含矩形边缘分层缺陷层合板的压缩性能

对含矩形边缘分层缺陷层合板的压缩性能进行试验研究和理论分析, 考察了层合板厚度(含铺层形式)、 分层位置、 形状、 面积以及环境等因素对压缩强度的影响, 并采用分层扩展以及软化夹杂两种模型对含分层层合板的压缩强度进行了计算和破坏机理分析。结果表明: 厚板对边缘分层缺陷不敏感, 中等厚度和薄层合板比较敏感; 缺陷的位置和形状对层合板压缩强度有一定的影响; 湿热环境改变了含缺陷板的压缩破坏机理, 并对中等厚度板和薄板的压缩强度有明显的影响。两种模型中软化夹杂模型效果较好, 可用于工程设计计算。      

RAPID OXIDATION OF COMMERCIAL EXTRA VIRGIN OLIVE OIL STORED UNDER FLUORESCENT LIGHT

Extra virgin olive oil is considered to be a high quality oil for health and nutrition and is widely consumed by the Mediterranean population. Presence of natural photosensitizers in olive oil may compromise its nutritional quality if stored in clear plastic or glass container under fluorescent light. In this study, the oxidative stability of commercial extra virgin olive oil (EVOO) and its chlorophyll and tocopherol stripped counterpart (SEVOO) stored at 60C in the dark and under fluorescent light (2650 lux) was evaluated. A column chromatographic procedure using silicic acid, Celite 545, activated charcoal and powdered sugar (sucrose), and eluted with hexane, provide an effective means for stripping extra virgin olive oil from its minor components. Minor components, mainly tocopherol and other phenolic compounds as well as carotenoids in SEVOO, influenced their oxidative stability in the dark. Meanwhile, natural pigments such as chlorophyll played a major role in the photooxidation of EVOO. Therefore, commercial extra virgin oil should be protected from direct light exposure in order to protect it from the oil from photooxidative deterioration.     

Gut microbiome modulation: Ancillary effects of inorganic nanoparticles on gut microflora

The association of gut microflora and human health is being increasingly recognized, and the impact of gut microflora on the host is well characterized, including the body’s energy metabolism and immune system maintenance. Several human diseases, including metabolic, autoimmune, obesity, hypothyroidism, and intestinal disorders, are closely associated with gut dysbiosis. Inorganic nanoparticles (NPs) are extensively utilized in numerous fields due to their distinctive, attractive physicochemical properties. Estimation of the potential impacts of NPs, with a high number of microorganisms inside the human body (microbiota) and its genomes (microbiome), represents one of the most important aspects of nano-toxicology. This review article aims to provide information on the association of gut microflora alterations to diseases and describe the impacts of various inorganic NPs, including silver, zinc, selenium, titania, silicon, and copper, on gut microflora. Research on the effect of inorganic NPs on gut microflora of animal models and the poultry industry is reviewed. The response of pathogenic Enterobacter species to inorganic NPs has been expounded in detail. This review also highlights the need to focus on the ancillary effects of various inorganic NPs on gut microflora to expedite the suitable advancement of these particles for future use. Finally, the key opportunistic areas for the application of nanotechnology are underlined to manipulate the microbiome of gut dysbiosis, provide an overview, and address potential challenges and our perspective on this evolving field.     

Role of foliar spray of plant growth regulators in improving photosynthetic pigments and metabolites in <i>Plantago ovata</i> (Psyllium) under salt stress–A field appraisal

Salinity is one of the major abiotic factors that limit the growth and productivity of plants. Foliar application of plant growth regulators (PGRs) may help plants ameliorate the negative impacts of salinity. Thus, a field experiment was conducted at the Botanical Garden University of Balochistan, Quetta, to explore the potential role of PGRs, i.e., moringa leaf extract (MLE; 10%), proline (PRO; 1 µM), salicylic acid (SA; 250 µM), and thiourea (TU; 10 mM) in ameliorating the impacts of salinity (120 mM) on Plantago ovata, an important medicinal plant. Salinity hampered plant photosynthetic pigments and metabolites but elevated oxidative parameters. However, foliar application of PGRs enhanced photosynthetic pigments, including Chl b (21.11%), carotenoids (57.87%) except Chl a, activated the defense mechanisms by restoring and enhancing the metabolites, i.e., soluble sugars (49.68%), soluble phenolics (33.34%), and proline (31.47%), significantly under salinity stress. Furthermore, foliar supplementation of PGRs under salt stress led to a decrease of about 43.02% and 43.27% in hydrogen peroxide and malondialdehyde content, respectively. Thus, PGRs can be recommended for improved photosynthetic efficiency and metabolite content that can help to get better yield under salt stress, with the best and most effective treatments being those of PRO and MLE to predominately ameliorate the harsh impacts of salinity.     

Machine learning-based seismic assessment of framed structures with soil-structure interaction

The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structure interaction (SSI). The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for prediction. Within the MLT, a sensitivity analysis was conducted on the main SSI parameters to select the most effective input parameters. Multiple limit state criteria were used for the seismic evaluation within the process. A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters (EDPs). The proposed framework is novel because it enables the designer to seismically assess the structure, while simultaneously considering different EDPs and multiple limit states. Moreover, the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio, which considers different levels of seismic hazards. The proposed framework was validated through comparison using non-linear time history (NLTH) analysis. The results show that the proposed framework provides more accurate results than conventional methods. Finally, the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities, namely, stiffness and mass irregularities. The results from the framework were in good agreement with the NLTH analysis results for the selected case studies, and peak ground acceleration (PGA) was found to be the most influential input parameter in the assessment process for the case study models investigated. The proposed framework shows high generalization potential for low- to mid-rise structures.     

吉贾尔-帕坦喀喇昆仑公路沿线落石和边坡稳定性数值研究

在中巴经济走廊的重要通道喀喇昆仑公路（KKH）沿线，由于构造运动和降雨渗透对破碎岩石和边坡稳定性的不利作用，造成了大量落石和不稳定边坡。利用数值软件DIPS、GeoRock 2D和SLIDE对巴基斯坦北部吉贾尔-帕坦喀喇昆仑公路沿线的落石和边坡稳定性进行了数值研究；以喀喇昆仑公路沿线两个主要的易受落石影响的路段为例，研究落石和边坡的失稳机理。对4组节理进行的赤平投影分析表明：两处边坡断面均易发生平面破坏和楔形破坏。基于极限平衡理论，在静力条件下，边坡断面1的安全系数为0.917，处于不稳定状态，边坡断面2的安全系数为1.131，处于欠稳定状态；但在地震条件下，两处断面边坡的安全系数均小于1，处于不稳定状态。研究结果表明，边坡断面1和断面2的落石回弹高度分别为33 m和29 m。边坡断面1的落石速度在0.5~44 m/s，总动能达到1 135.099 kJ，而边坡断面2的落石具有0.5~40.901 m/s的速度和973.012 kJ的破坏能力。研究表明，KKH沿线的落石和滑坡具有极大的破坏潜力。