有砟轨道路基翻浆冒泥模型试验系统的研发与应用

为研究既有线有砟轨道路基的翻浆冒泥机理，自主研发了一套能够模拟循环荷载–湿化耦合作用的模型试验系统。模型试样直径500 mm，由厚度分别为350 mm的路基土和200 mm的道砟组成，整个试样在高强度透明有机玻璃模型筒中制备完成。模型试验系统配备有监测荷载、位移、体积含水率和孔隙水压力的4种传感器，并通过高清相机对颗粒迁移过程进行图像捕捉。基于所研发的试验系统，针对辛泰铁路典型翻浆冒泥病害路段土样，开展翻浆冒泥模型试验。试验结果表明：动孔隙水压力是导致翻浆冒泥病害产生的关键因素。随着体积含水率的增加，动孔隙水压力引起的颗粒迁移量逐渐增加；在饱和状态下，会引起大量颗粒迁移，翻浆冒泥现象显著。试验结束时，道砟污染指数达到25%，在实际工程中已严重影响铁路的正常运营，有必要对污染道砟进行换填。     

A Systematic Review and Meta-Analysis of Pharmacogenetic Studies in Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is an important global public health problem due to its high prevalence and morbidity. Although the treatment of nephrology patients has changed considerably, ineffectiveness and side effects of medications represent a major issue. In an effort to elucidate the contribution of genetic variants located in several genes in the response to treatment of patients with CKD, we performed a systematic review and meta-analysis of all available pharmacogenetics studies. The association between genotype distribution and response to medication was examined using the dominant, recessive, and additive inheritance models. Subgroup analysis based on ethnicity was also performed. In total, 29 studies were included in the meta-analysis, which examined the association of 11 genes (16 polymorphisms) with the response to treatment regarding CKD. Among the 29 studies, 18 studies included patients with renal transplantation, 8 involved patients with nephrotic syndrome, and 3 studies included patients with lupus nephritis. The present meta-analysis provides strong evidence for the contribution of variants harbored in the ABCB1, IL-10, ITPA, MIF, and TNF genes that creates some genetic predisposition that reduces effectiveness or is associated with adverse events of medications used in CKD.     

α径迹法用于分辨高浓铀和Pu微粒的方法研究

擦拭样品微粒分析技术是核保障环境样品分析的一种主要手段，从大量灰尘颗粒中识别并定位含高浓铀（HEU）或含Pu微粒是微粒分析首先需要解决的问题。本文以HEU和Pu微粒为研究对象，建立了用于微粒α径迹测量的样品制备方法，采用CR-39固体径迹探测器为α径迹探测器，测量了不同蚀刻时间2种微粒产生的α径迹星的径迹参数。结果表明：可通过测量径迹短轴与曲率直径并作图来分辨HEU和Pu微粒，该方法对于蚀刻时间大于10 h的微粒径迹星，均能明显分辨，对于径迹非常密集的径迹星，也能准确分辨。     

Examining the role of regional culture and geographical distances on the representation of unfamiliar foods in a continental-size country

This study provides an experimental-exploratory investigation about the role of regional culture and Euclidean distances on the consumers’ representation of edible insects in Brazil, a country with an extensive geographical surface. Seven hundred and eighty participants were recruited on the streets of eight cities from different Brazilian states: Manaus in Amazonas; Porto Velho in Rondônia; Macapá in Amapá; Cuiabá in Mato Grosso; Aracaju in Sergipe; Rio de Janeiro in Rio de Janeiro; Campinas in São Paulo; and Santa Maria in Rio Grande do Sul. These participating cities were considered from their cultural identity differences and geographical distances. Through a continual restricted word association task, participants were instructed to promptly verbalize the first five terms that came to their minds when stimulated with the expression “food made with edible insects”. Following, they had to score the valence of each term they produced. The dictionaries produced in each city were compared and classified into groups using the Ellegård’s index. Each group presented distinct ways of expression and attitude with respect to the inductive expression. Basically, Brazil was divided into two main groups according to their representation of edible insects: one consisted by the cities situated near the shore of the Atlantic Ocean, which present a cultural formation influenced by the European immigrants; and the other comprised the cities from the continental region that have strong cultural influence from the Amerindians. Thus, the cultural formation was more decisive to explain the similar representations among the cities than their geographical proximity. Given that, to effectively introduce a novel food in a country with varied regional culture, the marketing strategy should be focused on the values and beliefs of their culture subgroups instead of a single strategy for the whole country.     

Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds

This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.     

Investigation of Copper Recovery from a New Copper Deposit (Nussir) in Northern Norway

ABSTRACT

Norway has seen an upsurge of interest in exploiting its mineral deposits during the last decade. One of the major areas of interest is a huge copper deposit, operated by Nussir ASA located in the Repparfjord tectonic window in the Caledonides of west Finnmark. Nussir ASA is evaluating the Nussir and Ulveryggen mineral resources that contain copper sulfides with a small amount of gold and silver bearing minerals. The performance of flotation operations is generally evaluated on the basis of degree of liberation of minerals or the surface interactions between the collector and mineral. Firstly, size-by-size mineralogical characterization of the flotation feed and cumulative final product using Zeiss automated mineralogy techniques (Mineralogic) revealed that mineral liberation heavily influenced the flotation behavior of the ore. Furthermore, in order to assess the role of pH, collector concentration and flotation time, bench scale flotation experiments were performed. The metallurgical results were maximum between pH 6 and 8 and at collector concentration 6 × 10^?5 M. A correlation is established using the zeta potential and Hallimond flotation tests to assess the role of operating parameters in flotation. The distinctive role of process mineralogy and flotation chemical influence for copper mineral flotation of Nussir ore is presented in this article.     

Two‐sided matching framework for optimal user association in 5G multi‐RAT UDNs

Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs.     

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from ?0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.