Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of snowpack on forest water stress in the Sierra Nevada

Higher global temperatures and intensification of extreme hydrologic events, such as droughts, can lead to premature tree mortality. In a Mediterranean climate like California, the seasonality of precipitation is out of sync with the peak growing season. Seasonal snowpack plays a critical role in reducing this mismatch between the timing of water input to the root zone and the peak forest water use. A loss of snowpack, or snow droughts, during warmer years, increases the asynchrony between water inputs and the peak of forest water use, intensifying water stress and tree mortality. Therefore, we hypothesize that the montane vegetation response to interannual climate variability in a Mediterranean climate is regulated by the snowpack. We tested this hypothesis using the 2012–2015 drought as a natural experiment. Regional Generalized Additive Models (GAMs) were used to infer and quantify the role of snowpack on forest water stress. The models simulate the Normalized Difference Infrared Index (NDII) as a proxy of forest water stress using water deficit (as seasonality index), location, slope, and aspect. The GAMs were trained using 75% of the data between 2001 and 2014. The remaining 25% of the data were used for validation. The model was able to simulate forest water stress for 2015 and 2016 across the northern, central, and southern Sierra Nevada with a range of R2 between 0.80 and 0.84. The simulated spatial patterns in forest water stress were consistent with those captured by the USDA Forest Service Aerial Detection Survey. Our findings suggest that the failure of a reduced snowpack in mitigating water deficit exacerbates forest water stress and tree mortality. Variations in water and surface energy budget across an elevational gradient play a critical role in modulating the vegetation response. These results provide insights into the importance of the Sierra Nevada snowpack under a warming climate. The models can aid forest managers to identify future forest water stress and tree die-off patterns.
Fucosylated N-glycans as early biomarkers of COVID-19 severity

Background The pathological mechanisms of SARS-CoV-2 in humans remain unclear and the unpredictability of COVID-19 progression may be attributed to the absence of biomarkers that contribute to the prognosis of this disease. Therefore, the discovery of biomarkers is needed for reliable risk stratification and to identify patients who are more likely to progress to a critical stage. Methods Aiming to identify new biomarkers we analysed N-glycan traits in plasma from 196 patients with COVID-19. Samples were classified into three groups according to their severity (mild, severe and critical) and obtained at diagnosis (baseline) and at 4 weeks of follow-up (postdiagnosis), to evaluate their behaviour through disease progression. N-glycans were released with PNGase F and labelled with Rapifluor-MS, followed by their analysis by LC-MS/MS. The Simglycan structural identification tool and Glycostore database were employed to predict the structure of glycans. Results We determined that plasma from SARS-CoV-2-infected patients display different N-glycosylation profiles depending on the disease severity. Specifically, levels of fucosylation and galactosylation decreased with increasing severity and Fuc1Hex5HexNAc5 was identified as the most suitable biomarker to stratify patients at diagnosis and distinguish mild from critical outcomes. Conclusion In this study we explored the global plasma glycosignature, reflecting the inflammatory state of the organs during the infectious disease. Our findings show the promising potential of glycans as biomarkers of COVID-19 severity.
Identifying vital nodes in recovering dynamical process of networked system

Vital nodes identification is the problem of identifying the most significant nodes in complex networks, which is crucial in understanding the property of the networks and has applications in various fields such as pandemic controlling and energy saving. Traditional methods mainly focus on some types of centrality indices, which have restricted application cases. To improve the flexibility of the process and enable simultaneous multiple nodes mining, a deep learning-based vital nodes identification algorithm is proposed in this study, where we train the influence score of each node by using a set of nodes to approximate the rest of the network via the graph convolutional network. Experiments are conducted with generated data to justify the effectiveness of the proposed algorithm. The experimental results show that the proposed method outperforms the traditional ways in adaptability and accuracy to recover the dynamical process of networked system under different classes of network structure.
Efficacy and tolerability of minocycline in depressive patients with or without treatment-resistant: a meta-analysis of randomized controlled trials

Background Minocycline, an antibiotic with anti-inflammatory, antioxidant, and neuroprotective properties, has been used for treating psychiatric disorders in research. This systematic review aimed to evaluate the efficacy and tolerability of minocycline in patients having depression with or without treatment-resistance. Methods Electronic databases including Embase, PubMed, and the Cochrane library were searched for relevant studies published up to October 17, 2022. The primary efficacy outcome was the change in depression severity scores and the secondary efficacy outcomes included the changes in Clinical Global Impression (CGI) and Beck Depression Inventory (BDI) scores and the incidence of response and partial response. Safety outcomes were evaluated based on the incidence of classified adverse events and all-cause discontinuation. Results Five studies with 374 patients were selected for analysis. The minocycline group demonstrated a significant reduction in depression severity scale (standardized mean difference [SMD]: −0.59, 95% confidence interval [CI]: −0.98 to −0.20, P = 0.003) and CGI (SMD: −0.28, 95% CI: −0.56 to −0.01, P = 0.042) scores; however, no statistical difference was found in terms of the BDI score, response, and partial response. No significant differences were found between the groups in terms of adverse events (other than dizziness) and discontinuation rates. Subgroup analysis showed that minocycline was also effective in reducing depression severity scores in treatment-resistant depression (SMD: −0.36, 95% CI: −0.64 to −0.09, P = 0.010). Subgroup analysis of Hamilton Depression Rating Scale (17-item) scores showed a statistical difference in response in patients with depression (relative risk: 2.51, 95% CI: 1.13 to 5.57, P = 0.024). Conclusions Minocycline may improve depressive symptoms and augment response to treatment in patients with depression irrespective of treatment-resistance. However, clinical trials with large sample sizes are warranted for evaluating long-term outcomes with minocycline. Systematic review registration https://inplasy.com/inplasy-2022-12-0051/.
Protistan community structure and the influence of a branch of Kuroshio in the northeastern East China Sea during the late spring

The northeastern East China Sea is an ecologically important marine ecosystem influenced by warm water derived from the Kuroshio Current. However, relatively little is known about the spatial variation of protist communities and their regulating factors from this region’s ecosystem during the spring season. Here, we investigated protistan community structures using a complementary approach combining 18S rRNA gene amplicon sequencing and light microscopy cell counts at nine stations from the northeastern East China Sea to the west of Jeju Island. The vertical profiles of physicochemical properties revealed that the Jeju Warm Current water mass, flowing from the southeast towards the northwest, created a thermohaline front dividing the region in two. These two regions had similar planktonic biomass, but the protistan communities differed significantly: dinoflagellates accounted for higher proportions of the protistan communities in the warm and saline waters, particularly at stations E35, E44, and E45, while the relative abundances of diatoms and picochlorophytes were higher in the low-density water of the western stations (E32 and E42). Furthermore, higher species richness and Shannon Diversity Index values in the warm and saline waters suggests that the Jeju Warm Current, a branch of the Kuroshio, increases protistan taxonomic diversity in the northeastern East China Sea during the late spring. Seed populations of harmful algal bloom-causing species were discovered in the warm and saline water originating from the Kuroshio, which is particularly important as it indicates that these waters could introduce harmful species that may spread to the Yellow Sea and Korea Strait. Taken together, the study suggests that potential changes to the current systems in the region could dramatically alter the structure of its protistan community.
Non-alcoholic fatty liver disease and incidence of microvascular complications of diabetes in patients with type 2 diabetes: a prospective cohort study

Objective To investigate the association between non-alcoholic fatty liver disease (NAFLD) and liver enzymes with the incidence of microvascular complications (neuropathy, retinopathy, and nephropathy) in a cohort of Iranian patients with type 2 diabetes. Methods For a total population of 3123 patients with type 2 diabetes, a prospective study was designed for 1215 patients with NAFLD and 1908 gender and age-matched control patients without NAFLD. The two groups were followed for a median duration of 5 years for the incidence of microvascular complications. The association between having NAFLD, the level of liver enzymes, aspartate aminotransferase to platelet ratio index (APRI), Fibrosis-4 (FIB-4) value, and the incidence risk of diabetic retinopathy, neuropathy, and nephropathy were assessed through logistic regression analysis. Results NAFLD was found to be associated with incidence of diabetic neuropathy and nephropathy (Odds ratio: 1.338 (95% confidence interval: 1.091-1.640) and 1.333 (1.007-1.764), respectively). Alkaline-phosphatase enzyme was found to be associated with higher risks of diabetic neuropathy and nephropathy ((Risk estimate: 1.002 (95% CI: 1.001-1.003) and 1.002 (1.001-1.004), respectively)). Moreover, gamma-glutamyl transferase was associated with a higher risk of diabetic nephropathy (1.006 (1.002-1.009). Aspartate aminotransferase and alanine aminotransferase were inversely associated with the risk of diabetic retinopathy (0.989 (0.979-0.998) and 0.990 (0.983-0.996), respectively). Furthermore, ARPI_T (1), ARPI_T (2), and ARPI_T (3) were shown to be associated with NAFLD (1.440 (1.061-1.954), 1.589 (1.163-2.171), and 2.673 (1.925, 3.710), respectively). However, FIB-4 score was not significantly associated with risk of microvascular complications. Conclusion Despite the benign nature of NAFLD, patients with type 2 diabetes should be always assessed for NAFLD to ensure early diagnosis and entry into proper medical care. Regular screenings of microvascular complications of diabetes is also suggested for these patients.
Effect of gut microbiome regulated Taohong Siwu Decoction metabolism on glioma cell phenotype

Introduction To establish a new model for exploring the mechanism of the gut microbiome and drug metabolism, we explored whether Taohong Siwu Decoction acts after metabolism by intestinal flora under the premise of clarifying the interaction between intestinal flora and drug metabolism. Methods Taohong Siwu Decoction (TSD) was fed to germ-free mice and conventional mice, respectively. The serum from both groups of mice was removed and co-cultured with glioma cells in vitro. The co-cultured glioma cells were compared separately for changes at the RNA level using RNA-seq technology. The genes of interest in the comparison results were selected for validation. Results The differences in the phenotypic alterations of glioma cells between serum from TSD-fed germ-free mice and normal mice were statistically significant. In vitro experiments showed that Taohong Siwu Decoction-fed normal mouse serum-stimulated glioma cells, which inhibited proliferation and increased autophagy. RNA-seq analysis showed that TSD-fed normal mouse serum could regulate CDC6 pathway activity in glioma cells. The therapeutic effect of TSD is significantly influenced by intestinal flora. Conclusion The treatment of tumors by TSD may be modulated by intestinal flora. We established a new method to quantify the relationship between intestinal flora and the regulation of TSD efficacy through this study.
The role of the broader autism phenotype in anxiety and depression in college-aged adults

The current study examines the relationship between the presence of autistic traits and anxiety and mood disorders in young adults from different racial groups. A representative sample from a predominately white university (2,791 non-Hispanic White (NHW) and 185 Black students) completed the broad autism phenotype questionnaire (BAPQ), a measure of depression (Patient Health Questionnaire, PHQ-9), and anxiety (Generalized Anxiety Disorder, GAD-7). Statistical Package for Social Sciences (SPSS) was used to perform two multiple regression analyses to determine the association between race, BAPQ score and anxiety and depression symptoms. The current study found a stronger association between autistic traits had depression and anxiety symptoms in Black participants than did NHW participants. These findings underscore the association between autistic traits and anxiety and depression in Black communities, and the need for further studies on this topic area. Additionally, it highlights the importance of improving access to mental health care for this population.
Why are human animacy judgments continuous rather than categorical? A computational modeling approach

Introduction The concept of animacy is often taken as a basic natural concept, in part I because most cases seem unambiguous. Most entities either are or are not animate. However, human animacy judgments do not reflect this binary classification. They suggest that there are borderline cases, such as virus, amoeba, fly, and imaginary beings (giant, dragon, god). Moreover, human roles (professor, mother, girlfriend) are consistently recognized as animate by far less than 100% of human judges. Method In this paper, I use computational modeling to identify features associated with human animacy judgments, modeling human animacy and living/non-living judgments using both bottom-up predictors (the principal components from a word embedding model) and top-down predictors (cosine distances from the names of animate categories). Results The results suggest that human animacy judgments may be relying on information obtained from imperfect estimates of category membership that are reflected in the word embedding models. Models using cosine distance from category names mirror human judgments in distinguishing strongly between humans (estimated lower animacy by the measure) and other animals (estimated higher animacy by the measure). Discussion These results are consistent with a family resemblance approach to the apparently categorical concept of animacy.
QTL mapping and improvement of pre-harvest sprouting resistance using japonica weedy rice

The stability of cultivation and production in terms of crop yield has been threatened by climate change due to global warming. Pre-harvest sprouting (PHS) is a threat to crops, especially staple foods, including rice, because of reductions in yield and quality. To address the problem of precocious germination before harvest, we performed quantitative trait loci (QTL) analysis for PHS using F8 RILs populations derived from japonica weedy rice in Korea. QTL analysis revealed that two stable QTLs, qPH7 and qPH2, associated with PHS resistance were identified on chromosomes 7 and 2, respectively, explaining approximately 38% of the phenotypic variation. The QTL effect in the tested lines significantly decreased the degree of PHS, based on the number of QTLs included. Through fine mapping for main QTL qPH7, the region for the PHS was found to be anchored within 23.575–23.785 Mbp on chromosome 7 using 13 cleaved amplified sequence (CAPS) markers. Among 15 open reading frames (ORFs) within the detected region, one ORF, Os07g0584366, exhibited upregulated expression in the resistant donor, which was approximately nine times higher than that of susceptible japonica cultivars under PHS-inducing conditions. Japonica lines with QTLs related to PHS resistance were developed to improve the characteristics of PHS and design practical PCR-based DNA markers for marker-assisted backcrosses of many other PHS-susceptible japonica cultivars.
Calderón-Zygmund Operators With Non-doubling Measures

In this survey, the authors review some basic results on Calderon-Zygmund theory on R d with the non-doubling Radon measure µ. Instead of the usual doubling condition, the measure µ is only assumed to satisfy some growth condition, that is, there exist positive con- stants n ∈ (0 ,d )a ndC such that µ(B(x,r)) ≤ Cr n for all x ∈ R d and r ∈ (0, ∞). In this setting, the results that we review are the following: the Hardy space H 1 (µ) and the regularized BMO space RBMO(µ), some interpolation results related to H 1 (µ )a nd RBMO(µ), the Calderon- Zygmund decomposition, the T(1) theorem and the properties of the Calderon-Zygmund op- erator on Lebesgue spaces and Hardy spaces, Cotlar's inequality and the boundedness of the maximal Calderon-Zygmund operator, the behaviors of the multilinear Calderon-Zygmund op- erator on Lebesgue spaces, weighted norm inequalities for the Calderon-Zygmund operator, the boundedness of the commutator generated by the Calderon-Zygmund operator and RBMO(µ) function. Moreover, some new progress obtained recently is also included.
Testing for Correlated Errors in the Analysis of Variance

SUMMARY In a two-way analysis of variance, one factor may have a spatial or temporal structure, in which case correlation may be expected between the errors for the different levels of that factor. This note suggests a procedure for checking this in analyses with just one observation per combination of levels of the two factors. The procedure involves calculation of correlation coefficients. It is illustrated on measurements of the size of mitral cells in the olfactory bulbs of rats. It is now standard practice, when fitting a model to data, to use residuals to check for inadequacies in the fit. In an analysis of variance the residuals may be checked for nonnormality or for an effect not included in the model-an interaction, for example. This note suggests a further test for the adequacy of the model in the two-way analysis of variance with just one observation per combination of levels of the two factors. The test is based on the correlations between the residuals and can be used to detect whether the errors are, contrary to assumption, correlated. Such a test is applicable if one factor in an experiment has some spatial or temporal structure so that neighbouring units may have error structures that are associated. (A biological example of such a factor is time of observation.) That the existence of serial correlations amongst the errors can invalidate the usual F-test has been noted by, for example, Andersen, Jensen, and Schou (1981), Box (1954), Daniels (1938), Fisher (1941, p. 226), and Hearne, Clark, and Hatch (1983). A simple approach is to compute an overall estimate of the lag-I serial correlation coefficient. This is inappropriate, however, if the "true" serial correlations vary with the levels of the spatial or temporal factor. The correlations may even have opposite signs at different levels. In the case of a two-way analysis of variance, where the first factor is spatial or temporal, the observations at the different levels of the second factor provide replicates that can be used to calculate sample correlation coefficients between the residuals at the different levels of the first factor. These correlation coefficients can then be assessed to determine whether there are any unusually large ones. The only difficulty is that there may be a large number of coefficients to consider so that the problem of "multiple comparisons" arises: If there are k levels of the spatial (temporal) factor, there are up to (ok) correlation coeffi1cients that may be of interest; thus, if an overall test at the a level of significance is required, the critical point for comparing each correlation must depend on the number of comparisons to be made.
True-Value Regression Theory

Design-based regression regards the survey response as a constant waiting to be observed. Bechtel (2007) replaced this constant with the sum of a fixed true value and a random measurement error. The present paper relaxes the assumption that the expected error is zero within a survey re- spondent. It also allows measurement errors in predictor variables as well as in the response variable. Reasonable assumptions about these errors over respondents, along with coefficient alpha in psychological test theory, enable the regression of true responses on true predictors. This resolves two major issues in survey regression, i.e. errors in variables and item non-response. The usefulness of this resolution is demonstrated with three large datasets collected by the European Social Survey in 2002, 2004 and 2006. The paper concludes with implications of true-value regression for survey theory and practice and for surveying large world populations.
An Investigation of the Collaborations Between Educators and Vocational Rehabilitation Counselors in Providing Pre-Employment Transition Services

Employment has historically provided a person with value and the ability to live a self-determined and independent life. Interagency collaborations have been found to play a key role in promoting employment for those with special needs. However, there is little research on identifying the needs of the field for collaborations between vocational rehabilitation and educational agencies. We conducted a series of eight focus groups in a large state in the United States and identified needs from educators and vocational rehabilitation counselors. Participants regularly noted that they needed increased collaboration and a need for additional training and education for all stakeholders. They also identified many barriers to this increased collaboration and training, including access to the community that they served, limitations on time for training, collaboration, and access, challenges in communication, including language limitations and trust, and limitations around the support that they received. On the other hand, they often felt supported by their administration, and, when collaboration was possible, their co-workers and external providers served as great resources.
A Negative Selection Algorithm Based on Chaos Theory

To increase antibody generating speed in artificial immune system,a chaos negative selection algorithm was presented which is based on the chaotic character of immune system.Over-spread character of chaos sequence was used to generate candidate set of detector firstly,and then the chaos disturbance was used to get some individuals directly and reduce search space,additionally chaos initial value sensitivity was used to overcome redundancies.The experimental results showed that the algorithm noy only retains the diversity of population but also increases the generating efficiency of detector.