outputs onto a tensor product space using decorrelation followed by a bi-linear map to improve acoustic separability in feature extraction. This extension makes extracting a more precise structure of the time-frequency pattern possible because the bilinear map yields higher-order correlations of features. Experimental comparisons carried out in phoneme recognition demonstrate that the tensor feature provides comparable results to the ﬁlter-bank feature, and the fusion of the two features yields an improvement over each feature.
Business Ethics: Managing Corporate Citizenship and Sustainability in the Age of Globalization

PART A: UNDERSTANDING BUSINESS ETHICS 1. Introducing Business Ethics 2. Framing Business Ethics: Corporate Responsibility, Stakeholders, and Citizenship 3. Evaluating Business Ethics: Normative Ethical Theories 4. Making Decisions in Business Ethics: Descriptive Ethical Theories 5. Managing Business Ethics: Tools and Techniques of Business Ethics Management PART B: CONTEXTUALIZING BUSINESS ETHICS 6. Shareholders and Business Ethics 7. Employees and Business Ethics 8. Consumers and Business Ethics 9. Suppliers, Competitors, and Business Ethics 10. Civil Society and Business Ethics 11. Government, Regulation, and Business Ethics 12. Conclusions and Future Perspectives
Iteration-free clustering algorithm for nonstationary image database

Image database systems must effectively and efficiently handle and retrieve images from a large collection of images. A serious problem faced by these systems is the requirement to deal with the nonstationary database. In an image database system, image features are typically organized into an indexing structure, and updating the indexing structure involves many computations. In this paper, this difficult problem is converted into a constrained optimization problem, and the iteration-free clustering (IFC) algorithm based on the Lagrangian function, is presented for adapting the existing indexing structure for a nonstationary database. Experimental results concerning recall and precision indicate that the proposed method provides a binary tree that is almost optimal. Simulation results further demonstrate that the proposed algorithm can maintain 94% precision in seven-dimensional feature space, even when the number of new-coming images is one-half the number of images in the original database. Finally, our IFC algorithm outperforms other methods usually applied to image databases.
English-Japanese Neural Machine Translation with Encoder-Decoder-Reconstructor

Neural machine translation (NMT) has recently become popular in the field of machine translation. However, NMT suffers from the problem of repeating or missing words in the translation. To address this problem, Tu et al. (2017) proposed an encoder-decoder-reconstructor framework for NMT using back-translation. In this method, they selected the best forward translation model in the same manner as Bahdanau et al. (2015), and then trained a bi-directional translation model as fine-tuning. Their experiments show that it offers significant improvement in BLEU scores in Chinese-English translation task. We confirm that our re-implementation also shows the same tendency and alleviates the problem of repeating and missing words in the translation on a English-Japanese task too. In addition, we evaluate the effectiveness of pre-training by comparing it with a jointly-trained model of forward translation and back-translation.
Individualized dietary counselling of families: serum cholesterol concentration and growth of children aged 7–13 months

We studied the effect of a change in dietary fat composition on serum total and high‐density lipoprotein cholesterol and growth in healthy infants between 7 and 13 months of age. The intervention families (n= 22) received individualized dietary counselling when the infant was 7, 8 and 10 months of age. The intervention diet was designed to have a fat content of 35–45 E%, of total energy intake in infants aged 7–12 months and 30–35 E% after 12 months of age. The ratio of saturated to monounsaturated to polyunsaturated fatty acids was designed to be 1:1:1. The children in the control group (n= 23) were given no specific advice on the fat composition of the diet. Intake of polyunsaturated fatty acids was significantly higher in the intervention group than in the controls (5.9 E% versus 3.6 E%, p < 0.05). Serum total cholesterol concentration decreased significantly in the intervention group during the study from 4.16± 0.41 mmol/l to 3.86 ± 0,48 mmol/l (p < 0.05). The infants of both groups grew like average Finnish children. Modification of dietary fat composition, as widely recommended for adults and older children to prevent coronary heart disease, decreases cholesterol values in infants without affecting their normal growth.