Prophylactic use of an ultra-diluted complex on health,metabolism, and performance of weaned Holstein calves and its carryover effect up to first lactation

The objective of this study was to evaluate the effect of an ultra-diluted complex supplemented as a prophylactic strategy on the incidence risk of diseases, metabolism, and performance of weaned Holstein calves immediately after grouping. Additionally, the objective was to investigate the carryover effects on heifer-raising and first-lactation periods, in a double-blind, placebo-controlled trial. A total of 184 weaned Holstein calves (83 ± 7.9 d of life; 112.5 ± 11.7 kg of body weight; values are mean ± standard deviation) were allocated to 8 paddocks in a completely randomized block design experiment. During a 112-d period, animals received a total mixed ration and were randomly allocated into 2 groups: (1) CON: placebo-control (basal diet + calcium carbonate, top-dressed at 30 g/animal per day of placebo), or (2) UD: ultra-diluted complex (basal diet + TopVita-Real H, top-dressed at 30 g/animal per day of sulfur (10⁻⁶⁰) + viola tricolor (10⁻¹⁴) + caladium seguinum (10⁻³⁰) + zincum oxydatum (10⁻³⁰) + phosphorus (10⁻⁶⁰) + carduus marianus (10⁻⁶⁰) + colibacillinum (10⁻³⁰) + podophyllum (10⁻³⁰) + vehicle: calcium carbonate; quantum sufficit 1 kg). Incidence risk of diseases, number of days with disease, and mortality events were recorded daily. Performance measurements and blood collection were carried out at enrollment and every 28 d until the end of the study period. The incidence risk of digestive problems was higher for the CON group. Additionally, the CON group had higher cumulative number of days per calf affected by tick-borne disease. Blood analysis revealed that CON calves had increased mean corpuscular hemoglobin amount and concentration than UD calves on d 28 after enrollment and had increased serum albumin and total protein concentration on d 84. Furthermore, higher albumin to globulin ratio was found in CON calves than in those of UD group at enrollment; however, on d 56, the inverse was observed. On d 28 after enrollment, CON calves had increased serum cortisol concentration. Regarding body measurements, higher withers height and body depth were detected in UD calves, on d 28 and d 84, respectively. Finally, higher culling risk was observed in the CON group during the heifer-raising period. In conclusion, a lower incidence risk of digestive problems and days with tick-borne disease were detected in the UD group. Additionally, systemic inflammation was improved by UD complex based on circulating inflammation and stress biomarkers on specific days after enrollment. However, UD product did not improve performance at the post-weaning, heifer-raising, and first-lactation periods.     

On the use of 1g physical models for ground movements and soil-structure interaction problems

The paper focusses on the use of physical modelling in ground movements (induced by underground cavity collapse or mining/tunnelling) and associated soil-structure interaction issues. The paper presents first an overview of using 1g physical models to solve geotechnical problems and soil-structure interactions related to vertical ground movements. Then the 1g physical modelling application is illustrated to study the development of damage in masonry structure due to subsidence and cavity collapse. A large-scale 1g physical model with a 6 m³ container and 15 electric jacks is presented with the use of a three-dimensional (3D) image correlation technique. The influence of structure position on the subsidence trough is analysed in terms of crack density and damage level. The obtained results can improve the methodology and practice for evaluation of damage in masonry structures. Nevertheless, ideal physical model is difficult to achieve. Thus, future improvement of physical models (analogue materials and instrumentation) could provide new opportunities for using 1g physical models in geotechnical and soil-structure applications and research projects.     

转制国有地矿企业人力资源开发管理问题思考

党的十八大以来，全国各省区地矿局系统转企改制加速推进。“脱胎”于事业体制、诞生于新时代的国有地矿企业，要在激烈的市场竞争中站稳脚跟，需要按企业机制补短板、强弱项，其中，人力资源开发与管理便是一个急需补齐的短板。为做好这方面工作，本文从国有地矿单位历史与现实、当前和未来的视角，在对人力资源开发与管理对地矿企业的重要性和紧迫性、地矿企业人力资源开发与管理存在的主要问题进行分析思考的基础上，提出了必须紧扣企业战略目标抓好人力资源规划、围绕留才用才聚才抓好员工职业生涯管理、着眼可持续发展抓好人力资源管理创新，迅速补齐地矿企业人力资源开发与管理短板的建议。     

融媒体时代广播电视工程技术中存在的问题及对策

由于受到各种因素的影响,广播电视的技术发展仍存在不少问题,亟待进行创新和转型,以提高广播电视工程的技术水平,为广大人民群众提供优质的服务。     

A novel approach for efficient stance detection in online social networks with metaheuristic optimization

In the 19th and 20th centuries, social networks have been an important topic in a wide range of fields from sociology to education. However, with the advances in computer technology in the 21st century, significant changes have been observed in social networks, and conventional networks have evolved into online social networks. The size of these networks, along with the large amount of data they generate, has introduced new social networking problems and solutions. Social network analysis methods are used to understand social network data. Today, several methods are implemented to solve various social network analysis problems, albeit with limited success in certain problems. Thus, the researchers develop new methods or recommend solutions to improve the performance of the existing methods. In the present paper, a novel optimization method that aimed to classify social network analysis problems was proposed. The problem of stance detection, an online social network analysis problem, was first tackled as an optimization problem. Furthermore, a new hybrid metaheuristic optimization algorithm was proposed for the first time in the current study, and the algorithm was compared with various methods. The analysis of the findings obtained with accuracy, precision, recall, and F-measure classification metrics demonstrated that our method performed better than other methods.     

Physics-informed deep learning for one-dimensional consolidation

Neural networks with physical governing equations as constraints have recently created a new trend in machine learning research.In this context,a review of related research is first presented and discussed.The potential offered by such physics-informed deep learning models for computations in geomechanics is demonstrated by application to one-dimensional(1D)consolidation.The governing equation for 1D problems is applied as a constraint in the deep learning model.The deep learning model relies on automatic differentiation for applying the governing equation as a constraint,based on the mathematical approximations established by the neural network.The total loss is measured as a combination of the training loss(based on analytical and model predicted solutions)and the constraint loss(a requirement to satisfy the governing equation).Two classes of problems are considered:forward and inverse problems.The forward problems demonstrate the performance of a physically constrained neural network model in predicting solutions for 1D consolidation problems.Inverse problems show prediction of the coefficient of consolidation.Terzaghi’s problem,with varying boundary conditions,is used as a numerical example and the deep learning model shows a remarkable performance in both the forward and inverse problems.While the application demonstrated here is a simple 1D consolidation problem,such a deep learning model integrated with a physical law has significant implications for use in,such as,faster realtime numerical prediction for digital twins,numerical model reproducibility and constitutive model parameter optimization.     

档案工作与创新思维

面对新世纪和知识经济新世代的到来，提出如何在档案工作中搞好创新思维。     

上公山隧洞TBM掘进主要工程地质问题及施工对策

阐述了上公山隧洞TBM掘进过程中遇到的诸如断层破碎带、节理密集带、软岩大变形、岩溶、地下水等主要工程地质问题，并详细地介绍了相应的工程处理措施。     

图文解码矿山地质环境问题

准确识别和把控矿山地质环境问题是矿山安全生产和矿区生态文明建设的重要内容,矿山地质环境问题的解码对于矿产资源开发和矿区环境保护具有十分重要的意义。本文通过常见矿山地质灾害、含水层破坏及其危害、水土污染和地形地貌景观破坏等四个方面对矿山地质环境问题进行阐述,通过图文并茂的形式解码矿山开采引发的环境问题,更直观地展现矿业开发对地质环境和生态空间的影响,以期增强人们对矿业开发引发环境问题的重视,引导更多人参与到保护矿山地质环境的行列中,也为科学规划矿业开发,匹配矿区环境承载能力等矿业综合监管提供了方向性支撑。