Miracle-dz/UniFAR-FTUs huggingface dataset:
Antidepressant Use During Acute Inpatient Care Is Associated With an Increased Risk of Psychiatric Rehospitalisation Over a 12-Month Follow-Up After Discharge

Background: Some evidence suggests that antidepressants may relate to poor outcomes in depression. The aim of this study was, therefore, to examine, whether antidepressant use may worsen the long-term outcome in real-world psychiatric patients with both primarily affective and non-affective mental disorders. Methods: Based on a total of n = 151 inpatients with a mixed range of diagnoses enrolled at two psychiatric hospitals in Zurich, Switzerland, matched pairs of n = 45 antidepressant users and n = 45 non-users were selected via nearest neighbor propensity score matching. Pairs were matched according to 14 clinically relevant covariates assessing psychosocial impairments, functioning deficits and illness severity. The two outcomes of interest were the number and total duration of all rehospitalisations over a 12-month follow-up after discharge from the hospital based on the official clinical registry. Results: Altogether 35.6% of antidepressant users were rehospitalised at least once, as compared to 22.2% in matched non-users. Two or more rehospitalisations occurred in 22.2% of antidepressant users but only in 2.2% of non-users. In antidepressant users, the mean total duration of rehospitalisations was 22.22 days, as compared to 8.51 in matched non-users. According to Poisson regression analyses, antidepressant use during acute inpatient care prospectively relates to both a higher risk (incidence rate ratio [IRR] = 3.64, 95% confidence interval [95%-CI] = 1.71–7.75, p = 0.001) and a longer duration (IRR = 2.61, 95%-CI = 1.01–6.79, p = 0.049) of subsequent rehospitalisations. These findings were consistently replicated when traditional multivariable regression analysis was applied to the full sample. Findings also replicated when patients with affective and non-affective disorders were analyzed separately. Conclusions: Our findings raise the possibility that, in the long-term, antidepressants may impair recovery and increase the risk of rehospitalisation in patients with both primarily affective and non-affective disorders. More work is required to explore possible aetiopathological pathways leading to psychiatric rehospitalisation.
Xpert MTB/RIF Ultra for Tuberculosis Testing in Children: A Mini-Review and Commentary

Tuberculosis (TB) remains a significant, yet under-recognized cause of death in the pediatric population, with a WHO estimate of 1 million new cases of childhood TB in 2016 resulting in 250,000 deaths. Diagnosis is notoriously difficult; manifestations are protean due to the high proportion of cases of extra-pulmonary TB in children, and logistical problems exist in obtaining suitable specimens. These issues are compounded by the paucibacillary nature of disease with the result that an estimated 96% of pediatric TB-associated mortality occurs prior to commencing anti-tuberculous treatment. Further development of sensitive, rapid diagnostic tests and their incorporation into diagnostic algorithms is vital in this population, and central to the WHO End-TB strategy. Initial gains were made with the expansion of nucleic acid amplification technology, particularly the introduction of the GeneXpert fully-automated PCR Xpert MTB/Rif assay in 2010, and more recently, the Xpert MTB/Rif Ultra (Ultra) assay in 2017. Ultra provides increased analytical sensitivity when compared with the initial Xpert assay in vitro; a finding now also supported by six clinical studies to date, two of which included pediatric samples. Here, we review the published evidence for the performance of Ultra in TB diagnosis in children, as well as studies in adults with paucibacillary disease providing results relevant to the pediatric population. Following on from this, we speculate upon future directions for Ultra, with focus on its potential use with alternative diagnostic specimens, which may be of particular utility in children.
Characterization of phoA, a Bacterial Alkaline Phosphatase for Phi Use Efficiency in Rice Plant

Fertilizers and herbicides are two major components in the agriculture system for achieving crop productivity. Massive use of orthophosphate fertilizers and herbicides poses threats to phosphate reserves and aids the evolution of herbicide tolerant weed biotypes. Phosphite (Phi), a phosphate analog, has been proposed as more beneficial than traditionally used phosphate fertilizers and herbicides in the agriculture. We developed phoA overexpressing transgenic rice that minimizes the phosphate loss and contributes to weed management in the agriculture. The phoA rice lines showed improved root, shoot length and total biomass production under phosphite conditions. Additionally, the complete phenotype and productivity of phoA lines under the phosphite treatment attained was similar to that of plants under phosphate sufficient condition. The Phi metabolizing properties of the phoA overexpressed lines improved under the Phi application and phi treatment enabled controlling of weeds without compromising the yield of transgenic rice plants. Our results indicated that phoA alone or in combination with other Phi metabolizing gene(s) can possibly be used as an effective ameliorating system for improving crop plants for phi-based fertilization and weed management strategy in the agriculture.
Determinants of 3G Adoption in Malaysia: A Structural Analysis

The main aim of this paper is to examine the factors that affect consumers' decisions to adopt 3G. The factors that are studied in this research include perceived ease of use (PEOU), perceived usefulness (PU), perceived cost (PC), social influence (SI), self efficacy (SE), privacy and security (PS), and fun or enjoyment (FE). The collection of data comprises of 371 mobile phone users in Malaysia. Structural equation modelling was applied to test the hypothesis developed in this research study. The findings from this study indicated that PU, SE and PS have a significant impact on consumers' decision to adopt Third Generation (3G). There are several implications from this study. Firstly, this study focuses on 3G adoption in a fast growing, developing country. Secondly, our study has also extended traditional TAM models by incorporating additional variables related to culture. As many developing countries are starting to embrace 3G technology, our study allows the government as well as service providers of these countries to formulate appropriate business strategies based on our study.
Congenital Cardiac Outflow Tract Abnormalities in Dogs: Prevalence and Pattern of Inheritance From 2008 to 2017

Subvalvular aortic stenosis (SAS) and valvular pulmonic stenosis (PS) are two of the most common congenital heart diseases of dogs. The aim of this study was to determine the prevalence and mode of inheritance of these congenital heart diseases in a large veterinary teaching hospital population. Case records of dogs presented to the University of California Davis, Veterinary Medical Teaching Hospital (UCD VMTH) between January 2008 to December 2017 were reviewed retrospectively and pedigree information was obtained when available. There were 259 unique SAS and 336 unique PS cases diagnosed during the study period. The prevalence of SAS was 0.3% of overall hospital admissions and 4.7% for all dogs seen by the cardiology service. The prevalence for PS was 0.41% of overall hospital admissions and 6.1% of dogs seen by the cardiology service. Bullmastiffs and Newfoundlands had the greatest prevalence (6.59 and 4.46%, respectively) and odds ratio (52.43 and 34.73, respectively) for SAS. Bulldogs and French Bulldogs had the greatest prevalence (4.8 and 2.7%, respectively) and odds ratio (13.32 and 7.52, respectively) for PS. The identified prevalence of SAS and PS is higher than previously reported. Pedigree analysis in SAS affected Bullmastiffs, Golden Retrievers, and Rottweilers suggested an autosomal recessive pattern of inheritance. The mode of inheritance for PS in Bulldogs, also appears to be autosomal recessive. The results of this study can be used to inform future selection of breeding pairs and genetic studies aimed at reducing the prevalence of these common congenital heart diseases.
Toward a Theory of Iformation Technology Professional Competence

Based on a field study of information technology (IT) executives a theoretical model of knowledge, skills, and abilities desired for IT professionals is developed (The Theory of IT Professional Competence). The field study consists of two group data gathering events with IT executives using a nominal group technique. The model is built by analyzing the data using the constant comparison approach proposed in the grounded theory literature. The model is then substantiated and strengthened using related skills concepts from the literature. This research makes a contribution on several dimensions: methodological, theoretical, managerial, and academic. For example, the theory should help to better understand gaps between IT academic programs, employers' needs, and IT students' perceptions.
Differentially-Private and Trustworthy Online Social Multimedia Big Data Retrieval in Edge Computing

The explosive growth of multimedia contents (MCs) in today's mobile social networks has pushed edge computing to face severe security and online big data-processing problems. On the one hand, the edge nodes (ENs) should help mobile users find, cache, and share MCs in the presence of an ever-increasing scale of multimedia big data. On the other hand, how to provide secure MC retrieval schemes to exclude dishonest-and-malicious untrusted ENs and to prevent privacy breaches from honest-but-curious ENs and users is a challenging issue. To tackle these problems, we study the privacy-preserving and trustworthy MCs retrieval system to make personalized MC recommendations from ENs to users with big data support. In our framework, each EN is modeled as a distributed context-aware online learner. ENs collaborate to learn users’ preferences based on their contexts and previous behaviors and social intimacy. To support big data analytics, we establish an MC-cluster tree from top to the bottom to handle the dynamically varying cached MC datasets. A differentially private algorithm is proposed to preserve the data privacy among honest-but-curious ENs and users. To guarantee trustworthy edge computing, a trust evaluation mechanism is designed to evaluate the reliability of ENs. We further consider the structure of edge networks to improve the performance of our algorithm. Experimental results validate that our new framework can support increasing multimedia big datasets while striking a balance among privacy-preserving level, Trustworthy level, and caching MC prediction accuracy.
It Impacts in Information and Physical Product Industries

While being an important question for IS research, there are contradictory views on the mediation of firm productivity on the IT-profit relationship. This study builds on prior studies that suggest that this relationship is completely mediated as well as those that suggest that this relationship is completely unmediated. This is studied in conjunction with prior research that posits that industries that make products composed of information are fundamentally different from industries that make physical products when it comes to their IT effects. Building on this, a complex but parsimonious moderated-mediation model is developed that can explain the contradictory mediation hypotheses. This model posits that the IT-profit relationship is completely mediated by productivity for information product industries, but less mediated for physical product industries. Results of PLS tests using a 7-year dataset of firms in both physical product and information product industries support these hypotheses.
A Functional Data Method for Causal Dynamic Network Modeling of Task-Related fMRI

Functional MRI (fMRI) is a popular approach to investigate brain connections and activations when human subjects perform tasks. Because fMRI measures the indirect and convoluted signals of brain activities at a lower temporal resolution, complex differential equation modeling methods (e.g., Dynamic Causal Modeling) are usually employed to infer the neuronal processes and to fit the resulting fMRI signals. However, this modeling strategy is computationally expensive and remains to be mostly a confirmatory or hypothesis-driven approach. One major statistical challenge here is to infer, in a data-driven fashion, the underlying differential equation models from fMRI data. In this paper, we propose a causal dynamic network (CDN) method to estimate brain activations and connections simultaneously. Our method links the observed fMRI data with the latent neuronal states modeled by an ordinary differential equation (ODE) model. Using the basis function expansion approach in functional data analysis, we develop an optimization-based criterion that combines data-fitting errors and ODE fitting errors. We also develop and implement a block coordinate-descent algorithm to compute the ODE parameters efficiently. We illustrate the numerical advantages of our approach using data from realistic simulations and two task-related fMRI experiments. Compared with various effective connectivity methods, our method achieves higher estimation accuracy while improving the computational speed by from tens to thousands of times. Though our method is developed for task-related fMRI, we also demonstrate the potential applicability of our method (with a simple modification) to resting-state fMRI, by analyzing both simulated and real data from medium-sized networks.
Correlates of Orthographic Learning in Swedish Children With Cochlear Implants

This study set out to explore the cognitive and linguistic correlates of orthographic learning in a group of 32 deaf and hard of hearing children with cochlear implants, to better understand the factors that affect the development of fluent reading in these children. To date, the research about the mechanisms of reading fluency and orthographic learning in this population is scarce. The children were between 6:0 and 10:11 years of age and used oral language as their primary mode of communication. They were assessed on orthographic learning, reading fluency and a range of cognitive and linguistic skills including working memory measures, word retrieval and paired associate learning. The results were analyzed in a set of correlation analyses. In line with previous findings from children with typical hearing, orthographic learning was strongly correlated with phonological decoding, receptive vocabulary, phonological skills, verbal-verbal paired-associate learning and word retrieval. The results of this study suggest that orthographic learning in children with CI is strongly dependent on similar cognitive and linguistic skills as in typically hearing peers. Efforts should thus be made to support phonological decoding skill, vocabulary, and phonological skills in this population.
A Sex-Specific Analysis of the Predictive Value of Troponin I and T in Patients With and Without Diabetes Mellitus After Successful Coronary Intervention

Background: Elevated levels of troponin are associated with future major adverse cardiac events (MACE). Data on the prognostic value of high sensitive troponin T (hs-TnT) compared to high sensitive troponin I (hs-TnI) in diabetic and non-diabetic patients are sparse. Methods: We analyzed patients of a single-center registry undergoing coronary stenting between 2003 and 2006. As a primary endpoint we assessed MACE, a composite of cardiovascular death, nonfatal myocardial infarction and nonfatal stroke according to sex and diabetes status using log-rank. As a second endpoint, we assessed the prognostic impact of hs-TnT and hs-TnI on MACE, adjusting for known confounders using Cox regression analysis. Results: Out of 818 investigated patients, 267 (32.6%) were female. Diabetes mellitus type 2 (T2DM) was diagnosed in 206 (25.2%) patients. After a mean follow-up of 6.6 ± 3.7 years, MACE occurred in 235 (28.7%) patients. The primary endpoint components of cardiovascular death occurred in 115 (14.1%) patients, MI in 75 (9.2%), and ischemic stroke in 45 (5.5%). Outcomes differed significantly according to sex and diabetes status (p = 0.003). In descending order, MACE rates were as follows: female diabetic patients (40.8%), female non-diabetic patients (32.7%), male diabetic patients (28.9%), and male non-diabetic patients (24.8%). Additionally, females with diabetes were at higher risk of cardiovascular death compared to diabetic men (28 vs. 15%). Hs-TnI (HR 1.477 [95% CI 1.100–1.985]; p = 0.010) and hs-TnT (HR 1.615 [95%CI 1.111–2.348]; p = 0.012) above the 99th percentile were significantly associated with MACE. Both assays showed tendency toward association with MACE in all subgroups. Conclusion: Diabetic patients, particularly females, with known coronary artery disease had a higher risk of subsequent MACE. Both, hs-TnI and hs-TnT significantly correlated with MACE.
Interference Hypergraph-Based Resource Allocation (IHG-RA) for NOMA-Integrated V2X Networks

Vehicular communication network is a core application scenario in the fifth generation (5G) mobile communication system which requires ultra high data rate and ultra low latency. Most recently, non-orthogonal multiple access (NOMA) has been regarded as a promising technique for future 5G systems due to its capability in significantly improving the spectral efficiency and reducing the data transmission latency. In this paper, we propose to introduce NOMA in D2D-enabled V2X networks, where resource sharing based on spatial reuse for different V2X communications are permitted through centralized resource management. Considering the complicated interference scenario caused by NOMA and spatial reuse-based resource sharing in the investigated NOMA-integrated V2X networks, we construct an interference hypergraph to model the interference relationships among different communication groups. In addition, based on the constructed hypergraph, we further propose an interference hypergraph-based resource allocation (IHG-RA) scheme with cluster coloring algorithm, which can lead to both effective and efficient QoS-guaranteed resource block (RB) assignment with low computational complexity. Simulation results verify the efficiency of our proposed IHG-RA scheme for NOMA-integrated V2X communications in improving the network sum rate.
An Enhanced Nonlinear Companding Scheme for Reducing PAPR of OFDM Systems

—A new companding scheme for reducing the peak-to-average power ratio (PAPR) of orthogonal frequency-division multiplexing (OFDM) systems is proposed in this study. It proceeds from speech signal processing similar to the earliest µ - law companding (MC) model. The proposed scheme compands (compresses and expands) the amplitudes of OFDM signals to a maximum of 1 − volt . Besides signiﬁcantly reducing the PAPR, the proposed technique is also able to function as a limiter thus reducing the system complexity and limiting the amplitudes of OFDM symbols to a unity maximum voltage which does not exist in other companding PAPR techniques. Over frequency-selective fading channels with frequency domain equalization and using minimum mean square error (MMSE) to minimize the noise overhead, the proposed technique outperforms four other companding schemes over light and severe fading conditions. Lastly, we demonstrate that PAPR reduction using companding can dispense with correspondingly applying decompanding at the receiver as it ampliﬁes the distortion noise thereby reducing the bit error ratio performance and increases the receiver complexity. We investigated the out-of-band interference of the proposed scheme and also show that it outperforms the other existing techniques by up to 5dB.
Trait Mindfulness Is Associated With the Self-Similarity of Heart Rate Variability

Previous studies have linked trait mindfulness with better self-regulation and adaptation. Heart rate variability (HRV) is a good physiological indicator of the capacity for self-regulation and adaptation. The present study explored the relationship between trait mindfulness and HRV from the viewpoint of crosstalking between different HRV parameter pairs, which would reflect the dynamic interactions between each pair of HRV parameters in different processes. We measured the trait mindfulness of seventy-four undergraduate students and recorded nine HRV parameters during the following four consecutive experimental phases: (1) calming phase, (2) mental arithmetic task phase, (3) recovery phase, and (4) mindfulness practice phase. The relationship between trait mindfulness and HRV was explored at the following three levels: (1) the absolute level, i.e., HRV parameters in four different states, (2) the difference-change level, i.e., differences in HRV parameters between different states, and (3) the crosstalking level, i.e., self-similarity of crosstalking HRV parameter pairs. The results supported the following hypothesis: trait mindfulness, as measured by the Mindful Attention Awareness Scale (MAAS), was significantly and positively correlated with the self-similarity of crosstalking HRV parameter pairs but was not significantly correlated with the HRV parameters at the difference-change and absolute levels. These findings indicate that as trait mindfulness increases, the ability to maintain ANS function homeostasis improves. HIGHLIGHTS - Trait mindfulness is associated with better self-regulation and adaptation. - Heart rate variability (HRV) is a good physiological indicator of the capacity for self-regulation and adaptation. - Trait mindfulness is significantly correlated with self-similarity of crosstalking HRV parameter pairs but not with the HRV parameters at the difference-change or absolute levels.
Atypical Autoimmune Encephalitis With Neuropil Antibodies Against a Yet Unknown Epitope

Autoimmune encephalitis often causes acute psychiatric symptoms and epileptic seizures. However, it is becoming increasingly clear that depending on the target antigen both symptoms and disease severity may vary. Furthermore, the identification and characterization of antibody subtypes are highly relevant for personalizing the treatment and to prevent relapses. Here we present an atypical case of encephalitis with cerebellar and temporal dysfunction but without seizures associated with high levels of cerebrospinal fluid neuropil antibodies against a yet unknown epitope on the neuronal surface in the cerebellum, hippocampus, thalamus, and the olfactory bulb. We treated the patient successfully with corticosteroids, plasmapheresis, and rituximab.