Miracle-dz/UniFAR-FTUs huggingface dataset:
Defect-engineered epitaxial VO2±δ in strain engineering of heterogeneous soft crystals

Heterogeneous strain engineering of soft crystals is realized via phase transition nanocrystals. The success of strain engineering has made a step further for the enhancement of material properties and the introduction of new physics, especially with the discovery of the critical roles of strain in the heterogeneous interface between two dissimilar materials (for example, FeSe/SrTiO3). On the other hand, the strain manipulation has been limited to chemical epitaxy and nanocomposites that, to a large extent, limit the possible material systems that can be explored. By defect engineering, we obtained, for the first time, dense three-dimensional strongly correlated VO2±δ epitaxial nanoforest arrays that can be used as a novel “substrate” for dynamic strain engineering, due to its metal-insulator transition. The highly dense nanoforest is promising for the possible realization of bulk strain similar to the effect of nanocomposites. By growing single-crystalline halide perovskite CsPbBr3, a mechanically soft and emerging semiconducting material, onto the VO2±δ, a heterogeneous interface is created that can entail a ~1% strain transfer upon the metal-insulator transition of VO2±δ. This strain is large enough to trigger a structural phase transition featured by PbX6 octahedral tilting along with a modification of the photoluminescence energy landscape in halide perovskite. Our findings suggest a promising strategy of dynamic strain engineering in a heterogeneous interface carrying soft and strain-sensitive semiconductors that can happen at a larger volumetric value surpassing the conventional critical thickness limit.
Trajectories of Marital, Parent-Child, and Sibling Conflict During Pediatric Cancer Treatment

Objective: The stress of having a child with cancer can impact the quality of relationships within the family. The current study describes the longitudinal trajectory of marital, parent–child, and sibling conflict beginning around the time of diagnosis through the first year of treatment. We examined the average level of marital, parent–child, and sibling conflict at each monthly time point in the first year of treatment; the proportion of families that fall into the distressed range of marital, parent–child, and sibling conflict at each time point; the typical trajectory of conflict during the first year of treatment and whether there are differences in trajectories across families. Method: A total of 160 families of children newly diagnosed with cancer (Mage = 5.6 years; range = 2–18 years) participated in a short-term prospective longitudinal study. Primary caregivers provided monthly reports of marital, parent–child, and sibling conflict. Results: Using multilevel modeling (MLM), most families showed stability in quality of family relationships, although considerable between-family variability was observed. For married couples, 25–36% of couples were in the distressed range at one time point over the first year of treatment. For married couples, more distress occurred at earlier months, particularly month 3. For parent–child and sibling dyads, the most difficult time periods were during later months. Conclusion: Implications for development of interventions that target at-risk family relationships are discussed. Identifying processes that predict between-family variability in trajectories of family relationships is an important next step, particularly for the marital relationship.
Thermal Recirculation Modeling for Power Plants in an Estuarine Environment

Many power plants require large quantities of water for cooling purposes. The water taken from the source water body (e.g., lakes, estuaries, bays and rivers) circulates through the plant and returns to the source through outfall with a higher temperature. For optimal performance of the power plant, the intake inlet and discharge outlet should be meticulously placed so that the heated water will not recirculate back into the power plant. In this study, the Flow module of the Delft3D software is employed to simulate the temperature transport within the study area in three-dimensional and nested format. Model results are used to optimize the location of intake inlets, outfall outlets and diffuser port orientations. The physical processes used in the study are tidal fluctuations, winds, river discharges, salinity and temperature. The subject power plant (power plant parameters presented in this paper are realistic; however, they do not target any specific power plant within the study area) has a nominal capacity of 2600 MW and is planned to be located in Delaware Bay, USA. Existing field measurements are used to calibrate the model in a coupled two-staged fashion for main tidal constituents, currents and water temperature. The sensitivity of the model against various input parameters is tested, and conservative values are selected. The location of the intake is fixed, and the location of the outfall is changed until the thermal impact to the intake is less than 1 °C. Analysis of the results shows that there is a linear logarithmic relation between the excess temperatures at the intake inlet and horizontal eddy diffusivity. The k - ϵ turbulence closure results in higher excess temperature and a more conservative design. Extending the outfall location to the deeper portion of the estuary combined with port orientations reduces the impact by keeping the thermal plume away from the intake inlet and meeting the established criteria. It is concluded that an approximate distance of 1300 m is the optimal location for the power plant outfall outlets. In addition, the diffuser ports should not discharge the heated water toward the intake and have to be oriented away from the line connecting outfall to the intake.
Longevity-Related Gene Transcriptomic Signature in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) (grade IV astrocytoma) has been assumed to be the most fatal type of glioma with low survival and high recurrence rates, even after prompt surgical removal and aggressive courses of treatment. Transcriptional reprogramming to stem cell-like state could explain some of the deregulated molecular signatures in GBM disease. The present study aimed to quantify the expression profiling of longevity-related transcriptional factors SOX2, OCT3/4, and NANOG to evaluate their diagnostic and performance values in high-grade gliomas. Forty-four specimens were obtained from glioblastoma patients (10 females and 34 males). Quantitative real-time polymerase chain reaction was applied for relative gene expression quantification. In silico network analysis was executed. NANOG and OCT3/4 mRNA expression levels were significantly downregulated while that of SOX2 was upregulated in cancer compared to noncancer tissues. Receiver operating characteristic curve analysis showed high diagnostic performance of NANOG and OCT3/4 than SOX2. However, the aberrant expressions of the genes studied were not associated with the prognostic variables in the current population. In conclusion, the current study highlighted the aberrant expression of certain longevity-associated transcription factors in glioblastoma multiforme which may direct the attention towards new strategies in the treatment of such lethal disease.
The Difference in Interleukin-19 Serum on Degrees of Acne Vulgaris Severity

Introduction Acne vulgaris is a multifactorial disease. Recent study showed that inflammation does have a central role in the formation of both inflammatory and noninflammatory lesions in acne vulgaris. There are various findings of proinflammatory cytokines related to acne vulgaris, but no previous study correlate interleukin- (IL-) 19 to acne vulgaris. This pilot study aims to look at difference in IL-19 serum concentration on degrees of severity of acne vulgaris. Methods This is an analytical observational cross-sectional study. Sample subjects were patients with acne vulgaris who met the inclusion criteria. Enzyme-linked immunosorbent assay (ELISA) study was applied to measure IL-19 serum. Result Analysis test found statistically significant difference between IL-19 serum concentration of group of patients with mild acne vulgaris and that of group of patients with severe acne vulgaris. Moreover, analysis revealed significant difference between IL-19 serum concentration of group of patients with moderate acne vulgaris and that of group of patients with severe acne vulgaris. Conclusions There are differences in serum levels of IL-19 on the severity of acne vulgaris. The significant difference might show that inflammation has a core role in severity of acne vulgaris, and IL-19 might potentially be related to acne vulgaris.
Chemical composition and nutritive values of cassava pulp for cattle.

We evaluated the chemical compositions of cassava pulp samples produced by four cassava starch factories at different locations in northeast Thailand and the metabolizable energy (ME) of the cassava pulp for cattle. There were significant differences in the P (0.03% ± 0.02%) and K (0.36% ± 0.2%) contents of the samples from different factories (p < .05). Moreover, we found interactions between factory and season in the neutral detergent fiber (36.02% ± 8.8%) and nonfibrous carbohydrate contents (59.33% ± 9.1%) (p < .05). For the evaluation of ME, a crossover-design experiment with four cattle maintained in each of two groups was conducted. There were two dietary treatments at a maintenance level of 1.27% body weight: (1) a control diet, and (2) a cassava pulp diet, containing the control diet at 70.2% and cassava pulp at 29.8% (dry matter [DM] basis). Feeding cassava pulp did not affect energy intake, energy loss, heat production, energy utilization efficiency (except for the urine-to-gross energy ratio), methane production, fecal N, or nutrient digestibility (except for crude protein digestibility). The total digestible nutrients, digestible energy, and ME contents of cassava pulp were 74.4%, 12.9 MJ/kg DM, and 11.3 MJ/kg DM, respectively.
Deep Person Detection in Two-Dimensional Range Data

Detecting humans is a key skill for mobile robots and intelligent vehicles in a large variety of applications. Although the problem is well studied for certain sensory modalities such as image data, few works exist that address this detection task using two-dimensional (2-D) range data. However, a widespread sensory setup for many mobile robots in service and domestic applications contains a horizontally mounted 2-D laser scanner. Detecting people from 2-D range data is challenging due to the speed and dynamics of human leg motion and the high levels of occlusion and self-occlusion particularly in crowds of people. While previous approaches mostly relied on handcrafted features, we recently developed the deep learning based wheelchair and walker detector distance robust wheelchair/walker (DROW). In this letter, we show the generalization to people, including small modifications that significantly boost DROW's performance. Additionally, by providing a small, fully online temporal window in our network, we further boost our score. We extend the DROW dataset with person annotations, making this the largest dataset of person annotations in 2-D range data, recorded during several days in a real-world environment with high diversity. Extensive experiments with three current baseline methods indicate it is a challenging dataset, on which our improved DROW detector beats the current state-of-the-art.
CrystalFeel at SemEval-2018 Task 1: Understanding and Detecting Emotion Intensity using Affective Lexicons

While sentiment and emotion analysis has received a considerable amount of research attention, the notion of understanding and detecting the intensity of emotions is relatively less explored. This paper describes a system developed for predicting emotion intensity in tweets. Given a Twitter message, CrystalFeel uses features derived from parts-of-speech, n-grams, word embedding, and multiple affective lexicons including Opinion Lexicon, SentiStrength, AFFIN, NRC Emotion & Hash Emotion, and our in-house developed EI Lexicons to predict the degree of the intensity associated with fear, anger, sadness, and joy in the tweet. We found that including the affective lexicons-based features allowed the system to obtain strong prediction performance, while revealing interesting emotion word-level and message-level associations. On gold test data, CrystalFeel obtained Pearson correlations of 0.717 on average emotion intensity and of 0.816 on sentiment intensity.
Alterations of Cortisol Metabolism in Human Disorders

The interconversion of active and inactive corticosteroids – cortisol and cortisone, respectively, in humans – is modulated by isozymes of 11β-hydroxysteroid dehydrogenase (11-HSD). Studies of this process have provided crucial insights into glucocorticoid effects in a wide variety of tissues. The 11-HSD1 isozyme functions mainly as an oxoreductase (cortisone to cortisol) and is expressed at high levels in the liver and other glucocorticoid target tissues. Because it is required for full physiological effects of cortisol, it has emerged as a drug target for metabolic syndrome and type 2 diabetes. Mutations in the corresponding HSD11B1 gene, or in the H6PD gene encoding hexose-6-phosphate dehydrogenase (which supplies the NADPH required for the oxoreductase activity of 11-HSD1), cause apparent cortisone reductase deficiency, a rare syndrome of adrenocortical hyperactivity and hyperandrogenism. In contrast, the 11-HSD2 isozyme functions as a dehydrogenase (cortisol to cortisone) and is expressed mainly in mineralocorticoid target tissues, where it bars access of cortisol to the mineralocorticoid receptor. Mutations in the HSD11B2 gene encoding 11-HSD2 cause the syndrome of apparent mineralocorticoid excess, a severe form of familial hypertension. The role of this enzyme in the pathogenesis of common forms of low-renin hypertension remains uncertain.
Rarefaction acceleration of ultrarelativistic magnetized jets in gamma-ray burst sources

When a magnetically dominated superfast-magnetosonic long/soft gamma-ray burst (GRB) jet leaves the progenitor star, the external pressure support will drop and the jet may enter the regime of ballistic expansion, during which additional magnetic acceleration becomes ineffective. However, recent numerical simulations by Tchekhovskoy et al. have suggested that the transition to this regime is accompanied by a spurt of acceleration. We confirm this finding numerically and attribute the acceleration to a sideways expansion of the jet, associated with a strong magnetosonic rarefaction wave that is driven into the jet when it loses pressure support, which induces a conversion of magnetic energy into kinetic energy of bulk motion. This mechanism, which we dub rarefaction acceleration, can only operate in a relativistic outflow because in this case the total energy can still be dominated by the magnetic component even in the superfast-magnetosonic regime. We analyse this process using the equations of relativistic magnetohydrodynamics and demonstrate that it is more efficient at converting internal energy into kinetic energy when the flow is magnetized than in a purely hydrodynamic outflow, as was found numerically by Mizuno et al. We show that, just as in the case of the magnetic acceleration of a collimating jet that is confined by an external pressure distribution – the collimation–acceleration mechanism – the rarefaction–acceleration process in a magnetized jet is a consequence of the fact that the separation between neighbouring magnetic flux surfaces increases faster than their cylindrical radius. However, whereas in the case of effective collimation–acceleration the product of the jet opening angle and its Lorentz factor does not exceed ∼1, the addition of the rarefaction–acceleration mechanism makes it possible for this product to become ≫1, in agreement with the inference from late-time panchromatic breaks in the afterglow light curves of long/soft GRBs.
An Ensemble Oversampling Model for Class Imbalance Problem in Software Defect Prediction

Software systems are now ubiquitous and are used every day for automation purposes in personal and enterprise applications; they are also essential to many safety-critical and mission-critical systems, e.g., air traffic control systems, autonomous cars, and SCADA systems. With the availability of massive storage capabilities, high speed Internet, and the advent of Internet of Things devices, modern software systems are growing in both size and complexity. Maintaining a high quality of such complex systems while manually keeping the error rate at a minimum is a challenge. Therefore, automated detection of faulty components in a software system is important during software development and also post-delivery. Fault detection models usually needs to be trained on a labeled-balanced dataset with both faulty and non-faulty samples. Earlier work, e.g. Mohsin et al. (2016), showed that most real fault detection training dataset are imbalanced. Thereby, the trained model gets over-fitted and classifies faulty components as non-faulty components. The consequence of a high false negative rate is cumulative and results in generating more errors when using the model in other software systems –never seen before, which is very expensive. In this paper, we propose a software defect prediction ensemble model which considers the class imbalance problem in real software datasets. We use different oversampling techniques to build an ensemble classifier that can reduce the effect of low minority samples in the defective data. The proposed approach is verified using PROMISE software engineering datasets. The results show that our ensemble oversampling technique can more greatly reduce the false negative rate compared to the standard classification techniques and identify the faulty components more accurately resulting in a less expensive detection system (lowering the rate of non-faulty predictions of faulty modules).
Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence

How do shocks to economic fundamentals in the world economy affect local labor markets? In a framework with a flexible structure of spatial linkages, we characterize the model-consistent shock exposure of a local market as the exogenous shift in its production revenues and consumption costs. In general equilibrium, labor outcomes in any market respond directly to the market’s own shock exposure, and indirectly to other markets shocks exposures. We show how spatial linkages control the size and the heterogeneity of these indirect effects. We then develop a new estimation methodology - the Model-implied Optimal IV (MOIV) - that exploits quasi-experimental variation in economic shocks to estimate spatial linkages and evaluate their counterfactual implications. Applying our methodology to US Commuting Zones, we find that difference-in-difference designs based on model-consistent measures of local shock exposure approximate well the differential effect of international trade shocks across CZs, but miss around half of the aggregate effect, partly due to the offsetting action of indirect effects.
Importance of tangible physical changes for quality of life improvements of type 2 diabetic and at-risk individuals involved in exercise intervention A quasi-experimental design.

Objectives 1) To document quality of life (QOL) changes in type 2 diabetes (T2D) and at-risk individuals who took part in the DiabetAction program and 2) to determine if changes in the QOL were associated with program attendance. Methods QOL (SF-36 questionnaire), physical activity (PA) level, body weight, skinfold thickness, aerobic capacity and handgrip strength were measured before and after the 10-week intervention in 15 T2D and 14 at-risk individuals. Results Physical and mental components of QOL and 6 out of 8 domains of QOL were significantly improved in T2D and at-risk individuals after the intervention. Four significant correlations were identified: physical functioning domain with skinfolds (r = – 0.56) and aerobic capacity (r = 0.49), social functioning domain with handgrip strength (r = 0.43) and the physical health summary measure with body weight (r = – 0.45). Conclusion QOL was significantly improved after the DiabetAction program. Also, PA intervention appears to impact QOL to a larger extent when participants experience changes in body composition and fitness.
The Effects of Acupuncture Combined with Auricular Acupressure in the Treatment of Chloasma

Objective To investigate the effectiveness of acupuncture combined with auricular acupressure in chloasma treatment. Methods A prospective, randomized controlled assessor-blind clinical trial was performed and 135 patients were assigned into acupuncture combined with auricular acupressure (A), acupuncture (B), and control (C) groups, each with 45 patients. For groups A and B, body and facial acupuncture were applied for 2 months. For group A, auricular acupressure was applied concomitantly. For group C, vitamins C and E were prescribed for 3 months. Primary outcome measure was the therapeutic effects while secondary outcome measure was safety evaluation. Results The total effective rate was 95.6%, 91.1%, and 75.6% for groups A, B, and C (P < 0.01 between groups A and C; P < 0.05 between groups B and C). The posttreatment estradiol (E2) levels in groups A and B were significantly decreased while the progesterone (P4) levels were significantly increased compared to pretreatment (P < 0.01 and P < 0.05, resp.). The differences were significant compared to group C (P < 0.01 and P < 0.05, resp.). No adverse events occurred. Conclusion Acupuncture combined with auricular acupressure could significantly increase the therapeutic effect of chloasma treatment and could be better than vitamins C and E.
First attempts for predicting future Salinization in coastal irrigated areas

Salinity contamination of irrigation ground water is a serious worldwide problem. The Mnasra zone, which has an agricultural land area that represents 70% of the total area and its agricultural production reaches 12% of the national production, is threatened by a Salinization of underground waters. The ground water available in this region allows the supply of a population of 145 000 inhabitants. We have developed a simple mechanistic simulation model for predicting future Salinization in this ground water. The method adopted to predict the variation of salinity pollution in ground water is the same as the population based on an increase (or decrease) geometry (geometric series). This work allows preparing for and coping with the environmental pollution that threatens not only humans, but also the fauna and flora of this region. According to this study, we predict an area of 8730 hectares where water will be polluted by the salinity in 2021. These results will have a negative impact at medium and long terms on the agricultural production of this region.
A Missense Mutation in POU4F3 Causes Midfrequency Hearing Loss in a Chinese ADNSHL Family

Hereditary nonsyndromic hearing loss is extremely heterogeneous. Mutations in the POU class 4 transcription factor 3 (POU4F3) are known to cause autosomal dominant nonsyndromic hearing loss linked to the loci of DFNA15. In this study, we describe a pathogenic missense mutation in POU4F3 in a four-generation Chinese family (6126) with midfrequency, progressive, and postlingual autosomal dominant nonsyndromic hearing loss (ADNSHL). By combining targeted capture of 129 known deafness genes, next-generation sequencing, and bioinformatic analysis, we identified POU4F3 c.602T>C (p.Leu201Pro) as the disease-causing variant. This variant cosegregated with hearing loss in other family members but was not detected in 580 normal controls or the ExAC database and could be classified as a “pathogenic variant” according to the American College of Medical Genetics and Genomics guidelines. We conclude that POU4F3 c.602T>C (p.Leu201Pro) is related to midfrequency hearing loss in this family. Routine examination of POU4F3 is necessary for the genetic diagnosis of midfrequency hearing loss.