Miracle-dz/UniFAR-FTUs huggingface dataset:
Biochemical and physiological responses of three wheat cultivars ( Triticum aestivum L . ) to salinity stress

For the purpose of studying the effect of different salinity levels on biochemical and physiologicalsc est characteristics and yield three cultivars of wheat, an experiment on research greenhouse; Islamic Azad University, kermanshah , was performed in 2007-2008. This facto rial experiment of research was carried out 3 repli cat on and in the form of the randomize complete blocks design . cultivars factor were placed in the blocks at 3 l evels including Chamran, Marvdasht and Shahryar and salinity stress factors at 3 levels including 0.6(control) ,8 and1 6 dSm in the blocks. The results showed that with increasing alinity, number of grain per spike, number of gra in per spikelet, number of fertile spikelet, number of tillers, 1000 grain wheat, plant hight, grain yield, biological yield , harvest index and relative water content were decreased but proline and water soluble carbohydrate were increa s d. The negative effect of salinity on plant was due increa sing Na and decreasing K + content in the leaves . The most this traits was observed at the Chamran cultivar but the highest sodium content belonged to Shahryar cultiv ar. Biological yield and harvest index, had the highest correlation with grain yield. The most tolerant an d stable was Chamran cultivar that had highest yield on salinity level of 16 dSmto other cultivars.
Thoracic calcifications on magnetic resonance imaging: correlations with computed tomography

ABSTRACT Objective: To identify the characteristics of thoracic calcifications on magnetic resonance (MR) imaging, as well as correlations between MR imaging and CT findings. Methods: This was a retrospective study including data on 62 patients undergoing CT scans and MR imaging of the chest at any of seven hospitals in the Brazilian states of Rio Grande do Sul, São Paulo, and Rio de Janeiro between March of 2014 and June of 2016 and presenting with calcifications on CT scans. T1- and T2-weighted MR images (T1- and T2-WIs) were semiquantitatively analyzed, and the lesion-to-muscle signal intensity ratio (LMSIR) was estimated. Differences between neoplastic and non-neoplastic lesions were analyzed. Results: Eighty-four calcified lesions were analyzed. Mean lesion density on CT was 367 ± 435 HU. Median LMSIRs on T1- and T2-WIs were 0.4 (interquartile range [IQR], 0.1-0.7) and 0.2 (IQR, 0.0-0.7), respectively. Most of the lesions were hypointense on T1- and T2-WIs (n = 52 [61.9%] and n = 39 [46.4%], respectively). In addition, 19 (22.6%) were undetectable on T1-WIs (LMSIR = 0) and 36 (42.9%) were undetectable on T2-WIs (LMSIR = 0). Finally, 15.5% were hyperintense on T1-WIs and 9.5% were hyperintense on T2-WIs. Median LMSIR was significantly higher for neoplastic lesions than for non-neoplastic lesions. There was a very weak and statistically insignificant negative correlation between lesion density on CT and the following variables: signal intensity on T1-WIs, LMSIR on T1-WIs, and signal intensity on T2-WIs (r = −0.13, p = 0.24; r = −0.18, p = 0.10; and r = −0.16, p = 0.16, respectively). Lesion density on CT was weakly but significantly correlated with LMSIR on T2-WIs (r = −0.29, p < 0.05). Conclusions: Thoracic calcifications have variable signal intensity on T1- and T2-weighted MR images, sometimes appearing hyperintense. Lesion density on CT appears to correlate negatively with lesion signal intensity on MR images.
Automatic 3 D Non-rigid Registration of Whole Body Serial MR Animal Images

Introduction Registration of serial images is critical for detecting or measuring changes such as variations in tumor size, shape, or physiological characteristics in response to therapy. A number of automatic methods have been proposed to address this problem, which have been successfully applied to the registration of head images. However, the automatic registration of whole body MR images, which requires non-rigid registration techniques, remains a challenge. Recently we proposed a novel registration method that permits the automatic registration of CT images [1, 2]. In this study, this algorithm is extended and applied to small animal MR images.
Observation of quality of life and negative emotions of patients with cervical cancer after neoadjuvant chemotherapy in early psychological nursing

Objective: The goal of this study was to assess the quality of life and negative emotions of patients with cervical cancer after neoadjuvant chemotherapy in early psychological nursing. Methods: A total of 154 patients with cervical cancer who received neoadjuvant chemotherapy in Linyi People’s Hospital were included and divided into two groups, with 77 cases in each group. The quality of life, negative emotions, mental health, and sleep quality were compared between the two groups after different nursing methods. Results: There was no significant difference in the general data, quality of life, negative emotions, mental health, and sleep quality scores before nursing intervention (P>0.05). The total effective rate after neoadjuvant adjuvant chemotherapy (NACT) treatment was 71.42% in the observation group and 68.83% in the control group. There was no significant difference in efficacy between the two groups (P>0.05). After the nursing intervention, quality of life scores, sleep quality, mental health, and anxiety and depression of the two groups were significantly improved compared with those before nursing intervention (all P<0.05). After the nursing intervention, the scores of life quality, anxiety and depression, mental health and sleep quality of the observation group were significantly improved and were better than those of the control group (all P<0.05), especially in terms of the scores of emotional function (P<0.001) and somatic pain (P=0.012). Conclusion: Psychological nursing intervention can improve the quality of life, reduce negative emotions such as anxiety and depression, improve mental health, and improve sleep quality of patients with cervical cancer. Thus, psychological nursing intervention is worthy of clinical application in the management of cancer.
GrAF version of Spanish portions of Wikipedia Corpus

This is the stand-off GrAF version of Spanish portions of the Wikipedia (based on a 2006 dump). This Wikipedia Spanish Corpus contains 257019 articles that contain about 150,1 million words in raw text format. It has been cleaned by erasing disambiguation pages, removing some XML tags and homogenizing lists ending tag. Then, the corpus has been processed for adding structural tagging (head, paragraph, sentence, list, etc.) and morphosyntactic information.
Dopamine and Dopamine Receptors in Alzheimer's Disease: A Systematic Review and Network Meta-Analysis

Background: The dopaminergic system has been associated with the progression of Alzheimer's disease. But previous studies found inconsistent results regarding the relationship between Alzheimer's disease and dopamine when looking at dopamine receptor concentrations. Objective: The aim of this review was to synthesize, using a random-effects model of meta-analysis, the link between the dopaminergic system and Alzheimer's disease. Methods: A detailed analysis protocol was registered at the PROSPERO database prior to data extraction (CRD42018110798). Electronic databases of PubMed, Embase, Web of Science, and Psyc-ARTICLES were searched up to December 2018 for studies that examined dopamine and dopamine receptors in relation to Alzheimer's disease. Standardized mean differences (SMD) were calculated to assess group differences in the levels of dopaminergic neurometabolites. Results: Seventeen studies met the eligibility criteria. Collectively, they included 512 patients and 500 healthy controls. There were significantly lower levels of dopamine in patients with Alzheimer's disease compared with controls (SMD = −1.56, 95% CI: −2.64 to −0.49). In addition, dopamine 1 receptor (SMD = −5.05, 95% CI: −6.14 to −3.97) and dopamine 2 receptor (SMD = −1.13, 95% CI: −1.52 to −0.74) levels were decreased in patients with Alzheimer's disease compared with controls. The results of network meta-analysis indicated that the rank of correlation with Alzheimer's disease from highest to lowest was dopamine (0.74), dopamine 2 receptor (0.49), dopamine 3 receptor (0.46), dopamine 4 receptor (0.33), dopamine 5 receptor (0.31), and dopamine 1 receptor (0.64). Conclusions: Overall, decreased levels of dopaminergic neurotransmitters were linked with the pathophysiology of Alzheimer's disease. Nonetheless, there is a clear need for more prospective studies to validate these hypotheses.
Polygenic Risk Score for Alzheimer’s Disease Is Associated With Ch4 Volume in Normal Subjects

Alzheimer’s disease (AD) is a common neurodegenerative disease. APOE is the strong genetic risk factor of AD. The existing genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) with minor effects on AD risk and the polygenic risk score (PRS) is presented to combine the effect of these SNPs. On the other hand, the volumes of various brain regions in AD patients have significant changes compared to that in normal individuals. Ch4 brain region containing at least 90% cholinergic neurons is the most extensive and conspicuous in the basal forebrain. Here, we investigated the relationship between the combined effect of AD-associated SNPs and Ch4 volume using the PRS approach. Our results showed that Ch4 volume in AD patients is significantly different from that in normal control subjects (p-value < 2.2 × 10−16). AD PRS, is not associated with the Ch4 volume in AD patients, excluding the APOE region (p-value = 0.264) and including the APOE region (p-value = 0.213). However, AD best-fit PRS, excluding the APOE region, is associated with Ch4 volume in normal control subjects (p-value = 0.015). AD PRS based on 8070 SNPs could explain 3.35% variance of Ch4 volume. In addition, the p-value of AD PRS model in normal control subjects, including the APOE region, is 0.006. AD PRS based on 8079 SNPs could explain 4.23% variance of Ch4 volume. In conclusion, PRS based on AD-associated SNPs is significantly related to Ch4 volume in normal subjects but not in patients.
Estimating the Aboveground Carbon Density of Coniferous Forests by Combining Airborne LiDAR and Allometry Models at Plot Level

Forest carbon density is an important indicator for evaluating forest carbon sink capacities. Accurate carbon density estimation is the basis for studying the response mechanisms of forest ecosystems to global climate change. Airborne light detection and ranging (LiDAR) technology can acquire the vertical structure parameters of forests with a higher precision and penetration ability than traditional optical remote sensing. Combining top of canopy height model (TCH) and allometry models, this paper constructed two prediction models of aboveground carbon density (ACD) with 94 square plots in northwestern China: one model is plot-averaged height-based power model and the other is plot-averaged daisy-chain model. The correlation coefficients (R2) were 0.6725 and 0.6761, which are significantly higher than the correlation coefficients of the traditional percentile model (R2 = 0.5910). In addition, the correlation between TCH and ACD was significantly better than that between plot-averaged height (AvgH) and ACD, and Lorey’s height (LorH) had no significant correlation with ACD. We also found that plot-level basal area (BA) was a dominant factor in ACD prediction, with a correlation coefficient reaching 0.9182, but this subject requires field investigation. The two models proposed in this study provide a simple and easy approach for estimating ACD in coniferous forests, which can replace the traditional LiDAR percentile method completely.
TLR7 Protein Expression in Mild and Severe Lupus-Prone Models Is Regulated in a Leukocyte, Genetic, and IRAK4 Dependent Manner

The global increase in autoimmunity, together with the emerging autoimmune-related side effects of cancer immunotherapy, have furthered a need for understanding of immune tolerance and activation. Systemic lupus erythematosus (SLE) is the archetypical autoimmune disease, affecting multiple organs, and tissues. Studying SLE creates knowledge relevant not just for autoimmunity, but the immune system in general. Murine models and patient studies have provided increasing evidence for the innate immune toll like receptor-7 (TLR7) in disease initiation and progression. Here, we demonstrated that the kinase activity of the TLR7-downstream signaling molecule, interleukin-1 receptor associated kinase 4 (IRAK4), is essential for mild and severe autoimmune traits of the Sle1 and Sle1-TLR7 transgenic (Sle1Tg7) murine models, respectively. Elimination of IRAK4 signaling prevented all pathological traits associated with murine lupus, including splenomegaly with leukocyte expansion, detectable circulating antinuclear antibodies and glomerulonephritis, in both Sle1 and Sle1Tg7 mice. The expansion of germinal center B cells and increased effector memory T cell phenotypes that are typical of lupus-prone strains, were also prevented with IRAK4 kinase elimination. Analysis of renal leukocyte infiltrates confirmed our earlier findings of an expanded conventional dendritic cell (cDC) within the kidneys of nephritic mice, and this was prevented with IRAK4 kinase elimination. Analysis of TLR7 at the protein level revealed that the expression in immune cells is dependent on the TLR7-transgene itself and/or autoimmune disease factors in a cell-specific manner. Increased TLR7 protein expression in renal macrophages and cDCs correlated with disease parameters such as blood urea nitrogen (BUN) levels and the frequency of leukocytes infiltrating the kidney. These findings suggest that controlling the level of TLR7 or downstream signaling within myeloid populations may prevent chronic inflammation and severe nephritis.
How the Realism of Robot Is Needed for Individuals With Autism Spectrum Disorders in an Interview Setting

The preliminary efficacy of interview training using an android robot whose appearance and movements resemble those of an actual human for treating social and communication difficulties in individuals with autism spectrum disorders (ASD) has been demonstrated. Patient preferences regarding the appearance of robots are crucial for incentivizing them to undergo robot-assisted therapy. However, very little is known about how the realistic nature of an android robot is related to incentivizing individuals with ASD in an interview setting. In this study, individuals with ASD underwent an interview with a human interviewer and an android robot. Twenty-three individuals with ASD (age, 17–25 years) participated in this study. After the interview, the participants were evaluated in terms of their motivation to practice an interview with an android robot and their impression of the nature of the android robot in terms of humanness. As expected, subjects exhibited higher motivation to undergo interview training with an android robot than with a human interviewer. Higher motivation to undergo an interview with the android robot was negatively correlated with the participants’ impressions of the extent to which the android robot exhibited humanness. This study brings us one step closer to understanding how such an android robot should be designed and implemented to provide sufficiently realistic interview training that can be of therapeutic value.
Coaches’ Emotional Intelligence and Reactive Behaviors in Soccer Matches: Mediating Effects of Coach Efficacy Beliefs

In the last 10 years, emotional intelligence (EI) has become a current issue of research in psychology, and there are indicators to consider that EI should be analyzed to help the coach to behave effectively during competitions. According to Boardley’s (2018) revised model of coaching efficacy, coaches’ EI is predictive of their efficacy beliefs, which, in turn, is predictive of coaching behavior. However, little is known about the mediating effects of coaching efficacy dimensions on the relationships between coach’s EI and reactive behaviors in competitive settings. Thus, the purpose of this study is to examine mediating effects of coaching efficacy dimensions on the relationship between EI and coaches’ reactive behaviors during a game using a multimethod approach. Participants were 258 coaches of youth football players aged 9 to 17 years old. Observations in situ using Coaching Behavior Assessment System (CBAS) were carried on 258 football games during two seasons. At the end of each game, coaches completed the Wong and Law Emotional Intelligence Scale (WLEIS) and the Coaching Efficacy Scale (CES). Structural equation modeling (SEM) analyses revealed that motivation efficacy and character building mediated the relationship between regulation of emotion and positive and negative coaches’ reactions during game. Specifically, motivation efficacy mediated the association between regulation of emotion and positive coaches’ reactions, and the relationship between regulation of emotion and negative coaches’ reactions were mediated by motivation efficacy and character building. In addition, coaching level moderated the relationships between EI, self-efficacy and coaches’ reactive behaviors. Findings of the present study showed that coaching efficacy dimensions (i.e., motivation efficacy and character building) that have the capacity to influence their confidence in ability to affect the psychological mood and positive attitude of athletes, transfer the effects of EI (i.e., regulation of emotion) on coaches’ verbal reactions during a youth soccer game. Specifically, a coach who feels competent to regulate their own emotions would perceive high beliefs of efficacy to motivate and to build character of their athletes, and this insight has an impact on their positive verbal reactions in response to athletes’ performances.
Soil Microbial Biomass and Fungi Reduced With Canola Introduced Into Long-Term Monoculture Wheat Rotations

With increasing canola (Brassica napus L.) acreage in the Inland Pacific Northwest of the USA, we investigated the effect of this relatively new rotational crop on soil microbial communities and the performance of subsequent wheat (Triticum aestivum L.) crops. In a 6-year on-farm canola-wheat rotation study conducted near Davenport, WA, grain yields of spring wheat (SW) following winter canola (WC) were reduced an average of 17% compared to SW yields following winter wheat (WW). Using soil samples collected and analyzed every year from that study, the objective of this research was to determine the differences and similarities in the soil microbial communities associated with WC and WW, and if those differences were associated with SW yield response. Microbial biomass and community composition were determined using phospholipid fatty acid analysis (PLFA). The WC-associated microbial community contained significantly less fungi, mycorrhizae, and total microbial biomass than WW. Additionally, reduced fungal and mycorrhizal abundance in SW following WC suggests that the canola rotation effect can persist. A biocidal secondary metabolite of canola, isothiocyanate, may be a potential mechanism mediating the decline in soil microbial biomass. These results demonstrate the relationship between soil microbial community composition and crop productivity. Our data suggest that WC can have significant effects on soil microbial communities that ultimately drive microbially mediated soil processes.
A Cationic Tetraphenylethene as a Light-Up Supramolecular Probe for DNA G-Quadruplexes

Guanine-quadruplexes (G4s) are targets for anticancer therapeutics. In this context, human telomeric DNA (HT-DNA) that can fold into G4s sequences are of particular interest, and their stabilization with small molecules through a visualizable process has become a challenge. As a new type of ligand for HT-G4, we designed a tetraimidazolium tetraphenylethene (TPE-Im) as a water-soluble light-up G4 probe. We study its G4-binding properties with HT-DNA by UV-Visible absorption, circular dichroism and fluorescence spectroscopies, which provide insights into the interactions between TPE-Im and G4-DNA. Remarkably, TPE-Im shows a strong fluorescence enhancement and large shifts upon binding to G4, which is valuable for detecting G4s. The association constants for the TPE-Im/G4 complex were evaluated in different solution conditions via isothermal titration calorimetry (ITC), and its binding modes were explored by molecular modeling showing a groove-binding mechanism. The stabilization of G4 by TPE-Im has been assessed by Fluorescence Resonance Energy Transfer (FRET) melting assays, which show a strong stabilization (ΔT1/2 around +20°C), together with a specificity toward G4 with respect to double-stranded DNA.
Semi-supervised learning for identifying opinions in web content

Opinions published on the World Wide Web (Web) offer opportunities for detecting personal attitudes regarding topics, products, and services. The opinion detection literature indicates that both a large body of opinions and a wide variety of opinion features are essential for capturing subtle opinion information. Although a large amount of opinion-labeled data is preferable for opinion detection systems, opinion-labeled data is often limited, especially at sub-document levels, and manual annotation is tedious, expensive and error-prone. This shortage of opinion-labeled data is less challenging in some domains (e.g., movie reviews) than in others (e.g., blog posts). While a simple method for improving accuracy in challenging domains is to borrow opinion-labeled data from a non-target data domain, this approach often fails because of the domain transfer problem: Opinion detection strategies designed for one data domain generally do not perform well in another domain. However, while it is difficult to obtain opinion-labeled data, unlabeled user-generated opinion data are readily available. Semi-supervised learning (SSL) requires only limited labeled data to automatically label unlabeled data and has achieved promising results in various natural language processing (NLP) tasks, including traditional topic classification; but SSL has been applied in only a few opinion detection studies. This study investigates application of four different SSL algorithms in three types of Web content: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. SSL algorithms are also evaluated for their effectiveness in sparse data situations and domain adaptation. Research findings suggest that, when there is limited labeled data, SSL is a promising approach for opinion detection in Web content. Although the contributions of SSL varied across data domains, significant improvement was demonstrated for the most challenging data domain—the blogosphere—when a domain transfer-based SSL strategy was implemented.