Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnostic accuracy and prognostic applications of CYFRA 21-1 in head and neck cancer: A systematic review and meta-analysis

Cytokeratin fraction 21–1 (CYFRA 21–1) has been widely studied as an important biomarker in non-small cell lung cancer for both diagnosis and prognosis. Many studies have also assessed the clinical applications of CYFRA 21–1 in head and neck cancer, but the diagnostic and prognostic values of CYFRA 21–1 are not yet fully established. This pooled analysis aims at evaluating the diagnostic accuracy and prognostic applications of CYFRA 21–1 in patients with head and neck cancer. A systematic retrieval of literatures was conducted without time or language restrictions by searching PubMed, EMBASE, Web of Science, Cochrane library and China National Knowledge Infrastructure. Twenty studies were eligible for systematic review, of which 14 conformed for diagnostic analysis and 7 for prognostic analysis. The pooled sensitivity and specificity of CYFRA 21–1 analysis were 0.53 (95% CI: 0.39–0.67) and 0.97 (95% CI: 0.93–0.99), respectively. A high level of CYFRA 21–1 was significantly correlated with shorter overall survival (HR 1.33, 95% CI: 1.13–1.56) and disease-free survival (HR 1.48; 95%CI: 1.10–1.97). Current evidence indicates that the level of CYFRA 21–1 in the serum could be used as an indicator for monitoring tumor status and evaluating its curative effects.
Under the Sea: Rapid Characterization of Restricted Marine Environments

In crisis situations, military operating units require a rapid evaluation of the local meteorological and oceanographic (METOC) conditions affecting their missions. An important role of military oceanography (MILOC) is thus to provide a timely METOC characterization of denied littoral areas [1]. Environmental sampling procedures in MILOC must be easily relocatable, discreet, and secure. Until recently, marine sampling technologies meeting these requirements were scarce. Remote sensing is the technology mostly used by navies to assess environmental conditions in restricted areas [2]. Very-near-shore bathymetry, sea state, surface currents, ocean color, and sea surface temperature (SST) are among the pieces of environmental information that can be obtained by means of remote sensors. Although valuable, this information is not sufficient to fully assess the three-dimensional (3-D) variability of the environment. Numerical approaches that simulate the ocean dynamics may provide additional information on the environmental conditions. In the coastal regions, numerical ocean models of different spatiotemporal resolutions are generally nested to downscale METOC information to the region of interest [3]. Numerical procedures used to feed back dynamical information between the models with different resolutions inevitably introduce errors in this nesting process. In addition, at present, the uncertainties in physical parameterizations, forcing, and model initialization limit the accuracy of model forecasts.
PHASE-FIELD APPROACH TO CRYSTAL GROWTH

The phase-field method has appeared in the context of diffuse interfaces. It has been applied to the three major materials processes: solidification, solid-state phase transformation, and grain growth and coarsening. Very recently, a number of new phase-field models have been developed for modelling thin films and surfaces (see (3)). The first part of this contribution is concerned with the phase-field model of spiral crystal growth (5) described by the Burton-Cabrera-Frank theory (2). We then present computational studies related to the pattern formation and to the dependence on model parameters. The second part is concerned with the phase-field model (4, 6) of heteroepitaxial growth. Finally, we present our latest results.
Vote-Based LELC for Positive and Unlabeled Textual Data Streams

In this paper, we extend LELC (PU Learning by Extracting Likely Positive and Negative Micro-Clusters) method to cope with positive and unlabeled data streams. Our developed approach, which is called vote-based LELC, works in three steps. In the first step, we extract representative documents from unlabeled data and assign a vote score to each document. The assigned vote score reflects the degree of belongingness of an example towards its corresponding class. In the second step, the extracted representative examples, together with their vote scores, are incorporated into a learning phase to build an SVM-based classifier. In the third step, we propose the usage of an ensemble classifier to cope with concept drift involved in the textual data stream environment. Our developed approach aims at improving the performance of LELC by rendering examples to contribute differently to the construction of the classifier according to their vote scores. Extensive experiments on textual data streams have demonstrated that vote-based LELC outperforms the original LELC method.
Error recovered hierarchical classification

Hierarchical classification (HC) is a popular and efficient way for detecting the semantic concepts from the images. However, the conventional HC, which always selects the branch with the highest classification response to go on, has the risk of propagating serious errors from higher levels of the hierarchy to the lower levels. We argue that the highest-response-first strategy is too arbitrary, because the candidate nodes are considered individually which ignores the semantic relationship among them. In this paper, we propose a novel method for HC, which is able to utilize the semantic relationship among candidate nodes and their children to recover the responses of unreliable classifiers of the candidate nodes, with the hope of providing the branch selection a more globally valid and semantically consistent view. The experimental results show that the proposed method outperforms the conventional HC methods and achieves a satisfactory balance between the accuracy and efficiency.
Segmentation and enhancement of fingerprint images using K-means, fuzzy C-mean algorithm and statistical features

Fingerprint segmentation is a crucial and important step of image processing in automatic fingerprint's identification. The aim of the segmentation of fingerprint is to extract the region of interest; foreground; and to exclude the background regions, in order to reduce the time of subsequent processing and to avoid detecting false features. This paper presents a new approach of segmentation and enhancement of fingerprints. This approach is based on the fuzzy c-means algorithm (FCM), statistical features and frame differences Experimental results show the effectiveness and robustness of the proposed methods. We have tested this technique on 100 images taken from database FVC2004.
Neurophenomenology Integrating Subjective Experience and Brain Dynamics in the Neuroscience of Consciousness

The paper presents a research programme for the neuroscience of con- sciousness called 'neurophenomenology' (Varela 1996) and illustrates it with a recent pilot study (Lutz et al., 2002). At a theoretical level, neurophenomenology pursues a n e mbodied a nd l arge-scale d ynamical a pproach t o t he neurophysiology of consciousness (Varela 1995; Thompson and Varela 2001; Varela and Thompson 2003). At a methodological level, the neurophenomeno- logical strategy is to make rigorous and extensive use of first-person data about subjective experience as a heuristic to describe and quantify the large-scale neurodynamics of consciousness (Lutz 2002). The paper foocuses on neurophenomenology in relation to three challenging methodological issues about incorporating first-person data into cognitive neuroscience: (i) first-person reports can be biased or inaccurate; (ii) the process of generating first-person reports about an experience can modify that experience; and (iii) there is an 'ex- planatory gap' in our understanding of how to relate first-person, phenomeno- logical data to third-person, biobehavioural data.
The Role of Attention in the Design of Learning Management Systems

Modern learning environments would greatly benefit from a better management of two apparently conflicting goals. On the one hand, in order to support autonomous, self paced, and discovery oriented learning, learners must be offered access to a large amount of information and tools. On the other hand the quantity and variety of the information and tools provided should not overwhelm learners who should instead be guided in the access, use, experimentation, and synthesis of the available resources. We propose that a shift of focus from information presentation to attention guidance in system design may allow reconciling the conflict between increased informational need and the limited human cognitive capabilities. On the basis of findings in cognitive psychology and pedagogy, we present some of the issues that should be taken into consideration for the design of systems capable of such guidance and we propose how these may be integrated in the architecture of an attention aware learning management system.
Code migration through transformations: an experience report

One approach to dealing with spiraling maintenance costs, manpower shortages and frequent breakdowns for legacy code is to "migrate" the code into a new platform and/or programming language. The objective of this paper is to explore the feasibility of semi-automating such a migration process in the presence of performance and other constraints for the migrant code. In particular, the paper reports on an experiment involving a medium-size software system written in PL/IX. Several modules of the system were migrated to C++, first by hand and then through a semiautomatic tool. After discovering that the migrant code was performing up to 50% slower than the original, a second migration effort was conducted which improved the performance of the migrant code substantially. The paper reports on the transformation techniques used by the transformation process and the effectiveness of the prototype tools that were developed. In addition, the paper presents preliminary results on the evaluation of the experiment.
Investigating the Needs, Capabilities and Decision Making Mechanisms in Digital Preservation: Insights from a Multiple Case Study

Firms are required to consciously retain information in an effort to ensure compliance with legal and business needs. However, sustained accessibility to digital information cannot be taken for granted as it is threatened by expeditiously changing technologies associated with the risk of obsolete soft-and hardware. As part of an effort to ensure long-term access to digital information, digital preservation DP provides effective means. But still little is known about DP in firms. In this study the authors aim to provide insights into a firm's DP needs, capabilities and decision making mechanisms by conducting a multiple case study through the lens of organizational information processing theory. The results indicate that a lack of decision making procedures and responsibilities impedes the alignment between DP needs and capabilities, which seems to foster a culture of information hoarding. Based on the authors' empirical insights about DP in firms they derive an explanatory model and provide five managerial recommendations.
Trainable Tree Distance and an Application to Question Categorisation

Continuing a line of work initiated in Boyer et al. (2007), the generalisation of stochastic string distance to a stochastic tree distance, specically to stochastic Tai distance, is considered. An issue in modifying Zhang/Shasha tree-distance for stochastic variants is noted, a Viterbi EM costadaptation algorithm for this distance is proposed and a counter-example noted to an all-paths EM proposal. Experiments are reported in which a kNN categorisation algorithm is applied to a semantically categorised, syntactically annotated corpus. We show that a 67.7% base-line using standard unitcosts can be improved to 72.5% by cost adaptation. 1 Theory and Algorithms The classification of syntactic structures into semantic categories arises in a number of settings. A possible approach to such a classifier is to compute a category for a test item based on its distances to a set of k nearest neighbours in a precategorised example set. This paper takes such an approach and deploying variants of a tree-distance measure, a measure which has been used with some success in a variety of semantically-oriented tasks such as Question-Answering, Entailment Recognition and Semantic Role Labelling (Punyakanok et al., 2004; Kouylekov and Magnini, 2005; Emms, 2006a; Emms, 2006b; Franco-Penya, 2010). An issue which will be considered is how to adapt the atomic costs underlying the tree-distance measure. Tai (1979) first proposed a tree-distance measure. WhereS and T are ordered, labelled trees, a T i mapping is apartial, 1-to-1 mappingσ from the nodes ofS to the nodes of T , which respectsleftto-right orderandancestry1, such as a
Generating Tests for Detecting Faults in Feature Models

We present a novel fault-based approach for testing feature models (FMs). We identify several fault classes that represent possible mistakes one can make during feature modeling. We introduce the concept of distinguishing configuration, i.e., a configuration that is able to detect a given fault. Starting from this definition, we devise a technique, based on the use of a logic solver, able either to find distinguishing configurations to be used as tests or to prove that a mutation produces an equivalent feature model. Compact test suites can be produced by exploiting an SMT solver. The experiments show that our methodology is viable and produces reasonable sized test suites in a short time. W.r. t. the approaches that use only the products, our approach has a better fault detection capability and requires fewer tests.
Emotion dysregulation in the experience of pain among persons living with HIV/AIDS

ABSTRACT Persons living with HIV and AIDS (PLWHA) report disproportionally high rates of pain. Pain among PLWHA has been associated with poor medication adherence and anxiety and depressive symptoms. This relationship may be primarily driven by elevated negative affect, and one factor that may be important to understanding elevated negative affect is emotion dysregulation. Therefore, the current study sought to examine emotion dysregulation (Difficulties in Emotion Regulation Scale) in terms of multi-dimensional pain experience (pain severity, pain interference, pain affective distress, pain life control; Multidimensional Pain Inventory; Turk and Rudy (1988) among a sample of 162 HIV+ individuals (M age = 47.65, SD = 8.59, 35.2% female). Two-step hierarchical regression analyses revealed that emotion dysregulation total score was significantly associated with each of the pain variables. These results may suggest PLWHA who demonstrate greater emotion dysregulation struggle to effectively manage negative affect associated with their pain experience, exacerbating the severity of pain symptoms across numerous clinically-relevant domains. The novel findings may provide important assessment and intervention targets for PLWHA living with pain.
Dibenzyl Disulfide Adsorption on Cationic Exchanged Faujasites: A DFT Study

Although dibenzyl disulfide (DBDS) is used as a mineral oil stabilizer, its presence in electrical transformer oil is associated as one of the major causes of copper corrosion and subsequent formation of copper sulfide. In order to prevent these undesirable processes, MY zeolites (with M = Li, Na, K, Cs, Cu or Ag) are proposed to adsorb molecularly DBDS. In this study, different MY zeolites are investigated at the DFT+D level in order to assess their ability in DBDS adsorption. It was found that CsY, AgY and CuY exhibit the best compromise between high interaction energies and limited S-S bond activation, thus emerging as optimal adsorbents for DBDS.
Treatment of Chinese adolescents with anorexia nervosa in Hong Kong: The gap between treatment expectations and outcomes

Background and objective Anorexia nervosa (AN) is one of the most difficult-to-treat psychiatric disorders. AN is associated with individual vulnerability, societal and family factors. There has been limited research in Asia regarding the patients or their families’ perceptions on its treatment. This study explored the perceived treatment outcomes among Chinese families having adolescents with AN. Methods Qualitative interviews were conducted on parents of adolescents with AN recruited through an eating disorder association in Hong Kong to understand their views and experiences regarding the help-seeking and treatment process. Results The parents expressed dissatisfaction towards help-seeking and treatment outcomes, including relationships with health professionals, hospitalization, health professionals’ knowledge of AN, understanding of the treatment model and parents’ role, amount of psychological support, and coordination among health professionals. The parents were unclear about the treatment plan as they received little explanation from the health professionals. The parents perceived that the AN treatment only focused on weight restoration with limited psychological support. Home diet monitoring was seen as a harsh task which worsened the relationship with their children. The parents often needed to take up the coordinator role and search around for different health professionals and integrate their advices by themselves. Conclusions The study shows that limited psychoeducation, communication and coordination in the treatment for AN are major problems in a Chinese context. Open communication between the health professionals and the parents about the expected treatment outcomes and limitations is needed to enhance their mutual trust. Besides, treatment should emphasize not only family involvement but also empower them to fight against AN.
Using Microworlds To Study Intuitive Battle Dynamics: A Concept For The Future

Intuitive Battle Dynamics concerns the understanding of time. The rapid changes in today’s society give us less time for reflection and thinking. A commander needs to develop sensitivity to the changes in the battlefield to be able to control the situation. To find out what sensitivity is needed and in a further perspective to be able to train command and control in dynamic processes we have used microworlds, i.e., computer simulations of dynamic tasks. The aim is to explore and develop the Commander’s need for intuitive battle dynamics, which we believe, is essential for command and control in the future. This paper is about a concept of using microworlds to study intuitive battle dynamics.
Climate and land use controls over terrestrial water use efficiency in monsoon Asia

Much concern has been raised regarding how and to what extent climate change and intensive human activities have altered water use efficiency (WUE, amount of carbon uptake per unit of water use) in monsoon Asia. By using a process‐based ecosystem model [dynamic land ecosystem model (DLEM)], we examined effects of climate change, land use/cover change, and land management practices (i.e. irrigation and nitrogen fertilization) on WUE in terrestrial ecosystems of monsoon Asia during 1948–2000. Our simulations indicated that due to climate variability/change, WUE in the entire area decreased by 3·6% during the study period, with the largest decrease of 6·8% in the 1990s. Grassland was the most sensitive biome to a drying climate, with a decrease of 16·2% in WUE in the 1990s. Land conversion from natural vegetation to croplands, accounting for 79% of the total converted land areas, led to a decrease in WUE, with the largest decrease of 42% while forest was converted to cropland. In contrast, WUE increased by more than 50% while cropland was converted to natural vegetation. Simulated results also showed that intensive land management practices could alleviate the decrease in WUE induced by climate change and land conversion. Changes in WUE showed substantial spatial variation, varying from the largest decrease of over 50% in northwestern China and some areas of Mongolia to the largest increase of over 30% in western, southern China, and large areas of India. To adapt to climate change and sustain terrestrial ecosystem production, more attention ought to be paid to enhance water use efficiency through land use and management practices, especially in the drying areas. Copyright © 2011 John Wiley & Sons, Ltd.
Age matters: differences in correlates of self-reported HIV antiretroviral treatment adherence between older and younger Black men who have sex with men living with HIV

ABSTRACT Black men who have sex with men (BMSM) show lower levels of adherence to antiretroviral therapy (ART) for HIV medications than other racial/ethnic groups in the U.S. Yet, little is known about age differences in factors that predict ART adherence among BMSM. We combined data from two surveys of HIV-positive BMSM, resulting in 209 participants (130 aged 18–50 years; 79 aged 50 years or older). Multivariate linear regressions examined associations between baseline characteristics and adherence to HIV medications as well as interactions of baseline characteristics with age. The associations between trust in healthcare and doctor satisfaction ratings with higher adherence were stronger for older vs younger men (p < .05); the association between problem drinking and lower adherence was stronger among younger men (p < .05). Future research should examine how interventions may address these age-specific factors to improve ART adherence among BMSM living with HIV.
Periodontal Health and Oral Microbiota in Patients with Rheumatoid Arthritis

This study aimed to investigate the periodontal health of patients with established rheumatoid arthritis (RA) in relation to oral microbiota, systemic and oral inflammatory mediators, and RA disease activity. Forty patients underwent full-mouth dental/periodontal and rheumatological examination, including collection of blood, saliva, gingival crevicular fluid (GCF) and subgingival plaque. Composition of plaque and saliva microbiota were analysed using 16S rRNA sequencing and levels of inflammatory mediators by multiplex-immunoassay. The majority of the patients (75%) had moderate or severe periodontitis and the rest had no/mild periodontitis. Anti-citrullinated protein antibody (ACPA) positivity was significantly more frequent in the moderate/severe periodontitis (86%) compared to the no/mild group (50%). No significance between groups was observed for RA disease duration or activity, or type of medication. Levels of sCD30/TNFRSF8, IFN-α2, IL-19, IL-26, MMP-1, gp130/sIL-6Rß, and sTNF-R1 were significantly higher in serum or GCF, and April/TNFSF13 was significantly higher in serum and saliva samples in moderate/severe periodontitis. The microbial composition in plaque also differed significantly between the two groups. In conclusion, the majority of RA patients had moderate/severe periodontitis and that this severe form of the disease was significantly associated with ACPA positivity, an altered subgingival microbial profile, and increased levels of systemic and oral inflammatory mediators.