Miracle-dz/UniFAR-FTUs huggingface dataset:
Lentivirus vector-mediated mitofusin-2 overexpression in rat ovary changes endocrine function and promotes follicular development in vivo

The aim of the present study was to evaluate the expression and effect of rat mitofusin-2 (rMfn2) in the ovaries and other organs in rats. Rat models were developed by the intraovarian microinjection of an rMfn2-overexpressing lentiviral vector. Lenti-green fluorescent protein (GFP)-rMfn2 was microinjected into rat ovaries at a dosage of 2×106 tuberculin units virosome (n=25) and lenti-GFP was microinjected as a control (n=25). The expression of rMfn2 in the ovaries and other tissues was observed by fluorescence microscopy on days 7, 15, 30, 45 and 60 after the microinjection (n=5/day from each group). The serum levels of estradiol (E2), progesterone (P), follicle-stimulating hormone (FSH) and luteinizing hormone (LH) were determined by radioimmunoassay. Western blotting was used for the quantitative analysis of the expression of rMfn2 and the progesterone receptor (PR), estradiol receptor (ER), luteinizing hormone receptor (LHR) and follicle-stimulating hormone receptor (FSHR). The expression of rMfn2 was detected on day 7 after infection, increased with time and was maintained efficiently until day 60. In addition, rMfn2 was highly expressed in the fallopian tubes, uterus, cardiac muscle, liver and kidney, but expressed at a low level in adipose tissue. The serum levels of E2 and P in the model group were significantly increased compared with those in the control group, whereas the FSH and LH levels showed no significant difference between groups. The expression levels of the ER and PR in the model group were higher than those in the control group; however, no significant difference was observed between groups for the expression levels of LHR and FSHR. These findings suggest that the intraovarian microinjection of lenti-GFP-rMfn2 resulted in a significant time-dependent overexpression of rMfn2 in various organs, and that rMfn2 overexpression in rat ovaries changed the endocrine function and promoted follicular development.
A Ten-MicroRNA Signature Identified from a Genome-Wide MicroRNA Expression Profiling in Human Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most common gynecologic malignancy. To identify the micro-ribonucleic acids (miRNAs) expression profile in EOC tissues that may serve as a novel diagnostic biomarker for EOC detection, the expression of 1722 miRNAs from 15 normal ovarian tissue samples and 48 ovarian cancer samples was profiled by using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. A ten-microRNA signature (hsa-miR-1271-5p, hsa-miR-574-3p, hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-182-3p, hsa-miR-141-5p, hsa-miR-130b-5p, and hsa-miR-135b-3p) was identified to be able to distinguish human ovarian cancer tissues from normal tissues with 97% sensitivity and 92% specificity. Two miRNA clusters of miR183-96-183 (miR-96-5p, and miR-182, miR183) and miR200 (miR-141-5p, miR200a, b, c and miR429) are significantly up-regulated in ovarian cancer tissue samples compared to those of normal tissue samples, suggesting theses miRNAs may be involved in ovarian cancer development.
Association of Cannabis With Cognitive Functioning in Adolescents and Young Adults: A Systematic Review and Meta-analysis

Importance Substantial shifts in perception and policy regarding cannabis have recently occurred, with use of cannabis increasing while its perceived harm decreases. One possible risk of increased cannabis use is poorer cognitive functioning, especially in youth. Objective To provide the first quantitative synthesis of the literature examining cannabis and cognitive functioning in adolescents and young adults (with a mean age of 26 years and younger). Data Sources PubMed, PsycInfo, Academic Search Premier, Scopus, and bibliographies of relevant reviews were searched for peer-reviewed, English-language studies from the date the databases began through May 2017. Study Selection Consensus criteria were used to determine study inclusion through abstract and manuscript review. Data Extraction and Synthesis This study followed Meta-analysis of Observational Studies in Epidemiology guidelines. Effect size estimates were calculated using multivariate mixed-effects models for cognitive functioning outcomes classified into 10 domains. Main Outcomes and Measures Results from neurocognitive tests administered in cross-sectional studies were primary outcomes, and we examined the influence of a priori explanatory variables on variability in effect size. Results Sixty-nine studies of 2152 cannabis users (mean [SD] age, 20.6 [2.8] years; 1472 [68.4%] male) and 6575 comparison participants with minimal cannabis exposure were included (mean [SD] age, 20.8 [3.4]; 3669 [55.8%] male). Results indicated a small overall effect size (presented as mean d) for reduced cognitive functioning associated with frequent or heavy cannabis use (d, −0.25; 95% CI, −0.32 to −0.17; P < .001). The magnitude of effect sizes did not vary by sample age or age at cannabis use onset. However, studies requiring an abstinence period longer than 72 hours (15 studies; n = 928) had an overall effect size (d, −0.08; 95% CI, −0.22 to 0.07) that was not significantly different from 0 and smaller than studies with less stringent abstinence criteria (54 studies; n = 7799; d, −0.30; 95% CI, −0.37 to −0.22; P = .01). Conclusions and Relevance Associations between cannabis use and cognitive functioning in cross-sectional studies of adolescents and young adults are small and may be of questionable clinical importance for most individuals. Furthermore, abstinence of longer than 72 hours diminishes cognitive deficits associated with cannabis use. Although other outcomes (eg, psychosis) were not examined in the included studies, results indicate that previous studies of cannabis in youth may have overstated the magnitude and persistence of cognitive deficits associated with use. Reported deficits may reflect residual effects from acute use or withdrawal. Future studies should examine individual differences in susceptibility to cannabis-associated cognitive dysfunction.
Proposed Solutions to the Tripper Car Positioning Problem

The trippers are equipments often found in mineral processing plants. Their role is to distribute ore coming from past stages of process in a silo with several hoppers. Positioning trippers is a scheduling problem defined by position determination of the equipment through the bins and along time. The system silo-tripper was modeled as a combinatorial linear optimization program aiming to get the optimal tripper positioning. Two paradigms were used to find out an exact solution: mixed integer linear programming and dynamic programming.
Battery drain in daily practice and medium-term projections on longevity of cardioverter-defibrillators: an analysis from a remote monitoring database

Aims The longevity of generators is a crucial determinant of the cost-effectiveness of therapy with implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy defibrillators (CRT-D). We evaluated the trend of device-measured residual battery capacity and longevity projections over 5-year follow-up. We also investigated possible factors associated with battery drain. Methods and results Data from 4851 patients in the European LATITUDE® database who were followed up for a minimum of 3 years were analysed. The factors associated with battery drain (i.e. year-to-year decrease in residual battery capacity), and thus potentially impacting on device longevity, were mainly the pacing parameters in CRT-D devices and the number of shocks delivered and diverted in both ICD and CRT-D (all P < 0.01 on linear regression analysis). Over the first 5 years, the longevity estimates provided by devices showed low intra-patient variability and increased with time. The estimates exceeded 10 years for CRT-D and 13 and 12 years for single- and dual-chamber ICDs, respectively. In CRT-D patients, the expected patient age on replacement was 80 ± 12 years, and the expected probability of undergoing device replacement was 63 ± 13% for New York Heart Association (NYHA) II patients and 37 ± 16% for NYHA III patients. For comparison, the probabilities of replacing a CRT-D lasting 5 years were 78 ± 8 and 59 ± 13%, respectively (both P < 0.001). Conclusion Battery drain was mainly associated with pacing output in CRT-D devices and with the number of capacitor charges in both ICD and CRT-D devices. The longevity estimates provided by the devices were consistent and conservative. According to these estimates, among CRT-D recipients a low proportion of patients should require device replacement.
Student evaluation of teachers : Effects of grading at college level

A preexperiment involving pretest and posttest was conducted to examine whether grades received affect students' evaluations of their instructors. Responses from 96 college students on the pretests and posttests were paired to observe individual and overall changes in evaluations. The results indicate that both received grades and discrepancies between received grades and expected grades affect teaching evaluations. The latter might function as a mechanism by which grades and evaluations are related. Because grade expectations play an important part in teaching evaluations, an instructor is able to achieve better teaching effectiveness ratings by assigning good grades to the students. This article suggests that numerical evaluations and grade records be examined simultaneously to better determine teaching effectiveness.
Mongolian Named Entity Recognition System with Rich Features

In this paper, we first build a manually annotated named entity corpus of Mongolian. Then, we propose three morphological processing methods and study comprehensive features, including syllable features, lexical features, context features, morphological features and semantic features in Mongolian named entity recognition. Moreover, we also evaluate the influence of word cluster features on the system and combine all features together eventually. The experimental result shows that segmenting each suffix into an individual token achieves better results than deleting suffixes or using the suffixes as feature. The system based on segmenting suffixes with all proposed features yields benchmark result of F-measure=84.65 on this corpus.
On the Suboptimality of Single-Factor Exercise Strategies for Bermudan Swaptions

In this paper we examine the cost of using recalibrated single-factor models to determine the exercise strategy for Bermudan swaptions in a multi-factor world. We demonstrate that single-factor exercise strategies applied in a multi-factor world only give rise to economically insignificant losses. Furthermore, we find that the conditional model risk as defined in Longstaﬀ, Santa-Clara & Schwartz (2001), is statistically insignificant given the number of observations. Additional tests using the Primal-Dual algorithm of Andersen & Broadie (2001) indicate that losses found in Longstaﬀ et al. (2001) cannot as claimed be ascribed to the number of factors. Finally we find that for valuation of Bermudan swaptions with long exercise periods, the simple approach proposed in Andersen (2000) is outperformed by the Least Square Monte Carlo method of Longstaﬀ & Schwartz (2001) and, surprisingly, also by the exercise strategies from the single-factor models.
Distribution-Based Active Contour Model for Medical Image Segmentation

Having being regarded as one of the classical methods in image segmentation, geodesic active contours (GAC) have the flaws of boundary leaking and expensive evolving time. In this paper, we present a distribution-based active contour model by measuring the Bhattacharyya distance between probability distributions of the object and background along with the evolution of GAC model. Due to combining the image cues of edge and statistical information which is computed by using kernel density estimation, this hybrid methodology prevents the boundary leaking as well as the under segmentation problem. Experimental results on the medical images show the improvements of our method in terms of comparisons with original GAC model, Bhattacharyya gradient flow, texture-based GAC and Li's active contour model.
Cytochrome P450 Expression and Regulation in CYP3A4/CYP2D6 Double Transgenic Humanized Mice

Analysis of the developmental and sexual expression of cytochrome P450 drug-metabolizing enzymes is impeded by multiple and varied external factors that influence its regulation. In the present study, a CYP2D6/CYP3A4-double transgenic (Tg-CYP2D6/CYP3A4) mouse model was employed to investigate hepatic CYP2D6 and CYP3A4 ontogeny and sexual dimorphism. Both age and sex have considerable effects on hepatic CYP3A4 protein expression in 3- to 8-week-old transgenic mice, whereas neither factor alters CYP2D6 content. Constitutive CYP2D6 expression resulted in 2- to 3-fold higher dextromethorphan O-demethylase activity in Tg-CYP2D6/CYP3A4 mouse liver microsomes compared with wild-type mice. In contrast, expression of CYP3A4 in transgenic mouse livers did not increase dextromethorphan N-demethylase and midazolam 1′-hydroxylase activities. Pretreatment with pregnenolone 16α-carbonitrile (PCN) and 1,4-bis-2-(3, 5-dichloropyridyloxy)-benzene (TCPOBOP) elevated CYP3A4 expression in double transgenic mice. Interestingly, induction of hepatic CYP3A4 was greater in females than age- and treatment-matched males. Consequently, the increase in midazolam 1′-hydroxylase activity was markedly higher in 8-week-old female mice than in corresponding males (8-fold versus 6-fold for PCN treatment and 6-fold versus 5-fold for TCPOBOP). Furthermore, increases in testosterone 6β-hydroxylase activity after CYP3A induction were relatively lower compared with those in midazolam 1′-hydroxylation for age-, sex-, and treatment-matched mice. The difference in CYP3A4 expression and induction between male and female mice suggests that women may be more susceptible to CYP3A4-mediated drug-drug interactions, and the extent of drug-drug interactions could be substrate dependent.
Evidence for training-induced crossmodal reorganization of cortical functions in trumpet players

The aim of this study was to compare multimodal information processing in the somatosensory and auditory cortices and related multimodal areas in musicians (trumpet players) and non-musicians. Magnetoencephalographic activity (MEG) was recorded in response to five stimulus conditions from 10 professional trumpet players and nine musically untrained control subjects. Somatosensory and auditory stimuli were presented alone or in combination. Our data suggest that musicians, in general, process multisensory stimuli differently to the control group. When stimulating the lip in professional trumpet players, a multimodal interaction (expressed as difference between the multimodal response and the sum of unimodal responses) in the corresponding somatosensory cortex showed a positive peak at 33 ms, which was not found in the control group. Conversely, the control group shows a significant interaction of opposite polarity around 60–80 ms. We suggest that training-induced reorganization in musicians leads to a qualitatively different way to process multisensory information. It favors an early stage of cortical processing, which is modified by the connections between multimodal and auditory neurons from thalamus to primary somatosensory area.
Contextual Combinatorial Cascading Bandits

We propose the contextual combinatorial cascading bandits, a combinatorial online learning game, where at each time step a learning agent is given a set of contextual information, then selects a list of items, and observes stochastic outcomes of a prefix in the selected items by some stopping criterion. In online recommendation, the stopping criterion might be the first item a user selects; in network routing, the stopping criterion might be the first edge blocked in a path. We consider position discounts in the list order, so that the agent's reward is discounted depending on the position where the stopping criterion is met. We design a UCB-type algorithm, C3-UCB, for this problem, prove an n-step regret bound O(√n) in the general setting, and give finer analysis for two special cases. Our work generalizes existing studies in several directions, including contextual information, position discounts, and a more general cascading bandit model. Experiments on synthetic and real datasets demonstrate the advantage of involving contextual information and position discounts.
Blind separation of binaural sound mixtures using SIMO-model-based independent component analysis

High-fidelity blind audio signal separation is addressed, adopting the extended ICA algorithm, single-input multiple-output (SIMO)-model-based ICA. The SIMO-ICA consists of multiple ICA parts and a fidelity controller, and each ICA runs in parallel under fidelity control of the entire separation system. SIMO-ICA can separate the mixed signals, not into monaural source signals, but into SIMO-model-based signals from independent sources as they are at the microphones. Thus, the separated signals of the SIMO-ICA can maintain the spatial qualities of each sound source. We apply the SIMO-ICA to the problem of blind separation of mixed binaural sounds, including the effect of the head-related transfer function (HRTF). Experimental results reveal that the performance of the proposed SIMO-ICA is superior to that of the conventional ICA-based method, and the separated signals of SIMO-ICA maintain the spatial qualities of each sound source.
Eigenvalues and the Laplacian of a graph

Spectral graph theory has a long history. In the early days, matrix theory and linear algebra were used to analyze adjacency matrices of graphs. Algebraic methods have proven to be especially effective in treating graphs which are regular and symmetric. Sometimes, certain eigenvalues have been referred to as the “algebraic connectivity” of a graph [127]. There is a large literature on algebraic aspects of spectral graph theory, well documented in several surveys and books, such as Biggs [26], Cvetković, Doob and Sachs [93] (also see [94]) and Seidel [228].
EXPLORING SHORT GAMMA-RAY BURSTS AS GRAVITATIONAL-WAVE STANDARD SIRENS

Recent observations support the hypothesis that a large fraction of “short-hard” gamma-ray bursts (SHBs) are associated with the inspiral and merger of compact binaries. Since gravitational-wave (GW) measurements of well-localized inspiraling binaries can measure absolute source distances, simultaneous observation of a binary's GWs and SHB would allow us to directly and independently determine both the binary's luminosity distance and its redshift. Such a “standard siren” (the GW analog of a standard candle) would provide an excellent probe of the nearby (z ≲ 0.3) universe's expansion, independent of the cosmological distance ladder, thereby complementing other standard candles. Previous work explored this idea using a simplified formalism to study measurement by advanced GW detector networks, incorporating a high signal-to-noise ratio limit to describe the probability distribution for measured parameters. In this paper, we eliminate this simplification, constructing distributions with a Markov Chain Monte Carlo technique. We assume that each SHB observation gives source sky position and time of coalescence, and we take non-spinning binary neutron star and black hole–neutron star coalescences as plausible SHB progenitors. We examine how well parameters (particularly distance) can be measured from GW observations of SHBs by a range of ground-based detector networks. We find that earlier estimates overstate how well distances can be measured, even at fairly large signal-to-noise ratio. The fundamental limitation to determining distance proves to be a degeneracy between distance and source inclination. Overcoming this limitation requires that we either break this degeneracy, or measure enough sources to broadly sample the inclination distribution.
Tree Cache – A Novel Approach to Non-Uniform Access Latency Cache Architectures for 3 D CMPs

This paper studies a new query on uncertain data, called k-selection query. Given an uncertain dataset of N objects, where each object is associated with a ranking score and a presence probability, a k-selection query returns k objects such that the expected ranking score of the best available objects is maximized. This query is useful in several applications such as information retrieval and decision making etc. In evaluating kselection queries, we need to tackle the challenges in computing the expected maximum score (EMS) for a candidate set and searching for the optimal result set with the highest EMS, both of which involve extremely large search space. In this paper, we identify several important properties of k-selection queries, including EMS decomposition, query recursion, and EMS bounding. Based upon these properties, we first present a dynamic programming (DP) algorithm that finds the optimal k-selection results in O(k ·N) time. Further, we propose another algorithm, called the Bounding-and-Pruning (BP) algorithm, that exploits effective search space pruning strategies to find the optimal selection without accessing low score data objects. We evaluate the DP and BP algorithms using both synthetic and real-world data. The results show that the proposed solutions outperform the naive approach by several orders of magnitude, and can efficiently answer k-selection queries over 100,000-object datasets within 1 second.
Cooperation without Communication : the problems of highly distributed working

The aim of this paper is to highlight the problems of highly distributed workers: mobile workers, tele-workers and those separated by slow networks. These are characterised by the intermittent nature of their communications. The standard time/space matrix is extended in order to adequately describe these workers, in the process revealing the ambiguity of the term ‘asynchronous’ as applied to groupware. Two specific problems areas are discussed: establishing context in direct communication and re-synchronisation of different versions of shared objects after periods of concurrent working. Nevertheless, patterns of individual work in these settings suggest a strong potential market for groupware.
Computer Administering of the Psychological Investigations: Set-relational Representation

Computer administering of a psychological investigation is the computer representation of the entire procedure of psychological assessments—test construction, test implementation, results evaluation, storage and maintenance of the developed database, its statistical processing, analysis and interpretation. A mathematical description of psychological assessment with the aid of personality tests is discussed in this article. The set theory and the relational algebra are used in this description. A relational model of data, needed to design a computer system for automation of certain psychological assessments is given. Some finite sets and relation on them, which are necessary for creating a personality psychological test, are described. The described model could be used to develop real software for computer administering of any psychological test and there is full automation of the whole process: test construction, test implementation, result evaluation, storage of the developed database, statistical implementation, analysis and interpretation. A software project for computer administering personality psychological tests is suggested.