NCK2 Is Significantly Associated with Opiates Addiction in African-Origin Men

Substance dependence is a complex environmental and genetic disorder with significant social and medical concerns. Understanding the etiology of substance dependence is imperative to the development of effective treatment and prevention strategies. To this end, substantial effort has been made to identify genes underlying substance dependence, and in recent years, genome-wide association studies (GWASs) have led to discoveries of numerous genetic variants for complex diseases including substance dependence. Most of the GWAS discoveries were only based on single nucleotide polymorphisms (SNPs) and a single dichotomized outcome. By employing both SNP- and gene-based methods of analysis, we identified a strong (odds ratio = 13.87) and significant (P value = 1.33E−11) association of an SNP in the NCK2 gene on chromosome 2 with opiates addiction in African-origin men. Codependence analysis also identified a genome-wide significant association between NCK2 and comorbidity of substance dependence (P value = 3.65E−08) in African-origin men. Furthermore, we observed that the association between the NCK2 gene (P value = 3.12E−10) and opiates addiction reached the gene-based genome-wide significant level. In summary, our findings provided the first evidence for the involvement of NCK2 in the susceptibility to opiates addiction and further revealed the racial and gender specificities of its impact

Driving risk assessment and prevention strategies for autonomous vehicle in open-pits

Driving risk assessment and protection is the critical technology of unmanned transportation systems in open-pits. In order to warrant the safe operation of unmanned vehicles in open-pits, the Driving Security Model (DSM) based on the vehicle-road-cloud transportation system is established. Based on the multi-source information from the vehicle, roadside, and cloud platform, the DSM can assess the driving risk level of driverless vehicles and provide corresponding driving risk prevention strategies. The DSM comprises driving state awareness, driving risk assessment, and driving risk protection. In terms of driving risk assessment, the threshold of pre-collision time is corrected through the road slope ahead of the vehicle, and the minimum braking safety distance is modified by the information of road slope and vehicle load state. In the meantime, a comprehensive driving risk assessment strategy is proposed, which can quantify the real-time collision risk of autonomous vehicles in open-pits. Then, a collision risk protection system that considers different driving risks is then designed based on a finite state machine. A smooth braking control strategy is developed to meet the minimum safety distance. Finally, a digital twin simulation system that corresponds to the autonomous vehicle in an open-pit is built based on the PreScan and Matlab co-simulation technology and some simulation tests in the horizontal, uphill-downhill road and full load scenes are carried out. The simulation results show that the DSM’s comprehensive risk assessment strategy can evaluate suitable risk levels in advance and timely brake, which indicates that the introduction of road slope information can improve the driving safety of the vehicle up and downhill scenes. By introducing vehicle load information, the designed minimum safe braking distance index can detect potential collision risk in time. The DSM’s emergency braking control strategy can smoothly stop the vehicle before 10 m safe distance, which improves the stability of heavy-duty vehicles during emergency braking

SVSI: Fast and Powerful Set-Valued System Identification Approach to Identifying Rare Variants in Sequencing Studies for Ordered Categorical Traits: SVSIfor Genetic Association Studies

For genetic association studies that involve an ordered categorical phenotype, we usually either regroup multiple categories of the phenotype into two categories (“cases” and “controls”) and then apply the standard logistic regression (LG), or apply ordered logistic (oLG) or ordered probit (oPRB) regression which accounts for the ordinal nature of the phenotype. However, these approaches may lose statistical power or may not control type I error rate due to their model assumption and/or instable parameter estimation algorithm when the genetic variant is rare or sample size is limited. Here to solve this problem, we propose a set-valued (SV) system model, which assumes that an underlying continuous phenotype follows a normal distribution, to identify genetic variants associated with an ordinal categorical phenotype. We couple this model with a set-valued system identification algorithm to identify all the key system parameters. Simulations and two real data analyses show that SV and LG accurately controlled the Type I error rate even at a significance level of 10−6 but not oLG and oPRB in some cases. LG had significantly smaller power than the other three methods due to disregarding of the ordinal nature of the phenotype, and SV had similar or greater power than oLG and oPRB. For instance, in a simulation with data generated from an additive SV model with odds ratio of 7.4 for a phenotype with three categories, a single nucleotide polymorphism with minor allele frequency of 0.75% and sample size of 999 (333 per category), the power of SV, oLG and LG models were 70%, 40% and <1%, respectively, at a significance level of 10−6. Thus, SV should be employed in genetic association studies for ordered categorical phenotype

Application of comprehensive advanced geological prediction technology in Da-puling tunnel

For the Da-puling tunnel of Puqing Expressway in Guangxi, the advanced geological prediction is carried out by combining TSP long-distance forecast method with short distance geological radar method. This paper describes the principle of seismic wave propagation in elastic medium, as well as the key points of data processing and analysis, some requirements that should be paid attention to the field test and scientific way of image interpretation put forward to improve the accuracy of prediction; When TSP is deployed, it should be sharp angle with potential joint surface. P-wave reacts surrounding rock properties, the shear wave is closely related to the transverse skeleton of medium. In data interpretation, it is necessary to focus on the analysis of the characteristics of P-wave and S-wave, weakening Poisson’s ratio and Young’s modulus. TSP and GPR can achieve the mutual complement and improve the detection accuracy

Dosing: The key to precision plasma oncology

Cold atmospheric plasma (CAP) is an emerging oncotherapeutic approach with selectivity for cancer cells. It can induce different cell survival and death programs depending on the CAP dose, and it can function as a neo or adjuvant therapy against cancer. Establishing an evaluation system for precise CAP dosing is the key to make plasma therapy act alone or in combination with other therapeutic modalities for achieving desirable treatment responses. By classifying CAP-induced effects and associating them with the dosing of plasma-reactive agents, we identify opportunities for CAP to contribute to precision oncotherapy and discuss challenges en route to clinical applications. We emphasize the importance of dosing in plasma medicine and encourage cross-disciplinary collaborations to develop suitable dosing metrics.</p

Dynamic cluster analysis of urban river ecosystem using water, climate, and economy nexus

Urban rivers are the origin of civilizations, the source of water supply, and the center of recreational and sports activities. The role of rivers can be investigated from various political, cultural, security, drought, economic, and health aspects. This study was conducted in order to identify the influencing components of urban rivers on ecosystem sustainability. The weight coefficients of climatic, social, economic, and ecological components were evaluated through dynamic cluster analysis, and their role in ecosystem sustainability was quantified. In addition, the relationship between water-based factors and environmental components was determined in finding the best components of river ecosystem evaluation for future decisions. The provided analysis can increase the stability of the urban river ecosystem and can rank the priority of the impact factors. Ecological environment statistics, nature measures, economic parameters, and land cover rate substantially affected the visual influence of the urban river ecosystem. Results showed that the proposed evaluation provided a reasonable framework to evaluate the sustainability of the urban river ecosystem and visual perception to improve the design efficiency by decision-makers. HIGHLIGHTS A dynamic analysis model is proposed to evaluate the river system.; The required information has been collected from four different ecosystems and put in the form of cluster analysis.; The sustainable management model of the river ecosystem can be obtained from the relationship between water, climate, and economy.

Some Physical Properties of Protein Moiety of Alkali-Extracted Tea Polysaccharide Conjugates Were Shielded by Its Polysaccharide

Polysaccharide conjugates were alkali-extracted from green tea (TPC-A). Although it contained 11.80% covalently binding proteins, TPC-A could not bind to the Coomassie Brilliant Blue dyes G250 and R250. TPC-A had no expected characteristic absorption peak of protein in the UV-vis spectrum scanning in the range of 200–700 nm. The UV-vis wavelength of 280 nm was not suitable to detect the presence of the protein portion of TPC-A. The zeta potential of TPC-A merely presented the negative charge properties of polysaccharides instead of the acid–base property of its protein section across the entire pH range. Furthermore, TPC-A was more stable when the pH of solution exceeded 4.0. In addition, no precipitation or haze was generated in the TPC-A/(−)-epigallocatechin gallate (EGCG) mixtures during 12 h storage. TPC-A has emulsifying activity, which indicated that its protein moiety formed hydrophobic groups. Thus, it was proposed that some physical properties of TPC-A protein were shielded by its olysaccharide, since the protein moiety was wrapped by its polysaccharide chains

Powertrain modeling and performance simulation of a novel flywheel hybrid electric vehicle

To improve vehicle performance and energy utilization, a novel planetary gear set based flywheel hybrid electric powertrain (PGS-FHEP) is proposed. The PGS-FHEP involves an internal combustion engine, a planetary gear set that integrated a control motor and an energy storage flywheel, which combines the high efficiency of the mechanical flywheel energy storage system with the flexible and controllable characteristics of the electric motor. The powertrain is analyzed and modeled using lever analogy method, and a rule-based control strategy is designed and verified under different test cycles. The simulation results indicate that compared with the traditional manual transmission vehicle, the fuel economy of the vehicle equipped with PGS-FHEP can be improved by more than 50%, and the acceleration performance can be increased by 28.01%. Up to 60.61% of vehicle kinetic energy can be recovered by PGS-FHEP, among which 37.85% can be directly captured by the energy storage flywheel. In addition, the battery charging power is reduced, which is beneficial to prolong the battery life

Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene

Many genetic association studies used single nucleotide polymorphisms (SNPs) data to identify genetic variants for complex diseases. Although SNP-based associations are most common in genome-wide association studies (GWAS), gene-based association analysis has received increasing attention in understanding genetic etiologies for complex diseases. While both methods have been used to analyze the same data, few genome-wide association studies compare the results or observe the connection between them. We performed a comprehensive analysis of the data from the Study of Addiction: Genetics and Environment (SAGE) and compared the results from the SNP-based and gene-based analyses. Our results suggest that the gene-based method complements the individual SNP-based analysis, and conceptually they are closely related. In terms of gene findings, our results validate many genes that were either reported from the analysis of the same dataset or based on animal studies for substance dependence