An ultrafast and self-powered MoSxSe2-x/Si photodetector with high light-trapping structures and a SiOx interface layer.

MoSxSe2-x nanofilms, as a typical metal dichalcogenide, have attracted great interest, due to their adjustable bandgap and distinctive electronic and optical properties. However, the inherent bandgap of MoSxSe2-x and the strong interface recombination impede the actualization of a high-sensitivity photodetector (PD). Few-layer MoSxSe2-x nanofilms were prepared with vertically orientation at 450 °C, which would be a less restrictive choice of substrates. Herein, a self-powered MoSxSe2-x/SiOx/Si photodetector was fabricated which exhibits unprecedented performance with excellent reproducibility and stability from 405 nm to 980 nm, a high responsivity (0.450 A W-1), normalized detectivity (4.968 × 1012 Jones) and ultrafast photoresponse (τr = 1.20 µs, τf = 4.92 µs) at zero bias under 980 nm incident laser illumination with a density of 200 µW cm-2. Significantly, the self-powered PD is capable of detecting ultraweak IR signals below 200 µW cm-2 with high on-off ratios. More importantly, an oxidized atomic layer is generated through the wet oxidation in the Piranha solution. The PD can work well at high frequencies even at 100 kHz, which shows its potential application in high-frequency photoelectric devices and health monitors. Summing up, this work not only suggests that an ultrathin SiOx interface layer can reduce carrier recombination via simple interface engineering, but also proposes a novel strategy for the preparation of high-performance and low-cost optoelectronic devices.

Quantifying microstructural evolution via time-dependent reduced-dimension metrics based on hierarchical n-point polytope functions.

We devise reduced-dimension metrics for effectively measuring the distance between two points (i.e., microstructures) in the microstructure space and quantifying the pathway associated with microstructural evolution, based on a recently introduced set of hierarchical n-point polytope functions P_{n}. The P_{n} functions provide the probability of finding particular n-point configurations associated with regular n polytopes in the material system, and are a special subset of the standard n-point correlation functions S_{n} that effectively decompose the structural features in the system into regular polyhedral basis with different symmetries. The nth order metric Ω_{n} is defined as the L_{1} norm associated with the P_{n} functions of two distinct microstructures. By choosing a reference initial state (i.e., a microstructure associated with t_{0}=0), the Ω_{n}(t) metrics quantify the evolution of distinct polyhedral symmetries and can in principle capture emerging polyhedral symmetries that are not apparent in the initial state. To demonstrate their utility, we apply the Ω_{n} metrics to a two-dimensional binary system undergoing spinodal decomposition to extract the phase separation dynamics via the temporal scaling behavior of the corresponding Ω_{n}(t), which reveals mechanisms governing the evolution. Moreover, we employ Ω_{n}(t) to analyze pattern evolution during vapor deposition of phase-separating alloy films with different surface contact angles, which exhibit rich evolution dynamics including both unstable and oscillating patterns. The Ω_{n} metrics have potential applications in establishing quantitative processing-structure-property relationships, as well as real-time processing control and optimization of complex heterogeneous material systems.

Effect of the Applied Fertilization Method under Full Straw Return on the Growth of Mechanically Transplanted Rice.

This study aimed to improve nitrogen utilization and alleviate the inhibition of straw decomposition during early tillering and the growth of paddy after straw return. Specifically, three different nitrogen fertilizer (base fertilizer) application methods were tested under full straw return: applying the compound fertilizer once (J1), applying the compound fertilizer twice (J3) and applying the ammonium carbonate fertilizer plus compound fertilizer (J2). Full straw return without fertilizer (CK1) and no straw return without fertilizer (CK2) were used as the controls. The results showed that treatment with ammonium carbonate fertilizer combined with compound fertilizer (J2) significantly enhanced straw decomposition, light interception and dry matter accumulation at an early stage of tillering, but reduced tiller occurrence at a late tillering stage. Grain yield was affected due to reduced dry matter accumulation, nitrogen use efficiency and number of effective panicles. There were no significant differences in rice growth, nitrogen use efficiency and grain yield between the one-time or two-time compound fertilizer application methods. In contrast, treatment with ammonium carbonate fertilizer combined with compound fertilizer (J2) under full straw return effectively improved straw decomposition and accelerated the return of green and tillering. In addition, the proportion of ammonium carbonate fertilizer affected the nutrient utilization efficiency and yield at later stages.

Evaluation of sludge reduction of three metabolic uncouplers in laboratory-scale anaerobic-anoxic-oxic process.

To evaluate the sludge reduction of three metabolic uncouplers (3,3',4',5-tetrachlorosalicylanilide (TCS), 2,4-dichlorophenol (DCP), and tetrakis (hydroxymethyl) phosphonium sulfate (THPS)), we conducted continuous experiments on laboratory-scale anaerobic-anoxic-oxic processes. The three metabolic uncouplers were separately added in each oxic tank of the three systems, and a system without uncoupler addition was used as control. During the 85-day operation, sludge production and observed growth yields decreased to 38.6% and 16.98%, 43.4% and 17.55%, and 39.3% and 17.04% by the addition of TCS, DCP, and THPS, respectively. The addition of metabolic uncouplers slightly reduced the wastewater treatment efficiencies of the system (about 1.1-8.7%) and increased sludge SVIs (about 69.9-80.6%). Meanwhile, the differences among three metabolic uncouplers were little. Besides metabolic uncoupling and maintenance metabolism, which exist in the TCS- and DCP-added systems, lysis-cryptic growth also exists in the THPS-added system.

Accurate stochastic reconstruction of heterogeneous microstructures by limited x-ray tomographic projections.

An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for its performance prediction, prognosis and optimization. X-ray tomography has provided a nondestructive means for microstructure characterization in 3D and 4D (i.e. structural evolution over time), in which a material is typically reconstructed from a large number of tomographic projections using filtered-back-projection (FBP) method or algebraic reconstruction techniques (ART). Here, we present in detail a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of absorption contrast x-ray tomographic projections. This discrete tomography reconstruction procedure is in contrast to the commonly used FBP and ART, which usually requires thousands of projections for accurate microstructure rendition. The utility of our stochastic procedure is first demonstrated by reconstructing a wide class of two-phase heterogeneous materials including sandstone and hard-particle packing from simulated limited-angle projections in both cone-beam and parallel beam projection geometry. It is then applied to reconstruct tailored Sn-sphere-clay-matrix systems from limited-angle cone-beam data obtained via a lab-scale tomography facility at Arizona State University and parallel-beam synchrotron data obtained at Advanced Photon Source, Argonne National Laboratory. In addition, we examine the information content of tomography data by successively incorporating larger number of projections and quantifying the accuracy of the reconstructions. We show that only a small number of projections (e.g. 20-40, depending on the complexity of the microstructure of interest and desired resolution) are necessary for accurate material reconstructions via our stochastic procedure, which indicates its high efficiency in using limited structural information. The ramifications of the stochastic reconstruction procedure in 4D materials science are also discussed.

Dynamic reconstruction of heterogeneous materials and microstructure evolution.

Reconstructing heterogeneous materials from limited structural information has been a topic that attracts extensive research efforts and still poses many challenges. The Yeong-Torquato procedure is one of the most popular reconstruction techniques, in which the material reconstruction problem based on a set of spatial correlation functions is formulated as a constrained energy minimization (optimization) problem and solved using simulated annealing [Yeong and Torquato, Phys. Rev. E 57, 495 (1998)]. The standard two-point correlation function S2 has been widely used in reconstructions, but can also lead to large structural degeneracy for certain nearly percolating systems. To improve reconstruction accuracy and reduce structural degeneracy, one can successively incorporate additional morphological information (e.g., nonconventional or higher-order correlation functions), which amounts to reshaping the energy landscape to create a deep (local) energy minimum. In this paper, we present a dynamic reconstruction procedure that allows one to use a series of auxiliary S2 to achieve the same level of accuracy as those incorporating additional nonconventional correlation functions. In particular, instead of randomly sampling the microstructure space as in the simulated annealing scheme, our procedure utilizes a series of auxiliary microstructures that mimic a physical structural evolution process (e.g., grain growth). This amounts to constructing a series auxiliary energy landscapes that bias the convergence of the reconstruction to a favored (local) energy minimum. Moreover, our dynamic procedure can be naturally applied to reconstruct an actual microstructure evolution process. In contrast to commonly used evolution reconstruction approaches that separately generate individual static configurations, our procedure continuously evolves a single microstructure according to a time-dependent correlation function. The utility of our procedure is illustrated by successfully reconstructing nearly percolating hard-sphere packings and particle-reinforced composites as well as the coarsening process in a binary metallic alloy.

Search for genetic determinants of sulfonylurea efficacy in type 2 diabetic patients from China.

AIMS/HYPOTHESIS: The aim of this study was to investigate whether genetic variance can influence the efficacy of glibenclamide in patients with type 2 diabetes. METHODS: A total of 747 patients with type 2 diabetes was enrolled from the Xiaoke Pills Clinical Trial, which is a double-blind, randomised controlled trial. All the patients had been treated with glibenclamide for 48 weeks, with strict drug dose adjustment and data collection. Treatment failure was confirmed when patients reached the criteria for terminating their participation in the study (fasting blood glucose level ≥ 7.0 mmol/l on two consecutive tests 4 weeks after reaching the pre-set maximal dose or maximal tolerated dose). Using this cohort, we tested 44 single-nucleotide polymorphisms (SNPs) in 27 gene regions. The genes in our study were involved in the metabolism of sulfonylureas, islet beta cell function, insulin resistance and beta cell growth and differentiation. A logistic regression model was used to evaluate the relationship between genetic variants and treatment failure over a period of 48 weeks. RESULTS: We found that no SNP reached the significance level of p < 0.00125 if Bonferroni correction was performed for multiple testing in the logistic regression model used in this pharmacogenetic study. Participants with the minor allele C of rs10811661 in CDKN2A/CDKN2B showed a significantly greater reduction in fasting blood glucose (TT vs TC vs CC: 9.3% (0-20.0%) vs 9.2% (0.9-20.5%) vs 12.7% (5.2-24.4%), p = 0.008) after the initial 4 weeks of treatment independent of age, sex and BMI. There was a significant difference in beta cell function among carriers of different genotypes of rs10811661. CONCLUSIONS/INTERPRETATION: Our study demonstrated that the CDKN2A/CDKN2B gene may be nominally associated with the efficacy of glibenclamide, and that CDKN2A/CDKN2B is associated with beta cell function.

An evidence-based proposal for predicting organ failure in severe acute pancreatitis.

OBJECTIVES: Early, efficient, and accurate evaluation for organ failure is an important step for improving outcome in severe acute pancreatitis (SAP). We aim to develop a method that can early, efficiently, and accurately evaluate the in-hospital organ failure in patients with SAP. METHODS: Using multivariate logistic regression analysis, the associative factors for in-hospital organ failure were evaluated retrospectively from conventional data obtained from 393 patients with SAP from 2000 to 2012. In classification and regression tree analysis, a new clinical scoring system was developed for the evaluation of in-hospital organ failure in SAP. We also compared the accuracy of our new scoring system with multiple organ dysfunction score and Acute Physiology and Chronic Health Examination II score by the receiver operating characteristic curve. RESULTS: Laboratory results revealed serum calcium level greater than or equal to 1.84 mmol/L, serum creatinine level greater than or equal to 110 µmol/L, age greater than or equal to 72 years, activated partial thromboplastin time less than or equal to 30.95 seconds, and Balthazar computed tomography score greater than or equal to 7 (CCAAB) score system, each contributed 1 point for the prediction of organ failure. The area under the curve of the CCAAB score system was similar to multiple organ dysfunction scores and Acute Physiology and Chronic Health Examination II scores. CONCLUSIONS: The new scoring system CCAAB is an efficient and accurate method for the early evaluation of patients with SAP for in-hospital organ failure.

Functional Val66Met polymorphism of Brain-derived neurotrophic factor in type 2 diabetes with depression in Han Chinese subjects.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) has been implicated in the pathogenesis of major depression. Individuals with type 2 diabetes (T2DM) have a high prevalence of major depression and low levels of BDNF. We therefore explored whether the BDNF Val66Met polymorphism is associated with co-morbid depression and whether depression affects the serum levels of BDNF in a Han Chinese subjects with T2DM. METHODS: A Total of 296 T2DM patients and 70 healthy volunteers (Health control, HC group) were recruited in this study. T2DM patients were divided into two subgroups: depressive diabetes group (DDM group, n = 64) and non-depressive diabetes group (NDDM group, n = 232), according to the presence or the absence of depression assessed by Center for Epidemiologic Studies Depression Scale (CES-D) and Patient Health Questionnaire-9 (PHQ-9). Val66Met polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism analysis (PCR-RFLP). Serum BDNF levels were measured by ELISA kit. RESULTS: In this study, 21.6% (64/296) patients with T2DM had depression. The BDNF Val66Met genotype distributions were statistically different among the three groups (χ2 = 7.39, p < 0.05). DDM group carried the highest frequencies of Met allele (53.9%) compared to HC group (39.3%) and NDDM group (38.8%). Subjects with Met/Met had lowest serum BDNF levels (76.59 ± 5.12 pg/ml, F = 7.39, p < 0.05) compared to subjects with Val/Met (79.04 ± 5.19 pg/ml) and Val/Val (83.83 ± 3.97 pg/ml). Within T2DM group, it was also observed that the serum BDNF levels in DDM group were significantly lower than those in NDDM group (76.67 ± 5.35 vs. 79.84 ± 3.97 pg/ml, p < 0.05). In type 2 diabetes subjects, BDNF serum levels were significant correlations with genotypes (r = -0.346, p < 0.01), depression scores (r = -0.486, p < 0.01) and HbA1c (r = -0.168, p < 0.05). After adjustment for gender, HbA1c, BMI and numbers of complications, BDNF Val/Met genotype distributions (OR = 2.105, p < 0.05) and decreased serum BDNF levels (OR = 0.835, p < 0.01) were independently associated with depression in T2DM. CONCLUSIONS: The BDNF Val66Met polymorphism might be implicated in the pathogenesis of depression in T2DM by decreasing serum BDNF levels in Han Chinese Subjects.

Effects of atorvastatin on bone metabolism and bone mineral density in Wistar rats.

OBJECTIVE: To investigate the effects of atorvastatin on bone formation, bone resorption and bone mineral density in Wistar rats. METHODS: Sixty healthy male Wistar rats were randomly divided into one control group treated with vehicle alone and three drug treatment groups, which were treated with atorvastatin at 5 mg/kg x d, 25 mg/kg x d and 50 mg/kg x d respectively. Left femur BMD and bone metabolic parameters were measured after 8 weeks of treatment. In high dose of atorvastatin group, 20 rats were randomly allocated into persistent treatment group or atorvastatin washout group for another 4 weeks; bone metabolic parameters were retested. RESULTS: Compared with vehicle alone, atorvastatin treatment significantly increased serum levels of ALP and BGP, but had no effects on serum Ca or P levels. Moreover, atorvastatin significantly decreased bone resorption markers including 24 h urinary Ca/Cr ratio, P/Cr ratio and serum IL-6 level. There was no significant difference among atorvastatin treatment groups. After 4 weeks of washout period, the effects of atorvastatin on bone formation and resorption markers decreased. Atorvastatin treatment did not alter BMD compared with the control group, even in the highest dose of atorvastatin group. CONCLUSION: Atorvastatin treatment in a certain extent inhibits bone resorption and promotes bone formation, but has no significant effects on bone mineral density in healthy rats.

Nosocomial mortality and early prediction of patients with severe acute pancreatitis.

BACKGROUND AND AIMS: The aim of this study is to analyze factors (especially serum total cholesterol) that can enable early prediction of in-hospital mortality of patients with severe acute pancreatitis (SAP). METHODS: Predictive factors (especially serum total cholesterol) for in-hospital mortality were evaluated retrospectively from the clinical data obtained from 338 SAP patients in our hospital from January 1999 to January 2008, who underwent intensive care, blood routine, blood biochemical tests and even computed tomography at the time of admission. RESULTS: This analysis revealed that within 24 h after admission, serum total cholesterol (TC) was a mortality-reduced factor when it is between 4.37 mmol/L and 5.23 mmol/L (P < 0.05). Evaluated TC was accompanied by decreased C-reactive protein (CRP). CRP > 170 mg/L and albumin (ALB) < 30 g/L increased the fatal outcome (P < 0.05). Low albumin was a stronger predictor than CRP. CONCLUSIONS: Within 24 h after admission, moderate elevation of TC level seemed to increase the resistance to inflammation and hence improved the survival rate in patients with SAP, and reduced the in-hospital mortality. Inflammatory reaction (with or without infection), hypoalbuminemia and TC were prognostic factors for in-hospital mortality; both high levels of CRP and low ALB levels were associated with in-hospital mortality in patients with SAP.