Miracle-dz/UniFAR-FTUs huggingface dataset:
Objective Identification of Cyclones and Their Circulation Intensity, and Climatology

Abstract An updated procedure for objective identification and tracking of surface cyclones from gridded analyses is described. Prior smoothing of the raw data with a constant radius spatial filter is used to remove distortions related to the particular grid configuration used and to consistently admit a known scale of disturbance over the domain. Pitfalls of using central pressure or vorticity to infer cyclone intensity are illustrated, and a procedure for obtaining a more realistic areal measure of circulation is described. An automated selection procedure for storms having specific properties is outlined. Case selection is by computer search of a database of cyclone tracks, obtained from an application of the cyclone finding and tracking procedure to an extended series of gridded mean sea level pressure analyses. A selection of winter season cyclone statistics for both hemispheres is obtained from European Centre for Medium-Range Weather Forecasts analyses. Discrepancies with and between earlier studie.
Syddansk Universitet MultiView Object Instance Recognition in an Industrial Context

We present a fast object recognition system coding shape by viewpoint invariant geometric relations and appearance information. In our advanced industrial work-cell, the system can observe the work space of the robot by three pairs of Kinect and stereo cameras allowing for reliable and complete object information. From these sensors, we derive global viewpoint invariant shape features and robust color features making use of color normalization techniques. We show that in such a set-up, our system can achieve high performance already with a very low number of training samples, which is crucial for user acceptance and that the use of multiple views is crucial for performance. This indicates that our approach can be used in controlled but realistic industrial contexts that require—besides high reliability—fast processing and an intuitive and easy use at the end-user side.
Acute Effects of Training on Hypofyse Hormon Levels in KickBoxers

This study was aimed to investigate the possible effects of acute training on hypofyse hormone levels and some biochemical analytes in kick-boxers. The study was included 23 healthy professional male kick-boxers (age range: from 17 to 32 years and BMI range: from 19.0 to 24.2). Sportsmen were exposed to a total of 95-minute training program including training and a kick-boxing match. Venous blood samples and urine were taken from sportsmen just before and immediately after training and some biochemical analytes were analyzed. The evaluation of preand post-training serum levels of analytes have shown that growth hormone, adrenocorticotropic hormone, prolactine, throide stimulating hormone, adrenalin and noradrenalin levels were significantly increased and serum insulin-like growth factor I and free thyroxine levels were significantly decreased by training. There were no significant differences between preand post-training serum levels of other biochemical analytes; luteinizing hormone, follicle-stimulating hormone, free triiodothyronine, cortisole and dopamin. Our results have revealed the fact that exercise alters pituitary functions and this increment is associated with response to exercise stress. “We are in agree with the previous recommendations about regulary screening of pituitary functions and total hormonal status of competing and retired kick-boxers. ” Clinical article (J Int Dent Med Res 2016; 9: (2), pp. 133-138)
Title Defining Trust Using Expected Utility Theory

Trust has been discussed in many social sciences including economics, psychology, and sociology. However, there is no widely accepted definition of trust. In particular, there is no definition that can be used for economic analysis. This paper regards trust as expectation and defines it using expected utility theory together with concepts such as betrayal premium. In doing so, it rejects the widely accepted black-and-white view that (un) trustworthy people are always (un)trustworthy. This paper also discusses various determinants and properties of trust on the basis of the idea that trust is not simply a matter of intention.
Understanding the Links among the Magnetic Fields, Filament, Bipolar Bubble, and Star Formation in RCW 57A Using NIR Polarimetry

The influence of magnetic fields (B-fields) on the formation and evolution of bipolar bubbles, due to the expanding ionization fronts (I-fronts) driven by the H ii regions that are formed and embedded in filamentary molecular clouds, has not been well-studied yet. In addition to the anisotropic expansion of I-fronts into a filament, B-fields are expected to introduce an additional anisotropic pressure, which might favor the expansion and propagation of I-fronts forming a bipolar bubble. We present results based on near-infrared polarimetric observations toward the central ∼8′ × 8′ area of the star-forming region RCW 57A, which hosts an H ii region, a filament, and a bipolar bubble. Polarization measurements of 178 reddened background stars, out of the 919 detected sources in the JHKs bands, reveal B-fields that thread perpendicularly to the filament long axis. The B-fields exhibit an hourglass morphology that closely follows the structure of the bipolar bubble. The mean B-field strength, estimated using the Chandrasekhar–Fermi method (CF method), is 91 ± 8 μG. B-field pressure dominates over turbulent and thermal pressures. Thermal pressure might act in the same orientation as the B-fields to accelerate the expansion of those I-fronts. The observed morphological correspondence among the B-fields, filament, and bipolar bubble demonstrate that the B-fields are important to the cloud contraction that formed the filament, to the gravitational collapse and star formation in it, and in feedback processes. The last one includes the formation and evolution of mid-infrared bubbles by means of B-field supported propagation and expansion of I-fronts. These may shed light on preexisting conditions favoring the formation of the massive stellar cluster in RCW 57A.
TLR2 Controls Intestinal Carcinogen Detoxication by CYP1A1. - DTU Orbit (09/10/2017)

Intestinal Carcinogen Detoxication CYP1A1. Intestinal cytochrome P450 subclass 1A1 (CYP1A1) contributes to a metabolic "shield" protecting the host from ingested carcinogens such as polycyclic aromatic hydrocarbons (PAH). The expression of CYP1 (including CYP1A2 and CYP1B1) is considered to depend solely on a heterodimeric transcription factor consisting of the arylhydrocarbon receptor (AHR) and the AHR nuclear translocator (ARNT). So far, no interference has been noted between the regulation of CYP1 and the activation of Toll-like receptor 2 (TLR2), which modulates the inflammatory response to bacterial cell wall components in immune cells and enterocytes. Here we report that intestinal CYP1A1 is silenced in TLR2-deficient mice, even when under exposure to the carcinogenic PAH benzo[a]pyrene (BaP). In contrast, hepatic CYP1A1 was moderately induced in TLR2-deficient mice without restoring their ability to clear BaP from systemic circulation, as present in wild-type animals. After feeding of BaP for 21 days, only TLR2(-/-) mice, but not their wild type littermates developed polyps in the colon. Gene expressions and protein concentrations of AHR and ARNT in the intestine did not differ between the genotypes. In conclusion, the presence of ligands for TLR2 of bacterial origin seems to be crucial for detoxication of luminal carcinogens by CYP1A1 in the intestine. This unprecedented finding indicates a complex interplay between the immune system of the host and intestinal bacteria with detoxication mechanisms. This highlights the relevance of intestinal microbiota when trying to unravel pathways present in mammals and opens new perspectives for research in human health.
Translog Cost Functions: An Application for Mexican Manufacturing *

We use translog cost functions to estimate own-price and substitution elasticities of input demands, economies of scale and average costs in Mexican manufacturing. Data from the Mexican Annual Industrial Survey is used for 1996, 2000 and 2003. We show that a model that allows for nonhomotheticity and nonunitary elasticities of substitution is appropriate to represent the production structure. Allen-Uzawa elasticities indicate the existence of substitution possibilities amongst inputs. The demand for electricity is essentially unitary elastic. All cross-price elasticities are less than one. Both scale economies and average costs diminish as the size of activity class increases. Economies of scale increased for any level of output. The differences in average costs between small and large activity classes were reduced and some disparities prevail in a number of manufacturing groups.
The Algorithm and Software Implementation of the Thermal Transient Testing Technology Applied in High-Power Electronics

Thermal transient testing technology is currently the most effective method for obtaining thermal characteristic parameters of high-power electronics and the structure functions can be used to evaluate the long life-time reliability. This paper briefly outlines the basic theory of the thermal transient testing technology, and then focuses on two key algorithms in the implementation of this technology: deconvolution and transformation of thermal network model algorithms. Meanwhile, a software system of the thermal transient testing applied to power semiconductor devices is established. Mathematicians used to solve the problem of data accuracy in network model transformation. By comparing the commonly used deconvolution algorithm, it is concluded that the thermal characteristic parameters of the device calculated by Bayesian deconvolution based on RichardsonLucy algorithm have better accuracy. Finally, the measurement data of power semiconductor devices tested by mature commercial thermal transient testing equipment is set as an example to verify the accuracy and effectiveness of the proposed software system.
Another Walk through the World of Chiral Dynamics

Chiral dynamics is a pretty mature field. Nonetheless, there are many exciting new developments. In this opening talk, I consider S-wave, isospin-zero pion-pion scattering and the calculation of the width of the lightest baryon resonances at two loops. New insights into the chiral dynamics of charm-strange mesons are discussed as well as recent results on the flavor decomposition of the pion-nucleon $\sigma$-term. I end with a short wish-list of lattice QCD tests pertinent to chiral dynamics.
Comparison of stress level and coping strategy between therapeutic phases in newly diagnosed tuberculosis

In newly diagnosed Tuberculosis (TB), the diagnosis and therapy duration may cause psychological stress requiring effective coping strategy. This study aimed to compare and analyze the differences of stress level and coping strategy between intensive and advanced phases in newly diagnosed TB. This cross-sectional study involved 16 respondents in intensive phase and 29 respondents in advanced phase (n=45), in the working area of Pacar Keling Public Health Center of Surabaya. Perceived Stress Scale (PSS) and coping strategy questionnaire were used for collecting data. Data were collected in May 2018. Independent sample t test was used in data analysis (α<0.05). Results showed that mostly moderate stress level and adaptive coping strategy were found in both phases. Overall, stress and coping were not significantly different between phases in newly diagnosed TB (p=0.259 and p=0.079 respectively), but the feeling of angry, losing control, nervous & depressed, whether things happened as wishes, talking problems to professionals, and trying new dangerous thing were differ significantly between phases (p=0.046, p=0.024, p=0.044, p=0.016, p=0.014, and p=0.005 respectively). Although stress level and coping strategy were not significantly different between therapeutic phases in newly diagnosed TB, but more attention needs to be given towards patients’ emotion, such as the feeling of angry, losing control, nervous and depressed, and patients’ wishes, especially in intensive phase.
Visual Target Tracking Based on Compressive Feature Weighting

At present, most of the features used for tracking are high in dimension, and each dimension of the feature have the same weight, which will increase the amount of computation during tracking and may lead to a poor tracking performance. In this paper, we propose a visual target tracking algorithm based on compressive feature weighting. Unlike the existing methods, we extract compressive features of the target to reduce the amount of calculation, and each dimension of the compressive features is given a different weight by feature weighting method, then the weighted compressive features are used in a Bayes classifier to track the target. In addition, to reduce information loss, multiple compressive features are extracted, and a Kalman Filter is also used to improve the tracking performance. Experimental results demonstrate that the proposed tracking algorithm can achieve a very good performance in some challenging environments, even when the camera is moving.
Persuasion, Symbols, and Alfajores: A Qualitative Study of Unique Advertising Approaches in Argentina

This study was conducted to gain a deeper understanding of how symbols are used in Argentine advertising and how Argentines interpret these symbols. Expanding on past research, the researcher took a deeper look at how identification is achieved with the use of symbols. The researcher investigated a particularly popular brand of dessert products called Havanna alfajores. Because of the immense popularity of the Havanna organization, the researcher interviewed 300 Argentine participants about their experiences with Havanna alfajores. Employing Strauss & Corbin’s (1990) data analysis technique, the constant comparative analysis, the researcher engaged in a structured and rigorous process of combing the messages from the interviews into five themes that addressed the research questions. The five themes that emerged from the data analysis were: the Sense of Trust that Havanna provides, Havanna facilitates relationships, Havanna is Symbol of Escape, Havanna is the Taste of Argentina, and Havanna Packaging Represents a Gift. The results of this study indicate that Havanna alfajores’ marketing effectively established identification with consumers to the point that they felt a relationship with the company and product. These findings extend Gennaro’s (2007) contention that the majority of meanings humans attach to symbols are not innate. Humans learn meaning as they grow into adulthood while the meanings are passed along members of a culture to younger generations.
Evaluation of the Raw Milk Quality Produced in Semiarid Areas from the Alagoas , Brazil : The influence of Vegetation Index and Bovine Thermal Comfort

The aim of this study was to evaluate the quality of the raw milk produced in the semiarid region of the Alagoas state, Brazil being influenced by bovine thermal control index and vegetation index. The raw milk was collected after the dairy cow of 12 small rural areas (semi-arid) of Alagoas state during four seasons. Fifty-eight collected raw milk samples were subjected to examine microbiologically for coliforms, Escherichia coli and coagulase-positive Staphylococcus. Only 02 rural associations presented low levels of microbiological contamination, which were located in areas of climatic conditions and parameters of Bovine Thermal Comfort Index (BCTI) and vegetation index favorable, but 10 rural associations presented high counting of coliforms at 45°C, Escherichia coli. The BTCI and Vegetation Index have shown to influence growth of coliforms at 45°C and Escherichia coli with high incidence during summer condition. The BCTI and vegetation index had influenced the coagulase-positive Staphylococcus count especially during the end of summer and start of the autumn seasons. History Submitted: Nov 21, 2016 1 Revision: Dec 19, 2016 2 Revision: Aug 8, 2017 Accepted: Aug 17, 2017 Online: Sep 12, 2017
Approach for detecting Black hole attack in MANETs

Black Hole attack is a serious threat in the modern era of mobile Ad Hoc network. In this attack when a sender node wants to communicate to the destination. A malicious node sends a reply with a shortest path or highest sequence number. In view of that sender sends the entire data packet through the malicious node and all the data dropped. Every conventional method to detect such an attack has a defect of high rate of failure. In order to overcome from this security issue, we propose a new detection method based on confirmation of route to destination and also propagates the information of malicious node to all other nodes in the network. The simulation results with graph show the efficiency of the proposed method. As it is obvious that once malicious node detected the throughput of the network will not get affected due to presence of black hole in attack.
Bringing the Leader Back in: Why, How, and When Leadership Empowerment Behavior Shapes Coworker Conflict

With the diffusion of team-based work organizations and flatter organizational hierarchies, many leaders empower employees to perform their work. Empowerment creates an interesting tension regarding coworker conflict, enhancing trust and giving employees more autonomy to prevent conflict, while also increasing workload and the potential for coworker conflict. Recent conflict research has focused on how characteristics of individuals, groups, and tasks contribute to conflict among coworkers. We extend this work by exploring the role of leader empowerment behavior (LEB) in influencing coworker conflict. Our model integrates research on LEB and coworker conflict to help organizations manage coworker conflict effectively. To test our model at the workplace level, we utilize data drawn from matched surveys of leaders and employees in 317 workplaces. We find that LEB relates negatively to relationship and task conflict through affective and cognitive trust in leaders. We further find that LEB relates negatively to relationship and task conflict through reduced workload, but only when employees have a clear role description. In contrast, if employees have unclear roles, LEB has a U-curve relationship with workload: a moderate level of LEB reduces workload, but a high level of LEB increases workload, in turn increasing coworker conflict. Finally, relationship conflict has a direct negative effect on task performance, whereas task conflict has an indirect negative effect through relationship conflict.
Placing Knowledge Management in Context

We welcome the increased emphasis on practice-based theories of knowing as an alternative to the more representational, knowledge-as-object approaches which have characterised many organizational attempts at 'knowledge management' to date. Building on the findings of a short empirical study into the 'knowledge management' initiatives of a global software organization, which highlighted the value of rich context in the generation of meaning, we seek to shed some light on a perceived confusion about the nature of organizational context. We show such context to be an inseparable part of knowing, which it creates and by which it is defined, and re-use Blackler's (1995) taxonomy of 'knowledge types' to illustrate the relational interaction between shared and deeply personal components of context. Finally, we use these insights to suggest a way in which organizations may be able to derive more value from their investments in internal initiatives by increasing their ability to support knowing - and hence the generation of meaning - amongst their employees. Copyright Blackwell Publishing Ltd 2004.
General Simhash-based Framework for News Aggregators

News aggregator usually indexes billions of news from Internet and try to recommend news according to readers’ intrinsic interests. Retrieval for similar news, deduplication and event detection are common problems in aggregator systems, and related works are reported in [1], [2], [3], [4] and [5]. We proposed a general simhash-based framework for news aggregator, the system has no necessary to process crawled news for retrieval, deduplication and event detection respectively, each piece of news is processed only one time and without extra storage space. Duplicates and breaking events can be detected online before new crawled news was stored in system’s database. Machine learning are widely used in news aggregator for tasks like topic classification and each piece of news is mapped into a feature vector with fixed length. Simhash fingerprints are generated on feature vectors rather than original text of news, therefore news retrieval, deduplication and breaking news detection can be integrated into any running aggregator systems without extra efforts. Our aggregator collected around 9.6 million of news from Internet and the framework function well in real scenario.
Expanded Screening of One Million Swedish Babies with R4S and CLIR for Post-Analytical Evaluation of Data

Sweden has one neonatal screening laboratory, receiving 115 to 120 thousand samples per year. Among the one million babies screened by tandem mass spectrometry from November 2010 until July 2019, a total of 665 babies were recalled and 311 verified as having one of the diseases screened for with this methodology, giving a positive predictive value (PPV) of 47% and an incidence of 1:3200. The PPV was high (41%) already in the first year after start of screening, thanks to the availability of the collaborative project Region 4 Stork database. The PPV is presently 58%. This improvement was achieved by the implementation of second-tier analyses in the screening for methylmalonic aciduria, propionic aciduria, isovaleric aciduria, and homocystinuria, and the employment of various post analytical tools of the Region 4 Stork, and its successor the collaborative laboratory integrated reports.
ENTROPY BASED EDAS DECISION MAKING MODEL FOR NEIGHBORHOOD SELECTION: A CASE STUDY IN ISTANBUL

Neighborhood selection problem has turned to be one of the important multi criteria problems which is affected by social, environmental, economic, and technical decision factors. Big cities in developing and developed countries have invested a noticeable amount of yearly budgets in educational sector. Development of education sectors have caused an increase in number of foreign student in most the universities. Neighborhood selection for accommodation of such students is very critical and important process. In this study, we proposed an Entropy based EDAS method to evaluate neighborhood alternatives for a new foreign student. To show the feasibility of the proposed methodology, a case study is performed for a new foreign student in Istanbul. A sensitivity analysis is presented to verify the obtained results from EDAS method
Developing Cross-lingual Sentiment Analysis of Malay Twitter Data Using Lexicon-based Approach

Sentiment analysis is a process of detecting and classifying sentiments into positive, negative or neutral. Most sentiment analysis research focus on English lexicon vocabularies. However, Malay is still under-resourced. Research of sentiment analysis in Malaysia social media is challenging due to mixed language usage of English and Malay. The objective of this study was to develop a cross-lingual sentiment analysis using lexicon based approach. Two lexicons of languages are combined in the system, then, the Twitter data were collected and the results were determined using graph. The results showed that the classifier was able to determine the sentiments. This study is significant for companies and governments to understand people’s opinion on social network especially in Malay speaking regions.