Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulation of Ca2+ Signaling by Anti-apoptotic B-Cell Lymphoma 2 Proteins at the Endoplasmic Reticulum–Mitochondrial Interface

Mitochondria are important regulators of cell death and cell survival. Mitochondrial Ca2+ levels are critically involved in both of these processes. On the one hand, excessive mitochondrial Ca2+ leads to Ca2+-induced mitochondrial outer membrane permeabilization and thus apoptosis. On the other hand, mitochondria need Ca2+ in order to efficiently fuel the tricarboxylic acid cycle and maintain adequate mitochondrial bioenergetics. For obtaining this Ca2+, the mitochondria are largely dependent on close contact sites with the endoplasmic reticulum (ER), the so-called mitochondria-associated ER membranes. There, the inositol 1,4,5-trisphosphate receptors are responsible for the Ca2+ release from the ER. It comes as no surprise that this Ca2+ release from the ER and the subsequent Ca2+ uptake at the mitochondria are finely regulated. Cancer cells often modulate ER-Ca2+ transfer to the mitochondria in order to promote cell survival and to inhibit cell death. Important regulators of these Ca2+ signals and the onset of cancer are the B-cell lymphoma 2 (Bcl-2) family of proteins. An increasing number of reports highlight the ability of these Bcl-2-protein family members to finely regulate Ca2+ transfer from ER to mitochondria both in healthy cells and in cancer. In this review, we focus on recent insights into the dynamic regulation of ER–mitochondrial Ca2+ fluxes by Bcl-2-family members and how this impacts cell survival, cell death and mitochondrial energy production.
Sense-Making and Synchronicity: Information-Seeking Behaviors of Millennials and Baby Boomers

A challenge facing libraries is to develop and update collections and services to meet the needs of the multiple generations of users with differing approaches to information seeking. The different characteristics and information needs of ‘Baby Boomers’ and ‘Millennials’ present a dichotomy for library service and system development. Results are reported here for two research projects that investigated habits and needs of library users and non-users. Both studies sought to identify how and why individuals seek and use information. The first study deals with the findings of focus group interviews with seventy-eight randomly selected participants, and fifteen semi-structured interviews with a subset of these participants. The second study reports the results of focus group interviews with twenty-three Millennials, and an analysis of 492 virtual reference services (VRS) transcripts. The studies indicate that both generations consistently identify Google and human sources as the first sources they use for quick searches. The younger Millennials mentioned consulting parents most frequently, while the older Millennials consult friends and professors. Baby Boomers indicate that they consult their personal libraries and colleagues. The findings have implications for the development of next generation library online catalogs, as well as services, including VRS.
Behavioral Differences in School Age Children after Perinatal Stroke

Little is known about the influence of the right hemisphere (RH) on social and emotional development in children. In order to examine the effect of RH damage on behavioral function, the Personality Inventory for Children was administered to parents of 17 children who had suffered perinatal strokes and 23 control children. Children with focal brain lesions, regardless of hemisphere, had higher T scores (indicating greater abnormality) than controls on scales measuring social competence, emotional behavior, cognitive and academic development. Children with lesions involving the frontal lobe obtained higher T scores than did those with nonfrontal lesions or controls on scales related to cognitive function. The nonfrontal group had higher T scores than those with frontal lesions on measures of social competence and behavior. The data suggest that any focal brain lesion of early onset may predispose one to social and cognitive deficits. The site of the lesion within the hemisphere may be of importance in determining what difficulties the child may experience (i.e., frontal lobe lesions are more likely to result in cognitive deficits, whereas posterior lesions are more likely to be associated with social problems). These findings further suggest that brain localization for cognitive and social skills may be determined very early in development.
Control of step-down DC-DC power converter with LCL output filter feeding a constant power load

This paper proposes a control strategy for a step-down Buck power converter with LCL output filter feeding a constant power load. The control strategy uses exact feedback linearization, including the power estimation of the load. This allows to obtain fast response when the power demanded changes between different values. The power estimate is obtained by using a non-linear reduced-order observer with linear error dynamics. Hence, the control strategy uses a reduced number of sensors, increasing reliability and reducing the cost of the system. The system performance obtained with the proposed control strategy is tested through numerical simulations.
An accelerometer-based gesture recognition algorithm and its application for 3D interaction

This paper proposes an accelerometer-based gesture recognition algorithm. As a pre-process procedure, raw data output by accelerometer should be quantized, and then use discrete Hidden Markov Model to train and recognize them. Based upon this recognition algorithm, we treat gesture as a method of human-computer interaction and use it in 3D interaction subsystem in VR system named VDOM by following steps: establish Gesture-Semantic Map, train standard gestures, finally do recognition. Experimental results show that the system can recognize input gestures quickly with a reliable recognition rate. The users are able to perform most of the typical interaction tasks in virtual environment by this accelerometer-based device.
ON THE ANALYSIS OF LARGE-SCALE DATASETS TOWARDS ONLINE CONTEXTUAL ADVERTISING

STRACT With the rise of the internet, there came the rise of online advertising. It in turn has been playing a growing part in shaping and supporting the development of the Web. In contextual advertising, ad messages are displayed related to the content of the target page. It leads to the problem in information retrieval community: how to select the most matching ad messages given the content of a web page. While retrieval algorithms, such as determining the similarities by calculating overlapping words, can propose somewhat related ad messages, the problem of contextual matching requires a higher precision. As words can have multiple meanings and there are many unrelated words in a web page, it can lead to the miss-match. To deal with this problem, we propose another approach to contextual advertising by taking advantage of large scale external datasets. Using a hidden topic analysis model, we add analyzed topics to each web page and ad message. By expanding them with hidden topics, we have decreased their vocabularies' difference and improved the matching quality by taking into account their latent semantic relations. Our framework has been evaluated through a number of experiments. It shows a significant improvement in accuracy over the current retrieval method. ABSTRACT With the rise of the internet, there came the rise of online advertising. It in turn has been playing a growing part in shaping and supporting the development of the Web. In contextual advertising, ad messages are displayed related to the content of the target page. It leads to the problem in information retrieval community: how to select the most matching ad messages given the content of a web page. While retrieval algorithms, such as determining the similarities by calculating overlapping words, can propose somewhat related ad messages, the problem of contextual matching requires a higher precision. As words can have multiple meanings and there are many unrelated words in a web page, it can lead to the miss-match. To deal with this problem, we propose another approach to contextual advertising by taking advantage of large scale external datasets. Using a hidden topic analysis model, we add analyzed topics to each web page and ad message. By expanding them with hidden topics, we have decreased their vocabularies' difference and improved the matching quality by taking into account their latent semantic relations. Our framework has been evaluated through a number of experiments. It shows a significant …
Factors influencing adherence to paediatric antiretroviral therapy in Portharcourt, South- South Nigeria

Introduction The efficiency of antiretroviral therapy (ART) depends on a near-perfect level of patient's adherence. Adherence in children poses peculiar challenges. The aim of the study was to determine the adherence level and factors influencing adherence among HIV-infected children and adolescents in University of Port Harcourt Teaching Hospital, Nigeria. Methods A cross-sectional survey of HIV-infected children and adolescents on ART using self-report by the caregiver/child in the past one month. Results A total of 213 caregivers and their children were interviewed. A hundred and sixty-two (76.1%) had adherence rates ≥95%. Only 126 (59.2%) were completely (100%) adherent. The commonest caregiver-related factors for missing doses were forgetfulness 48(55.2%), travelled 22(25.3%) and drugs finished 16(18.4%), while the child-related factors were refused drugs 10(11.5%), slept 8(9.2%), and vomited 8(9.2%). Sixty-eight (31.9%) caregivers reported missing clinic visit and reasons given were travelled 18(26.5%), caregiver ill 12(17.6%) and family problems 9(13.2%). Predictors of poor adherence include mother as the primary caregiver (OR 3.32; 95%CI, 1.33-8.67), younger than 5years (OR 2.62; 95%CI, 1.30-5.31) and presence of a co-morbidity (OR 3.97; 95%CI, 1.92-8.33). Having a medication reminder strategy (OR 6.34; 95%CI, 3.04-13.31), regular clinic visits (OR 8.55; 95%CI 4.01-18.45) and status disclosure (p = 0.008) predicted a better adherence. The caregiver's age (p= 0.11), education (p = 0.86), socioeconomic status (p = 0.89), gender of the child (p = 0.84), type of ART (p = 0.2) and duration of ART (1.0) did not significantly affect adherence. Conclusion Adherence is still suboptimal. Since barriers to Paediatric ART adherence are largely caregiver-dependent, identifying and addressing these barriers in each caregiver-child pair will improve adherence and patient outcome.
Prospective early childhood educators’ meta-cognitive knowledge and teacher self-efficacy: exploring domain-specific associations

The present study explored South Korean prospective early childhood educators’ situation-specific meta-cognitive knowledge about five problem-solving strategies, investigating whether situated strategic knowledge contributed to teacher self-efficacy domains. Overall, pre-service teachers with higher meta-cognitive knowledge were found to have higher teacher self-efficacy, but the strength of correlations differed according to types of strategies (free production, analogy, step-by-step analysis, visualisation and combining) and situations (interpersonal, practical, study). Through multiple regressions, meta-cognitive knowledge of the strategy-free production in practical situations emerged as the most powerful contributor to all teacher self-efficacy domains. With meta-cognitive knowledge of free production in practical situations as a domain-general predictor, each teacher self-efficacy domain was also found to involve a unique set of meta-cognitive features as contributors. The facets of the predictors imply that combinations of relevant strategic knowledge contribute to confidence in specific teaching domains.
A Cryptographic Solution to Discretionary Access Control in Structurally Object-Oriented Databases

A new approach to the discretionary access control in structurally object-oriented databases is suggested. The approach is based on the use of pseudo-random functions and sibling intractable functions, rather than on the traditional access control list associated with each class. The advantage of this approach is that each class in the hierarchy of a complex object class can be associated with one access key such that it can be directly accessed by its ancestor without the need to pass through any intermediate classes. The security of the model depends on the diiculty of predicting the output of pseudo-random functions and on nding extra sibling collision for the sibling intractable function family.
Infectious Pulmonary Nodules in Immunocompromised Patients: Usefulness of Computed Tomography in Predicting Their Etiology

Purpose To review the high-resolution computed tomography (CT) findings in immunocompromised patients who had nodular opacities and a proven diagnosis to determine whether the various infectious pulmonary nodules have distinguishing features on CT. Materials and Methods The high-resolution CT scans obtained in 78 immunocompromised patients with solitary or multiple nodular opacities of proven infectious etiology were reviewed retrospectively by 2 independent thoracic radiologists. Patients whose predominant abnormality consisted of branching linear or nodular opacities (tree-in-bud pattern) characteristic of infectious bronchiolitis and endobronchial spread of tuberculosis were excluded. The CT scans were assessed for the presence, appearance, size, and distribution of parenchymal nodules. Relations between findings at CT and the different infectious etiologies of nodules were assessed with regression analysis. Agreement between the 2 observers was assessed using the &kgr; statistic. Results The infectious causes included mycobacteria (n = 24), fungi (n = 22), bacteria (n = 20), and viruses (n = 12). Multivariate analysis demonstrated that a diameter <10 mm was the only independent predictor of etiology (P < 0.0001) and that patients whose nodules all measured less than 10 mm in diameter were most likely to have a viral infection. Nodules limited in size to less than 10 mm in diameter were seen in 83% of viral infections compared with 5% of bacterial infections (odds ratio [OR] = 95.0; 95% confidence interval (CI): 6.08–4,321.5, P < 0.0001), 0% of mycobacterial infections (OR = 91.7; 95% CI: 7.21–4,090.22, P < 0.0001), and 14% of fungal infections (OR = 31.67; 95% CI: 3.56–375.09, P = 0.0003). Conclusion Although some overlap exists, nodule size is helpful in the differential diagnosis of infectious causes of nodules in immunocompromised patients. Patients whose nodules are all less than 10 mm in diameter are most likely to have a viral infection.
A fine pitch model for speech

An accurate model for the structure of speech is essential to many speech processing applications, including speech enhancement, synthesis, recognition, and coding. This paper explores some deficiencies of standard harmonic methods of modeling voiced speech. In particular, they ignore the effect of fundamental frequency changing within an analysis frame, and the fact that the fundamental frequency is not a continuously varying parameter, but a side effect of a series of discrete events. We present an alternative, time-series based framework for modeling the voicing structure of speech called the fine pitch model. By precisely modeling the voicing structure, it can more accurately account for the content in a voiced speech segment.
Incidence and the risk factor of malignancy in Japanese patients with systemic sclerosis.

OBJECTIVE To evaluate the incidence and risk factors for malignancy in Japanese patients with systemic sclerosis (SSc). METHODS A cohort of 405 Japanese patients with SSc who visited Kitasato University hospital between 1973 and 2008 was analyzed retrospectively until the end of 2009. The incidence of malignancy was compared with that of the general population, with calculation of the standardized incidence ratio (SIR) and 95% confidence interval (CI). RESULTS The cohort represented 4,787 person-years of total disease duration after the diagnosis of SSc. Of 27 malignancies clinically found, lung cancer (n=10, 37%), especially adenocarcinoma, was the most frequent, followed by breast (n=4, 15%) or gastric (n=3, 11%) cancer. SSc patients with overlapping CTD tended to have less malignancy. Multivariable analysis revealed heart involvement of SSc as a significant risk factor for breast cancer (RR 8.2, 95% CI 1.2-72.8). Other than gastric cancer, the calculated SIRs of malignancies in SSc patients were above 1 (SIR of overall malignancy 1.24, 95% CI 0.77-1.71), even though only lung cancer had a significantly elevated incidence (SIR 5.73, 95% CI 2.18-9.29). Every patient with lung cancer had interstitial lung disease (ILD) and every autopsy performed on patients with lung cancer found a primary lesion of lung cancer in their ILD lesion (n=4). CONCLUSION Lung cancer was significantly frequent in SSc patients, which could develop on the basis of complicated ILD.
Average electrical distance-based bus clustering method for network equivalence

Network equivalence is useful for electrical market analysis in large power networks. Generation shift factors (GSF)-based bus clustering methods have been used for network equivalence to analyze the impact of changes in transactions between operating areas or congestion zones on transmission line flows. However, GSFs are sensitive to the location change of slack generator. Equivalent networks based on GSF bus clustering methods change with the location of slack generator, which may increase the complexity of market behavior analysis in the equivalent networks. In this paper, we present a new bus clustering method for network equivalence based on the average electrical distance (AED) from buses to a designated transmission line. AED is independent of the location changes of slack generator in a power system, which can reduce the complexity of market behavior analysis in the equivalent network. The efficacy of the proposed method is demonstrated by comparing the proposed bus clustering method and GSF-based clustering method on the IEEE 39-bus system.
Estimating embedded data from clustered halftone dots via learned dictionary

Modulating the orientation of elliptically clustered dots in each halftone cell enables binary data to be embedded into the clustered halftone dots. In this paper, a new decoding method is proposed for recovering hidden binary data from clustered halftone dots by using learned dictionaries, which are optimized to represent clustered dots with different elliptical shapes. The basic idea is that the reconstruction errors of the clustered dots in a halftone cell are differentiable according to the dictionaries used. The experimental results showed that determining which of the learned dictionaries provides a minimum reconstruction error in a halftone cell can reveal the orientation of the clustered dots and thus indicate the embedded binary data. The experiment results also showed that the proposed decoding method can be applied to other types of clustered halftone dots to infer hidden binary data.
New Functions of Ctf18-RFC in Preserving Genome Stability outside Its Role in Sister Chromatid Cohesion

Expansion of DNA trinucleotide repeats causes at least 15 hereditary neurological diseases, and these repeats also undergo contraction and fragility. Current models to explain this genetic instability invoke erroneous DNA repair or aberrant replication. Here we show that CAG/CTG tracts are stabilized in Saccharomyces cerevisiae by the alternative clamp loader/unloader Ctf18-Dcc1-Ctf8-RFC complex (Ctf18-RFC). Mutants in Ctf18-RFC increased all three forms of triplet repeat instability—expansions, contractions, and fragility—with effect over a wide range of allele lengths from 20–155 repeats. Ctf18-RFC predominated among the three alternative clamp loaders, with mutants in Elg1-RFC or Rad24-RFC having less effect on trinucleotide repeats. Surprisingly, chl1, scc1-73, or scc2-4 mutants defective in sister chromatid cohesion (SCC) did not increase instability, suggesting that Ctf18-RFC protects triplet repeats independently of SCC. Instead, three results suggest novel roles for Ctf18-RFC in facilitating genomic stability. First, genetic instability in mutants of Ctf18-RFC was exacerbated by simultaneous deletion of the fork stabilizer Mrc1, but suppressed by deletion of the repair protein Rad52. Second, single-cell analysis showed that mutants in Ctf18-RFC had a slowed S phase and a striking G2/M accumulation, often with an abnormal multi-budded morphology. Third, ctf18 cells exhibit increased Rad52 foci in S phase, often persisting into G2, indicative of high levels of DNA damage. The presence of a repeat tract greatly magnified the ctf18 phenotypes. Together these results indicate that Ctf18-RFC has additional important functions in preserving genome stability, besides its role in SCC, which we propose include lesion bypass by replication forks and post-replication repair.
Modèles de Documents Parcimonieux basés sur les annotations et les " word embeddings " -Application à la personnalisation

RÉSUMÉ. Nous présentons dans cet article des modèles de langues parcimonieux sociaux de documents qui permettent de détecter les termes les plus importants du document et d’éliminer les termes communs ou non signiﬁcatifs. La détection de ces termes est guidée et renforcée par les liens entre les termes du document et ses annotations sociales (tags). En prenant le contre-pied des approches classiques de personnalisation qui généralement s’intéressent en priorité aux proﬁls utilisateurs ou à la fonction de correspondance, notre proposition porte sur la mise en avant des termes les plus importants des documents aﬁn de mieux personnaliser les réponses. Les évaluations effectuées sur le corpus Social Book Search 2016 montrent que nos propositions apportent dans certains cas une amélioration aux modèles de l’état de l’art. ABSTRACT. In this paper, we deﬁne social parcimonious language models that emphasize the most important terms in documents, and lower less important terms. The detection of important terms relies on the document itsef and on the tags that were employed by users to describe the document. Conversely to classical personalization approaches that focus ﬁrst on user’s proﬁles or on the matching function, our proposal focuses on the documents representations. Evaluation achieved on the Social Book Search 2016 collection show that our proposal outperforms reference approaches in several cases.
The Reality Monitoring Deficit as a Common Neuropsychological Correlate of Schizophrenic and Affective Psychosis

For many decades, Neuropsychological functioning has been a key point in the study of psychotic disorders. The main aim of these studies is to give a description of the neurocognitive “profile” of schizophrenia, with only little attention being paid to the common and discriminating features of different psychotic disorders. Recent studies support the hypothesis that patients affected by psychiatric disorders with psychotic symptoms have specific abnormalities of reality testing of ongoing perception, which become evident with source monitoring task. Ninety-eight patients and 50 controls were studied. Patients were divided by diagnosis and previous history of psychotic features and were administered Source Monitoring Task to test reality testing of ongoing perception. Frequencies of correct and false attributions were recorded. To obtain measures of observer sensitivity and response biases, a signal detection analysis was performed. Aims: Studying neuropsychological correlate of psychosis in euthymic mood disordered patients and patients with schizophrenia with or without delusions. Results: Patients with psychotic features use more lax criteria in evaluating self-generated, but not perceived stimuli compared to patients without psychotic features. Conclusions: Our findings support the hypothesis of selective biases in reality monitoring as neuropsychological correlates of psychosis.