Miracle-dz/UniFAR-FTUs huggingface dataset:
New Collection Announcement: Focused Retrieval Over the Web

Focused retrieval (a.k.a., passage retrieval) is important at its own right and as an intermediate step in question answering systems. We present a new Web-based collection for focused retrieval. The document corpus is the Category A of the ClueWeb12 collection. Forty-nine queries from the educational domain were created. The $100$ documents most highly ranked for each query by a highly effective learning-to-rank method were judged for relevance using crowdsourcing. All sentences in the relevant documents were judged for relevance.
Prevalence of oral mucosal alterations in type 2 diabetes mellitus patients attending a diabetic center

Objective: To explore an association between oral mucosal alterations and type 2 Diabetes mellitus. Methods: This study was conducted at Baqai Institute of Diabetology and Endocrinology and Baqai Medical University from September 2010 to September 2012. A total of 800 individuals’ 395 type 2 diabetes mellitus patients and 405 healthy individuals were enrolled in this study. An oral clinical examination was carried out for all participants using a mouth mirror, visible light source and cotton gauze. Results: The prevalence of oral mucosal lesions was high significantly < 0.0001; odd ratio 2.601, CI 1.929-3.509 in type 2 diabetic as compared to non-diabetic. With respect to specific oral mucosal lesions, highly significant association p<0.0001; Odd ratio 4.275, CI 2.798-6.534 was found between coated tongue with type 2 diabetes mellitus. This study did not find any association (p>0.05) between type 2 diabetes mellitus and potentially malignant disorders. Conclusion: This study showed that the prevalence of oral mucosal lesions was higher in type 2 diabetic than non-diabetics. This study provides evidence that diabetes has a negative influence on oral health.
White Matter Integrity, Creativity, and Psychopathology: Disentangling Constructs with Diffusion Tensor Imaging

That creativity and psychopathology are somehow linked remains a popular but controversial idea in neuroscience research. Brain regions implicated in both psychosis-proneness and creative cognition include frontal projection zones and association fibers. In normal subjects, we have previously demonstrated that a composite measure of divergent thinking (DT) ability exhibited significant inverse relationships in frontal lobe areas with both cortical thickness and metabolite concentration of N-acetyl-aspartate (NAA). These findings support the idea that creativity may reside upon a continuum with psychopathology. Here we examine whether white matter integrity, assessed by Fractional Anisotropy (FA), is related to two measures of creativity (Divergent Thinking and Openness to Experience). Based on previous findings, we hypothesize inverse correlations within fronto-striatal circuits. Seventy-two healthy, young adult (18–29 years) subjects were scanned on a 3 Tesla scanner with Diffusion Tensor Imaging. DT measures were scored by four raters (α = .81) using the Consensual Assessment Technique, from which a composite creativity index (CCI) was derived. We found that the CCI was significantly inversely related to FA within the left inferior frontal white matter (t = 5.36, p = .01), and Openness was inversely related to FA within the right inferior frontal white matter (t = 4.61, p = .04). These findings demonstrate an apparent overlap in specific white matter architecture underlying the normal variance of divergent thinking, openness, and psychotic-spectrum traits, consistent with the idea of a continuum.
Audited Financial Reporting and Voluntary Disclosure as Complements: A Test of the Confirmation Hypothesis

We examine the “confirmation” hypothesis that audited financial reporting and disclosure of managers' private information are complements, because independent verification of outcomes disciplines and hence enhances disclosure credibility. Committing to higher audit fees (a measure of financial statement verification) is associated with management forecasts that are more frequent, specific, timely, accurate and informative to investors. Because private information disclosure and audited financial reporting are complements, their economic roles cannot be evaluated separately. Our evidence cautions against drawing inferences exclusively from market reactions around “announcement periods” because audited financial reporting indirectly affects information released at other times and through other channels.
Domain-specific language design requires feature descriptions

A domain-specific language (DSL) provides a notation tailored towards an application domain and is based on the relevant concepts and features of that domain. As such, a DSL is a means to describe and generate members of a family of programs in the domain. A prerequisite for the design of a DSL is a detailed analysis and structuring of the application domain. Graphical feature diagrams have been proposed to organize the dependencies between such features, and to indicate which ones are common to all family members and which ones vary. In this paper, we study feature diagrams in more details, as well as their relationship to domain-specific languages. We propose the Feature Description Language (FDL), a textual language to describe features. We explore automated manipulation of feature descriptions such as normalization, expansion to disjunctive normal form, variability computation and constraint satisfaction. Feature descriptions can be directly mapped to UML diagrams which in their turn can be used for Java code generation. The value of FDL is assessed via a case study in the use and expressiveness of feature descriptions for the area of documentation generators.
Training spiking neural networks with the improved grey-level co-occurrence matrix algorithm for texture analysis

Texture refers to the tactile impression, such as rough, silky, bumpy, and other texture terms. The Grey-Level Co-occurrence Matrix (GLCM) algorithm is widely used in visual images for texture feature extraction, image structure characterization analysis and texture classification. The GLCM can not only give the statistics of pixel gray values occur in an image, but also give multiple characteristics of the images. Since the primate brain, which is constructed with spiking neurons, has excellent performance in terms of image feature extraction, the improved GLCM algorithm is used to train a spiking neural network and also to simulate the brain's ability about extract key information and utilize these extracted feature information to classify different texture image. Experimental results in this article show that this combination of the GLCM and spiking neural network can effectively extract image features, and the texture classification results is also to achieve satisfactory effect.
The Effect of Self-Control on Attentional Bias for Alcohol Cues in Male Heavy Drinkers 1 H anneke

Attentional bias for alcohol cues increases craving and subsequent alcohol consumption. Override processes can be used to disengage attention from alcohol cues. This requires self-control and implies that depletion of self-control would impair the ability to disengage attention from alcohol cues. This study examined the effect of self-control on attentional bias among male heavy drinkers. To manipulate selfcontrol resources, an expression control task was used. Attentional bias was measured with a visual probe task. The Obsessive Compulsive Drinking Scale (OCDS; Anton, Moak, & Latham, 1996) assessed the urge to drink and persistent thoughts about alcohol. The results suggest that participants who scored relatively high on the OCDS showed more attentional bias after controlled emotional expression, compared to free emotional expression. jasp_800 776.792
Olfactory dysfunction, central cholinergic integrity and cognitive impairment in Parkinson’s disease

Olfactory dysfunction is common in subjects with Parkinson’s disease. The pathophysiology of such dysfunction, however, remains poorly understood. Neurodegeneration within central regions involved in odour perception may contribute to olfactory dysfunction in Parkinson’s disease. Central cholinergic deficits occur in Parkinson’s disease and cholinergic neurons innervate regions, such as the limbic archicortex, involved in odour perception. We investigated the relationship between performance on an odour identification task and forebrain cholinergic denervation in Parkinson’s disease subjects without dementia. Fifty-eight patients with Parkinson’s disease (mean Hoehn and Yahr stage 2.5 ± 0.5) without dementia (mean Mini-Mental State Examination, 29.0 ± 1.4) underwent a clinical assessment, [11C]methyl-4-piperidinyl propionate acetylcholinesterase brain positron emission tomography and olfactory testing with the University of Pennsylvania Smell Identification Test. The diagnosis of Parkinson’s disease was confirmed by [11C]dihydrotetrabenazine vesicular monoamine transporter type 2 positron emission tomography. We found that odour identification test scores correlated positively with acetylcholinesterase activity in the hippocampal formation (r = 0.56, P < 0.0001), amygdala (r = 0.50, P < 0.0001) and neocortex (r = 0.46, P = 0.0003). Striatal monoaminergic activity correlated positively with odour identification scores (r = 0.30, P < 0.05). Multiple regression analysis including limbic (hippocampal and amygdala) and neocortical acetylcholinesterase activity as well as striatal monoaminergic activity, using odour identification scores as the dependent variable, demonstrated a significant regressor effect for limbic acetylcholinesterase activity (F = 10.1, P < 0.0001), borderline for striatal monoaminergic activity (F = 1.6, P = 0.13), but not significant for cortical acetylcholinesterase activity (F = 0.3, P = 0.75). Odour identification scores correlated positively with scores on cognitive measures of episodic verbal learning (r = 0.30, P < 0.05). These findings indicate that cholinergic denervation of the limbic archicortex is a more robust determinant of hyposmia than nigrostriatal dopaminergic denervation in subjects with moderately severe Parkinson's disease. Greater deficits in odour identification may identify patients with Parkinson's disease at risk for clinically significant cognitive impairment.
REVIEW OF STUDENT ATTENDANCE SYSTEM USING RFID 1

The Most educational institution’s administrators are concerned about student irregular attendance, which may affect the student overall academic performance and finally it affects the students growth in education. The conventional method of taking attendance by calling names or signing on paper is very time consuming and even insecure because there is possibility of proxy attendance. Therefore, web-based student attendance management system is required to assist the faculty and the lecturer for the time-consuming process. For this purpose, GSM/GPRS based student’s attendance management system using RFID is a much convenient method to take the attendance. Student is provided with the RFID tags. When student comes near to the reader, it will sense the respective student and update attendance. The whole process is controlled using the microcontroller. This paper reviews some of these monitoring systems and proposes an RFID based student attendance system. The reports can be generated in real-time processing, thus, provides valuable information about the students’ commitments in attending the classes.
For maximally monotone linear relations, dense type, negative-infimum type, and Fitzpatrick-Phelps type all coincide with monotonicity of the adjoint

It is shown that, for maximally monotone linear relations defined on a general Banach space, the monotonicities of dense type, of negative-infimum type, and of FitzpatrickPhelps type are the same and equivalent to monotonicity of the adjoint. This result also provides affirmative answers to two problems: one posed by Phelps and Simons, and the other by Simons.
Contextual term equivalent search using domain-driven disambiguation

This article presents a domain-driven algorithm for the task of term sense disambiguation (TSD). TSD aims at automatically choosing which term record from a term bank best represents the meaning of a term occurring in a particular context. In a translation environment, finding the contextually appropriate term record is necessary to access the proper equivalent to be used in the target language text. The term bank TERMIUM Plus, recently published as an open access repository, is chosen as a domain-rich resource for testing our TSD algorithm, using English and French as source and target languages. We devise an experiment using over 1300 English terms found in scientific articles, and show that our domain-driven TSD algorithm is able to bring the best term record, and therefore the best French equivalent, at the average rank of 1.69 compared to a baseline random rank of 3.51.
Correlates of past year dental health visits: findings from the Indiana black men's health study.

OBJECTIVES To examine the role of social support and additional predisposing, enabling and need factors that may be associated with past year dental visits among adult Black men. METHODS Data came from a 2011 study of 1,444 Black men from 12 Indiana counties. Based on Andersen's Behavioral Model of Health Service Utilization, we conducted multivariable logistic regression analyses examining predisposing (age, sex, marital status, education), enabling (income, employment, health insurance, place of sick care, social support) and need factors (self-reported smoking status, health status, mental health days, and fruit and vegetable consumption). RESULTS Overall, 42% of African American males sought dental care in the past year. Several predisposing (being married, having a college degree), enabling (being unemployed, having higher income, having health insurance and reporting high levels of social support) and need (increased fruit consumption) factors were found to be positively associated (P < 0.05) with past year dental care utilization in the fully adjusted model. Vegetable consumption was not significantly associated with past year dental use. CONCLUSION Adult black men in this sample underutilized dental services. Results suggest several factors that can be used to target Black men to increase utilization rates. In particular, social support may be a promising factor that should be explored in further studies.
Monitoring brain repair in stroke using advanced magnetic resonance imaging.

Thrombolysis and endovascular interventions have revolutionized stroke treatment, but many patients are excluded from such therapies, and residual disability is common.1 Emerging approaches to enhance poststroke brain repair may have no time constraints and are applicable to most stroke patients. Novel interventions to enhance brain repair include electromagnetic or robotic techniques, brain–computer interface, and restorative cell-based and pharmacological therapies.2–4 A major impediment to translation to patient care, however, is the lack of robust in vivo techniques to monitor the effects of such interventions in humans.3 Noninvasive imaging of the human brain for multiparametric in vivo monitoring of poststroke recovery presents challenges. The clinical application of certain techniques such as positron emission tomography is frequently restricted by radiation exposure, limited resolution, high cost, or difficult access.5–7 Magnetic resonance imaging (MRI), however, is accessible, noninvasive, safe, and versatile, with high resolution, making this an ideal modality for multiparametric in vivo monitoring of stroke recovery. This review concentrates on MRI markers of stroke recovery in experimental models and, when available, in humans (Table). View this table: Table. Magnetic Resonance Options for Imaging Poststroke Recovery ### Angiogenesis The peri-infarct cortex is a unique neurovascular niche, within which angiogenesis is closely and causally linked to neurogenesis through vascular growth factors and chemokines.2 Together with parenchymal astrocytes, angiogenic vessels facilitate synaptogenesis and axonal sprouting.2 Angiogenesis stimulated by cell-based or pharmacological interventions correlates with improved behavioral outcome.2 In rodents, capillary sprouting at the ischemic boundary leads to new vessel development between 2 and 28 days.8 Angiogenesis has been observed in the ischemic penumbra of humans 3 to 4 days after stroke, and higher cerebral blood vessel density has been associated with improved survival.9 Angiogenic vessels are permeable during the early stages of development and become less leaky as they …
Vibrio damsela from wounds in bottlenose dolphins Tursiops truncates

Some of the bottlenose dolphins kept in coastal sea pens in Hawaii developed slowhealing wounds and were treated with trimethoprim/sulfadiazine. Vibrio bacteria recovered from healthy skin and wounds of dolphins as well as the sea pen water were identified using the 54 test system of West & Colwell. The popular 26 test API-20 E system was of limited value in identifying many vibrios recovered from environmental sources. Predominant vibrios recovered from sea pen water and from healthy dolphin skin were Vibrio alginolyticus and V. marinus, respectively. These vibrios remained sensitive to trimethoprim and sulfadiazine. The predominant vibrio recovered from dolphin wounds was V. damsela which developed resistance to the 2 antimicrobial agents used to treat the dolphins. This resistance was taken as additional evidence that V. damsela was multiplying at the wound site. V. damsela is a known pathogen of fish and humans and is believed to be the primary bacterium causing wound infections in dolphins.
Geometrical compensation for multi-view video in multiple camera array

In this paper, we present a geometrical compensation method for a calibrated multi-view video that is captured by the one-dimensional (1-D) parallel or arc camera array. Since the multi-view video may include geometical errors, we define a compensating transformation based on a two-dimensional (2-D) homography. After we apply the compensating transformation, we obtain all the image planes which are aligned vertically and rotated to be suitable for the camera array. Experimental results show that the proposed method correctly compensates the geometrical errors of the multi-view video. We can provide not only a clear viewpoint change in the multi-view video but also the simplicity and accuracy in matching between adjacent views.
Temporal and spatial dynamics of C-band brightness temperature over the Brazilian tropical savanna

The soil moisture is one of the key hydrological parameters that control the water and energy flows between the atmosphere and land surface, the partitioning of rainfall into infiltration, runoff and evapotranspiration, the photosynthetic activities of vegetation, and the respiration of soil microorganisms. Conventional methods of measuring soil moisture are time-consuming and the data are typically point-based estimates. This study presents the results of spatial and temporal variation analyses of Aqua/AMSR-E brightness temperature data from the Brazilian tropical savanna.
Protein identification in the post-genome era: the rapid rise of proteomics

Most advances in biology can usually be traced back to the development of a new technique: the recent explosion in sequence information in the databases arose from the pioneering work on separation methods by Frederick Sanger which paved the way for the development of protein (Sanger, 1945) and DNA/RNA (Maxam & Gilbert, 1977; Sanger, 1981) sequencing and culminated in the receipt of two Nobel prizes by Sanger. The initial phase of sequence database expansion was slow due to the tedious and slow nature of protein sequencing. Peptide sequencing was carried out manually and the complete analysis of a protein was tiresome, requiring the isolation of sufficient peptides from several digests of the target protein using proteases of different specialities to collect an overlapping set of fragments which cover the whole sequence. Protein sequencing gained momentum when the phenylisothiocyanate sequencing chemistry developed by Edman in 1949 was automated (Edman & Begg, 1967) and a commercial instrument requiring lower amounts (nanomoles) of sample was put on the market. Further technical advances such as novel valves to deal with small volumes of aggressive chemicals, the introduction of high pressure liquid chromatography (HPLC), and novel supports for sample immobilization, were all combined in the first gas phase sequencers, greatly increasing the sensitivity and allowing automated data collection (Hewick et al. 1981) and analysis. The new instruments with a sensitivity in the low picomole range appeared as rapid advances in DNA technology such as the development of restriction mapping (Danna et al. 1973), cloning (Cohen et al. 1973) and the dideoxynucleotide sequencing chemistry were threatening to make protein chemistry a relic of the past (Malcolm, 1978).
Experimental Investigation of Classification Algorithms for Predicting Lesion Type on Breast DCE-MR Images

Timely revealing of breast cancer is one of the most important issues in determining prognosis for women with malignant tumors. Dynamic contrast-enhanced (DCE) MRI is being increasingly used in the clinical setting to help detect and characterise tissue, suspicious for malignancy and has been shown to be the most sensitive modality for screening highrisk women. Computer-assisted evaluation (CAE) systems have the potential to assist radiologists in the early detection of cancer. A crucial module of the development of such a CAE system will be the selection of an appropriate classification function responsible for separating malignant and benign lesions. The motivation of this paper is to provide qualitative evaluation of three advanced classifiers like artificial neural network, support vector machine and artificial bee colony optimization algorithm trained neural network are being developed for classification of the suspicious lesions in breast MRI. A comparative study of these techniques for lesion classification is made to identify relative merits. As a result, the paper concluded that the neural network trained by artificial bee colony optimization algorithm based classifier outperforms all other explored classifiers for the examined dataset of breast DCE –MR images.
Improving image similarity with vectors of locally aggregated tensors

Within the Content Based Image Retrieval (CBIR) framework, three main points can be highlighted: visual descriptors extraction, image signatures and their associated similarity measures, and machine learning based relevance functions. While the first and the last points have vastly improved in recent years, this paper addresses the second point. We propose a novel approach to compute vector representations extending state of the art methods in the field. Furthermore, our method can be viewed as a linearization of efficient well known kernel methods. The evaluation shows that our representation significantly improve state of the art results on the difficult VOC2007 database by a fair margin.
Mixed Consistency Model: Meeting Data Sharing Needs of Heterogeneous Users

Heterogeneous users usually have different requirements as far as consistency of shared data is concerned. This paper proposes and investigates a mixed consistency model to meet this heterogeneity challenge in large scale distributed systems that support shared objects. This model allows combining strong (sequential) consistency and weak (causal) consistency. The paper defines the model, motivates it and proposes a protocol implementing it