Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Bounding Syntactic Resources on Presburger LTL

We study decidability and complexity issues for fragments of LTL with Presburger constraints by restricting the syntactic resources of the formulae (the class of constraints, the number of variables and the distance between two states for which counters can be compared) while preserving the strength of the logical operators. We provide a complete picture refining known results from the literature, in some cases pushing forward the known decidability limits. By way of example, we show that model-checking formulae from LTL with quantifier-free Presburger arithmetic over one-counter automata is only PSPACE-complete. In order to establish the PSPACE upper bound, we show that the nonemptiness problem for Buchi one-counter automata taking values in Z and allowing zero tests and sign tests, is only NLOGSPACE-complete.
Creativity in entrepreneurship education

This paper uses social cognitive theory to investigate entrepreneurial intent among participants in graduate entrepreneurship programs. To the best of our knowledge, the paper is the first to investigate the importance of creativity in entrepreneurship education and theoretical models of entrepreneurial intentions. Specifically, we test whether students creative potential is related to their intention to engage in entrepreneurship. Theoretically derived hypotheses are tested using multiple and ordinal regression analyses. We find that high scores on a creativity test and prior entrepreneurial experiences were positively associated with entrepreneurial intentions, whereas perception of risks had a negative influence. Our theoretical predictors of entreprenurial intention received strong support, indicating that creativity should be considered in models of entrepreneurial intentions. Yet, the use of intentions as dependent variable has its know weaknesses in that we might not distinguish between 'dreamers' and 'doers'. The findings indicate that exercises in creativity can be used to raise entrepreneurial intentions of students in entrepreneurship education. Heterogeneity in creative styles among students also points to the problems of a ‘one-size-fits-all’ approach to entrepreneurship education.
InfTucker: t-Process based Infinite Tensor Decomposition

Tensor decomposition is a powerful tool for multiway data analysis. Many popular tensor decomposition approaches—such as the Tucker decomposition and CANDECOMP/PARAFAC (CP)—conduct multi-linear factorization. They are insufficient to model (i) complex interactions between data entities, (ii) various data types (e.g. missing data and binary data), and (iii) noisy observations and out-liers. To address these issues, we propose a tensor-variate latent t process model, InfTucker, for robust multiway data analysis: it conducts robust Tucker decomposition in an infinite feature space. Unlike classical tensor decomposition models, it handles both continuous and binary data in a probabilistic framework. Unlike previous nonparametric Bayesian models on matrices and tensors, our latent t-process model focuses on multiway analysis and uses nonlinear covariance functions. To efficiently learn InfTucker from data, we develop a novel variational inference technique on tensors. Compared with classical implementation, the new technique reduces both time and space complexities by several orders of magnitude. This technique can be easily adopted in other contexts (e.g. , multitask learning) where we encounter tensor-variate t processes or Gaussian processes. Our experimental results on chemometrics and social network datasets demonstrate that the new InfTucker model achieves significantly higher prediction accuracy than several state-of-art tensor decomposition approaches including High Order Singular Value Decomposition (HOSVD), Weighted CP, and nonnegative tensor decomposition .
CMV‐Specific CD8+ T‐Cell Dynamics in the Blood and the Lung Allograft Reflect Viral Reactivation Following Lung Transplantation

Despite the potentially high burden of cytomegalovirus (CMV)‐related disease following lung transplantation, the role of the cytotoxic T‐lymphocyte (CTL) response to CMV in this patient group is ill‐defined. We assessed the CMV‐specific T‐cell response in the blood and lung allograft of immunosuppressed lung transplant recipients receiving antiviral prophylaxis and following their withdrawal. While the proportion of CMV‐specific CTL varied between patients, in the absence of CMV reactivation the level of CMV‐specific CD8+ T cells in the blood remained stable over time. In the majority of patients CMV‐specific cells could be detected in the lung allograft, often in the absence of viral DNA. Additionally, following primary CMV lung infection, CMV‐specific CD8+ T cells were detected no earlier than 100 days post‐transplantation but still prior to the detection of viral DNA in the lung allograft. Together these findings suggest that very low levels of CMV replication are sufficient to both prime and recruit CMV‐specific CD8+ T cells to the MHC‐mismatched lung allograft. The direct detection of CMV‐specific T cells with an effector phenotype in the lung allograft suggests a protective antiviral function. This study provides a framework upon which the association between CMV and chronic allograft rejection can be further studied.
A Feature Point Matching Based on Spatial Order Constraints Bilateral-Neighbor Vote

Feature point matching is a fundamental and challenging problem in many computer vision applications. In this paper, a robust feature point matching algorithm named spatial order constraints bilateral-neighbor vote (SOCBV) is proposed to remove outliers for a set of matches (including outliers) between two images. A directed k nearest neighbor (knn) graph of match sets is generated, and the problem of feature point matching is formulated as a binary discrimination problem. In the discrimination process, the class labeled matrix is built via the spatial order constraints defined on the edges that connect a point to its knn. Then, the posterior inlier class probability of each match is estimated with the knn density estimation and spatial order constraints. The vote of each match is determined by averaging all posterior class probabilities that originate from its associative inliers set and is used for removing outliers. The algorithm iteratively removes outliers from the directed graph and recomputes the votes until the stopping condition is satisfied. Compared with other popular algorithms, such as RANSAC, RSOC, GTM, SOC and WGTM, experiments under various testing data sets demonstrate strong robustness for the proposed algorithm.
Sociodemographic and Clinical Characteristics of Psychiatric Inpatients Hospitalized Involuntarily and Voluntarily in a Mental Health Hospital.

INTRODUCTION In this study, we aimed to investigate and compare the sociodemographic and clinical characteristics of psychiatric inpatients hospitalized involuntarily and voluntarily. To our knowledge, there is no study analyzing involuntary psychiatric hospitalization in our country. METHOD In this retrospective study, we included a total of 504 patients who were involuntarily or voluntarily hospitalized in Bolu Izzet Baysal Mental Health Hospital between 1st of May and 31st October 2010. The data were obtained from the hospital records. RESULT In the 6-month period, 13.1% of 504 inpatients were hospitalized involuntarily. The number of male patients who were involuntarily hospitalized was higher than the number of female patients. Most of the patients in the involuntary hospitalized group were graduates of primary school, were not married and were not working at the time of hospitalization. Schizophrenia was the most common diagnosis in the involuntarily hospitalized psychiatric patients and these patients needed longer stay in the hospital. The next hospitalization of the involuntarily hospitalized patients was mostly involuntary. CONCLUSION Most of the involuntarily hospitalized psychiatric inpatients were male, were not working and had the diagnosis of schizophrenia. These general psychiatric risk factors were more important in involuntary hospitalization compared to voluntary hospitalization. We concluded that the high prevalence of involuntary hospitalizations deserved further studies.
Cost evaluation of current uprating of overhead transmission lines using ACSR and HTLS conductors

This work presents cost evaluation of current uprating of overhead transmission lines by using Aluminum Conductor Steel Reinforced (ACSR) and High Temperature Low Sag (HTLS) conductors. The evaluation method is carried out based on twofold and fourfold ampacities, under both normal and stressed operating conditions. The test case is a 230-kV, double-circuit, transmission lines using 1272 MCM ACSR conductors. The candidate conductors are five types of HTLS conductors with comparable size. The cost components under consideration are demolition cost, construction and installation costs, conductor cost, cost of energy losses, and land cost. Upon evaluation of the total costs, the selection criteria of proper conductor are proposed.
MAP Decoding of Correlated Sources over Soft-Decision Orthogonal Multiple Access Fading Channels with Memory

We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error correcting code, over a multiple access channel (MAC) which consists of two orthogonal point-to- point time-correlated Rayleigh fading sub-channels with soft- decision demodulation. At the receiver side, a joint sequence maximum a posteriori (MAP) detector is used to exploit the correlation between the two sources as well as the redundancy left in the quantizer's indices, the channel's soft-decision outputs, and noise memory. The MAC's sub-channels are modeled via non-binary Markov noise discrete channels recently shown to effectively represent point-to-point fading channels. For the simple case of quantizing the sources with two levels, we establish a necessary and sufficient condition under which the joint sequence MAP decoder can be reduced to a simple instantaneous symbol-by-symbol decoder. Then, using numerical results obtained by system simulation, it is observed that when the sources are highly correlated and soft-decision quantization is used, JSCC can profit from a high correlation in the channel noise process and provide significant signal-to-distortion ratio improvements of up to 6.3 dB over a fully interleaved channel.
Antiemetic prophylaxis with temozolomide: an audit from a tertiary care center.

Background In our previous experience, a significant proportion of patients who received 5-HT3 antagonist monotherapy with adjuvant temozolomide (150-200 mg/m2) had chemotherapy-induced nausea and vomiting (CINV). This is an audit comparing the multiple antiemetic therapies in the prevention of temozolomide-associated CINV. Methods This was a retrospective audit. Adult glioma patients treated with temozolomide at a dose of 150-200 mg/m2 between October 2017 and June 2018 were selected for this analysis. Three antiemetic prophylaxis were used in this time period: ondansetron (October 2017 to November 2017), ondansetron + domperidone (December 2017 to February 2018), and ondansetron + olanzapine (March 2018 to June 2018). The rates of nausea and vomiting were compared among the 3 cohorts using the chi-squared test with Bonferroni correction. A P value of less than . 016 was considered significant. Results A total of 360 patients were selected for this analysis. There were 91 patients in the ondansetron prophylaxis group (25.3%), 113 (31.4%) in the ondansetron plus domperidone group, and 156 (43.3%) in the ondansetron plus olanzapine group. The overall incidence of nausea and vomiting was 25.0% (n = 90) and 7.2% (n = 26). Overall the rates of nausea (P = .052) and vomiting (P = .481) were similar in all 3 cohorts. However, the rates of grade 2 and above nausea (P = .012) and vomiting (P = .015) were significantly lower in the olanzapine group. Conclusion The combination of ondansetron with olanzapine leads to a statistically significant decrease in the rate of moderate-to-severe emesis and nausea and needs to be explored in a prospective study.
Dense Segmentation-Aware Descriptors

In this work we exploit segmentation to construct appearance descriptors that can robustly deal with occlusion and background changes. For this, we downplay measurements coming from areas that are unlikely to belong to the same region as the descriptor's center, as suggested by soft segmentation masks. Our treatment is applicable to any image point, i.e. dense, and its computational overhead is in the order of a few seconds. We integrate this idea with Dense SIFT, and also with Dense Scale and Rotation Invariant Descriptors (SID), delivering descriptors that are densely computable, invariant to scaling and rotation, and robust to background changes. We apply our approach to standard benchmarks on large displacement motion estimation using SIFT-flow and wide-baseline stereo, systematically demonstrating that the introduction of segmentation yields clear improvements.
acute coronary syndrome Relationship between premature ventricular complexes and depressive symptoms in non-ST-elevation

Aims: Depression is a recognized risk marker for mortality among acute coronary syndrome (ACS) patients. We hypothesized that ventricular arrhythmia detected by inpatient telemetry monitoring is more frequent among ACS patients with elevated depressive symptoms compared to those without depressive symptoms. Methods and results: We analysed data from patients enrolled in a prospective observational study of depression in ACS. Telemetry recordings during the index admission (average recording 21.3±3.0 hours) were analysed for frequent premature ventricular complexes (PVCs), defined as ≥10 per hour. The self-report Beck Depression Inventory (BDI) was used to assess depressive symptoms. Among 200 ACS patients, frequent PVCs were observed in 29% of patients with moderate depressive symptoms (BDI ≥10), 27% of those with mild symptoms (BDI 5–9), and only 11% of those with no/minimal symptoms (p=0.02). Log-transformed PVCs per hour were associated with depressive symptom category (p=0.008). In a multivariable logistic regression model that included age, gender, left ventricular ejection fraction, cardiovascular risk score, heart rate, and QT interval, mild symptoms (OR 3.02, 95% 0.97–9.43, p=0.058) and moderatesevere symptoms (OR 3.94, 95% CI 1.27–12.22, p=0.018) were associated with frequent PVCs. Conclusions: In this sample of ACS patients, depressive symptoms were independently associated with frequent PVCs during inpatient telemetry monitoring.
Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition

The characterization of dynamic electrophysiological brain activity, which form and dissolve in order to support ongoing cognitive function, is one of the most important goals in neuroscience. Here, we introduce a method with tensor decomposition for measuring the task-induced oscillations in the human brain using electroencephalography (EEG). The time frequency representation of source-reconstructed single-trail EEG data constructed a third-order tensor with three factors of time ∗ trails, frequency and source points. We then used a non-negative Canonical Polyadic decomposition (NCPD) to identify the temporal, spectral and spatial changes in electrophysiological brain activity. We validate this method using both simulation EEG data and real EEG data recorded during a task of irony comprehension. The results demonstrated that proposed method can track dynamics of the temporal-spectral modes of the rhythm in the brain on a timescale commensurate to the task they are undertaking.
Wideband Spectrum Reconstruction with Multicoset Sub-Nyquist Sampling and Collision Classification

This paper proposes an improved method for reconstructing wideband sparse spectrum. We utilize a multicoset setup based on time delay. The simple multicoset setup is more suitable for practical implementation in comparison to more sophisticated sub-Nyquist systems. We first introduce the general reconstruction model that solves for a fixed number of variables. We employ a simple machine learning technique to classify the aliased sub-Nyquist bins into two categories. The classification method reduces the reconstruction time by decreasing the number of combinations and variables needed for resolving the signals. The saving in solution time is significant at low occupancy levels. Furthermore, the approach is robust against higher noise levels, because although the classification accuracy decreases as SNR decreases, the reduction in the accuracy of the classifier does not adversely affect the overall detection. We define detection performance metrics and provide simulation results to demonstrate the effectiveness of our approach.
Escherichia coli and Sudden Infant Death Syndrome

This review examines the association of strains of Escherichia coli with sudden infant death syndrome (SIDS) and the possible role these bacteria play in this enigmatic condition. The review addresses evidence for E. coli in SIDS infants, potential sources of E. coli in the environment, colonization by commensal and pathogenic strains, the variety of currently accepted pathotypes, and how these pathotypes could compromise intestinal integrity and induce inflammation. Both intestinal and extraintestinal pathotypes are compared in relation to the apparent liability in which virulence traits can be gained or lost by strains of E. coli. The way in which E. coli infections fit with current views on infant sleeping position and other SIDS risk factors is highlighted.
Three-Dimensional Modeling of the Pelvic Floor Support Systems of Subjects with and without Pelvic Organ Prolapse

The purpose of this study was to develop three-dimensional finite element models of the whole pelvic support systems of subjects with and without pelvic organ prolapse (POP) that can be used to simulate anterior and posterior wall prolapses. Magnetic resonance imaging was performed in one healthy female volunteer (55 years old, para 2) and one patient (56 years old, para 1) with anterior vaginal wall prolapse. Contours of the pelvic structures were traced by a trained gynecologist. Smoothing of the models was conducted and attachments among structures were established. Finite element models of the pelvic support system with anatomic details were established for both the healthy subject and the POP patient. The models include the uterus, vagina with cavity, cardinal and uterosacral ligaments, levator ani muscle, rectum, bladder, perineal body, pelvis, obturator internus, and coccygeal muscle. Major improvements were provided in the modeling of the supporting ligaments and the vagina with high anatomic precision. These anatomically accurate models can be expected to allow study of the mechanism of POP in more realistic physiological conditions. The resulting knowledge may provide theoretical help for clinical prevention and treatment of POP.
Adenovirus E1B 19-kDa Death Suppressor Protein Interacts with Bax but Not with Bad*

Adenovirus E1B 19-kDa protein (19K) is a member of the Bcl-2 family of suppressors of apoptosis. The suppressors function through heterodimerization with the death promoters, Bax and related proteins, thus establishing a set point within the cell that determines whether or not apoptosis is executed in response to a death signal. Sequence similarities between 19K and Bcl-2 are largely restricted to short Bcl-2 homology (BH) domains that mediate interaction with Bax. The BH1 sequence in 19K is degenerate but nevertheless contains a conserved glycine residue found in all family members that when mutated to alanine in Bcl-2 results in loss of Bcl-2 function and ability to dimerize with Bax (Yin, X.-M., Oltvai, Z. N., and Korsmeyer, S. J. (1994) Nature 369, 321-323). Here, we show that the analogous mutation in BH1 of 19K also abrogates the anti-apoptotic properties of 19K and its ability to interact with Bax, thus establishing the critical importance of this residue within BH1 and the likely similarity of Bcl-2 and 19K function. In distinct contrast to Bcl-2, however, 19K interaction was not detected with Bad, a Bcl-2/Bcl-XL dimerizing protein that can potentially regulate a Bax·Bcl-2/Bcl-XL survival set point and reinstate susceptibility to a death signal. Furthermore, the anti-apoptotic function of 19K was not overcome by enforced expression of Bad in transfected cells. This feature of 19K may provide adenovirus with a selective advantage in evading premature induction of apoptosis by the host cell.
Disparities in the Use of Diabetes Screening in Appalachia

PURPOSE The Appalachian region presents disproportionately high rates of chronic disease compared to the rest of the United States. Early diagnosis of diabetes through screening is an important step in reducing diabetes complications. This study examines disparities in the use of diabetes screening in Appalachia. METHODS We analyzed 2009 and 2010 Behavioral Risk Factor Surveillance System data for 96,111 adults aged ≥45 years from 11 Appalachian states. Based on economic status, Appalachian counties were grouped into distressed (least affluent), at-risk, transitional, and competitive (most affluent). Logistic regression analyses were used to estimate the statistical significance and effect size of factors associated with diabetes screening. RESULTS Competitive counties had the highest rate of diabetes screening (65.4%). At-risk counties had the lowest rate (60.3%), about 7.8% lower compared to competitive counties (P < .001). After adjusting for socioeconomic factors, differences in screening rates between county economic levels in Appalachia were not statistically significant. Among respondents ≥65 years, at-risk counties had an 8.1% lower screening rate compared to competitive counties; this difference was not adequately explained by differences in socioeconomic factors. Screening rates in distressed and transitional counties were not significantly different from competitive counties in unadjusted or adjusted models. CONCLUSIONS At-risk counties had significantly lower screening rates than competitive counties. They should receive more policy attention similar to that received by distressed counties. Social policies that improve socioeconomic status and educational attainment, and health policies that reduce barriers to access to care may reduce disparities in diabetes screening rates in the less affluent Appalachian counties.