Miracle-dz/UniFAR-FTUs huggingface dataset:
Seroprevalence to avian influenza A(H7N9) virus among poultry workers and the general population in southern China: a longitudinal study.

BACKGROUND Confirmed cases of avian influenza A(H7N9) virus infection in humans continue to occur in mainland China. Few confirmed cases have occurred in poultry workers despite potentially higher rates of exposure. METHODS A serological survey was conducted in May and December 2013 in poultry market workers, and in March and September 2013 in the general population. Blood samples were collected and tested for antibodies to H7N9 and H5N1 viruses by hemagglutination inhibition (HI) assays. Multivariable analysis was employed to identify risk factors related to H7N9 infection indicated by serology among poultry workers. RESULTS In the poultry workers, 36 of 501 (7.2%) in May and 56 of 375 (14.9%) in December had HI antibody titers ≥1:160 to H7N9. Of 96 individuals who participated in both surveys, 52 (54.2%) workers had a ≥4-fold rise in H7N9 antibody titers from May to December. In a multivariable analysis, female sex (odds ratio [OR], 2.713; 95% confidence interval [CI], 1.098-6.705) and ≥10 years of occupational exposure (OR, 3.592; 95% CI, 1.246-10.354) were identified as risk factors for infection. Seroprevalence against H5N1 at ≥1:160 was low in May (4/501 [0.8%]) and December (3/375 [0.8%]). In the general population, 0 of 417 individuals in March and 0 of 408 individuals in September had antibody titers ≥1:160 to H7N9 or to H5N1. CONCLUSIONS Although none of the participants in our study had virologically confirmed H7N9 infection, the high proportion of poultry workers with serologic evidence of H7N9 infection between May and December 2013 suggests a substantial risk of mild H7N9 infections in this group, supporting stricter control measures in live poultry markets.
The clinical meaning of walking speed as measured by the timed 25-foot walk in patients with multiple sclerosis.

IMPORTANCE Walking impairment, a common clinical manifestation of multiple sclerosis (MS), is often measured in clinical practice and clinical trials using the Timed 25-Foot Walk (T25-FW). OBJECTIVE To evaluate the relationship between walking speed measured by the T25-FW and the Physical Component Summary (PCS) score of the 36-Item Short Form Health Survey (SF-36) to better understand the clinical meaning of T25-FW walking speed in MS. DESIGN, SETTING, AND PARTICIPANTS We retrospectively analyzed data from 3 clinical trials (Natalizumab Safety and Efficacy in Relapsing-Remitting Multiple Sclerosis [AFFIRM], Safety and Efficacy of Natalizumab in Combination With Interferon Beta-1a in Patients With Relapsing-Remitting Multiple Sclerosis [SENTINEL], and International MS Secondary Progressive Avonex Controlled Trial [IMPACT]) that included T25-FW and SF-36 scores as outcomes in patients with MS. Patients had secondary-progressive MS and an Expanded Disability Status Scale score of 3.5 to 6.5 or relapsing-remitting MS and an Expanded Disability Status Scale score of 0 to 5.0. MAIN OUTCOMES AND MEASURES We used Spearman rank correlation and Pearson product moment correlation (r ) and descriptive statistics to evaluate retrospectively the relationship between the SF-36 PCS score and T25-FW walking speed at baseline and the 2-year changes from baseline. RESULTS Among all 2549 patients from the 3 trials, walking speed and SF-36 PCS score at baseline were significantly correlated (n = 2333; r = 0.48; P < .001). In placebo-treated patients at 2 years, the percentage of change from baseline in walking speed was significantly correlated with the change from baseline in SF-36 PCS score (r = 0.35; P < .001). Significant correlations between the change in SF-36 PCS scores and the percentage of change in walking speed at 2 years also were observed in groups receiving active treatment (r, 0.13-0.28; P ≤ .005). Among placebo-treated patients, 27.5% had a clinically meaningful worsening (≥ 5-point decrease) in SF-36 PCS scores during the 2 years. Walking speed declined by 21.8% in these patients after 2 years, but only by 5.4% in those without worsening of SF-36 PCS scores. CONCLUSIONS AND RELEVANCE In patients with MS, walking speed measured using the T25-FW correlated with SF-36 PCS scores such that a decline in walking speed of 20% to 25% corresponded to a clinically meaningful worsening of SF-36 PCS scores. A 20% to 25% decline in walking speed may be a clinically meaningful threshold for defining worsening using the T25-FW in MS clinical trials and for monitoring patients in clinical settings.
Lymphocytes as an Indicator for Initial Kidney Function: A Single Center Analysis of Outcome after Alemtuzumab or Basiliximab Induction

Alemtuzumab, an anti-CD52 T-cell and B-cell depleting monoclonal antibody, is established for induction therapy in renal transplantation (KTx). We herein provide a comparative analysis between alemtuzumab and basiliximab induction therapy and correlate lymphocyte depletion and recovery with the clinical course after KTx. This is a single center retrospective analysis of 225 patients/consecutive kidney transplantations treated with alemtuzumab for lymphocyte depletion and 205 recipients treated with basiliximab. Mean lymphocyte counts were 22.8 ± 9.41% before Tx and 2.61 ± 3.11% between week 1 and week 3 in the alemtuzumab group and 23.77 ± 10.42% before Tx and 13.92 ± 8.20% in the basiliximab group. Delayed graft function (DGF), cytomegalovirus (CMV) status, and recipient age showed a significant correlation with lymphocyte counts in the alemtuzumab group only. The outcome was read in reference to the velocity of lymphocyte recovery and in comparison to the control group. Lymphocyte counts early after transplantation, following alemtuzumab treatment, could be identified as a predictive factor for kidney function early after transplantation. A detailed analysis of phenotype and function of lymphocytes after alemtuzumab induction together with a correlation with the clinical course is warranted.
New Biomaterials and Regenerative Medicine Strategies in Periodontology, Oral Surgery, Esthetic and Implant Dentistry 2016

1Department of Oral and Maxillofacial Surgery, The University of Michigan Health System, Ann Arbor, MI, USA 2Department of Periodontics and Oral Medicine, The University of Michigan, School of Dentistry, Ann Arbor, MI, USA 3LoB5 Research Unit, School of Dentistry & Research Center for Biomineralization Disorders, Chonnam National University, Gwangju, Republic of Korea 4Department of Medical, Oral and Biotechnological Sciences, University G. D’Annunzio of Chieti-Pescara, Chieti, Italy 5Department of Oral Surgery, Faculty of Medicine, University Federico II of Naples, Naples, Italy
IDtension: a narrative engine for Interactive Drama

choosing the more convenient theories for their application. Furthermore, most theories of narrative are not justification. There are plenty of different theories of narrative, and researchers in digital story telling are in fact computer model, in order to justify specific algorithmic choices. However, this would be an illusion of It is tempting in our current description to start from the theories, and show how these theories are used in the These theories can yield a computer model of narrative. Any attempt to build a system for interactive story telling is guided by a set of theories about what a narrative is. Finally, some experimental results of highly interactive drama are provided. theoretical and computer models are described, in relation with existing narrative theories. In the following, we will first expose the methodology and the approach that guide this research. Then, the author [17], [18]. narrative skill from the author to the user. Note that in other systems for Interactive Drama, the user is a co-act and dialog. So, in the system we are designing, interactive narrative is not about transferring artistic or It is important to note as explained in [16] that this action does not require any artistic skill: any user is able to narrative, through the choice of some actions of characters. where the dialogical nature of the narrative takes a concrete form: the audience can indeed dialog with the someone to help him working " (our translation) [15]. Interactive narrative is an extension of the linear narrative, constructs an " ideal reader " , with whom he imagines the interaction. As stated by Umberto Eco, " a text needs A linear narrative, although unidirectional, is a kind of dialog [14]. The author, in his writing process, position on this debate, which will be developed in an upcoming publication. debate on this topic. Although this is not the focus of this paper, we shall give here a quick overview of our Other claims are conceptual: Interactive narrative would be fundamentally impossible. There is an open computer system, called IDtension, that demonstrates the possibility of combining narrativity and interactivity. Among the " claims of impossibility " , some are at a technical level. The goal of this paper is to exhibit a Our work is situated within the latter attitude. − Claims that interactive narrative or drama is impossible [4], [5] These failures have led to two attitudes: between …
Modified Reduced Look Ahead Orthogonal Matching Pursuit under the Condition of Unknown Sparsity

This paper introduces the basic information about compressive sensing theory and some reconstruction algorithms, such as Orthogonal Matching Pursuit (OMP) and Reduced Look Ahead Orthogonal Matching Pursuit (RLAOMP). RLAOMP performs well in reconstruction, but it needs the exact sparsity. We introduces a modified sparsity adaptive version of RLAOMP, which uses a Modified Sparsity Adaptive Matching Pursuit instead of the Subspace Pursuit to estimate the sparsity. The simulation results showed that it performs well under the condition of unknown sparsity.
Authoring web-based tutoring systems with WETAS

Constraint-based modelling (CBM) is a student modelling technique for intelligent tutoring systems (ITS) that is especially suited to complex, open-ended domains. It is easier to build tutors in such domains using CBM than other common approaches. The authors present WETAS (Web-Enabled Tutor Authoring System), a tutoring engine that facilitates the rapid implementation of ITS in new domains using CBM. They describe the architecture of WETAS and give examples of two domains they have implemented. They also present the results of an evaluation of a tutoring system built using WETAS in a New Zealand school.
Behavioral responses of Drosophila to biogenic levels of carbon dioxide depend on life-stage, sex and olfactory context

SUMMARY Drosophila melanogaster (Meigen) detects and uses many volatiles for its survival. Carbon dioxide (CO2) is detected in adults by a special class of olfactory receptor neurons, expressing the gustatory receptor Gr21a. The behavioral responses to CO2 were investigated in a four-field olfactometer bioassay that is new for Drosophila. We determined (1) whether the sensitivity of this response changes with odor context, and (2) if it depends on sex and life stage. When CO2 was added to ambient air in one field and tested against ambient air in the three other fields, individually observed adults avoided CO2 (0.1-1% above ambient), but did not respond to a low rise of 0.02%. We relate this behavior to measurements of CO2 production in bananas and flies. When 0.02% CO2 was combined with the odor of apple cider vinegar in one field of the olfactometer and tested against ambient air in the three other fields, the addition of CO2 did not affect the attractiveness of apple cider vinegar alone. However, this combination of CO2 and vinegar became repellent when it was tested against vinegar at ambient CO2 concentrations in the three other fields. This `odor background effect' was female-specific, revealing a sexually dimorphic behavior. The new assay allowed us to test larvae under similar conditions and compare their behavior to that of adults. Like adults, they avoided CO2, but with lower sensitivity. Larvae lacking neurons expressing Gr21a lost their avoidance behavior to CO2, but kept their positive response to vinegar odor. Hence, Gr21a-expressing neurons mediate similar behaviors in larvae and adults.
Gender, Social Support, and Resiliency in Suicidal Ideation among U.S. Army Soldiers

Gender, Social Support, and Resiliency in Suicidal Ideation among U.S. Army Soldiers by John F. Ambrose MPH, Drexel University, 2004 BS, Virginia Tech, 2001 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Public Health
Tracking Objects in Color Image Sequences: Application to Football Images

— In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Labeling Adipose-Derived Stem Cells with Hoechst 33342: Usability and Effects on Differentiation Potential and DNA Damage

Adipose-derived stem cells (ASCs) have been extensively studied in the field of stem cell research and possess numerous clinical applications. Cell labeling is an essential component of various experimental protocols and Hoechst 33342 (H33342) represents a cost-effective and easy methodology for live staining. The purpose of this study was to evaluate the labeling of rat ASCs with two different concentrations of H33342 (0.5 μg/mL and 5 μg/mL), with particular regard to usability, interference with cell properties, and potential DNA damage. Hoechst 33342 used at a low concentration of 0.5 μg/mL did not significantly affect cell proliferation, viability, or differentiation potential of the ASCs, nor did it cause any significant DNA damage as measured by the olive tail moment. High concentrations of 5 μg/mL H33342, however, impaired the proliferation and viability of the ASCs, and considerable DNA damage was observed. Undesirable colabeling of unlabeled cocultivated cells was seen in particular with higher concentrations of H33342, independent of varying washing procedures. Hence, H33342 labeling with lower concentrations represents a usable method, which does not affect the tested cell properties. However, the colabeling of adjacent cells is a drawback of the technique.
HIGH CAPACITY DATA HIDING USING SEMI-HEXAGONAL PIXELS VALUE DIFFERENCE

This paper proposes a novel data hiding scheme that employs human visual sensitivity (HVS) to hide a large amount of secret bits into a still image with a high imperceptibility. In this method, the cover image is divided into sub-blocks of semihexagonal shape. The embedding technique is based on pixel value difference (PVD) approach. The semi-hexagonal (SH-PVD) technique enjoys better objective and subjective qualities over the standard PVD methods. It has been found that the capacity of the proposed algorithm is higher than that of the most recent published algorithms. The simulation results give an increased in the capacity ranged between 10348 to 366637 bits. The visual quality of the cover images is of excellent quality. The new algorithm adds no complexity to the existing PVD methods.
Semantic segmentation considering location and co-occurrence in scene

Semantic segmentation is a process that recognizes objects and their regions in images and is a significant challenge in image recognition. Many conventional methods have been proposed, and these studies are expected to be used for many applications such as image retrieval, robot vision for autonomous mobile robots, an automatic driving system for motor vehicles. However, semantic segmentation is one of the most difficult task because of the diversity and appearance of objects in images. This problem causes incorrect recognition not related to an image, or inconsistent with the spatial structure of the real world. We focus on understanding the scene in an image. For example, objects like “car” and “buildings” are likely to exist in the scene of street. On the other hand, those are not likely to exist in the scene of prairie. Besides, we expect that location and co-occurrence of objects are efficient information to recognize images. The region of “sky” is likely to exist in the upper part of them. In addition, “car” and “road” are likely to exist in the same image. This paper presents a method of semantic segmentation considering location and co-occurrence in the natural outdoor scene. Before recognizing objects in images, we classify them in terms of scene and execute pixel-wise object recognition. Then, we consider the location and co-occurrence of objects in the scene. Experimental results show that our proposed method is effective compared to other methods not considering scene information.
Effects of Visualizing Missing Data: An Empirical Evaluation

This paper presents an empirical study that evaluates the effects of visualizing missing data on decision-making tasks. A comparison between three visualization techniques: (1) emptiness, (2) fuzziness, and (3) emptiness plus explanation, revealed that the latter technique induced significantly higher degree of decision-confidence than the visualization technique fuzziness. Moreover, emptiness plus explanation yield the highest number of risky choices of the three. This result suggests that uncertainty visualization techniques affect the decision-maker and the decisionconfidence. Additionally, the results indicate a possible relation between the degree of decision-confidence and the decision-maker's displayed risk behavior.
Which Monetary Regime for Europe? A Quantitative Evaluation

There is a large and growing literature on the benefits and costs of moving to a single currency in Europe. Much of the literature is theoretical in nature with very little empirical evaluation of the magnitudes of effects. This paper places some quantitative magnitudes on the scale of some issues in European monetary integration. It uses the European version of the MSG2 multi-country model to evaluate the variance of a number of European variables in the face of shocks to money markets, fiscal policy and total factor productivity, under three alternative European monetary regimes: the current European monetary system; a European monetary Union with a European central bank setting monetary policy; and a system of floating exchange rates within Europe. For each type of shock we consider the adjustment to global shocks, European wide shocks, shocks in Germany and shocks in Europe excluding Germany. Within the constraints of each monetary regime we allow any unconstrained monetary instruments to be set either cooperatively between European countries or non-cooperatively where each country is allowed to set their policy instruments to maximize an objective function. We find that no monetary regime consistently dominates for all shocks and regimes are ranked differently across European economies for the same shock. Abstracting from the serious question of policy credibility, this suggests that maintaining some flexibility in the setting of monetary policy in countries could potentially be invaluable to facilitate smooth adjustment to global, regional and country specific shocks. (This abstract was borrowed from another version of this item.)
Outlier based Predictors for Health Insurance Fraud Detection within

This paper describes an effective method of outlier based predictors for health insurance fraud detection that identifies suspicious behavior of health care providers. Fraud and abuse on medical claims became a major concern for health insurance companies last decades. Estimates made for the studied U.S. Medicaid health insurance program is that up to 10% of the claims are fraudulent. Unsupervised data mining techniques such as outlier detection are suggested to be an effective predictors for fraud detection and should be used to support the initiations of audits. A method, based on comparative research, fraud cases and literature study has been proposed. We evaluated the method, by applying the method in a real life case study, were behavioral metrics were designed and 14 analytic experiments were built using outlier detection. The analysis ran on dental claim data and showed promising results. The proposed methodology enabled successful identification of fraudulent activity in several cases; however linking these identified incidents with irrefutable de jure fraud proved to be a difficult process. From 17 top suspicions analyzed, we reported eventually 12 of those to officials, a precision rate of approximately 71%. In the two interviews conducted with Medicaid Fraud Experts, experiences were gained on requirements for the design of the analytics and an effective implementation of the method. We found that outlier based predictors are not likely to succeed as fraud classification technology, though it explored an important role as decision supportive technology for resource allocation of fraud audits. keywords: Health Insurance, Outlier based Analytics, Fraud and Abuse, Electronic Fraud Detection, Outlier Detection
The Applicability of CALL in Teaching EFL Based on Sudanese Universities Teachers’ Attitudes

This research article tackles “the applicability of CALL in teaching EFL based on Sudanese EFL teachers’ attitudes”. The researchers utilized quantitative and experimental methods using two data gathering tools for the study in question: The first is the questionnaire is administered to (50) different EFL Sudanese universities and colleges teachers, andsecond one is pre and post-tests given to an experimental group consisting of (30) students of English in the second year selected from the Department of English in the Faculty Education at the University of Kassala; they were taught reading comprehension lessons through the use of computers. The data obtained from the questionnaire and the two have been computationally processed with the SPSS program to check the truth hypotheses, to reflect the Sudanese EFL teachers’ perceptions towards the integration CALL in teaching EFL and to see to what an extent there is a significant impact integration of CALL on the students’ performance. Finally, Sudanese EFL teachers through this study recommend strongly the ultimate integration of CALL in teaching EFL.