Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of changes in personality and behavior in adult glioma patients: a systematic review.

Background Gliomas are rare, with a dismal outcome and an obvious impact on quality of life, because of neurological, physical and cognitive problems, as well as personality and behavioral changes. These latter changes may affect the lives of both patients and their relatives in a profound way, but it is unclear how often this occurs and to what extent. Methods We performed a systematic review to determine the prevalence of changes in personality and behavior in glioma patients. Searches were conducted in PubMed/Medline, PsycINFO, Cochrane, CINAHL and Embase. Based on predetermined in- and exclusion criteria, papers were screened for eligibility. Information on the topics of interest were extracted from the full-text papers. Results The search yielded 9895 papers, of which 18 were found to be eligible; 9 qualitative and 9 quantitative studies. The reported prevalence rates of changes in personality and/or behavior varied from 8%-67% in glioma patients, and was 100% in a case series with bilateral gliomas. Moreover, these changes were associated with distress and a lower quality of life of patients as well as informal caregivers. Methods of measurement of personality and behavioral changes differed considerably, as did the description of these changes. Conclusion To determine the true prevalence of changes in behavior and personality, present but poorly labeled in the reported studies, prospective studies are needed using proper definitions of personality and behavioral changes and validated measurement tools. Ultimately, these findings may result in improved supportive care of both patients and caregivers, during the disease trajectory.
Towards a Hybrid Design for Fast Query Processing in DB2 with BLU Acceleration Using Graphical Processing Units: A Technology Demonstration

In this paper, we show how we use Nvidia GPUs and host CPU cores for faster query processing in a DB2 database using BLU Acceleration (DB2's column store technology). Moreover, we show the benefits and problems of using hardware accelerators (more specifically GPUs) in a real commercial Relational Database Management System(RDBMS). We investigate the effect of off-loading specific database operations to a GPU, and show how doing so results in a significant performance improvement. We then demonstrate that for some queries, using just CPU to perform the entire operation is more beneficial. While we use some of Nvidia's fast kernels for operations like sort, we have also developed our own high performance kernels for operations such as group by and aggregation. Finally, we show how we use a dynamic design that can make use of optimizer metadata to intelligently choose a GPU kernel to run. For the first time in the literature, we use benchmarks representative of customer environments to gauge the performance of our prototype, the results of which show that we can get a speed increase upwards of 2x, using a realistic set of queries.
Effects of a Mindfulness Meditation App on Subjective Well-Being: Active Randomized Controlled Trial and Experience Sampling Study

Background Mindfulness training (MT) includes a variety of contemplative practices aimed at promoting intentional awareness of experience, coupled with attitudes of nonjudgment and curiosity. Following the success of 8-week, manualized group interventions, MT has been implemented in a variety of modalities, including smartphone apps that seek to replicate the success of group interventions. However, although smartphone apps are scalable and accessible to a wider swath of population, their benefits remain largely untested. Objective This study aimed to investigate a newly developed MT app called Wildflowers, which was codeveloped with the laboratory for use in mindfulness research. It was hypothesized that 3 weeks of MT through this app would improve subjective well-being, attentional control, and interoceptive integration, albeit with weaker effects than those published in the 8 week, manualized group intervention literature. Methods Undergraduate students completed 3 weeks of MT with Wildflowers (n=45) or 3 weeks of cognitive training with a game called 2048 (n=41). State training effects were assessed through pre- and postsession ratings of current mood, stress level, and heart rate. Trait training effects were assessed through pre- and postintervention questionnaires canvassing subjective well-being and behavioral task measures of attentional control and interoceptive integration. State and trait training data were analyzed in a multilevel model using emergent latent factors (acceptance, awareness, and openness) to summarize the trait questionnaire battery. Results Analyses revealed both state and trait effects specific to MT; participants engaging in MT demonstrated improved mood (r=.14) and a reduction of stress (r=−.13) immediately after each training session compared with before the training session and decreased postsession stress over 3 weeks (r=−.08). In addition, MT relative to cognitive training resulted in greater improvements in attentional control (r=−.24). Interestingly, both groups demonstrated increased subjective ratings of awareness (r=.28) and acceptance (r=.23) from pre- to postintervention, with greater changes in acceptance for the MT group trending (r=.21). Conclusions MT, using a smartphone app, may provide immediate effects on mood and stress while also providing long-term benefits for attentional control. Although further investigation is warranted, there is evidence that with continued usage, MT via a smartphone app may provide long-term benefits in changing how one relates to their inner and outer experiences. Trial Registration ClinicalTrials.gov NCT03783793; https://clinicaltrials.gov/ct2/show/NCT03783793 (Archived by WebCite at http://www.webcitation.org/75EF2ehst)
Dealing with Class Noise in Large Training Datasets for Malware Detection

This paper presents the ways we explored until now for detecting and dealing with the class noise found in large annotated datasets used for training the classifiers that we have previously designed for industrial-scale malware identification. First we established a number of distance-based filtering rules that allow us to identify different "levels'' of potential noise in the training data, and secondly we analysed the effects produced by either removal or "cleaning'' of the potentially-noised records on the performances of our simplest classifiers. We show that a careful distance-based filtering can lead to sensibly better results in malware detection.
Seven Cases of Anaphylaxis to Paracetamol

Background: Paracetamol (acetaminophen, N-acetyl-para-amino-phenol) is a well-known antipyretic and analgesic drug. Hypersensitivity reactions to paracetamol are rare. However, we report seven cases of anaphylaxis to paracetamol and a review of the literature.
Small-Scale Fisheries Bycatch Jeopardizes Endangered Pacific Loggerhead Turtles

Background Although bycatch of industrial-scale fisheries can cause declines in migratory megafauna including seabirds, marine mammals, and sea turtles, the impacts of small-scale fisheries have been largely overlooked. Small-scale fisheries occur in coastal waters worldwide, employing over 99% of the world's 51 million fishers. New telemetry data reveal that migratory megafauna frequent coastal habitats well within the range of small-scale fisheries, potentially producing high bycatch. These fisheries occur primarily in developing nations, and their documentation and management are limited or non-existent, precluding evaluation of their impacts on non-target megafauna. Principal Findings/Methodology 30 North Pacific loggerhead turtles that we satellite-tracked from 1996–2005 ranged oceanwide, but juveniles spent 70% of their time at a high use area coincident with small-scale fisheries in Baja California Sur, Mexico (BCS). We assessed loggerhead bycatch mortality in this area by partnering with local fishers to 1) observe two small-scale fleets that operated closest to the high use area and 2) through shoreline surveys for discarded carcasses. Minimum annual bycatch mortality in just these two fleets at the high use area exceeded 1000 loggerheads year−1, rivaling that of oceanwide industrial-scale fisheries, and threatening the persistence of this critically endangered population. As a result of fisher participation in this study and a bycatch awareness campaign, a consortium of local fishers and other citizens are working to eliminate their bycatch and to establish a national loggerhead refuge. Conclusions/Significance Because of the overlap of ubiquitous small-scale fisheries with newly documented high-use areas in coastal waters worldwide, our case study suggests that small-scale fisheries may be among the greatest current threats to non-target megafauna. Future research is urgently needed to quantify small-scale fisheries bycatch worldwide. Localizing coastal high use areas and mitigating bycatch in partnership with small-scale fishers may provide a crucial solution toward ensuring the persistence of vulnerable megafauna.
A machine vision system for forensic analysis

Human skeletal remains are analysed by forensic anthropologists in order to draw conclusions about the probable identity of the deceased. During the analysis, the skull is used, along with other bones, to help determine the identity of the decedent. If only the base of the skull is available, forensic researchers take manual measurements from the large oval aperture in this region, the foramen magnum, in order to obtain information about the gender of the deceased. As this operation requires human intervention, the measurements are affected by the bias introduced by the human operator. The aim of this paper is to describe a full machine vision solution to perform precise morphological measurements of the foramen magnum. The system has been designed to extract measurements from 2D and 3D data and the returned results accurately match the manual measurements.
TRUSS Exacerbates NAFLD Development by Promoting IκBα Degradation in Mice

There is no effective treatment method for nonalcoholic fatty liver disease (NAFLD), the most common liver disease. The exact mechanism underlying the pathogenesis of NAFLD remains to be elucidated. Here, we report that tumor necrosis factor receptor–associated ubiquitous scaffolding and signaling protein (TRUSS) acts as a positive regulator of NAFLD and in a variety of metabolic disorders. TRUSS expression was increased in the human liver specimens with NAFLD or nonalcoholic steatohepatitis, and in the livers of high‐fat diet (HFD)‐induced and genetically obese mice. Conditional knockout of TRUSS in hepatocytes significantly ameliorated hepatic steatosis, insulin resistance, glucose intolerance, and inflammatory responses in mice after HFD challenge or in spontaneous obese mice with normal chow feeding. All of these HFD‐induced pathological phenotypes were exacerbated in mice overexpressing TRUSS in hepatocytes. We show that TRUSS physically interacts with the inhibitor of nuclear factor κB α (IκBα) and promotes the ubiquitination and degradation of IκBα, which leads to aberrant activation of nuclear factor κB (NF‐κB). Overexpressing IκBαS32A/S36A, a phosphorylation‐resistant mutant of IκBα, in the hepatocyte‐specific TRUSS overexpressing mice almost abolished HFD‐induced NAFLD and metabolic disorders. Conclusion: Hepatocyte TRUSS promotes pathological stimuli‐induced NAFLD and metabolic disorders, through activation of NF‐κB by promoting ubiquitination and degradation of IκBα. Our findings may provide a strategy for the prevention and treatment of NAFLD by targeting TRUSS.
Focal Manipulations of Formant Trajectories Reveal a Role of Auditory Feedback in the Online Control of Both Within-Syllable and Between-Syllable Speech Timing

Within the human motor repertoire, speech production has a uniquely high level of spatiotemporal complexity. The production of running speech comprises the traversing of spatial positions with precisely coordinated articulator movements to produce 10–15 sounds/s. How does the brain use auditory feedback, namely the self-perception of produced speech sounds, in the online control of spatial and temporal parameters of multisyllabic articulation? This question has important bearings on the organizational principles of sequential actions, yet its answer remains controversial due to the long latency of the auditory feedback pathway and technical challenges involved in manipulating auditory feedback in precisely controlled ways during running speech. In this study, we developed a novel technique for introducing time-varying, focal perturbations in the auditory feedback during multisyllabic, connected speech. Manipulations of spatial and temporal parameters of the formant trajectory were tested separately on two groups of subjects as they uttered “I owe you a yo-yo. ” Under these perturbations, significant and specific changes were observed in both the spatial and temporal parameters of the produced formant trajectories. Compensations to spatial perturbations were bidirectional and opposed the perturbations. Furthermore, under perturbations that manipulated the timing of auditory feedback trajectory (slow-down or speed-up), significant adjustments in syllable timing were observed in the subjects' productions. These results highlight the systematic roles of auditory feedback in the online control of a highly over-learned action as connected speech articulation and provide a first look at the properties of this type of sensorimotor interaction in sequential movements.
The role of local currency pricing in international transmission effects of monetary and productivity shocks in an economy with vertical production linkage and firm entry

In this paper, we construct a two-country model with the three factors of asymmetry in price-setting behavior between home and foreign intermediate goods firms, vertical production and trade, and endogenous entry of home and foreign final goods firms. We mainly examine the effect of asymmetric price-setting behavior on the welfare effects of monetary and productivity shocks, taking into account firm entry and exit. We show that when the ratio of home and/or foreign intermediate goods firms that set their export prices in the local currency rises, a home monetary shock has a beggar-thy-neighbor effect. In scenarios other than one where the ratios of both countries' intermediate goods firms that set their export prices in the local currency are unity, we show that the two types of home productivity shocks cause foreign welfare to deteriorate. When the ratios of both countries' intermediate goods firms that set their export prices in the local currency are unity, we show that the two types of home productivity shocks have a different effect on foreign welfare.
Novel Mutations Detected in Avirulence Genes Overcoming Tomato Cf Resistance Genes in Isolates of a Japanese Population of Cladosporium fulvum

Leaf mold of tomato is caused by the biotrophic fungus Cladosporium fulvum which complies with the gene-for-gene system. The disease was first reported in Japan in the 1920s and has since been frequently observed. Initially only race 0 isolates were reported, but since the consecutive introduction of resistance genes Cf-2, Cf-4, Cf-5 and Cf-9 new races have evolved. Here we first determined the virulence spectrum of 133 C. fulvum isolates collected from 22 prefectures in Japan, and subsequently sequenced the avirulence (Avr) genes Avr2, Avr4, Avr4E, Avr5 and Avr9 to determine the molecular basis of overcoming Cf genes. Twelve races of C. fulvum with a different virulence spectrum were identified, of which races 9, 2.9, 4.9, 4.5. 9 and 4.9. 11 occur only in Japan. The Avr genes in many of these races contain unique mutations not observed in races identified elsewhere in the world including (i) frameshift mutations and (ii) transposon insertions in Avr2, (iii) point mutations in Avr4 and Avr4E, and (iv) deletions of Avr4E, Avr5 and Avr9. New races have developed by selection pressure imposed by consecutive introductions of Cf-2, Cf-4, Cf-5 and Cf-9 genes in commercially grown tomato cultivars. Our study shows that molecular variations to adapt to different Cf genes in an isolated C. fulvum population in Japan are novel but overall follow similar patterns as those observed in populations from other parts of the world. Implications for breeding of more durable C. fulvum resistant varieties are discussed.
Data-Driven Sub-Units and Modeling Structure for Continuous Sign Language Recognition with Multiple Cues

We investigate the automatic phonetic modeling of sign lang u ge based on phonetic sub-units, which are data driven and w ithout any prior phonetic information. Visual processing is based on a probabilistic skin color model and a framewise geodesic act ive contour segmentation; occlusions are handled by a forward-backwar d prediction component leading finally to simple and effecti ve region-based visual features. For sign-language modeling we propose a mo deling structure for data-driven sub-unit construction. T his utilizes the cue that is considered crucial to segment the signal into parts; at the same time we also classify the segments by implicitly assigning labels of Dynamic or Static type. This segmentation and classificat on step disentangles Dynamic from Static parts and allows us to employ for each type of segment the appropriate cue, modeling and clustering approach. The constructed Dyn amic segments are exploited at the model level via hidden Markov models (HMMs). The Static s egments are exploited via k-means clustering. Each Dynamic or Static part, exploits the appropriate cue related to the movement. We propose that the movement cues are normalized in order to b translation and scaleinvariant. We apply the proposed modeling for further combination of t he movement trajectory individual cues. The proposed approaches are evaluated in recognition experiments condu ted on the continuous sign language corpus of Boston Univer sity (BU-400) showing promising preliminary results.
Heuristics for assessing Computational Archival Science (CAS) research: The case of the human face of big data project

Computational Archival Science (CAS) has been proposed as a trans-disciplinary field that combines computational and archival thinking. To provide grounded evidence, a foundational paper explored eight initial themes that constitute potential building blocks [1]. In order for a CAS community to emerge, further studies are needed to test this framework. While the foundational paper for CAS provides a conceptual and theoretical basis of this new field, there is still a need to articulate useful guidelines and checkpoints that validate a CAS research agenda. In this position paper, we propose heuristics for assessing emerging CAS-related studies that researchers from traditional fields can use in their research design stage. The Human Face of Big Data project, a digital curation and interface design project for urban renewal data, is presented and analyzed to demonstrate the validity of the suggested heuristics. Finally, implications for CAS and future work are discussed.
Towards School Transformation. Evaluation of a Coexistence Program from the Voice of Students and Teachers

Learning to coexist continues to be one of the challenges faced by the current educational system, especially for those schools located in contexts at risk of social exclusion where the violence rate increases on a daily basis. The main aim sought by the present study consists in assessing the impact of a program developed at an educational center located in a vulnerable neighborhood of the city of Valencia (Spain). It is a quasi-experimental, pretest-posttest research with a control group that involved a total of 109 teachers and students. It deserves to be highlighted that this paper forms part of a broader research initiative, for which reason the results obtained in the qualitative part through the implementation of a content analysis are presented. The results show the success of the program applied in accordance with the perceptions of the teachers and students involved, who state that all the program strategies have significantly improved school coexistence.
TV ad video categorization with probabilistic latent concept learning

In this paper we present a multi-modal approach to TV ads classification by advertised products/services. A bag-of-words representation is proposed to discover ad categories-related latent visual and textual concepts by probabilistic latent semantics analysis (PLSA). We use multi-modal concepts to represent ad categories in the latent semantics space. In particular, we resort to external resources (e.g., a brand list, encyclopedia) to expand sparse textual information. A semi-supervised co-training is finally employed to fuse visual and textual features for ad classification. Our experiments have achieved promising results in terms of classification accuracy and scalability to new ad categories. The resulting ad classifiers can be applied to digest ads from TV streams, which is useful for TV viewers to manage ads in a positive manner. The digested ads can be considered the video-based alert for emerging products/services. Thus the reachability and focus of TV ads can be improved.
Granville Sharp’s manuscript letter to the admiralty on the Zong massacre: a new discovery in the British Library

ABSTRACT During research at the British Library (BL) in May 2015, I discovered a previously unknown manuscript letter from 1783 by Granville Sharp to the Lords Commissioners of the Admiralty. The document concerns the case of the infamous Zong slave ship: Sharp wrote the letter to demand that the Admiralty bring murder charges against the crew of the Zong. This article argues that the BL letter is the only known fair-copy of Sharp’s letter to the Admiralty, that the only other extant copy at the National Maritime Museum is a rough draft that should be considered as secondary to the BL letter, and that Sharp intended to publish the letter to the Admiralty.
Study on the Testing Method to Determine the Performance of Personal Respiratory Protection Equipment against a Viral Aerosol

Respiratory illnesses are increasingly recognized as a growing concern for healthcare workers (HCWs) and patients. The 2003 hospital-based outbreak of Severe Acute Respiratory Syndrome (SARS) has once again highlighted the vulnerability of HCWs to aerosol-transmitted viral infections. Personal respiratory protective equipment was one of the key means for the HCWs to avoid nosocomial transmission of the virus. This article studied a testing method for determining the performance of personal respiratory protection equipment against a viral aerosol. Full-mask respirators with HEPA filters were selected for this study. Phage f2 was used as a surrogate for a viral pathogen. A viral aerosol was generated and then sampled in front of and behind the test respirators, allowing a percentage efficiency value to be calculated against viral aerosols. HEPA-filtered respirators demonstrated a high filtration efficiency of >99.99% and can protect the wearers against the viral aerosol transmission. This test methodology can be used to assess the filtration efficacy of personal respiratory protection equipment against a viral aerosol.
Human action recognition with spatial-temporal feature filter

Spatial-temporal interest points (STIP) is the main method in human action recognition. However, there are some STIPs with low discriminative power for action recognition and weak ability for classification. To resolve the problem and achieve high recognition accuracy, this paper proposes a variance filter method for STIP selection. Finally, various experiments are conducted to prove that variance filter for STIP selection for action classification is superior to existing methods based on STIPs.