Additional file 1: of Social supports and mental health: a cross-sectional study on the correlation of self-consistency and congruence in China

Social Support Rating Scale (SSRS) (Xiao, 1999). (DOCX 14 kb

Additional file 2: of Social supports and mental health: a cross-sectional study on the correlation of self-consistency and congruence in China

Self-Consistence and Congruence Scale (SCCS) (Wang, 1994). (DOCX 15 kb

Joint Network Reconstruction and Community Detection from Rich but Noisy Data

Most empirical studies of complex networks return rich but noisy data, as they measure the network structure repeatedly but with substantial errors due to indirect measurements. In this article, we propose a novel framework, called the group-based binary mixture (GBM) modeling approach, to simultaneously conduct network reconstruction and community detection from such rich but noisy data. A generalized expectation-maximization (EM) algorithm is developed for computing the maximum likelihood estimates, and an information criterion is introduced to consistently select the number of communities. The strong consistency properties of the network reconstruction and community detection are established under some assumption on the Kullback-Leibler (KL) divergence, and in particular, we do not impose assumptions on the true network structure. It is shown that joint reconstruction with community detection has a synergistic effect, whereby actually detecting communities can improve the accuracy of the reconstruction. Finally, we illustrate the performance of the approach with numerical simulations and two real examples. Supplementary materials for this article are available online.</p

Label-Free Fluorescence Sensing of Lead(II) Ions and Sulfide Ions Based on Luminescent Molybdenum Disulfide Nanosheets

Fluorescent molybdenum disulfide (MoS₂) nanosheets were synthesized hydrothermally by employing sodium molybdate and thiourea as the starting materials. Lead­(II) ion was introduced as a chemical dopant into the fluorescent nanosheets for the first time, and it was found that the fluorescence of the doped MoS₂ nanosheets showed a considerable enhancement compared with that of initial MoS₂ nanosheets, implying that lead­(II)-doping into the MoS₂ nanosheets could result in an increase in the fluorescence quantum yield. In parallel, we exploited the lead­(II)-induced fluorescence enhancement of MoS₂ nanosheets to design a green and facile fluorescent “turn on” nanosensor for lead­(II) detection. Moreover, we found that the fluorescent intensity of the doped MoS₂ nanosheets was drastically quenched by the successive addition of sulfide ions. Hence, the “turn off” process was used to fabricate a green fluorescence quenching sensor for detection of sulfide ions. Finally, we elucidated the origin of the lead­(II)-induced fluorescence enhancement and sulfide-induced fluorescence reduction by using various analytical techniques like scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and UV–vis spectroscopy. The work not only opens a door for the further development of new approaches for the preparation of various fluorescent layered transition metal dichalcogenides with high quantum yields but also provides a versatile and sustainable sensing platform for ion detection

Table_1_Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model.docx

IntroductionThe rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage.MethodsTo bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools.ResultsHypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution.ConclusionOverall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice.</p

Теория антикризисного управления предприятием

Учеб.-метод. пособие для самостоят. работы [для студентов спец. 080503.65 "Антикризисное управление"].Доступ к полному тексту открыт из сети СФУ, вне сети доступ возможен для читателей Научной библиотеки СФУ или за плату.Учебно-методическое пособие по дисциплине «Теория антикризисного управления предприятием» предназначено для организации самостоятельной работы. В нем предложены варианты проведения самостоятельной работы по дисциплине. При этом используются: метод выполнения домашних заданий, метод подготовки к эссе, метод выполнения рефератов, метод использования докладов по результатам «домашних заданий» и по выполненным рефератам. Предназначено для студентов специальности 080503.65 Антикризисное управление очной и заочной форм обучения

Changes in the maximum air temperature variation (MaxATV) values (a) and explanatory power, R² values (b) of regression models for air temperatures as a function of the percentage of man-made surfaces with spatial scale during daytime and nighttime in winter and summer.

<p>Changes in the maximum air temperature variation (MaxATV) values (a) and explanatory power, R² values (b) of regression models for air temperatures as a function of the percentage of man-made surfaces with spatial scale during daytime and nighttime in winter and summer.</p

Image_1_Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model.tif

IntroductionThe rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage.MethodsTo bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools.ResultsHypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution.ConclusionOverall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice.</p

A map of the study area and location of measurement points.

<p>The numbers represent the mobile measurement points, while the lowercase letters represent the three fixed air temperature measurement sites.</p

Correlation coefficients between air temperature and land cover types at different temporal and spatial scales.

<p>Note: PerBA, PerPA, PerTC, PerLA and PerWA refer to the percentage of building area, paved area, tree area, lawn area, and water body area respectively. The bold numbers represent the highest correlation coefficient for each land cover type among different spatial extents (from 20 to 300 m in radius).</p><p>*Correlation is significant at the 0.05 level (two-tailed).</p><p>**Correlation is significant at the 0.01 level (two-tailed).</p