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.     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

Fuel-oxidizer mixtures: a lab and field study

ABSTRACT

Improvised explosive may be as primitive as a fuel and oxidizer mixture; yet not all fuel-oxidizer mixtures are explosive. Predicting explosive potential from laboratory-scale tests is desirable to screen a large matrix of potential threats in varying concentrations. Herein the properties of various fuel/oxidizer mixtures were measured at small scale (2 g) with bomb calorimetry and on large scale (5 kg) with high speed photography for detonation velocity and with piezoelectric pressure probes for TNT air blast equivalence. Potassium nitrate (KN), potassium chlorate (KC), potassium permanganate (KMnO₄), potassium iodate (KIO₃), ammonium nitrate (AN), and ammonium perchlorate (AP) were prepared with sucrose (Su) and aluminum (Al) fuel. Results were compared to each other as well as predictions from Cheetah thermochemical code.     

The Impact of the ‘Mis-Peptidome’ on HLA Class I-Mediated Diseases: Contribution of ERAP1 and ERAP2 and Effects on the Immune Response

The strong association with the Major Histocompatibility Complex (MHC) class I genes represents a shared trait for a group of autoimmune/autoinflammatory disorders having in common immunopathogenetic basis as well as clinical features. Accordingly, the main risk factors for Ankylosing Spondylitis (AS), prototype of the Spondyloarthropathies (SpA), the Behçet’s disease (BD), the Psoriasis (Ps) and the Birdshot Chorioretinopathy (BSCR) are HLA-B*27, HLA-B*51, HLA-C*06:02 and HLA-A*29:02, respectively. Despite the strength of the association, the HLA pathogenetic role in these diseases is far from being thoroughly understood. Furthermore, Genome-Wide Association Studies (GWAS) have highlighted other important susceptibility factors such as Endoplasmic Reticulum Aminopeptidase (ERAP) 1 and, less frequently, ERAP2 that refine the peptidome presented by HLA class I molecules to CD8⁺ T cells. Mass spectrometry analysis provided considerable knowledge of HLA-B*27, HLA-B*51, HLA-C*06:02 and HLA-A*29:02 immunopeptidome. However, the combined effect of several ERAP1 and ERAP2 allelic variants could generate an altered pool of peptides accounting for the “mis-immunopeptidome” that ranges from suboptimal to pathogenetic/harmful peptides able to induce non-canonical or autoreactive CD8⁺ T responses, activation of NK cells and/or garbling the classical functions of the HLA class I molecules. This review will focus on this class of epitopes as possible elicitors of atypical/harmful immune responses which can contribute to the pathogenesis of chronic inflammatory diseases.     

基于声源定位的高校在线巡课系统设计与研究

随着网络建设以及信息化教学方法在高校教学过程中的应用普及,越来越多的高校使用在线巡课系统对教师的教学过程进行跟踪和管理,以便发现课堂教学中的亮点、问题和不足。文章提出的在线巡课系统,基于声源定位的技术,对传统的在线巡课系统做出了改进,解决了已有巡课系统中“只闻其声,不见其人”的问题,能够更直观地跟踪到教师的教学过程,包括教学行为以及师生互动过程,有效提升教务人员巡课效果和体验感受。     

Distant Supervised Relation Extraction with Cost-Sensitive Loss

Recently, many researchers have concentrated on distant supervision relation extraction (DSRE). DSRE has solved the problem of the lack of data for supervised learning, however, the data automatically labeled by DSRE has a serious problem, which is class imbalance. The data from the majority class obviously dominates the dataset, in this case, most neural network classifiers will have a strong bias towards the majority class, so they cannot correctly classify the minority class. Studies have shown that the degree of separability between classes greatly determines the performance of imbalanced data. Therefore, in this paper we propose a novel model, which combines class-to-class separability and cost-sensitive learning to adjust the maximum reachable cost of misclassification, thus improving the performance of imbalanced data sets under distant supervision. Experiments have shown that our method is more effective for DSRE than baseline methods.     

A General Strategy for Antimony-Based Alloy Nanocomposite Embedded in Swiss-Cheese-Like Nitrogen-Doped Porous Carbon for Energy Storage

Due to its suitable working voltage and high theoretical storage capacity, antimony is considered a promising negative electrode material for lithium-ion batteries (LIBs) and has attracted widespread attention. The volume effect during cycling, however, will cause the antimony anode to undergo a severe structural collapse and a rapid decrease in capacity. Here, a general in situ self-template-assisted strategy is proposed for the rational design and preparation of a series of M Sb (M = Ni, Co, or Fe) nanocomposites with M N C coordination, which are firmly anchored on Swiss-cheese-like nitrogen-doped porous carbon as anodes for LIBs. The large interface pore network structure, the introduction of heteroatoms, and the formation of strong metal N C bonds effectively enhance their electronic conductivity and structural integrity, and provide abundant interfacial lithium storage. The experimental results have proved the high rate performance and excellent cycling stability of antimony-based composite materials. Electrochemical kinetics studies have demonstrated that the increase in capacity during cycling is mainly controlled by the diffusion mechanism rather than the pseudocapacitance contribution. This facile strategy can provide a new pathway for low-cost and high-yield synthesis of Sb-based composites with high performance, and is expected to be applied in other energy-related fields such as sodium-/potassium-ion batteries or electrocatalysis.     

Patterns and stability of food preferences among a national representative sample of young,middle-aged,and elderly adults in China: A latent transition analysis

The purpose of this study was to explore the patterns and stability of, as well as the predictors for, Chinese adults’ food preferences. With the panel data set derived from the China Health and Nutrition Survey (CHNS), latent class analysis (LCA) and latent transition analysis (LTA) were employed to analyze the data of 8850 adults aged 18–40 years (young), 41–60 years (middle-aged) and 61 years above (elderly) over a 4-year period (year 2011 as baseline and year 2015 as follow-up). Latent class analysis revealed three types of food preferences: preference for fruits and vegetables, preference for a varied diet and low food preference. Gender, dietary knowledge, residence, education, and BMI were revealed as significant predictors of the class memberships. From baseline to follow-up, the most stable status in young adult group was preference for fruits and vegetables as it had a high transition probability 0.764 of remaining in the same class. While low food preference and preference for a varied diet statuses were unstable, they had transition probabilities of 0.590 and 0.554, respectively, moving to the preference for fruits and vegetables in year 2015. For middle-aged and elderly groups, the most stable and unstable statuses were preference for fruits and vegetables and preference for a varied diet, respectively. The unstable classes all had over 50% probability of moving to the preference for fruits and vegetables after four years. Potential explanations and implications are also discussed.     

某燃气电厂NOx排放测值异常分析与处理

某F级燃气电厂运行中发现NOx数值存在较大波动,通过分析和排查,发现烟气分析仪存在老化现象,同时CEMS仪表间存在布置不合理情况,通过处理NOx数值波动得以有效改善,可为同类电厂烟气系统数据异常处理提供参考。     

“电力系统分析”课程可持续发展的建设与实践

本文探索了新工科背景下“电力系统分析”课程建设情况,摸索工程教育的新理念,以学生发展为中心,尝试翻转课堂的互动式教学模式,实现了创新人才的培养目标。编著《电力系统分析》教材,实现了内容的继承和创新、重要知识点的交叉和融合。建设数字仿真及物理模拟实验室,解决高校人才培养与社会需求脱节的问题。以“注重学习过程,加强平时考核,淡化期末考试”的方式进行综合考评,提高了教学效果与教学质量。经过几年的教学探索与实践,证明了本课程建设效果良好。