Key Influencing Factors Affecting the Student Academic Performance and Student Satisfactions Ratings: Evidence from Undergraduate Students in China

This paper has developed a sound and practical method to evaluate the key teaching quality including the student academic performance and student satisfaction ratings. The method makes use of the existing data already readily available in a Chinese university, focusing on the identification of key influencing factors affecting the student academic performance and student satisfactions ratings. The data analyses have shown the university student academic performance is significantly affected student gender, age, previous academic performance, settlements and occupations of parents. There is significant difference in the student ratings for different genders and academic positions of teaching staff. The student performance and satisfaction ratings also significantly vary in different years of intakes and different Schools/programs. The student’s university academic performance can be accurately predicted using artificial neural networks with a prediction error of about 7%. This approach can help the university to improve the student academic performance and student satisfactions

Bayesian imaging inverse problem with SA-Roundtrip prior via HMC-pCN sampler

Bayesian inference with deep generative prior has received considerable interest for solving imaging inverse problems in many scientific and engineering fields. The selection of the prior distribution is learned from, and therefore an important representation learning of, available prior measurements. The SA-Roundtrip, a novel deep generative prior, is introduced to enable controlled sampling generation and identify the data's intrinsic dimension. This prior incorporates a self-attention structure within a bidirectional generative adversarial network. Subsequently, Bayesian inference is applied to the posterior distribution in the low-dimensional latent space using the Hamiltonian Monte Carlo with preconditioned Crank-Nicolson (HMC-pCN) algorithm, which is proven to be ergodic under specific conditions. Experiments conducted on computed tomography (CT) reconstruction with the MNIST and TomoPhantom datasets reveal that the proposed method outperforms state-of-the-art comparisons, consistently yielding a robust and superior point estimator along with precise uncertainty quantification

Application of Nanotechnology in Wastewater Treatment

Because the current social water pollution is serious, and the conventional method cannot eff ectively manage alltypes of water pollution, and its single eff ect cannot be satisfactory, we must seek new and eff ective treatment. Thepaper is a comprehensive review of the best practices of the conventional wastewater treatment method with referenceto the experiments and research results of nanotechnology in sewage treatment. Comparison of nanotechnology canbe compared with conventional methods to make the particles have a special function, and some special performancejust in the sewage treatment medium to a good effect: the depth of the catalytic method can be effective in thedecomposition of many types of organic pollutants such as halogenated hydrocarbons Class, chlorinated phenols,cyanide, various organic acids and can handle metal particles; adsorption method for the water heavy metal pollutiontreatment costs less, simple and widely used, nanofi ltration membrane can replace the adsorption and electrochemicalmethods, Pulping and precipitation are one of the most eff ective methods for the treatment of colloidal wastewater. Itcan eff ectively reduce the turbidity and chroma of waste water, remove a variety of macromolecular organic matter andsome heavy metal ions ( Mercury and lead); organic / inorganic composite nanoparticles with its excellent inorganicmaterials, light, electricity, magnetic and other properties, organic materials, excellent processing performance,biocompatibility, for many diffi cult to deal with water pollution control, which has a corresponding method, can besimple and eff ective to solve the problem. The application of nanotechnology in water treatment has shown a broadprospect, but needs further research and improvement

Paracrine GABA and insulin regulate pancreatic alpha cell proliferation in a mouse model of type 1 diabetes

Aims/hypothesis: This study aimed to elucidate the mechanism of increased proliferation of alpha cells in recent-onset type 1 diabetes. Pancreatic beta cells express GAD and produce γ-aminobutyric acid (GABA), which inhibits alpha cell secretion of glucagon. We explored the roles of GABA in alpha cell proliferation in conditions corresponding to type 1 diabetes in a mouse model and in vitro. Methods: Type 1 diabetes was induced by injecting the mice with streptozotocin (STZ). Some of the STZ-injected mice were treated with GABA (10 mg/kg daily) for 12 days. Isolated pancreatic islets were treated with STZ or STZ together with GABA for 2 days. The effects of GABA treatment on STZ-induced alpha cell proliferation in vivo and in vitro were assessed. The effect of muscimol, a GABA receptor agonist, on αTC1-6 cell proliferation was also examined. Results: STZ injection substantially decreased levels of GAD, GABA and insulin in pancreatic beta cells 12 h after injection; this was followed by an upsurge of phosphorylated mechanistic target of rapamycin (p-mTOR) in the alpha cells at day 1, and a significant increase in alpha cell mass at day 3. Treating STZ-injected mice with GABA largely restored the immunodetectable levels of insulin and GAD in the beta cells and significantly decreased the number of aldehyde dehydrogenase 1 family, member A3 (ALDH1a3)-positive cells, alpha cell mass and hyperglucagonaemia. STZ treatment also increased alpha cell proliferation in isolated islets, which was reversed by co-treatment with GABA. Muscimol, together with insulin, significantly lowered the level of cytosolic Ca2+ and p-mTOR, and decreased the proliferation rate of αTC1-6 cells. Conclusions/interpretation: GABA signalling critically controls the alpha cell population in pancreatic islets. Low intraislet GABA may contribute to alpha cell hyperplasia in early type 1 diabetes

Altitudinal Patterns of Leaf Traits and Leaf Allometry in Bamboo Pleioblastus amarus

Awareness of local-scale variation in leaf traits for a single species and the relationships between these traits and their dependence on altitude might be essential for extrapolating ecophysiological processes from the leaf to the ecosystem level. While altitudinal patterns of leaf traits have been extensively studied in a number of species, little is known about such patterns in bamboos. We analyzed leaf functional traits and leaf allometric relationships of Pleioblastus amarus at three different altitudes (200, 400, and 800 m). With increasing altitude, most functional traits, including leaf length, width, perimeter, area, dry weight, and water content, decreased significantly, while the leaf length:width ratio exhibited a marked increase, resulting in a tendency toward narrow leaves. Specific leaf area first increased, and then decreased, while the change in leaf dry matter content showed the opposite trend. Leaf area was positively correlated with leaf length, leaf width and leaf perimeter, but negatively correlated with the leaf length:width ratio. With increasing altitude, the slopes of these relationships for leaf area first increased, and then decreased. Leaf biomass was positively correlated with leaf length, width, perimeter, and area, with the slopes of the relationships being the same at all altitudes. Thus, the leaves of this bamboo species at middle altitude have the highest specific leaf area and lowest leaf dry matter content. Our findings suggest that this bamboo species has a big potential of growth and morphological plasticity

Vertically-aligned Mn(OH)2 nanosheet films for flexible all-solid-state electrochemical supercapacitors

The arrangement of the electrode materials is a significant contributor for constructing high performance supercapacitor. Here, vertically-aligned Mn(OH)2 nanosheet thin films were synthesized by cathodic electrodeposition technique on flexible Au coated polyethylene terephthalate substrates. Morphologies, microstructures, chemical compositions and valence state of the nanosheet films were characterized systematically. It shows that the nanosheets arranged vertically to the substrate, forming a porous nanowall structures and creating large open framework, which greatly facilitate the adsorption or diffusion of electrolyte ions for faradaic redox reaction. Electrochemical tests of the films show the specific capacitance as high as 240.2 F g−1 at 1.0 A g−1. The films were employed to assemble symmetric all-solid-state supercapacitors with LiCl/PVA gel severed as solid electrolyte. The solid devices exhibit high volumetric capacitance of 39.3 mF cm−3 at the current density 0.3 mA cm−3 with robust cycling stability. The superior performance is attributed to the vertically-aligned configuration

S-Nitrosylation of STIM1 by Neuronal Nitric Oxide Synthase Inhibits Store-Operated Ca\u3csup\u3e2 +\u3c/sup\u3e Entry

Store-operated Ca2 + entry (SOCE) mediated by stromal interacting molecule-1 (STIM1) and Orai1 represents a major route of Ca2 + entry in mammalian cells and is initiated by STIM1 oligomerization in the endoplasmic or sarcoplasmic reticulum. However, the effects of nitric oxide (NO) on STIM1 function are unknown. Neuronal NO synthase is located in the sarcoplasmic reticulum of cardiomyocytes. Here, we show that STIM1 is susceptible to S-nitrosylation. Neuronal NO synthase deficiency or inhibition enhanced Ca2 + release-activated Ca2 + channel current (ICRAC) and SOCE in cardiomyocytes. Consistently, NO donor S-nitrosoglutathione inhibited STIM1 puncta formation and ICRAC in HEK293 cells, but this effect was absent in cells expressing the Cys49Ser/Cys56Ser STIM1 double mutant. Furthermore, NO donors caused Cys49- and Cys56-specific structural changes associated with reduced protein backbone mobility, increased thermal stability and suppressed Ca2+ depletion-dependent oligomerization of the luminal Ca2 +-sensing region of STIM1. Collectively, our data show that S-nitrosylation of STIM1 suppresses oligomerization via enhanced luminal domain stability and rigidity and inhibits SOCE in cardiomyocytes