Miracle-dz/UniFAR-FTUs huggingface dataset:
Tobacco taxation, policy-relevant attributes and smoking behaviour

In this paper, we first aim at contributing to the understanding of smokers’ responses to prices increases and, second, at analysing the role of other potentially policy-relevant attributes on smoking behaviour. To do this, we propose an empirical analysis to evaluate the effect on smokers’ utility of a set of choice-specific attributes that can be more or less directly affected by policymakers, such as price, health impact perception and social conditioning. To this end, we provide an empirical analysis based on individual-level data drawn from a survey on smokers’ habits. The main findings stemming from our analysis are the following. First, the average utility of an extra cigarette proves to be negative. Second, breaking down this result across five latentclasses of smokers, we find that all but one class of smokers exhibit negative marginal utility; the only class characterized by positive utility of an extra cigarette is the one composed of the youngest individuals, with a lower smoking intensity and with a higher propensity to use other products both traditional (fine cut) and new generation (e-cig). Third, a uniform across-brand price increase, by limiting the scope for product substitutions and downtrade, maximize the potential effect on reducing tobacco consumption.
Broad linguistic modeling is beneficial for German L2 proficiency assessment

We investigate the applicability of a broad range of language features to German second language proficiency assessment by comparing the performance of classification models based on linguistically diverse vs. homogeneous feature groups in terms of their overall performance and their success at individual proficiency levels (A1 to C1/ C2). For this, we extract 400 measures of linguistic complexity from the domains of syntax, lexicon, morphology, discourse, language use, and human language processing. Overall, our results show that a broad feature set integrating aspects of language as a system, language use, and human sentence processing costs results in higher classification performance on language learner data. At individual proficiency levels, lexical complexity in particular, but also clausal and phrasal complexities as well as discourse measures successfully distinguish several proficiency levels. Morphological complexity is particularly important for more advanced learners.
Interntional Conference On Business Management And Economics

A majority of 700 million people live in rural areas where the condition of medical facilities is appalling. Considering the picture of dismal facts there is a urging need of new practices and procedures to ensure that quality and timely healthcare reaches the deprived corners of the villages in India. The government has implemented scores of policies and programs but the success and effectiveness of these programs is questionable due to disparity in the implementation. The government of India has promoted primary and community health centres in all the states and Union territories. In the recent development private health centres also play a major role in rural health. Coimbatore district caters its rural population with primary, community and private health centres.The study aims at the perception of quality of services provided by these health care centres in Coimbatore district. The research data were collected through survey and total of 256 participants completed the questionnaire. The study is descriptive in nature with the sampling method being simple random sampling. T-test, factor analysis, Mean and SD was applied to compare the different health care centres. The result of this empirical study proved that overall quality of services provided by both primary and private health care centres is higher compare to community health care centre.
Bacteria isolated from the lower respiratory tract of sheep and their relationship to clinical signs of sheep respiratory disease

ABSTRACT: Respiratory diseases are among the most important diseases in sheep flocks. Herein was studied the bacterial etiology of respiratory disease and the clinical signs of 99 female and male sheep breed in the states of São Paulo (SP) and Rio de Janeiro (RJ), Brazil. After physical examination of animals, tracheobronchial flushing samples were obtained. The usual bacteria and Mycoplasma spp. were searched, as well as their association with the clinical status and clinical signs of sheep with respiratory disease. The main observed signs were: tachypnea (75%), increase of rectal temperature (09.4%), mucopurulent/purulent nasal discharge (21.9%), cough (25%), dyspnea (31.2%), changes of lung sounds at auscultation (87.5%) and chest percussion (28.1%) in pneumonic sheep. Non-fermenting gram-negative bacteria and Bacillus sp. were the most isolated bacteria. Microorganisms of the Mollicutes class were molecularly (PCR) detected in 33.3% of the animals. In addition, the specific detection of M. mycoides subsp. capri was described for the first time in sheep from the state of São Paulo, Brazil.
Upper and lower bounds for finite domain constraints to realize skeptical inference over conditional knowledge bases

Skeptical c-inference for a knowledge base containing conditionals of the form If A then usually B is defined by taking the set of all c-representations into account. C-representations are ranking functions induced by impact vectors encoding the conditional impact of the conditionals on each possible world. We deal with the question of determining a maximal impact factor u ∈ N such that c-inference can be implemented by a finite domain constraint problem with solutions bounded by u. While in general, determining a sufficient upper bound for these CSPs is an open problem, we prove that for a knowledge base with n conditionals with a world verifying all conditionals it follows that n− 1 is a sufficient maximal impact factor. Furthermore, we show that the conjecture supported by previous work that the number of conditionals is sufficient does not hold. By constructing suitable knowledge bases with n conditionals we establish that the exponential lower bound 2n−1 is needed as possible impact factor for solutions of these finite domains problems to fully realize skeptical c-inference.
Lens distortion calibration for mid-wave and long-wave infrared thermal cameras

Camera calibration is an indispensable process for improving measurement accuracy in industry fields such as machine vision. However, existing calibration targets cannot be applied to the calibration of mid-wave and longwave infrared cameras. Recently, as the use of infrared thermal cameras that can measure defects from thermal properties has spread, development of an applicable calibration target development has become required. Thus, based on heat conduction analysis using finite element analysis, this paper presents a calibration target that can be used with both existing visible cameras and infrared thermal cameras by implementing the optimal design conditions, considering factors such as thermal conductivity and emissivity, colours and materials.
Counselling on Pediatric T 2 DM

T2DM occurs when insulin secretion is inadequate to meet the increased demand due to insulin resistance then progressively there is apparition of hyperglycemia [1-5]. These children/adolescent are most of the time overweight or obese and commonly are associated either with acanthosis nigricans, PCOS, hyperlipidemia, HTN, and NAFLD. In 75 % of the cases they have strong family history of T2DM [4-5]. The presentation often coincides with the peak of pubertal insulin resistance as explained earlier [8-9].
Mindfulness Transpersonal Psychology and tumors: This Approach may be always Suitable and Effective with the Patient?

Mindfulness is the psychological process of bringing one's attention to the internal and external experiences occurring in the present moment. This comes from the practice of meditation especially Buddhist meditation and Advaita Vedanta Path (Transpersonal Psychology). The recent popularity of mindfulness in the West is generally considered to have been initiated by Jon Kabat Zinn. Mindfulness practice is being employed in psychology to alleviate a variety of mental and physical conditions, such as bringing about reductions in depression symptoms, reducing stress, anxiety, and in the treatment of drug addiction. Recent studies demonstrate that mindfulness meditation significantly attenuates pain through multiple, unique mechanisms. It has gained worldwide popularity as a distinctive method to handle emotions. Studies have also shown that rumination and worry contribute to mental illnesses such as depression and anxiety, and that mindfulness-based interventions are effective in the reduction of both anxiety and depression. Clinical psychology and psychiatry since the 1970s have developed a number of therapeutic applications based on mindfulness for helping people who are experiencing a variety of psychological conditions (Kabat Zinn). Clinical studies have documented both physical and mental health benefits of mindfulness in different patient categories as well as in healthy adults and children. Programs based on MBSR and similar models have been widely adopted in schools, prisons, hospitals, veterans' centers, and other environments. Mindfulness meditation can be defined in many ways and can be used for a variety of different therapies. When defining mindfulness meditation, it is useful to draw upon Buddhist psychological traditions and the developing scholarship within empirical psychology.
GREEN TEA ANTIOXIDANT EFFECTS AND ITS AMELIORATIVE ROLE AGAINST MANY DISEASES

Green tea flavonoids have been found to play important roles in the non-enzymatic protection against oxidative stress, especially in case of cancer. Epidemiological and laboratory studies have reported that green tea presents diverse beneficial health effects including antioxidant , hypocholesterolemic , anti-hyperglycemic, antiparasitic, anti-inflammatory, antimicrobial, hepatoprotective , antinephrotoxcity and anticarcinogenic effects. Green tea ameliorating effects against oxidative stress caused by many pollutants and chemical toxins are also recorded by many studies.
Fusion of Elliptical Extended Object Estimates Parameterized With Orientation and Axes Lengths

This article considers the tracking of elliptical extended targets parameterized by center, orientation, and semiaxes. The focus of this article lies on the fusion of extended target estimates, e.g., from multiple sensors, by handling the ambiguities in this parameterization and the unclear meaning of the mean square error. For this purpose, we introduce a novel Bayesian framework for elliptic extent estimation and fusion based on two new concepts: 1) A probability density function for ellipses called random ellipse density which incorporates the ambiguities that come with the ellipse parameterization, and 2) the minimum mean Gaussian Wasserstein (MMGW) estimate, which is optimal with respect to the squared Gaussian Wasserstein (GW) distance—A suitable distance metric on ellipses. We develop practical algorithms for ellipse fusion and approximating the MMGW estimate. Different implementations, e.g., based on Monte Carlo simulation, are introduced and compared to state-of-the-art methods, highlighting the benefits of estimators tailored to the GW distance.
A CRITICAL REVIEW LITERATURE ON TALENT RETENTION IN TECHNICAL EDUCATION INSTITUTIONS

Technical institutions play an important and critical role in the development of the nation‘s growth in the field of science and technology.The performance of the technical institutes are majorly influenced by the intellectual capital of that institute, in this regard the retention of the intellectuals is a challenging task for the educational institute managements. It is widely known that technical institutes are severely influenced by shortage of intellectuals (faculty) because of various parameters, primarily due to recent increases in enhanced student enrolments.Starting of new courses in the existing institutes, starting new institutes and faculty retirements etc., are also considered among the primary reasons. Technical institute staffing problems are not primarily due to shortage in intellectuals/teacher shortages, in the sense insufficient availability of qualified teachers. Rather, technical institute staffing problems are primarily due to a ―revolving door‖ where large number of qualified teachers departs their jobs for reasons other than retirement. The present study emphasizes on the review of available literature on talent retention in technical education institutions in India during 19902017.
ICSC 2006

This research was done to investigate the ratio between environmental characteristics and the wayfinding model. Research makes use of integration in a wayfinding system of a typical parameter of the traditional transport models such as distance, and of the space syntax analysis, such as integration. Space syntax (Hillier and Hanson, 1984) is a morphologic analysis system of space and its constitutive elements: buildings and urban areas. Tha purpose is to supply a useful instrument to the analysis and the social improvement of urban and architectonic projects (Teklenburg, Timmermans and Wagenberg, 1992). It was A. M. Nenci ( ) LUMSA University, Rome, Italy e-mail: nenci@lumsa.it R. Troffa University of Rome ‘‘La Sapienza’’, Rome, Italy proposed as a model to forecast wayfinding with the aim to demonstrate the ratio between the integration values of urban space and the movements of people within. Moreover (Steadman, 2004), there is another empirical problem to analyze: the way used by people to move in urban areas to reach a place. If they choose shortest routes or if they rather choose the shortes number of axial lines. In that optycal it has been related, from the teorethical view-point, with traditional transport models (Ratti, 2004; Hillier and Penn, 2004). In this research we asked university students, sorted by gender, to make a wayfinding task by computer. Results are valued by the metric distance (transports model) and the integration (space syntax model).
CHLORIDE ION INGRESSION THROUGH AND AROUND THE CRACK IN REINFORCED CONCRETE STRUCTURES

This study was carried out in order to observe the penetration profile of the chloride ions through cracks in reinforced concrete structures. Concentration and penetration depth profile of Cl ions might be useful information to consider degradation of life span of structures due to localized corrosion where a crack exists. EPMA and Colorimetric tests were conducted on specimens exposed to NaCl solution under different exposure conditions. The increase of w/c leads obvious dilation on ingression rate of Cl ions not only from exposed surface but also around the crack. In general, the penetration depth around crack is higher than that from exposed surface except for those with very low w/c of 0.25.
SHREC19 Protein Shape Retrieval Contest

This track aimed at retrieving protein evolutionary classiﬁcation based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this track offers a challenging issue using biologically relevant molecules. We evaluated the performance of 5 different algorithms and analyzed their ability, over a dataset of 5,298 objects, to retrieve various conformations of identical proteins and various conformations of ortholog proteins (proteins from
Risk-Based Design Optimization Via Probability of Failure, Conditional Value-at-Risk, and Buffered Probability of Failure

When designing systems, uncertainties must be dealt with at various levels. The designer must define appropriate cost and constraint functions that account for such uncertainties and capture the risk associated with unwanted system behavior. The choice of these cost and constraint functions additionally plays an important role in the convergence behavior of the optimization and, among other things, the final design. This paper studies different types of risk-based optimization problem formulations that can aid in efficient and robust design of complex engineering systems. In tutorial form, the paper describes risk-based optimization problem formulations, specifically, reliability-based design optimization, conditional-value-atrisk-based optimization, and buffered-failure-probability-based optimization. The properties of each formulation are analyzed and general guidelines for the appropriate choice of the optimization problem are provided for a given application setup. An in-depth understanding of the different optimization problems should facilitate development of future methods for designing safe engineering systems.
Towards a SAR System for Personalized Cardiac Rehabilitation: A Patient with PCI

Physical activity has been shown to have multiple benefits, such as reducing mortality rate caused by cardiovascular diseases and providing an optimal health status, making it one of the most important components of cardiac rehabilitation (CR) programs. However, the adherence to the program is low, and finding strategies to mo-tivate people to perform physical training is a priority. This work proposes the introduction of a socially assistive robotics system in order to provide monitoring and motivation to patients within a CR program. A study was carried out with one patient accompanied by the robot during a conventional phase II, namely 16 sessions of the cardiac rehabilitation program. The results show the reliability of the system to provide information to assess the patient’s performance during the activity. Additionally, the patient was able to improve his posture patterns along the sessions due to the continuous monitoring provided by the robot.
Emotional Robots for Coaching: Motivating Physical Rehabilitation using Emotional Robots

It is complicated to maintain the interest of the patients performing long rehabilitation programs. When a therapist proposes together repetitive physical exercises and non-supervised sessions the adherence to the program decreases. This is even worst for young patients feeling well after some weeks of rehabilitation. In this scenario, the usage of social robots for improving patient motivation during the rehabilitation exercises present an opportunity for researchers and therapists. This paper defines a rehabilitation framework that provides positive reinforcement to enhance user experience during the process of rehabilitation using verbal and non-verbal communication. The framework will provide qualitative and quantitative feedback to patient attending therapist requirements using the feedback set: voice, gestures, and emotions through facial expressions A pilot study has been performed to young people in order to test the system before the trials with real patients in a rehabilitation center. Preliminary results suggest the importance of the feedback to engage the individuals during non-supervised repetitive physical exercise.
Making Recommendations when Users Experience Fatigue

In this paper we consider an online recommendation setting, where a platform recommends a sequence of items to its users at every time period. The users respond by selecting one of the items recommended or abandon the platform due to fatigue from seeing less useful items. Assuming a parametric stochastic model of user behavior, which captures positional effects of these items as well as the abandoning behavior of users, the platform’s goal is to recommend sequences of items that are competitive to the single best sequence of items in hindsight, without knowing the true user model a priori. Naively applying a stochastic bandit algorithm in this setting leads to an exponential dependence on the number of items. We propose a new Thompson sampling based algorithm with expected regret that is polynomial in the number of items in this combinatorial setting, and performs extremely well in practice.
Developing a Framework for Potential Candidate Selection

Recruitment is the process of hiring the right person for the right job. In the current competitive world, recruiting the right person from thousands of applicants is a tedious work. In addition, analyzing these huge numbers of applications manually might result into biased and erroneous output which may eventually cause problems for the companies. If these pools of resumes can be analyzed automatically and presented to the employers in a systematic way for choosing the appropriate person for their company, it may help the applicants and the employers as well. So in order to solve this need, we have developed a framework that takes the resume of the candidates, pull out information from them by recognizing the named entities using machine learning and score the applicants according to some predefined rules and employer requirements. Furthermore, employers can select the best suited candidates for their jobs from these scores by using skyline filtering.
Comparing Learning Gains in Cryptography Concepts Taught Using Different Instructional Conditions and Measuring Cognitive Processing Activity of Cryptography Concepts

Information security practitioners and researchers who possess sufficient depth of conceptual understanding to reconstitute systems after attacks or adapt information security concepts to novel situations are in short supply. Education of new information security professionals with sufficient conceptual depth is one method by which this shortage can be reduced. This study reports research that instructed two groups of ten undergraduate, pre-cryptography students majoring in Computer Science in cryptography concepts using representational understanding first and representational fluency first instructional treatment methods. This study compared learning results between the treatment groups using traditional paper-based measures of cognitions and fMRI scans of brain activity during cryptography problem solving. Analysis found no statistical difference in measures of cognitions or in cognitive processing, but did build a statistical model describing the relationships between explanatory variables and cryptography learning, and found common areas of cognitive processing of cryptography among the study’s twenty subjects.