基于FLAC3D的破碎围岩巷道支护效果分析

为了解破碎围岩分别采用锚杆支护、锚喷支护以及锚喷+锚索耦合三种支护方式下的支护效果,进而为破碎围岩巷道选择合理的支护方式提供参考。通过借助FLAC^3D软件建立数值模型,分析不同支护条件下的破碎围岩巷道位移量、应力分布以及塑性区的时空演化特征。结果表明,采用锚喷+锚索耦合支护时,可以较好的控制巷道围岩的位移量、减小应力集中效应、缩小塑性区的影响范围。     

In Silico Analysis of the Molecular-Level Impact of SMPD1 Variants on Niemann-Pick Disease Severity

Sphingomyelin phosphodiesterase (SMPD1) is a key enzyme in the sphingolipid metabolism. Genetic SMPD1 variants have been related to the Niemann-Pick lysosomal storage disorder, which has different degrees of phenotypic severity ranging from severe symptomatology involving the central nervous system (type A) to milder ones (type B). They have also been linked to neurodegenerative disorders such as Parkinson and Alzheimer. In this paper, we leveraged structural, evolutionary and stability information on SMPD1 to predict and analyze the impact of variants at the molecular level. We developed the SMPD1-ZooM algorithm, which is able to predict with good accuracy whether variants cause Niemann-Pick disease and its phenotypic severity; the predictor is freely available for download. We performed a large-scale analysis of all possible SMPD1 variants, which led us to identify protein regions that are either robust or fragile with respect to amino acid variations, and show the importance of aromatic-involving interactions in SMPD1 function and stability. Our study also revealed a good correlation between SMPD1-ZooM scores and in vitro loss of SMPD1 activity. The understanding of the molecular effects of SMPD1 variants is of crucial importance to improve genetic screening of SMPD1-related disorders and to develop personalized treatments that restore SMPD1 functionality.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

A PV installation framework concerning electricity variable rates

This paper assesses building integrated photovoltaic (BIPV) installation parameters based on the profit generated by a photovoltaic system. It takes into consideration a home building case study and it investigates its monthly energy demand based on a specific location and a typical occupancy. The capability of a photovoltaic (PV) system to generate more profit occurs when solar intensity is maximum while the electric energy price is at its highest rate. The paper traces a framework that encompasses different aspects such as energy demand, energy price, and solar intensity. This framework identifies profit alternatives according to different installation parameters. A tool that predicts a PV installation hourly electric energy production is developed. The profit generated is simulated for home buildings located in Beirut (Lebanon) and Xihua (China), both at 33.8° latitude north. The paper highlights a new approach for BIPV installations, taking into account weather conditions, energy demand, and electric energy utility rates.     

Predicting Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae) populations and associated grain damage in smallholder farmers’ maize stores: A machine learning approach

Prostephanus truncatus is a notorious pest of stored-maize grain and its spread throughout sub-Saharan Africa has led to increased levels of grain storage losses. The current study developed models to predict the level of P. truncatus infestation and associated damage of maize grain in smallholder farmer stores. Data were gathered from grain storage trials conducted in Hwedza and Mbire districts of Zimbabwe and correlated with weather data for each site. Insect counts of P. truncatus and other common stored grain insect pests had a strong correlation with time of year with highest recorded numbers from January to May. Correlation analysis showed insect-generated grain dust from boring and feeding activity to be the best indicator of P. truncatus presence in stores (r = 0.70), while a moderate correlation (r = 0.48) was found between P. truncatus numbers and storage insect parasitic wasps, and grain damage levels significantly correlated with the presence of Tribolium castaneum (r = 0.60). Models were developed for predicting P. truncatus infestation and grain damage using parameter selection algorithms and decision-tree machine learning algorithms with 10-fold cross-validation. The P. truncatus population size prediction model performance was weak (r = 0.43) due to the complicated sampling and detection of the pest and eight-week long period between sampling events. The grain damage prediction model had a stronger correlation coefficient (r = 0.93) and is a good estimator for in situ stored grain insect damage. The models were developed for use under southern African climatic conditions and can be improved with more input data to create more precise models for building decision-support tools for smallholder maize-based production systems.     

Psychrophilic hydrogen production from petrochemical wastewater via anaerobic sequencing batch reactor: techno-economic assessment and kinetic modelling

Independent hydrogen production from petrochemical wastewater containing mono-ethylene glycol (MEG) via anaerobic sequencing batch reactor (ASBR) was extensively assessed under psychrophilic conditions (15–25 °C). A lab-scale ASBR was operated at pH of 5.50, and different organic loading rates (OLR) of 1.00, 1.67, 2.67, and 4.00 gCOD/L/d. The hydrogen yield (HY) progressed from 134.32 ± 10.79 to 189.09 ± 22.35 mL/gMEG_initial at increasing OLR from 1.00 to 4.00 gCOD/L/d. The maximum hydrogen content of 47.44 ± 3.60% was achieved at OLR of 4.0 gCOD/L/d, while methane content remained low (17.76 ± 1.27% at OLR of 1.0 gCOD/L/d). Kinetic studies using four different mathematical models were conducted to describe the ASBR performance. Furthermore, two batch-mode experiments were performed to optimize the nitrogen supplementation as a nutrient (C/N ratio), and assess the impact of salinity (as gNaCl/L) on hydrogen production. HY substantially dropped from 62.77 ± 4.09 to 6.02 ± 0.39 mL/gMEG_initial when C/N ratio was increased from 28.5 to 114.0. Besides, the results revealed that salinity up to 10.0 gNaCl/L has a relatively low inhibitory impact on hydrogen production. Eventually, the cost/benefit analysis showed that environmental and energy recovery revenues from ASBR were optimized at OLR of 4.0 gCOD/L/d (payback period of 7.13 yrs).     

面向医院建筑项目的IPD模式应用研究

医院建筑项目是非常复杂且具有挑战性的建设项目。传统的交付模式无法满足人们对医院建筑建设、运营方面的高要求,为此开展面向医院建筑项目的IPD模式应用研究。在对IPD模式发展现状整理的基础上,阐述医院建筑项目IPD模式的适用性。分析采用IPD模式的医院建筑项目特点,并以上海市某公立三甲专科医院项目为例,对IPD模式在国内的应用进行探索性研究。