Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of occupational exposures in a general population: comparison of different methods.

OBJECTIVES: To evaluate the relative merits of job specific questionnaires and various alternative assessment methods of occupational exposures often used in general population studies. METHODS: Subjects were participants in a hospital based case-control study of risk factors for male infertility. Estimates of exposure to organic solvents and chromium, based on job specific questionnaires, generic questionnaires, self reports of exposure, an external job exposure matrix (JEM), and a population specific JEM were compared with passive diffuse dosimeter results and measurements in urine. Urine samples from the end of the shift were analysed for metabolites of toluene, xylene, several glycol ethers, trichloroethylene, and chromium. Passive dosimeter date, metabolites of specific solvents, and urinary chromium concentrations were available for 89, 267, and 156 subjects, respectively. The alternative methods and measurements in urine were compared by means of the Cohen's kappa statistic and by computing the positive predictive value, sensitivity, and specificity of the alternative methods against measurements in urine. RESULTS: Passive dosimeter results indicated that exposure classifications with job specific questionnaire information could discriminate between high and low exposures. The kappa coefficients were < 0.4, so agreement between the various methods and measurements in urine was poor. Sensitivity of the methods ranged from 0.21 to 0.85, whereas specificity ranged from 0.34 to 0.94. Positive predictive values ranged from 0.19 to 0.58, with the highest values for job specific questionnaires. CONCLUSIONS: The results indicate that the implementation of job specific questionnaires in a general population study might be worth the extra expense it entails, bearing in mind the paramount importance of avoiding false positive exposure estimates when exposure prevalence is low.
The distribution of carbapenem‐ and colistin‐resistance in Gram‐negative bacteria from the Tamil Nadu region in India

Purpose. The occurrence of carbapenem‐ and colistin‐resistance among Gram‐negative bacteria is increasing worldwide. The aim of this study was to understand the distribution of carbapenem‐ and colistin‐resistance in two areas in Tamil Nadu, India. Methodology. The clinical isolates (n=89) used in this study were collected from two diagnostic centres in Tamil Nadu, India. The bacterial isolates were screened for meropenem‐ and colistin‐resistance. Further, resistance genes blaNDM‐1, blaOXA‐48‐like, blaIMP, blaVIM, blaKPC, mcr‐1 and mcr‐2 and integrons were studied. The synergistic effect of meropenem in combination with colistin was assessed. Results. A total of 89 bacterial isolates were studied which included Escherichia coli (n=43), Klebsiella pneumoniae (n=18), Pseudomonas aeruginosa (n=10), Enterobacter cloacae (n=6), Acinetobacter baumannii (n=5), Klebsiella oxytoca (n=4), Proteus mirabilis (n=2) and Salmonella paratyphi (n=1). MIC testing showed that 58/89 (65%) and 29/89 (32%) isolates were resistant to meropenem and colistin, respectively, whereas 27/89 (30%) isolates were resistant to both antibiotics. Escherichia coli, K. pneumoniae, K. oxytoca, Pseudomonas aeruginosa, and Enterobacter cloacae isolates were blaNDM‐1‐positive (n=20). Some strains of Escherichia coli, K. pneumoniae and K. oxytoca were blaOXA‐181‐positive (n=4). Class 1, 2 and 3 integrons were found in 24, 20 and 3 isolates, respectively. Nine NDM‐1‐positive Escherichia coli strains could transfer carbapenem resistance via plasmids to susceptible Escherichia coli AB1157. Meropenem and colistin showed synergy in 10/20 (50%) isolates by 24 h time‐kill studies. Conclusion. Our results highlight the distribution of carbapenem‐ and colistin‐resistance in Gram‐negative bacteria isolated from the Tamil Nadu region in South India.
Partial Escape Analysis and Scalar Replacement for Java

Escape Analysis allows a compiler to determine whether an object is accessible outside the allocating method or thread. This information is used to perform optimizations such as Scalar Replacement, Stack Allocation and Lock Elision, allowing modern dynamic compilers to remove some of the abstractions introduced by advanced programming models. The all-or-nothing approach taken by most Escape Analysis algorithms prevents all these optimizations as soon as there is one branch where the object escapes, no matter how unlikely this branch is at runtime. This paper presents a new, practical algorithm that performs control flow sensitive Partial Escape Analysis in a dynamic Java compiler. It allows Escape Analysis, Scalar Replacement and Lock Elision to be performed on individual branches. We implemented the algorithm on top of Graal, an open-source Java just-in-time compiler, and it performs well on a diverse set of benchmarks. In this paper, we evaluate the effect of Partial Escape Analysis on the DaCapo, ScalaDaCapo and SpecJBB2005 benchmarks, in terms of run-time, number and size of allocations and number of monitor operations. It performs particularly well in situations with additional levels of abstraction, such as code generated by the Scala compiler. It reduces the amount of allocated memory by up to 58.5%, and improves performance by up to 33%.
Enhancing personalized ranking quality through multidimensional modeling of inter-item competition

This paper presents MAPS — a personalized Multi-Attribute Probabilistic Selection framework — to estimate the probability of an item being a user's best choice and rank the items accordingly. The MAPS framework makes three original contributions in this paper. First, we capture the inter-attribute tradeoff by a visual angle model which maps multi-attribute items into points (stars) in a multidimensional space (sky). Second, we model the inter-item competition using the dominating areas of the stars. Third, we capture the user's personal preferences by a density function learned from his/her history. The MAPS framework carefully combines all three factors to estimate the probability of an item being a user's best choice, and produces a personalized ranking accordingly. We evaluate the accuracy of MAPS through extensive simulations. The results show that MAPS significantly outperforms existing multi-attribute ranking algorithms.
Logistic Regression Analysis to Determine the Significant Factors Associated with Substance Abuse in School-Aged Children

Substance abuse is the overindulgence in and dependence on a drug or chemical leading to detrimental effects on the individual’s health and the welfare of those surrounding him or her. Logistic regression analysis is an important tool used in the analysis of the relationship between various explanatory variables and nominal response variables. The objective of this study is to use this statistical method to determine the factors which are considered to be significant contributors to the use or abuse of substances in school-aged children and also determine what measures can be implemented to minimize their effect. The logistic regression model was used to build models for the three main types of substances used in this study; Tobacco, Alcohol and Drugs and this facilitated the identification of the significant factors which seem to influence their use in children.
VIRO: A virtual routing method for eliminating dead end in Opportunistic Mobile Social Network

Opportunistic Mobile Social Networks (MSNs) as a kind of social network in which nodes are opportunistically connected. Many data routing strategies have been proposed for opportunistic MSNs. Most of them apply a utility for relay selection that a node with a higher utility value is selected as relay. However, such utility-based routing strategies run into dead end problem in which the data is stuck into a node with local maximal utility value. In this paper, we propose a virtual routing method named VIRO, which exerts conformal mapping to convert the local topology of dead end into a virtual geometric map to guarantee data dissemination to the next relay. We first convert the utility into geometric planner, and then conduct the discrete Ricci Flow bypass the gap between the dead end and next relay. Extensive experiment results suggest VIRO can reduce the ratio of dead end effectively so that the data delivery ratio is enhanced up to 42% by increasing only a slight amount of delay and cost.
Robust multiplicative watermarking technique with Maximum Likelihood detector

In this paper, a new multiplicative semi-blind image-adaptive watermarking system has been presented, which exploits human visual model for adapting the watermark data to local properties of the host image. To have a better robustness, the proposed algorithm is implemented on the low-frequency coefficients of the wavelet transform. Moreover, regarding invisibility of the algorithm, the strength factor which controls the watermark power is optimally selected. To extract the watermark data, the Maximum Likelihood (ML) estimator is used. Experimental results confirm the imperceptibility of the proposed method and its high robustness against various attacks such as JPEG compression, noise addition, and filtering compared to similar methods reported so far.
Topic-Focused Multi-Document Summarization Using an Approximate Oracle Score

We consider the problem of producing a multi-document summary given a collection of documents. Since most successful methods of multi-document summarization are still largely extractive, in this paper, we explore just how well an extractive method can perform. We introduce an "oracle" score, based on the probability distribution of unigrams in human summaries. We then demonstrate that with the oracle score, we can generate extracts which score, on average, better than the human summaries, when evaluated with ROUGE. In addition, we introduce an approximation to the oracle score which produces a system with the best known performance for the 2005 Document Understanding Conference (DUC) evaluation.
A comparison of features for speech, music discrimination

Several approaches have previously been taken to the problem of discriminating between speech and music signals. These have used different features as the input to the classifier and have tested and trained on different material. In this paper we examine the discrimination achieved by several different features using common training and test sets and the same classifier. The database assembled for these tests includes speech from thirteen languages and music from all over the world. In each case the distributions in the feature space were modelled by a Gaussian mixture model. Experiments were carried out on four types of feature, amplitude, cepstra, pitch and zero-crossings. In each case the derivative of the feature was also used and found to improve performance. The best performance resulted from using the cepstra and delta cepstra which gave an equal error rate (EER) of 1.28. This was closely followed by normalised amplitude and delta amplitude. This however used a much less complex model. The pitch and delta pitch gave an EER of 4% which was better than the zero-crossing which produced an EER of 6%.
Urinary Protein Biomarker Panel for the Detection of Recurrent Bladder Cancer

Background: Up to 70% of patients with non–muscle-invasive bladder cancer (NMIBC) experience disease recurrence, making it one of the most prevalent cancers in the United States. The purpose of this study was to test the performance of a multiplex urinary biomarker assay for the monitoring of voided urine for recurrent bladder cancer. Methods: This retrospective, multicenter study included a total of 125 subjects with a history of bladder cancer. Voided urine specimens were collected before procedure from these subjects (53 with confirmed tumor recurrence and 72 with confirmed non-tumor recurrence) for analysis. A prediction rule generated from the performance characteristics of 10 single biomarkers (IL8, MMP9, MMP10, SERPINA1, VEGFA, ANG, CA9, APOE, SERPINE1, and SDC1) was measured using ELISA. The diagnostic performance of the biomarker panel was assessed using receiver operator curves (ROC) and descriptive statistical values (e.g., sensitivity and specificity). Results: The combination of all 10 biomarkers outperformed any single biomarker with a calculated AUROC for the diagnostic panel of 0.904 [95% confidence interval (CI), 0.853–0.956]. The multiplex assay achieved an overall sensitivity of 79% and specificity of 88% for recurrent bladder cancer and significantly outperformed the Urovysion cytogenetic assay (sensitivity 42%, specificity 94%) and voided urinary cytology (sensitivity 33%, specificity 90%). Conclusions: A diagnostic panel of 10 urinary biomarkers that accurately detects primary bladder cancer also performs well for the detection of recurrent bladder cancer. Impact: The identification of a reliable urine-based surveillance and detection assay would be of benefit to both patients and the healthcare system. Cancer Epidemiol Biomarkers Prev; 23(7); 1340–5. ©2014 AACR.
The influence of CYP2C9 and VKORC1 gene polymorphisms on optimal warfarin doses after heart valve replacement.

UNLABELLED A clinical effect of warfarin depends on highly polymorphic drug-metabolizing (CYP2C9) and drug-target (VKORC1) enzymes. The objective of this study was to investigate the impact of CYP2C9*2, CYP2C9*3, and VKORC1 (G-1639A) polymorphisms on the variability of warfarin dosage requirements in Lithuanian patients after heart valve replacement. MATERIALS AND METHODS The study included 83 patients with a mean age of 65.2 years (SD, 13.31) after heart valve replacement with an achieved stable international normalized ratio of 2-3.5. The restriction fragment length polymorphism method was used to identify polymorphisms of VKORC1 and CYP2C9. RESULTS Daily warfarin dosage significantly correlated with weight (r=0.4087) and height (r=0.3883) of the patients. Patients younger than 60 years required significantly higher daily warfarin dosages than older patients. Two-thirds (66.3%) of the patients had the wild-type (WT) CYP2C9*1/*1 genotype; 38.6% and 54.2% of the patients had WT VKORC1 (G/G) and VKORC1 (G/A) genotypes, respectively. WT CYP2C9*1/*1 genotype was associated with a higher daily warfarin dosage (5.84 mg [SD, 2.84]) as compared to other CYP2C9 genotypes. Carriers of WT VKORC1 (G/G) required a higher warfarin dose as compared to (A/A) carriers (6.20±2.78 mg and 3.75±1.40 mg, respectively; P=0.04). Patients having CYP2C9*1/*1 or 1/*2 in combination with VKORC1 (G/G) or (G/A) genotypes required the highest daily warfarin dosage in comparison to other combinations of genotypes. CONCLUSIONS The Lithuanian study sample is characterized by high a frequency (92.8%) of VKORC1 G/G and G/A genotypes that determines a higher warfarin-loading dose. Analysis of combined CYP2C9 and VKORC1 gene variants allows the prediction of warfarin dosage. These results can be used to individualize treatment with warfarin in the field of heart surgery in Lithuania.
Functional programming for dynamic and large data with self-adjusting computation

Combining type theory, language design, and empirical work, we present techniques for computing with large and dynamically changing datasets. Based on lambda calculus, our techniques are suitable for expressing a diverse set of algorithms on large datasets and, via self-adjusting computation, enable computations to respond automatically to changes in their data. To improve the scalability of self-adjusting computation, we present a type system for precise dependency tracking that minimizes the time and space for storing dependency metadata. The type system eliminates an important assumption of prior work that can lead to recording spurious dependencies. We present a type-directed translation algorithm that generates correct self-adjusting programs without relying on this assumption. We then show a probabilistic-chunking technique to further decrease space usage by controlling the fundamental space-time tradeoff in self-adjusting computation. We implement and evaluate these techniques, showing promising results on challenging benchmarks involving large graphs.
State-of-art neuroanatomical target analysis of high-definition and conventional tDCS montages used for migraine and pain control

Although transcranial direct current stimulation (tDCS) studies promise to modulate cortical regions associated with pain, the electric current produced usually spreads beyond the area of the electrodes’ placement. Using a forward-model analysis, this study compared the neuroanatomic location and strength of the predicted electric current peaks, at cortical and subcortical levels, induced by conventional and High-Definition-tDCS (HD-tDCS) montages developed for migraine and other chronic pain disorders. The electrodes were positioned in accordance with the 10–20 or 10–10 electroencephalogram (EEG) landmarks: motor cortex-supraorbital (M1-SO, anode and cathode over C3 and Fp2, respectively), dorsolateral prefrontal cortex (PFC) bilateral (DLPFC, anode over F3, cathode over F4), vertex-occipital cortex (anode over Cz and cathode over Oz), HD-tDCS 4 × 1 (one anode on C3, and four cathodes over Cz, F3, T7, and P3) and HD-tDCS 2 × 2 (two anodes over C3/C5 and two cathodes over FC3/FC5). M1-SO produced a large current flow in the PFC. Peaks of current flow also occurred in deeper brain structures, such as the cingulate cortex, insula, thalamus and brainstem. The same structures received significant amount of current with Cz-Oz and DLPFC tDCS. However, there were differences in the current flow to outer cortical regions. The visual cortex, cingulate and thalamus received the majority of the current flow with the Cz-Oz, while the anterior parts of the superior and middle frontal gyri displayed an intense amount of current with DLPFC montage. HD-tDCS montages enhanced the focality, producing peaks of current in subcortical areas at negligible levels. This study provides novel information regarding the neuroanatomical distribution and strength of the electric current using several tDCS montages applied for migraine and pain control. Such information may help clinicians and researchers in deciding the most appropriate tDCS montage to treat each pain disorder.
Avoidance of harvesting and sampling artefacts in hydraulic analyses: a protocol tested on Malus domestica

A prerequisite for reliable hydraulic measurements is an accurate collection of the plant material. Thereby, the native hydraulic state of the sample has to be preserved during harvesting (i.e., cutting the plant or plant parts) and preparation (i.e., excising the target section). This is particularly difficult when harvesting has to be done under transpiring conditions. In this article, we present a harvesting and sampling protocol designed for hydraulic measurements on Malus domestica Borkh. and checked for possible sampling artefacts. To test for artefacts, we analysed the percentage loss of hydraulic conductivity, maximum specific conductivity and water contents of bark and wood of branches, taking into account conduit length, time of day of harvesting, different shoot ages and seasonal effects. Our results prove that use of appropriate protocols can avoid artefactual embolization or refilling even when the xylem is under tension at harvest. The presented protocol was developed for Malus but may also be applied for other angiosperms with similar anatomy and refilling characteristics.
The Healthy Eating Index and the Alternate Healthy Eating Index as predictors of 10-year CHD risk in Cuban Americans with and without type 2 diabetes

Abstract Objective To examine the relationship between dietary patterns, as measured by the Healthy Eating Index (HEI) and the Alternate Healthy Eating Index (AHEI), and 10-year predicted CHD risk in Cuban Americans with and without type 2 diabetes (T2D). Design In a cross-sectional study participants were selected from two randomly generated mailing lists of individuals with and without T2D. HEI and AHEI scores were calculated from a self-reported FFQ. CHD risk was determined using the 10-year CHD risk calculator of the Adult Treatment Panel III. Setting Miami Dade and Broward Counties, FL, USA. Subjects Cuban Americans (n 358) aged ≥30 years. Results Participants with T2D had a higher waist circumference (P = 0·001) and 10-year CHD risk score (P = 0·008) compared with those without T2D. Participants without T2D had a higher energy intake (P = 0·034), total blood cholesterol (P = 0·007), HDL cholesterol (P = 0·001) and HEI score (P = 0·006) compared with participants with T2D. AHEI score was a significant predictor of 10-year CHD risk (F(1,351) = 4·44, P = 0·036). An association between AHEI and 10-year CHD risk was found only for participants with T2D (β = −0·244, se = 0·049, P = 0·001). Conclusion The present study showed that only participants with T2D with significantly higher AHEI scores had lower scores for 10-year predicted CHD risk. No association was found between HEI score and CHD risk among Cuban Americans. Individuals with T2D are advised to follow the AHEI dietary pattern.
Dynamic adaptive streaming over HTTP --: standards and design principles

In this paper, we provide some insight and background into the Dynamic Adaptive Streaming over HTTP (DASH) specifications as available from 3GPP and in draft version also from MPEG. Specifically, the 3GPP version provides a normative description of a Media Presentation, the formats of a Segment, and the delivery protocol. In addition, it adds an informative description on how a DASH Client may use the provided information to establish a streaming service for the user. The solution supports different service types (e.g., On-Demand, Live, Time-Shift Viewing), different features (e.g., adaptive bitrate switching, multiple language support, ad insertion, trick modes, DRM) and different deployment options. Design principles and examples are provided.
Recent Advances: the Cytochrome P450 Enzymes

Successful application of information on cytochrome P450 to prevent drug interactions and improve the therapeutic risk: benefit ratio can occur only if we know which enzyme is responsible for the metabolism of a drug. Until recently, this information was not usually available when new drugs reached the market. It is not enough to know the fraction of a dose metabolized versus excreted unchanged or the metabolic pathways by which a compound is degraded. Studies conducted during drug development must identify the enzyme or enzymes involved in the metabolism of new drugs. In addition, the ability of new drugs to inhibit or induce the activity of the key P450 enzymes must be known if we are to take full advantage of our current knowledge of how the cytochrome P450 system works.
Designing a receptionist robot: Effect of voice and appearance on anthropomorphism

Robots are possible candidates for performing tasks as helpers in activities of daily living in the future: working as a receptionist is one possible employment. However, the way the receptionist robot should appear, sound and behave needs to be investigated carefully, in order to design a robot which is accepted and perceived in a positive way by common users. This paper describes a study on anthropomorphism of a receptionist robot made for Brazilian people depending on the appearance and on the voice of the receptionist. This experiment was preceded by a preliminary survey about expectation of people regarding receptionists. The main experiment consisted in having Brazilian people interacting with a conversational agent and with a humanoid robot through a video conference. The two receptionists are not only different in physical appearance, but in the sound of the voice, too, which can be either human-like or robotic sound. The two receptionists gave indications to the participants to reach rooms where they could evaluate the receptionists through questionnaires concerning anthropomorphism and uncanniness among other concepts. The results gathered from both experiments provide useful hints to design a receptionist robot.