Preparation of Kaolin Composites and Its Adsorption for Sb(Ⅲ)

Antimony is an important element in the production of flame retardants and semiconductor materials. In the process of antimony mining, it may cause local environmental pollution, which has adverse effects on human health, and the development of economical and efficient adsorbents to remove antimony from wastewater has become a hot research topic. In this paper, the hydrothermal synthesis method was adopted, and purified Kaolin was selected as the carrier, potassium permanganate, manganese chloride and ferric chloride are the metal sources, urea is the precipitant, and sodium dodecyl benzene sulfonate is the structure guide agent. Under the conditions of 5% mass fraction of dispersant, loading temperature of 140 ℃, reaction time of 8 h, mass ratio of iron to manganese of 1.84:1, and mass of precipitant of 0.9 g, the composites prepared were effective in adsorbing the Sb(Ⅲ) from the wastewater. The optimum adsorption efficiency of the prepared composites on Sb(Ⅲ) is 92.83%, which showed excellent adsorption performance

Learning to Accelerate Symbolic Execution via Code Transformation

Symbolic execution is an effective but expensive technique for automated test generation. Over the years, a large number of refined symbolic execution techniques have been proposed to improve its efficiency. However, the symbolic execution efficiency problem remains, and largely limits the application of symbolic execution in practice. Orthogonal to refined symbolic execution, in this paper we propose to accelerate symbolic execution through semantic-preserving code transformation on the target programs. During the initial stage of this direction, we adopt a particular code transformation, compiler optimization, which is initially proposed to accelerate program concrete execution by transforming the source program into another semantic-preserving target program with increased efficiency (e.g., faster or smaller). However, compiler optimizations are mostly designed to accelerate program concrete execution rather than symbolic execution. Recent work also reported that unified settings on compiler optimizations that can accelerate symbolic execution for any program do not exist at all. Therefore, in this work we propose a machine-learning based approach to tuning compiler optimizations to accelerate symbolic execution, whose results may also aid further design of specific code transformations for symbolic execution. In particular, the proposed approach LEO separates source-code functions and libraries through our program-splitter, and predicts individual compiler optimization (i.e., whether a type of code transformation is chosen) separately through analyzing the performance of existing symbolic execution. Finally, LEO applies symbolic execution on the code transformed by compiler optimization (through our local-optimizer). We conduct an empirical study on GNU Coreutils programs using the KLEE symbolic execution engine. The results show that LEO significantly accelerates symbolic execution, outperforming the default KLEE configurations (i.e., turning on/off all compiler optimizations) in various settings, e.g., with the default training/testing time, LEO achieves the highest line coverage in 50/68 programs, and its average improvement rate on all programs is 46.48%/88.92% in terms of line coverage compared with turning on/off all compiler optimizations

Plateau pika fecal microbiota transplantation ameliorates inflammatory bowel disease manifestations in a mouse model of colitis

Inflammatory bowel disease (IBD) is a serious global public health concern. Although the pathogenesis of the disease is currently unknown, it has been reported to be associated with both intestinal microbiota and inflammatory mediators. There is evidence suggesting that the feces of the Plateau pika is useful for treating gastrointestinal injuries and pain. Although fecal microbiota transplantation is highly efficacious intervention for IBD prevention, however, potential the transfer of pathogenic microbes or toxic substances is potentially hazardous. Fortunately, micropore filtering of the donor feces can minimize the risk of bacterial infection allowing retention of the therapeutic effects of the residual bacteriophages. Here, we demonstrated that Plateau pika feces not only alleviated the IBD symptoms but also promoted optimal structure and composition of the intestinal microbiota. Additionally, Plateau pika feces transfer also enhanced phenotypic features, such as, body-weight, disease activity index, and histological scores. In conclusion, Plateau pika feces was found to protect mice against colitis induced by dextran sodium sulfate by reducing inflammation and regulating microbial dysbiosis. These findings suggest the potential of Plateau pika feces as an alternative therapy for IBD

Chiral Assemblies of Pinwheel Superlattices on Substrates

The unique topology and physics of chiral superlattices make their self-assembly from nanoparticles a holy grail for (meta)materials. Here we show that tetrahedral gold nanoparticles can spontaneously transform from a perovskite-like low-density phase with corner-to-corner connections into pinwheel assemblies with corner-to-edge connections and denser packing. While the corner-sharing assemblies are achiral, pinwheel superlattices become strongly mirror-asymmetric on solid substrates as demonstrated by chirality measures. Liquid-phase transmission electron microscopy and computational models show that van der Waals and electrostatic interactions between nanoparticles control thermodynamic equilibrium. Variable corner-to-edge connections among tetrahedra enable fine-tuning of chirality. The domains of the bilayer superlattices display strong chiroptical activity identified by photon-induced near-field electron microscopy and finite-difference time-domain simulations. The simplicity and versatility of the substrate-supported chiral superlattices facilitate manufacturing of metastructured coatings with unusual optical, mechanical and electronic characteristics

Genetic Evidence for the Association between the Early Growth Response 3 (EGR3) Gene and Schizophrenia

Recently, two genome scan meta-analysis studies have found strong evidence for the association of loci on chromosome 8p with schizophrenia. The early growth response 3 (EGR3) gene located in chromosome 8p21.3 was also found to be involved in the etiology of schizophrenia. However, subsequent studies failed to replicate this finding. To investigate the genetic role of EGR3 in Chinese patients, we genotyped four SNPs (average interval ∼2.3 kb) in the chromosome region of EGR3 in 470 Chinese schizophrenia patients and 480 healthy control subjects. The SNP rs35201266 (located in intron 1 of EGR3) showed significant differences between cases and controls in both genotype frequency distribution (P = 0.016) and allele frequency distribution (P = 0.009). Analysis of the haplotype rs35201266-rs3750192 provided significant evidence for association with schizophrenia (P = 0.0012); a significant difference was found for the common haplotype AG (P = 0.0005). Furthermore, significant associations were also found in several other two-, and three-SNP tests of haplotype analyses. The meta-analysis revealed a statistically significant association between rs35201266 and schizophrenia (P = 0.0001). In summary, our study supports the association of EGR3 with schizophrenia in our Han Chinese sample, and further functional exploration of the EGR3 gene will contribute to the molecular basis for the complex network underlying schizophrenia pathogenesis

A Novel Performance Adaptation and Diagnostic Method for Aero-Engines Based on the Aerothermodynamic Inverse Model

Aero-engines are faced with severe challenges of availability and reliability in the increasing operation, and traditional gas path filtering diagnostic methods have limitations restricted by various factors such as strong nonlinearity of the system and lack of critical sensor information. A method based on the aerothermodynamic inverse model (AIM) is proposed to improve the adaptation accuracy and fault diagnostic dynamic estimation response speed in this paper. Thermodynamic mechanisms are utilized to develop AIM, and scaling factors are designed to be calculated iteratively in the presence of measurement correction. In addition, the proposed method is implemented in combination with compensation of the nonlinear filter for real-time estimation of health parameters under the hypothesis of estimated dimensionality reduction. Simulations involved experimental datasets revealed that the maximum average simulated error decreased from 13.73% to 0.46% through adaptation. It was also shown that the dynamic estimated convergence time of the improved diagnostic method reached 2.183 s decrease averagely without divergence compared to the traditional diagnostic method. This paper demonstrates the proposed method has the capacity to generalize aero-engine adaptation approaches and to achieve unbiased estimation with fast convergence in performance diagnostic techniques

A Novel Performance Adaptation and Diagnostic Method for Aero-Engines Based on the Aerothermodynamic Inverse Model

Aero-engines are faced with severe challenges of availability and reliability in the increasing operation, and traditional gas path filtering diagnostic methods have limitations restricted by various factors such as strong nonlinearity of the system and lack of critical sensor information. A method based on the aerothermodynamic inverse model (AIM) is proposed to improve the adaptation accuracy and fault diagnostic dynamic estimation response speed in this paper. Thermodynamic mechanisms are utilized to develop AIM, and scaling factors are designed to be calculated iteratively in the presence of measurement correction. In addition, the proposed method is implemented in combination with compensation of the nonlinear filter for real-time estimation of health parameters under the hypothesis of estimated dimensionality reduction. Simulations involved experimental datasets revealed that the maximum average simulated error decreased from 13.73% to 0.46% through adaptation. It was also shown that the dynamic estimated convergence time of the improved diagnostic method reached 2.183 s decrease averagely without divergence compared to the traditional diagnostic method. This paper demonstrates the proposed method has the capacity to generalize aero-engine adaptation approaches and to achieve unbiased estimation with fast convergence in performance diagnostic techniques

Downregulation of CDC25C in NPCs Disturbed Cortical Neurogenesis

Cell division regulators play a vital role in neural progenitor cell (NPC) proliferation and differentiation. Cell division cycle 25C (CDC25C) is a member of the CDC25 family of phosphatases which positively regulate cell division by activating cyclin-dependent protein kinases (CDKs). However, mice with the Cdc25c gene knocked out were shown to be viable and lacked the apparent phenotype due to genetic compensation by Cdc25a and/or Cdc25b. Here, we investigate the function of Cdc25c in developing rat brains by knocking down Cdc25c in NPCs using in utero electroporation. Our results indicate that Cdc25c plays an essential role in maintaining the proliferative state of NPCs during cortical development. The knockdown of Cdc25c causes early cell cycle exit and the premature differentiation of NPCs. Our study uncovers a novel role of CDC25C in NPC division and cell fate determination. In addition, our study presents a functional approach to studying the role of genes, which elicit genetic compensation with knockout, in cortical neurogenesis by knocking down in vivo