Miracle-dz/UniFAR-FTUs huggingface dataset:
Exposure to Polycyclic Aromatic Hydrocarbons Among Never Smokers in Golestan Province, Iran, an Area of High Incidence of Esophageal Cancer – a Cross-Sectional Study with Repeated Measurement of Urinary 1-OHPG in Two Seasons

Studies have suggested a possible role of polycyclic aromatic hydrocarbons (PAHs) in the etiology of esophageal cancer in Golestan Province, Iran, where incidence of this cancer is very high. In order to investigate the patterns of non-smoking related exposure to PAHs in Golestan, we conducted a cross-sectional study collecting questionnaire data, genotyping polymorphisms related to PAH metabolism, and measuring levels of 1-hydroxypyrene glucuronide (1-OHPG), a PAH metabolite, in urine samples collected in two seasons from the same group of 111 randomly selected never-smoking women. Beta-coefficients for correlations between 1-OHPG as dependent variable and other variables were calculated using linear regression models. The creatinine-adjusted 1-OHPG levels in both winter and summer samples were approximately 110 μmol/molCr (P for seasonal difference = 0.40). In winter, red meat intake (β = 0.208; P = 0.03), processed meat intake (β = 0.218; P = 0.02), and GSTT1-02 polymorphism (“null” genotype: β = 0.228; P = 0.02) showed associations with 1-OHPG levels, while CYP1B1-07 polymorphism (GG versus AA + GA genotypes: β = –0.256; P = 0.008) showed an inverse association. In summer, making bread at home (> weekly versus never: β = 0.203; P = 0.04), second-hand smoke (exposure to ≥3 cigarettes versus no exposure: β = 0.254; P = 0.01), and GSTM1-02 “null” genotype (β = 0.198; P = 0.04) showed associations with 1-OHPG levels, but GSTP1-02 polymorphism (CT + TT versus CC: β = –0.218; P = 0.03) showed an inverse association. This study confirms high exposure of the general population in Golestan to PAHs and suggests that certain foods, cooking methods, and genetic polymorphisms increase exposure to PAHs.
PERFORMANCE OF REFERENCE EVAPOTRANSPIRATION MODELS USING TEMPERATURE DATA

The use of reference evapotranspiration (ETo) models that require a lower number of meteorological variables are simpler, more operational and lower cost alternatives for farmers. This work evaluated the performance of ETo estimated from the maximum and minimum air temperature data using the Hargreaves and reduced-set FAO Penman-Monteith (FAO-PM) equations on the daily scale and with annual and seasonal adjustment for 5 meteorological stations of the Jequitinhonha River Valley. The values obtained were compared with the full set FAO-PM standard method. The correlation (r), determination (R2) and efficiency (E) coefficients; the agreement (d) and performance (c) indexes; and the standard error of estimate (SEE). The results showed that both models, Hargreaves and reduced-set FAO-PM, even without adjustment, may be a viable recommendation for irrigation management. The seasonal adjustment provided an improvement in the performance of the Hargreaves method and the annual adjustment provided an improvement in the FAO PenmanMonteith method with missing data.
MAP decoder design for Distributed Video Coding in error prone wireless channels

In this paper MAP (maximum a posteriori) algorithm in the turbo decoder has been modified to use with the distributed video coding (DVC) decoder, when the parity bit stream is transmitted over a noisy/fading channel. The proposed modification allows independent probability distributions for the systematic and parity components at the input to the turbo decoder. The designed MAP decoder has been tested with an AWGN and with a WCDMA channel.
A Comparison of Donor-Acceptor Pairs for Genetically Encoded FRET Sensors: Application to the Epac cAMP Sensor as an Example

We recently reported on CFP-Epac-YFP, an Epac-based single polypeptide FRET reporter to resolve cAMP levels in living cells. In this study, we compared and optimized the fluorescent protein donor/acceptor pairs for use in biosensors such as CFP-Epac-YFP. Our strategy was to prepare a wide range of constructs consisting of different donor and acceptor fluorescent proteins separated by a short linker. Constructs were expressed in HEK293 cells and tested for FRET and other relevant properties. The most promising pairs were subsequently used in an attempt to improve the FRET span of the Epac-based cAMP sensor. The results show significant albeit not perfect correlation between performance in the spacer construct and in the Epac sensor. Finally, this strategy enabled us to identify improved sensors both for detection by sensitized emission and by fluorescent lifetime imaging. The present overview should be helpful in guiding development of future FRET sensors.
Precursors of CD3+CD4+CD8+ cells in the human thymus are defined by expression of CD34. Delineation of early events in human thymic development

Studies of the most immature T cell progenitors in the human thymus have been hampered by the lack of markers and assays that define these cells. In this report we used a novel human fetal thymic organ culture system to determine the potential of T cell precursors isolated from human postnatal thymus, to differentiate into CD3+ thymocytes, and to investigate early stages of human T cell development. It was found that thymocytes that lack the markers CD3, CD4, and CD8 (triple negative [TN]) can differentiate in an allogeneic organotypic thymic culture. The capacity of TN thymocytes to differentiate was exclusively confined to the CD34+ population. CD34- TN thymocytes failed to differentiate in this system. In contrast, cloned lines of CD3- thymocytes could only be established from CD34- TN thymocytes. Five subsets of CD3- thymocytes were found with the following phenotype: CD1-TN, CD1+TN, CD1+CD4+CD8-, CD1+CD4+CD8 alpha+ beta-, and CD1+CD4+CD8 alpha beta+. These subpopulations expressed decreasing levels of CD34. The CD1-CD3- population expressed the highest levels of CD34 supporting the notion that this population is the most immature T cell precursor in the thymus, whereas the CD1+CD4+CD8 alpha+ beta+ which did not express CD34 seems to be the most mature of these CD3- populations. This notion is supported by the observations that CD34+ cells isolated from fetal liver, which differentiated into T cells in a FTOC, developed into CD3+ cells via CD1- and CD4+CD8- intermediates. Based on these data, we present a model of early stages in human intrathymic development.
Transductive learning with nonlinear flexibility using trace norm minimization and fixed point continuation

In this paper, the affine Schatten p-norm minimisation problem with one-side inequality constraints is formulated. Through the optimisation process, many trace norm minimisation methods just achieve some degree of denoising. Contrarily, flexible nonlinearity relationship is established with this relaxed formulation, and thus existing traditional theories can be successfully applied for many real data-sets in machine learning, particularly for those violating the linearity assumption. We show that our new objective function is convex, and its global minimum can be obtained by a more general form of the Fixed-Point Continuation framework with almost the same computational cost. Experiments show that our algorithm is generally competitive among the state-of-the-art on widely used data-sets.
Applications of the synthesized iron nanoparticles in the degradation of p-nitrophenol

p-nitrophenol (4-NP) is a common raw material in the industrial production of many valuable sub-stances. With the rapid development of chemical industry, the production of 4-NP has increased substantially. However, due to its characteristic toxicity, p-nitrophenol inevitably causes pollution to the environment during its synthesis and usage. In this paper, sodium borohydride (NaBH 4 ) and ferric chloride (FeCl 3 ·6H 2 O) were used as raw materials to prepare iron nanoparticles by liquid phase reduction technique, and their performance in 4-NP pollutant degradation was investigated. The experimental results showed that the iron nanoparticles presented excellent degradation performance for 4-NP. When the concentration of 4-NP was 15 mg/L, only 0.25 g/L of iron nanoparticles degraded more than 74% of 4-NP in 1 h.
Virtual platforms for mixed time-criticality applications : the CoMPSoC architecture and SDF3 design flow

Systems-on-Chip (SoC) complexity increases as a growing number of applications are integrated and executed on contemporary systems. These applications consist of communicating tasks mapped on heterogeneous multi-processor platforms with distributed memory hierarchies that strike a good balance between performance, cost, power consumption and flexibility [1], [2]. Complexity is further increased by an increasing number of use-cases, which are different combinations of concurrently running applications. The applications have mixed time-criticality, which is a mix between firm, soft, and no real-time requirements. Firm real-time requirements must always be satisfied to prevent unacceptable output quality loss, while occasional failures to meet soft requirements can be tolerated. Lastly, non-real-time applications do not have welldefined timing requirements, but must still be responsive. Applications from different domains and that have different time criticalities use different design and verification methods. After applications are developed, the verification process begins. Verification of real-time requirements is traditionally performed using formal analysis, simulation, or a combination of the two. Firm real-time applications demand rigorous formal verification, since their requirements must always be met. In contrast, soft real-time applications are often verified by simulation for a large set of inputs, as they are often dynamic by nature and difficult to verify by formal methods in a costeffective manner. To reduce cost, platform resources, such as processors, interconnect, and memories, are shared between applications. However, resource sharing causes interference between applications, making their temporal behaviors inter-dependent. This results in three problems with respect to system design, verification, and integration. Firstly, accurate system-level simulation and several approaches to formal analysis in complex SoCs are infeasible, because of the state-space explosion resulting from the many use-cases, application inputs, and resources states. Secondly, use-case verification becomes a circular process that must be repeated if an application is added, removed, or modified [3]. Thirdly, it is difficult to support various automatic analysis and design flows. As a result, the integration and verification process is a dominant part of SoC development, both in terms of time and money [3]. The CoMPSoC platform [4] addresses these problems by executing each application in an independent virtual platform, and by using the SDF design flow [5] that automatically analyses firm real-time applications and maps them on a virtual platform. The CoMPSoC virtualization technology Fig. 1. CoMPSoC architecture and SDF design flow.
Semideﬁnite and Spectral Relaxations for Multi-Label Classiﬁcation

In this paper, we address the problem of multi-label classiﬁcation. We consider linear classiﬁers and propose to learn a prior over the space of labels to directly leverage the performance of such methods. This prior takes the form of a quadratic function of the labels and permits to encode both attractive and repulsive relations between labels. We cast this problem as a structured prediction one aiming at optimizing either the accuracies of the predictors or the F 1 -score. This leads to an optimization problem closely related to the max-cut problem, which naturally leads to semideﬁnite and spectral relaxations. We show on standard datasets how such a general prior can improve the performances of multi-label techniques.
Emotion Recognition in Music Signal using AANN and SVM

main objective of this work is to develop a music emotion recognition technique using Mel frequency cepstral coefficient (MFCC), Auto associative neural network (AANN) and support vector machine (SVM). The emotions taken are anger, happy, sad, fear, and neutral. Music database is collected at 44.1 KHz with 16 bits per sample from various movies and websites related to music. For each emotion 15 music signals are recorded and each one is by 15sec duration. The proposed technique of music emotion recognition (MER) is done in two phases such, i) Feature extraction, and ii) Classification. Initially, music signal is given to feature extraction phase to extract MFCC features. Second the extracted features are given to Auto associative neural networks (AANN) and support vector machine (SVM) classifiers to categorize the emotions and finally their performance are compared. The experimental results show that MFCC with AANN classifier achieves a recognition rate of about 94.4% and with SVM classifier of about 85.0% thus outperforms SVM classifier.
Is work organisation associated with work status 3 months after injury? Results from a case-control study of New Zealand workers.

BACKGROUND Little empirical examination of the relationship between work organisational factors and return to work following injury has been undertaken despite the growing recognition of examining broader multi-dimensional contexts for recovery following injury. OBJECTIVE To explore relationships between pre-injury work organisational factors and work status (working/work absent) 3-month after injury among people employed prior to injury. METHODS Cases (work absent) and controls (working), selected from a larger study of injury outcomes according to reported work status 3-month after injury, completed a postal questionnaire. Work organisational factors were compared between cases and controls using univariate and multivariable analyses. RESULTS One hundred and twelve participants completed the questionnaire (44 cases; 68 controls). Of 11 work organisation factors examined, organisational size was the only explanatory variable significantly associated with work status in the multivariable model. Higher odds of work absence were found in small (< 50 employees) (OR 5.6) and large (> 500 employees) (OR 7.2) workplaces, compared with medium-sized (50-500 employees) organisations. CONCLUSIONS Variations in post-injury work patterns among those working pre-injury may be partly explained by organisation size. Future research examining work status following injury should examine the influence of work organisational factors in larger studies.
Fluorescent tracer evaluation of chemical protective clothing during pesticide applications in central Florida citrus groves.

Chemical protective clothing (CPC) is often recommended as a method of exposure mitigation among pesticide applicators. This study evaluated four CPC regimens (cotton work shirts and work pants, cotton/polyester coveralls, and two non-woven garments) during 33 airblast applications of the organophosphorus insecticide ethion in central Florida citrus groves. CPC performance was determined by measurement of fluorescent tracer deposition on skin surfaces beneath garments with a video imaging analysis instrument (VITAE system), and by alpha-cellulose patches placed outside and beneath the garments. Non-woven coveralls allowed significantly greater exposure than did traditional woven garments, primarily because of design factors (e.g., large sleeve and neck openings). The greatest exposure occurred on the forearms beneath the non-woven garments. Fabric penetration was detected for all test garments; 5% to 7% of the ethion measured outside the garments was found beneath the garments. The clothing materials tested were not chemically resistant under these field conditions. Exposurepathways that would probably be undetected by the patch technique were characterized effectively with fluorescent tracers and video imaging analysis. However, the patch technique was more sensitive in detecting fabric penetration. CPC garments have been improved since this study was conducted, but performance testing under field conditions is not widespread. Workers conducting airblast applications would be better protected by closed cab systems or any technology that places an effective barrier between the worker and the pesticide spray.
Block-Based Salient Region Detection Using a New Spatial-Spectral-Domain Contrast Measure

Visual saliency is an important cue in human visual system, it can identify salient region in image. Image contrast has been utilized as an effective feature to detect the salient region. The conventional contrast measures utilize both spectral and spatial properties of image in many salient region detection methods. However, they only consider the local characteristics of image region, consequently, the global characteristics are neglected. This paper presented a new contrast measure by exploiting both local and global characteristics of image regions. Furthermore, the proposed measure is utilized to perform salient region detection in image. Experiments are conducted on the MSRA test database to compare the performance of the proposed approach with the state-of-the-art salient region detection algorithms.
Synthetic Peptides as Potential Antigens for Cutaneous Leishmaniosis Diagnosis

This work's goal was to research new candidate antigens for cutaneous leishmaniosis (CL). In order to reach the goal, we used random peptide phage display libraries screened using antibodies from Leishmania braziliensis patients. After selection, three peptides (P1, P2, and P3) were synthesized using Fmoc chemistry. The peptides individually or a mixture of them (MIX) was subsequently emulsified in complete and incomplete Freund's adjuvant and injected subcutaneously in golden hamsters. Sera from the hamsters administered with P1 presented antibodies that recognized proteins between 76 and 150 kDa from L. braziliensis. Sera from hamsters which had peptides P2 and P3, as well as the MIX, administered presented antibodies that recognized proteins between 52 and 76 kDa of L. braziliensis. The research on the similarity of the peptides' sequences in protein databases showed that they match a 63 kDa glycoprotein. The three peptides and the MIX were recognized by the sera from CL patients by immunoassay approach (ELISA). The peptides' MIX showed the best performance (79% sensitivity) followed by the P1 (72% sensitivity), and the AS presented 91% sensitivity. These results show a new route for discovering molecules for diagnosis or for immunoprotection against leishmaniosis.
ISO-TimeML Event Extraction in Persian Text

Recognizing TimeML events and identifying their attributes, are important tasks in natural language processing (NLP). Several NLP applications like question answering, information retrieval, summarization, and temporal information extraction need to have some knowledge about events of the input documents. Existing methods developed for this task are restricted to limited number of languages, and for many other languages including Persian, there has not been any effort yet. In this paper, we introduce two different approaches for automatic event recognition and classification in Persian. For this purpose, a corpus of events has been built based on a specific version of ISO-TimeML for Persian. We present the specification of this corpus together with the results of applying mentioned approaches to the corpus. Considering these methods are the first effort towards Persian event extraction, the results are comparable to that of successful methods in English. TITLE AND ABSTRACT IN PERSIAN
Efficient allocation of power of two terms in FIR digital filter design using tabu search

This paper concerns the design of FIR filters using quantized coefficients belonging to a sum of signed power-of-two terms (SPT) domain. Unlike other SPT filter design approaches, we added a global constraint that a priori fixes the total number of shift registers; thus each coefficient can be represented using different precision. The difficult FIR filter design optimization task, is solved by a specific Tabu Search (TS) method. Several experimental results and comparisons with other well known approaches, demonstrate the effectiveness of this filter architecture and the proposed optimization algorithm.
Text-based image retrieval using progressive multi-instance learning

Relevant and irrelevant images collected from the Web (e.g., Flickr.com) have been employed as loosely labeled training data for image categorization and retrieval. In this work, we propose a new approach to learn a robust classifier for text-based image retrieval (TBIR) using relevant and irrelevant training web images, in which we explicitly handle noise in the loose labels of training images. Specifically, we first partition the relevant and irrelevant training web images into clusters. By treating each cluster as a “bag” and the images in each bag as “instances”, we formulate this task as a multi-instance learning problem with constrained positive bags, in which each positive bag contains at least a portion of positive instances. We present a new algorithm called MIL-CPB to effectively exploit such constraints on positive bags and predict the labels of test instances (images). Observing that the constraints on positive bags may not always be satisfied in our application, we additionally propose a progressive scheme (referred to as Progressive MIL-CPB, or PMIL-CPB) to further improve the retrieval performance, in which we iteratively partition the top-ranked training web images from the current MIL-CPB classifier to construct more confident positive “bags” and then add these new “bags” as training data to learn the subsequent MIL-CPB classifiers. Comprehensive experiments on two challenging real-world web image data sets demonstrate the effectiveness of our approach.
Evolutionary behavior testing of commercial computer games

We present an approach to use evolutionary learning of behavior to improve testing of commercial computer games. After identifying unwanted results or behavior of the game, we propose to develop measures on how near a sequence of game states comes to the unwanted behavior and to use these measures within the fitness function of a GA working on action sequences. This allows to find action sequences that produce the unwanted behavior, if they exist. Our experimental evaluation of the method with the FIFA-99 game and scoring a goal as unwanted behavior shows that the method is able to find such action sequences, allowing for an easy reproduction of critical situations and improvements to the tested game.