Miracle-dz/UniFAR-FTUs huggingface dataset:
The dynamic relationships of the cocaine system in the United States.

The nonlinear effects of cocaine availability, the potential user population, price, and purity on cocaine consumption are defined and incorporated in a dynamic simulation model. Confidence in these relationships is supported by the model's behavior which closely replicates the historical performance of the US cocaine system from 1975 to 1982. The model may be adapted for regional applications and to countries other than the United States.
A Framework for Sentiment Analysis Implementation of Indonesian Language Tweet on Twitter

Sentiment analysis is the process of understanding, extracting, and processing the textual data automatically to obtain information. Sentiment analysis can be used to see opinion on an issue and identify a response to something. Millions of digital data are still not used to be able to provide any information that has usefulness, especially for government. Sentiment analysis in government is used to monitor the work programs of the government such as the Government of Bandung City through social media data. The analysis can be used quickly as a tool to see the public response to the work programs, so the next strategic steps can be taken. This paper adopts Support Vector Machine as a supervised algorithm for sentiment analysis. It presents a framework for sentiment analysis implementation of Indonesian language tweet on twitter for Work Programs of Government of Bandung City. The results of this paper can be a reference for decision making in local government.
QFD approach to define CSR: Indian perspective

Corporate social responsibility (CSR) has been present in the management literature for more than five decades (Wood, 2010). Both organizations and societies have significantly increased their focus on CSR in the recent years. There are a number of CSR definitions such as stakeholders, business strategy, popularity, societal development, environment, and sustainability. An issue of concern is ‘there is a common set of definitions across all the dimensions? ’ The intent of this paper is to determine if the QFD (QFD) method could be used to derive a single CSR definition especially for under developed countries. QFD is a quantitative technique that structures a multi-attribute, multi-person and multiperiod problem hierarchically so that solutions are facilitated. This paper presents the development of an QFD model and the derivation of a CSR definition through it. The QFD approach is unique in the sense that in developing the model requirements are considered from miltiple dimensions and concept is developed. The advantages of using such a technique are discussed.
Identifying the Reasons why Users in China Recommend Bike Apps

This study examines factors affecting users' intention to recommend bike-sharing apps from the perspective of internal and external benefits perception. Since the end of 2016, bike sharing has suddenly taken off in China, and competition is fierce. Bike-sharing users' intention to recommend bike apps is particularly important as it can help operators attract more potential users. However, little research to date has focused on bike-sharing users' intention to recommend bike apps in the Chinese context. This study aims to fill this research gap using structural equation modelling. Data were collected from 209 bike-sharing app customers and the results show the following key findings: (1) the usefulness of the bike-sharing app is the most important factor contributing to users' intention to recommend, followed by economic incentive and ease of use; (2) users' trust that interacts with perceived ease of use has positive effect on users' intention to recommend, while users' trust that interacts with economic incentive has negative effect on users' intention to recommend. Implications for researchers and practice are discussed.
The Carryover Effect of Customer Satisfaction on Service Quality Focused on Moderating Effect of Customer Trust and Cooperative Orientation

ABSTRACT The current study is intended to provide a novel contribution in regards to the relationship between service quality and customer satisfaction by focusing on carryover effects of satisfaction judgment on perceived service quality of the subsequent transaction. In addition, we probe the role of customer trust in the relationship between customer satisfaction and service quality. The results indicate a cycle of customer satisfaction and perceived quality over time, which validates the concept of cycle of satisfaction. The results also indicate trust toward a service provider has a moderating role on the relationship between customer satisfaction and perceived service quality.
Role of hippocampal neurogenesis in mnemonic segregation: implications for human mood disorders

Abstract Objectives. Although hippocampal neurogenesis has been implicated in mood disorders, the precise role new neurons play in mood regulation is not fully elucidated. Here we examine whether neurogenesis improves mood by facilitating segregation of novel experiences that conflict with older maladaptive memories. Methods. Study 1: Four groups (N = 9 each) of adult male rats (exposed to stress or control conditions plus antidepressant or placebo) underwent active training on the place-avoidance task (PAT) on week 0; tested on recalling the “Initial PAT” on weeks 4 and 8; learning a subtly “Altered PAT” on week 8; and euthanazed on week 9. Study-2: Two groups (N = 12 each) rats tested either on the Initial-PAT or Altered-PAT 3 days post-training and immediately euthanized. Results. Stressed subjects treated with placebo were slower in learning the week 8 Altered Task and had lower neurogenesis rates than non-stressed animals and Stressed subjects given drug (Study 1). Synaptic activation of mature hippocampal neurons inversely correlated with Altered-PAT performance and with neurogenesis rates (Study 2). Conclusions. Increasing neurogenesis enhances acquisition of novel experiences possibly by suppressing activation of mature hippocampal neurons that mediate established, conflicting memories. Therefore, antidepressants may improve mood by stimulating new hippocampal neurogenesis that facilitate detection of positive experiences while suppressing interference from recurring depressogenic thought patterns.
A two-stage stochastic programming optimisation for sugar-ethanol-electricity production from sugarcane: a case study of Mauritius

Sugarcane is an economically essential plant from which juice is extracted to produce raw sugar and molasses. The raw sugar can further be refined while the molasses can be fermented to manufacture ethanol. Other than cane juice, bagasse is another by-product of sugarcane which can be used to generate electricity and as a raw material to manufacture paper and chemicals. In this paper, we present a two-stage stochastic programming model to quantify the optimal amount of sugar, ethanol and electricity to be made from sugarcane so as to minimise total production cost. The model developed is based on variation of prices of sugar, ethanol and electricity and energy required to produce them. We establish the boundedness, convexity and existence of solution of the model. The latter is then applied to data available for Mauritius and solved using a genetic algorithm approach. We estimate the optimal amount of sugar, ethanol and electricity to be produced up to the year 2027. Finally, we analyse three different scenarios, namely decrease in land under sugarcane, increase/decrease in price of sugar and increase/decrease in price of ethanol.
A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records

There is a growing body of research focusing on automatic detection of ischemia and myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI are diagnosed using electrocardiogram (ECG) recordings as well as medical context including patient symptoms, medical history, and risk factors—information that is often stored in the electronic health records. The ECG signal is inspected to identify changes in the morphology such as ST-segment deviation and T-wave changes. Some of the proposed methods compute similar features automatically while others use nonconventional features such as wavelet coefficients. This review provides an overview of the methods that have been proposed in this area, focusing on their historical evolution, the publicly available datasets that they have used to evaluate their performance, and the details of their algorithms for ECG and EHR analysis. The validation strategies that have been used to evaluate the performance of the proposed methods are also presented. Finally, the paper provides recommendations for future research to address the shortcomings of the currently existing methods and practical considerations to make the proposed technical solutions applicable in clinical practice.
AN ONTOLOGICAL APPROACH TO DATA MINING FOR EMERGENCY MEDICINE

We propose a system for assisting emergency personnel in making evidencebased medical decisions in scenarios with constraints on time and knowledge. Our approach is based on the artificial intelligence technique of semantic data mining, focusing on the use of ontology-based knowledge representation to provide the precise definition of entities and their relationships. This is particularly useful in medical applications due to the heterogeneity of medical data and the diversity of health care environments. Leveraging the SNOMED-CT medical terminology encoding system, we are able to extract information by applying context-aware semantic reasoning. Our high level system architecture includes four primary layers: an aggregation of data repositories, an ontology, a reasoning engine, and the application interface. The backbone of the system consists of knowledge representation and a reasoning engine connected to an end user system via a natural language processing mechanism. We also compare our approach with other methodologies for medical decision making (under similar constraints), emphasizing the particular value offered by our ontological approach for these time critical environments.
STACKELBERG GAME BETWEEN A CUSTOMER AND COOPERATING SUPPLIERS: STABILITY AND EFFICIENCY

In this paper, we analyse a Stackelberg game between a customer and multiple suppliers faced with the proposition of a new product manufacturing. Suppliers apply base stock policy to replenish their inventories. The customer, being the leader, anticipates suppliers’ optimal base stock levels and allocates demand volume to suppliers in a way to maximize his own profit. In addition, the customer as well as each of the suppliers has the option of accepting or rejecting this new product affair according to its profitability. We let suppliers cooperate by forming coalitions. In order to study coalition structures stability, we endow suppliers with foresight. We show that the grand coalition may be unstable particularly when system load is relatively low. We show that suppliers’ profits are better when they cooperate if the system load is high. However, for weakly loaded systems, suppliers may find it better not to cooperate. By comparing to the centralized system performances, we show that decentralization of decisions may lead to the loss of the affair in quite a lot of situations even when suppliers cooperate, and that in the case of acceptance, the system inefficiency is considerable.
The impact of informal caregiving networks on adult children ’ s caregiver burden

Previous research on the care-giver burden experienced by adult children has typically focused on the adult child and parent dyad. This study uses information on multiple informal care-givers and examines how characteristics of the informal care-giving network affect the adult child’s care-giver burden. In 2007, 602 Dutch care-givers who were assisting their older parents reported on parental and personal characteristics, care activities, experienced burden and characteristics of other informal care-givers. A path model was applied to assess the relative impact of the informal care-giving network characteristics on the care-giver burden. An adult child experienced lower care-giver burden when the informal care-giving network size was larger, when more types of tasks were shared across the network, when care was shared for a longer period, and when the adult child had no disagreements with the other members of the network. Considering that the need for care of older parents is growing, being in an informal care-giving network will be of increasing benefit for adult children involved in long-term care. More caregivers will turn into managers of care, as they increasingly have to organise the sharing of care among informal helpers and cope with disagreements among the members of the network.
Basic properties of teletraffic networks

In network calculus, a special class of teletraffic networks is formulated, saying only that they are linear, causal and time-invariant. Their network calculus representations use, however, other type of convolution, with the infimum operation, and also another algebra, called min-plus algebra. Therefore, it must be checked whether they really have the following properties: linearity, causality, time-invariance, associativity and commutativity. This paper presents a thorough treatment of the subject, provided with the needed mathematical details.
The chromatic index of block intersection graphs of Kirkman triple systems and cyclic Steiner triple systems

The block intersection graph of a combinatorial design with block set B is the graph with B as its vertex set such that two vertices are adjacent if and only if their associated blocks are not disjoint. The chromatic index of a graph G is the least number of colours that enable each edge of G to be assigned a single colour such that adjacent edges never have the same colour. A graph G for which the chromatic index equals the maximum degree is called Class 1; otherwise the chromatic index exceeds the maximum degree by one and G is called Class 2. We conjecture that whenever a Steiner triple system has a block intersection graph with an even number vertices, the graph is Class 1. We prove this to be true for Kirkman triple systems and cyclic Steiner triple systems of order v ≡ 9 (mod 12). We also prove that the conjecture holds for cyclic Steiner triple systems of order v ≡ 1 (mod 12) for which φ(v) v−1 2 3 , where φ is Euler’s totient function.
Oxidative stress and serum paraoxonase activity in experimental hypothyroidism: effect of vitamin E supplementation

Thyroid hormones are associated with the oxidative and antioxidative status of the organism. Since data on the oxidative status of hypothyroidism are limited and controversial, we investigated the oxidant and antioxidant status and serum paraoxonase/arylesterase activities in propylthiouracil‐induced hypothyroidism and examined the effect of vitamin E supplementation on this experimental model. Forty male Sprague Dawley rats were randomly divided into four groups (group 1, control; group 2, control+vitamin E; group 3, propylthiouracil; group 4, propylthiouracil+vitamin E). Plasma, red blood cell, liver, heart and skeletal muscle malondialdehyde levels were increased in the propylthiouracil‐treated group compared with the control rats and were decreased in propylthiouracil+vitamin E group compared with the propylthiouracil‐treated group. Vitamin E supplementation also significantly increased liver and kidney reduced glutathione levels in propylthiouracil treated animals. Serum paraoxonase and arylesterase activities were decreased in propylthiouracil treated group and vitamin E supplementation caused significant increase in serum paraoxonase activity compared with the propylthiouracil‐treated rats. These findings suggest that hypothyroidism is accompanied with increased oxidative stress and vitamin E supplementation exerts beneficial effects on this situation. Copyright © 2004 John Wiley & Sons, Ltd.
XML-based e-business frameworks and supply chain integration

OF DOCTORAL DISSERTATION HELSINKI UNIVERSITY OF TECHNOLOGY P.O. BOX 1000, FI-02015 TKK http://www.tkk. fi Author Juha-Miikka Nurmilaakso Name of the dissertation XML-based E-business Frameworks and Supply Chain Integration Manuscript submitted 12.9. 2006 Manuscript revised 17.10. 2007 Date of the defence 3.12. 2007 Monograph Article dissertation (summary + original articles) Department Department of Computer Science and Engineering Laboratory Software Business and Engineering Institute Field of research Electronic Business Opponent Professor Airi Salminen Supervisor Professor Reijo Sulonen Instructor Professor Reijo Sulonen
Comparing consumer evaluations of services-to-services brand extensions with services-to-goods

Purpose The purpose of this paper is to examine the influences of parent brand characteristics and brand-extension fit on attitude towards the extension in the context of services-to-goods (SG) brand extension compared with services-to-services (SS) brand extension. Design/methodology/approach A survey design was used to collect data from 626 individual respondents. The respondents were selected using probability sampling from two cities in India. The data were analyzed using structural equation modeling (SEM). Findings The study indicated that context (SS or SG) moderated the influence of factors on attitude toward brand extension. A favorable attitude towards the parent brand had a greater positive influence on SS brand extension compared with SG brand extension. Quality variance among service types under the parent brand had a higher negative impact on attitude towards SG brand extension than on attitude towards SS brand extension. Practical implications Managers may prefer extending a service brand to another service rather than a good when consumers have a favorable attitude towards the brand. Furthermore, when the perceived quality of service types under a service brand varies substantially, extension of the brand to a good requires greater concern than extension to a service. Originality/value The unique contribution of this study is the examination of the moderating influence of the characteristics of an offering (SS vis-a-vis SG) on the link between brand extension attitude and its influencing factors.
THUMT: An Open-Source Toolkit for Neural Machine Translation

THUMT is an open-source toolkit for neural machine translation (NMT) developed by the Natural Language Processing Group at Tsinghua University. The toolkit is easy to use, modify and extend while provides the latest advances in NMT research and production. THUMT implements several standard NMT models and supports distributed training across multiple machines, fast inference, and model visualization. Experiments on English-German and Chinese-English datasets show that THUMT can obtain results that are comparable to state-of-the-art NMT systems.
Datapolis: A Public Governance Perspective on “Smart Cities”

Smart cities are presented as both inevitable and benign futures: the technological development is unstoppable and will bring us wealthier, safer and more sustainable cities. Putting technology to use, however, is never entirely a matter of engineering but of strategic, political and value-laden choices. This article combines the literature on technology in the public sector and on (urban) governance to develop a public governance perspective on smart cities. The central theoretical concept “datapolis” highlights how the construction of smart cities can be understood in term of “actors,” “rules,” and “games” of urban governance. The theoretical analysis results in the identification of three types of actors (state, market, and civil society), three governance challenges (balancing perceptions, guaranteeing checks and balances and building upon different forms of knowing), and five governance games (the politics of data collection, data storage, data usage, data visualization and data access). The governance of smart cities is re-conceptualized as the socio-technical structures that emerge from the governance games. The governance challenge is to develop legitimate rules for perceptions, power relations and decisions in smart cities.
The Visual Computing Database : A Platform for Visual Data Processing and Analysis at Internet Scale 1 Introduction

There is strong evidence that a fundamental requirement of the next generation of visual and experiential computing (VEC) applications will be the efficient analysis and manipulation of large repositories of visual data (images, videos, RGBD, point clouds, etc.). For example, highly publicized recent advances in image understanding [24] stem not only from improved deep-learning techniques, but also from the ability to execute these techniques on internet-scale, human-annotated image collections [11, 28, 1, 45]. Analysis of visual data collections is also a major component of other advanced VEC applications such as computational photography, high-level image and video manipulation [19, 26, 25], and 3D scene reconstruction [36] and understanding [14]. Further, with image sensors rapidly becoming ubiquitous in all environments (in public spaces, on vehicles, the body, etc.), we anticipate the emergence of entirely new ecosystems of applications made possible by large-scale mining of streams of visual sensor data. These applications may range from consumer-centric personal assistants, to management of critical infrastructure for transportation and smart cities, and even include data-analysis for fundamental science.
An exploration of Canadian emergency physicians' and residents' knowledge of computed tomography radiation dosing and risk.

OBJECTIVE The objective of this study was to measure the current knowledge of Canadian emergency physicians and emergency medicine residents regarding computed tomography (CT) radiation dosing and its associated risks. METHODS Three focus groups were conducted as the qualitative element of this study. Cognitive debriefing was carried out to ensure the validity and reliability of the focus group findings and to aid with survey development. A 26-item electronic survey was developed and pilot tested for distribution to the membership of the Canadian Association of Emergency Physicians. RESULTS Eighteen emergency medicine physicians and three emergency medicine residents participated in the focus groups. Four major themes emerged: 1) physician knowledge of risks associated with CT, 2) risk management strategies, 3) communication, and 4) knowledge translation. The survey response rate was 49.8% (638 of 1,281). The mean respondent age was 40.9±9.9 years, and 70.7% were male. Of all respondents, 82.5% were actively practicing attending physicians, 56.4% of all respondents practiced in urban academic emergency departments, and the average time practicing was 10.7±9.6 years. Radiography and CT were correctly identified by 92.2% and 95.1% of respondents, respectively, as sources of ionizing radiation, whereas magnetic resonance imaging and ultrasonography were selected by 1.0% and 0.5%, respectively. With respect to the lifetime attributable risk (LAR) of malignancy due to CT, 82.2% of participants correctly identified that abdominal CT increases the risk of cancer by 0.2 to 2%, whereas 51.3% correctly identified that the LAR increases twofold in a 7- year-old boy. When asked to identify populations at risk for potential harm due to ionizing radiation, 92.2% of respondents identified children, 80.3% identified pregnant women, and 71.4% identified women of reproductive age. A minority (37.2%) reported communicating the potential risks of CT to a majority of their patients. Electronic platforms were identified by 74.8% of respondents as their preferred method of knowledge translation on this topic. CONCLUSIONS Canadian emergency medicine physicians and emergency medicine residents demonstrated identifiable gaps in knowledge surrounding CT radiation dose and risk.