Miracle-dz/UniFAR-FTUs huggingface dataset:
Motivating factors and barriers towards exercise in severe mental illness: a systematic review and meta-analysis

Exercise can improve clinical outcomes in people with severe mental illness (SMI). However, this population typically engages in low levels of physical activity with poor adherence to exercise interventions. Understanding the motivating factors and barriers towards exercise for people with SMI would help to maximize exercise participation. A search of major electronic databases was conducted from inception until May 2016. Quantitative studies providing proportional data on the motivating factors and/or barriers towards exercise among patients with SMI were eligible. Random-effects meta-analyses were undertaken to calculate proportional data and 95% confidence intervals (CI) for motivating factors and barriers toward exercise. From 1468 studies, 12 independent studies of 6431 psychiatric patients were eligible for inclusion. Meta-analyses showed that 91% of people with SMI endorsed ‘improving health’ as a reason for exercise (N = 6, n = 790, 95% CI 80–94). Among specific aspects of health and well-being, the most common motivations were ‘losing weight’ (83% of patients), ‘improving mood’ (81%) and ‘reducing stress’ (78%). However, low mood and stress were also identified as the most prevalent barriers towards exercise (61% of patients), followed by ‘lack of support’ (50%). Many of the desirable outcomes of exercise for people with SMI, such as mood improvement, stress reduction and increased energy, are inversely related to the barriers of depression, stress and fatigue which frequently restrict their participation in exercise. Providing patients with professional support to identify and achieve their exercise goals may enable them to overcome psychological barriers, and maintain motivation towards regular physical activity.
ERIS: A NUMA-Aware In-Memory Storage Engine for Analytical Workload

The ever-growing demand for more computing power forces hardware vendors to put an increasing number of multiprocessors into a single server system, which usually exhibits a non-uniform memory access (NUMA). In-memory database systems running on NUMA platforms face several issues such as the increased latency and the decreased bandwidth when accessing remote main memory. To cope with these NUMA-related issues, NUMA-awareness has to be considered as a major design principle for the fundamental architecture of a database system. In this paper we present ERIS, a NUMA-aware inmemory storage engine that is based on a data-oriented architecture. In contrast to existing approaches that focus on transactional workloads on a disk-based DBMS, ERIS aims at tera-scale analytical workloads that are executed entirely in main memory. ERIS uses an adaptive partitioning approach that exploits the topology of the underlying NUMA platform and significantly reduces NUMA-related issues. We evaluate ERIS on widespread standard server systems as well as on a system consisting of 64 multiprocessors and 512 cores. On these platforms, we achieve a more than linear speedup for index lookups and scalable parallel scan operations that are only limited by the available local bandwidth of the multiprocessor. Moreover, we measured a performance gain of up to 200% (index lookups) respectively 660% (column scans) in the memory-bound case compared to a NUMA-agnostic storage subsystem.
Density-of-States Based Numerical and Analytical Models for Solution-Processed Polymer TFTs

In this work, we propose the subgap density-ofstates (DOS) based design platform for solutionprocessed polymer-based thin-film-transistors (PTFTs). For the model simulation, numerical and analytical I-V models were established from experimentally extracted DOS parameters, and verified by comparing the simulation result with the measured characteristics of solution-processed PTFTs.
Long-distance transport of gases in plants: a perspective on internal aeration and radial oxygen loss from roots

Internal transport of gases is crucial for vascular plants inhabiting aquatic, wetland or flood-prone environments. Diffusivity of gases in water is approximately 10 000 times slower than in air; thus direct exchange of gases between submerged tissues and the environment is strongly impeded. Aerenchyma provides a low-resistance internal pathway for gas transport between shoot and root extremities. By this pathway, O2 is supplied to the roots and rhizosphere, while CO2, ethylene, and methane move from the soil to the shoots and atmosphere. Diffusion is the mechanism by which gases move within roots of all plant species, but significant pressurized through-flow occurs in stems and rhizomes of several emergent and floating-leaved wetland plants. Through-flows can raise O2 concentrations in the rhizomes close to ambient levels. In general, rates of flow are determined by plant characteristics such as capacity to generate positive pressures in shoot tissues, and resistance to flow in the aerenchyma, as well as environmental conditions affecting leaf-to-air gradients in humidity and temperature. O2 diffusion in roots is influenced by anatomical, morphological and physiological characteristics, and environmental conditions. Roots of many (but not all) wetland species contain large volumes of aerenchyma (e.g. root porosity can reach 55%), while a barrier impermeable to radial O2 loss (ROL) often occurs in basal zones. These traits act synergistically to enhance the amount of O2 diffusing to the root apex and enable the development of an aerobic rhizosphere around the root tip, which enhances root penetration into anaerobic substrates. The barrier to ROL in roots of some species is induced by growth in stagnant conditions, whereas it is constitutive in others. An inducible change in the resistance to O2 across the hypodermis/exodermis is hypothesized to be of adaptive significance to plants inhabiting transiently waterlogged soils. Knowledge on the anatomical basis of the barrier to ROL in various species is scant. Nevertheless, it has been suggested that the barrier may also impede influx of: (i) soil-derived gases, such as CO2, methane, and ethylene; (ii) potentially toxic substances (e.g. reduced metal ions) often present in waterlogged soils; and (iii) nutrients and water. Lateral roots, that remain permeable to O2, may be the main surface for exchange of substances between the roots and rhizosphere in wetland species. Further work is required to determine whether diversity in structure and function in roots of wetland species can be related to various niche habitats.
Inverter power module parasitics modeling with cross-coupling simplification for fast model extraction and switching characteristics simulation

Inverter power module parasitics models are commonly used for inverter switching analysis, gate drive tuning, and EMI characterization. This paper investigates the parasitics modeling and simplification of an inverter power module. The circuit cross-coupling is characterized by Z-parameter matrix. Three types of cross-coupling modeling/simplification methods are studied in this research. The effect of cross-coupling simplification on model extraction time and circuit simulation time are evaluated. To validate the accuracy of the parasitics models, the circuit simulations are compared with the experimental results.
Knowledge‐based automated planning for oropharyngeal cancer

Purpose The purpose of this study was to automatically generate radiation therapy plans for oropharynx patients by combining knowledge‐based planning (KBP) predictions with an inverse optimization (IO) pipeline. Methods We developed two KBP approaches, the bagging query (BQ) method and the generalized principal component analysis‐based (gPCA) method, to predict achievable dose–volume histograms (DVHs). These approaches generalize existing methods by predicting physically feasible organ‐at‐risk (OAR) and target DVHs in sites with multiple targets. Using leave‐one‐out cross validation, we applied both models to a large dataset of 217 oropharynx patients. The predicted DVHs were input into an IO pipeline that generated treatment plans (BQ and gPCA plans) via an intermediate step that estimated objective function weights for an inverse planning model. The KBP predictions were compared to the clinical DVHs for benchmarking. To assess the complete pipeline, we compared the BQ and gPCA plans to both the predictions and clinical plans. To isolate the effect of the KBP predictions, we put clinical DVHs through the IO pipeline to produce clinical inverse optimized (CIO) plans. This approach also allowed us to estimate the complexity of the clinical plans. The BQ and gPCA plans were benchmarked against the CIO plans using DVH differences and clinical planning criteria. Iso‐complexity plans (relative to CIO) were also generated and evaluated. Results The BQ method tended to predict that less dose is delivered than what was observed in the clinical plans while the gPCA predictions were more similar to clinical DVHs. Both populations of KBP predictions were reproduced with inverse plans to within a median DVH difference of 3 Gy. Clinical planning criteria for OARs were satisfied most frequently by the BQ plans (74.4%), by 6.3% points more than the clinical plans. Meanwhile, target criteria were satisfied most frequently by the gPCA plans (90.2%), and by 21.2% points more than clinical plans. However, once the complexity of the plans was constrained to that of the CIO plans, the performance of the BQ plans degraded significantly. In contrast, the gPCA plans still satisfied more clinical criteria than both the clinical and CIO plans, with the most notable improvement being in target criteria. Conclusion Our automated pipeline can successfully use DVH predictions to generate high‐quality plans without human intervention. Between the two KBP methods, gPCA plans tend to achieve comparable performance as clinical plans, even when controlling for plan complexity, whereas BQ plans tended to underperform.
Modified Fusarium Mycotoxins in Cereals and Their Products—Metabolism, Occurrence, and Toxicity: An Updated Review

Mycotoxins are secondary fungal metabolites, toxic to humans, animals and plants. Under the influence of various factors, mycotoxins may undergo modifications of their chemical structure. One of the methods of mycotoxin modification is a transformation occurring in plant cells or under the influence of fungal enzymes. This paper reviews the current knowledge on the natural occurrence of the most important trichothecenes and zearalenone in cereals/cereal products, their metabolism, and the potential toxicity of the metabolites. Only very limited data are available for the majority of the identified mycotoxins. Most studies concern biologically modified trichothecenes, mainly deoxynivalenol-3-glucoside, which is less toxic than its parent compound (deoxynivalenol). It is resistant to the digestion processes within the gastrointestinal tract and is not absorbed by the intestinal epithelium; however, it may be hydrolysed to free deoxynivalenol or deepoxy-deoxynivalenol by the intestinal microflora. Only one zearalenone derivative, zearalenone-14-glucoside, has been extensively studied. It appears to be more reactive than deoxynivalenol-3-glucoside. It may be readily hydrolysed to free zearalenone, and the carbonyl group in its molecule may be easily reduced to α/β-zearalenol and/or other unspecified metabolites. Other derivatives of deoxynivalenol and zearalenone are poorly characterised. Moreover, other derivatives such as glycosides of T-2 and HT-2 toxins have only recently been investigated; thus, the data related to their toxicological profile and occurrence are sporadic. The topics described in this study are crucial to ensure food and feed safety, which will be assisted by the provision of widespread access to such studies and obtained results.
Ranking-Preserving Low-Rank Factorization for Image Annotation With Missing Labels

Automatic image annotation has been extensively studied in the recent decades. Nevertheless, existing methods usually assume a properly labeled training set, which greatly inhibits their application to real-world datasets with incomplete labels. Due to their lack of special treatments for noisy data, most existing methods simply consider the missing labels as strictly negative ones, leading to the degradation of tagging accuracy. In light of such challenges, we propose a novel model in this paper, called ranking-preserving low-rank factorization. Specifically, we construct a local training set for each test image, and conduct low-rank matrix factorization on the model coefficient matrix, to simultaneously capture the label dependency and reduce the model complexity. Furthermore, to alleviate the ambiguity introduced by missing labels, the prediction model is learnt via tag ranking regularized by sample similarities and tag correlations, and both regularization terms are incorporated into our factorization scheme. By assembling all the aforementioned components together, our method obviates the need for making binary decisions based on unreliable data, and thus is more robust towards missing labels. Extensive empirical evaluations conducted on four datasets demonstrate the effectiveness of the proposed method.
Observer based kinematic tracking controllers for a unicycle-type mobile robot

In this paper the problem of global trajectory tracking for the kinematic model of a unicycle-type mobile robot is considered. It is assumed that some of the tracking error coordinates are not measurable. Using a cascaded systems approach we develop full order and reduced order observers, and introduce an observer based controller resulting in K-exponential convergence of the tracking error. Simulations are provided to illustrate the results.
Functions and Signaling Pathways of Amino Acids in Intestinal Inflammation

Intestine is always exposed to external environment and intestinal microorganism; thus it is more sensitive to dysfunction and dysbiosis, leading to intestinal inflammation, such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and diarrhea. An increasing number of studies indicate that dietary amino acids play significant roles in preventing and treating intestinal inflammation. The review aims to summarize the functions and signaling mechanisms of amino acids in intestinal inflammation. Amino acids, including essential amino acids (EAAs), conditionally essential amino acids (CEAAs), and nonessential amino acids (NEAAs), improve the functions of intestinal barrier and expressions of anti-inflammatory cytokines and tight junction proteins but decrease oxidative stress and the apoptosis of enterocytes as well as the expressions of proinflammatory cytokines in the intestinal inflammation. The functions of amino acids are associated with various signaling pathways, including mechanistic target of rapamycin (mTOR), inducible nitric oxide synthase (iNOS), calcium-sensing receptor (CaSR), nuclear factor-kappa-B (NF-κB), mitogen-activated protein kinase (MAPK), nuclear erythroid-related factor 2 (Nrf2), general controlled nonrepressed kinase 2 (GCN2), and angiotensin-converting enzyme 2 (ACE2).
Down-Regulated E-Cadherin Expression Is Associated with Poor Five-Year Overall Survival in Bone and Soft Tissue Sarcoma: Results of a Meta-Analysis

Purpose To conduct a meta-analysis to evaluate the prognostic role of E-cadherin expression in bone and soft tissue sarcomas. Methods The PubMed, EMBASE, and Web of Science databases were searched using terms related to E-cadherin, sarcoma, and prognosis for all articles published in English before March 2014. Pooled effect was calculated from the available data to evaluate the association between negative E-cadherin expression and 5-year overall survival and tumor clinicopathological features in sarcoma patients. Pooled odds ratios (OR) and risk ratios (RR) with 95% confidence intervals (CI) were calculated using a fixed-effects model. Result Eight studies met the selection criteria and reported on 812 subjects. A total of 496 subjects showed positive E-cadherin expression (59.9%). Negative E-cadherin expression in bone and soft tissue sarcomas was correlated with lower 5-year overall survival (OR = 3.831; 95% CI: 2.246–6.534), and was associated with higher clinical stage (RR = 1.446; 95% CI: 1.030–2.028) and with male sex (RR = 0.678; 95% CI: 0.493–0.933). Conclusion In the E-cadherin negative group, 5-year overall survival was significantly worse than in the E-cadherin positive group. However, further studies are required to confirm these results.
Two-Dimensional Edge Detection by Guided Mode Resonant Metasurface

In this letter, a new approach to perform edge detection is presented using an all-dielectric complimentary metal–oxide–semiconductor-compatible metasurface. Our design is based on the guided-mode resonance, which provides a high quality factor resonance to make the edge detection experimentally realizable. The proposed structure is easy to fabricate, and it can be exploited for detection of edges in two dimensions due to its symmetry. In addition, a tradeoff between gain and the resolution of edge detection is discussed, which can be adjusted using appropriate design parameters. The proposed edge detector potentially can be used in ultrafast analog computing and image processing.
Suspended sediment transport at the instantaneous and event time scales in semiarid watersheds of southeastern Arizona, USA

We investigated the high variability of suspended sediment transport in 16 watersheds of Walnut Gulch, southeastern Arizona, USA that were distinguished at three spatial scales: the plot (ca. 0.001–0.01 km2), unit‐source (ca. 0.01–0.1 km2), and large (ca. 1–150 km2) scales. Event‐based data of water discharge and suspended sediment concentration were compiled in variable periods between the 1960s and 2010s. By subjectively distinguishing five different intraevent transport patterns that may be ascribed to a combination of various hydrological and sediment‐transport processes, we showed that no single sediment rating curve could be developed for these data. However, at the event temporal scale, event specific sediment yield (SSYe, t/km2) was significantly correlated to event runoff depth (h, mm) for all transport patterns of the watersheds, suggesting that the complexity of suspended sediment transport at the intraevent scale is effectively reduced at the event scale regardless of watershed sizes. Further regression analysis indicated that the SSYe‐h relationship can be generally characterized by a proportional model, SSYe = nh where n, is conceptually equivalent to the volume‐weighted event mean sediment concentration and is mainly determined by large events. For watersheds dominated by shrub cover, the change of the n value with watershed area was limited and thus may be reasonably regarded as a constant, implying that despite the highly variable suspended sediment concentrations during individual storm events in variable‐sized watersheds, the synoptic effect of suspended sediment transport was similar and may be determined by a single value.
On the Analysis of Request-Response Communication in a Token Passing Ring

The paper investigates performance issues related to request-response communication in distributed systems built around a token passing ring. The objective of this paper is to construct a model of a distributed system using request-response communication, to point out the difficulties related to an exact analysis of the model in case of a cyclic server system, and then to discuss an approximation. The analysis is then carried out for a traditional system and for a modified cyclic server system.
Placental hypoxia during placental malaria.

BACKGROUND Placental malaria causes fetal growth retardation (FGR), which has been linked epidemiologically to placental monocyte infiltrates. We investigated whether parasite or monocyte infiltrates were associated with placental hypoxia, as a potential mechanism underlying malarial FGR. METHODS We studied the hypoxia markers hypoxia inducible factor (HIF)-1alpha, vascular endothelial growth factor (VEGF), placental growth factor, VEGF receptor 1 and its soluble form, and VEGF receptor 2. We used real-time polymerase chain reaction (in 59 women) to examine gene transcription, immunohistochemistry (in 30 women) to describe protein expression, and laser-capture microdissection (in 23 women) to examine syncytiotrophoblast-specific changes in gene expression. We compared gene and protein expression in relation to malaria infection, monocyte infiltrates, and birth weight. RESULTS We could not associate any hallmark of placental malaria with a transcription, expression, or tissue-distribution profile characteristic of a response to hypoxia, but we found higher HIF-1alpha levels (P= .0005) and lower VEGF levels (P= .0026) in the syncytiotrophoblasts of cases of malaria than in those of asymptomatic control placentas. CONCLUSIONS Our data are inconsistent with a role for placental hypoxia in the pathogenesis of malaria-associated FGR. The laser-capture microdissection study was small, but its results suggest (1) that malaria affects syncytiotrophoblast-gene transcription and (2) novel potential mechanisms for placental malaria-associated FGR.
BODY SCARRING ON CETACEA-ODONTOCETES

An attempt is made to give some interpretation to the numerous and various scars found on the exterior of Odontocetes. Some of the scars are the result of male contests; firstly, in play, establishing superiority, inter se, between young males, and secondly, in the more serious combats to establish final mastery in anticipation of the breeding season for possession of an harem. Other causes of scarring are also discussed.
A Personalized Risk Stratification Platform for Population Lifetime Healthcare

Chronic diseases are the leading cause of death worldwide. It is well understood that if modifiable risk factors are targeted, most chronic diseases can be prevented. Lifetime health is an emerging health paradigm that aims to assist individuals to achieve desired health targets, and avoid harmful lifecycle choices to mitigate the risk of chronic diseases. Early risk identification is central to lifetime health. In this paper, we present a digital health-based platform (PRISM) that leverages artificial intelligence, data visualization and mobile health technologies to empower citizens to self-assess, self-monitor and self-manage their overall risk of major chronic diseases and pursue personalized chronic disease prevention programs. PRISM offers risk assessment tools for 5 chronic conditions, 2 psychiatric disorders and 8 different cancers.
Prevalence of Learned Grapheme-Color Pairings in a Large Online Sample of Synesthetes

In this paper we estimate the minimum prevalence of grapheme-color synesthetes with letter-color matches learned from an external stimulus, by analyzing a large sample of English-speaking grapheme-color synesthetes. We find that at least 6% (400/6588 participants) of the total sample learned many of their matches from a widely available colored letter toy. Among those born in the decade after the toy began to be manufactured, the proportion of synesthetes with learned letter-color pairings approaches 15% for some 5-year periods. Among those born 5 years or more before it was manufactured, none have colors learned from the toy. Analysis of the letter-color matching data suggests the only difference between synesthetes with matches to the toy and those without is exposure to the stimulus. These data indicate learning of letter-color pairings from external contingencies can occur in a substantial fraction of synesthetes, and are consistent with the hypothesis that grapheme-color synesthesia is a kind of conditioned mental imagery.