Irradiated Ch/GG/PVP-based stimuli-responsive hydrogels for controlled drug release

Hydrogels based on gamma (γ) irradiated chitosan (pre-irradiated), guar gum, and polyvinyl pyrrolidone were crosslinked with various concentrations of (3-mercapto propyl)trimethoxysilane and fabricated by solution casting technique for the drug delivery applications. High molecular weight chitosan (Ch) possesses lower solubility and higher viscosity, these problems overcame by γ irradiation, which also generated hydrophilicity and effect of irradiated Ch on controlled drug release was assessed. FTIR analysis showed the development of chemical and physical interactions and confirmed the incorporation of characteristic peaks. SEM micrographs revealed porous structure of the prepared hydrogels. Swelling analysis of the hydrogels was performed in distilled water, buffer, and electrolyte mediums. All the hydrogel samples showed higher swelling at acidic pH and lower swelling at neutral and basic pH. These pH-responsive characteristics made these RCGP hydrogels an important contender for injectable controlled drug release. The ampicillin sodium drug was loaded and in vitro controlled release mechanism was evaluated in the PBS, SIF, and SGF which shown out of all prepared hydrogels (RCGP-1, RCGP-2, and RCGP-3), RCGP-1 has exhibited 87.4% release in PBS and 81.3% in SIF in 180 min.     

"人机环管"在煤矿供电安全管理中的应用

制定供电过程中消除安全隐患的针对性措施,可以为矿井安全生产提供必要保障。为探究煤矿供电管理中安全隐患的具体分析方法,首先介绍“人机环管”管理体系的建立过程和核心内容,接着以“人机环管”的管理方法分析了供电管理中的普遍问题。在分析供电管理中的具体问题时,分别得出了“人”“机”“环”“管”4方面的具体措施。分析认为,“人机环管”方法可以有效查找出存在的安全隐患,进而保证煤矿供电系统的安全可靠。     

基于顾客退货的风险规避型双渠道供应链最优策略

在随机市场需求条件下,考虑风险规避型双渠道供应链中存在顾客退货时的最优决策问题,决策变量为两个渠道的商品售价和制造商批发价。以集中决策时的最优决策作为比较标杆,重点利用均值—方差方法分析了分散决策时风险规避型制造商和零售商的最优决策。结合灵敏度分析和数值试验,讨论了分散决策下的风险规避度,以及市场需求波动和顾客退货率对最优决策的影响。结果表明,高退货率不利于零售商、制造商及整个供应链的收益;风险规避度对收益的影响不是一成不变的,与需求波动大小有关;分散决策虽然引起了双边际效应,但制造商风险规避度的增加将降低双边际效应的负面影响。     

Sustainability impact assessment for local energy supplies' development – The case of the alpine area of Lake Como,Italy

The development of distributed energy systems has important environmental, social and economic implications. Local decision-making processes must be guided by a careful evaluation of the sustainability of production chains and alternative choices. The aim of this study is to explore if and how an integrated assessment can quantify the extent to which bioenergy supply chain development contributes to rural development and energy policy objectives. We applied a Sustainability Impact Assessment (SIA) for local bioenergy development in the alpine area of Lake Como (Italy). We modeled the local bioenergy chain in 2008 and eleven scenarios considering different biomass utilizations, mechanization levels, combustion technologies, and subsidies schemes at 2020. We calculated economic, social and environmental indicators. We interpret and discuss the scenario analysis in order to support the bioenergy planning under the light of its implications for the different policy aims and concerns.     

Competitive closed-loop supply chain network design under uncertainty

This paper studies the competition between two closed-loop supply chains including manufacturers, retailers and recyclers in an uncertain environment. The competition factors are the retail prices of new products and incentives paid to consumers for taking back the used products. Market demands are price sensitive and also the amount of returned products is sensitive to incentives. The primary goal of this paper is to investigate the impact of simultaneous and Stackelberg competitions between two closed-loop supply chains on their profits, demands and returns. A game theoretic approach which is empowered by possibility theory is applied to obtain the optimal solutions under uncertain condition. Finally the theoretical results are analyzed using sample data inspired by a real industrial case.     

Multiplex PCR system to track authorized and unauthorized genetically modified soybean events in food and feed

A diverse range of genetic elements has been used to develop genetically modified organisms (GMOs) over the last 18 years. Screening methods that target few elements, such as the Cauliflower Mosaic Virus 35S promoter (P-35S) and Agrobacterium tumefaciens nopaline terminator (T-nos), are not sufficient to screen GMOs. In the present study, a multiplex PCR system for all globally commercialized GM soybean events was developed to easily trace the events. For this purpose, screening elements of 24 GM soybean events were investigated and 9 screening targets were selected and divided into three individual triplex PCR systems: P-35S, ribulose-1,5-bisphosphate carboxylase small subunit promoter of Arabidopsis thaliana, T-nos, T-35S, pea E9 terminator, open reading frame 23 terminator of A. tumefaciens, proteinase inhibitor II terminator of potato, acetohydroxy acid synthase large subunit terminator of A. thaliana, and the revealed 3′ flanking sequences of DP-305423-1. The specificity of the assays was confirmed using thirteen GM soybean events as the respective positive/negative controls. The limit of detection of each multiplex set, as determined using certified reference materials of specific GM events, ranged from 0.03 to 0.5%, depending upon target. Furthermore, 26 food samples that contained soybean ingredients, which were purchased from the USA, China, Japan, and Korea, were analyzed, 17 of which contained one or more GM soybean events. These results suggest that the developed screening method can be used to efficiently track and identify 24 GM soybean events in food and feed.     

生鲜农产品冷链管理及关键技术研究进展

冷链已经成为世界各国提高生鲜农产品流通条件、食品质量安全、农产品附加值及促进农产品走向国际市场的重要保障。与世界发达国家相比,中国的生鲜农产品冷链在技术、整体设备拥有量和系统管理水平等方面均存在一定的差距。在对国内外冷链管理研究进行梳理的基础上,对冷链管理中的几类主要问题:库存、物流系统规划、质量安全、协调机制及关键技术等进行综述和比较分析,最后从生鲜农产品冷链碳排放、消费者行为倾向、闭环供应链等方面探讨中国未来生鲜农产品冷链的发展趋势。     

New Insights to Clathrin and Adaptor Protein 2 for the Design and Development of Therapeutic Strategies

The Amyloid Precursor Protein (APP) has been extensively studied for its role as the precursor of the β-amyloid protein (Aβ) in Alzheimer’s disease (AD). However, our understanding of the normal function of APP is still patchy. Emerging evidence indicates that a dysfunction in APP trafficking and degradation can be responsible for neuronal deficits and progressive degeneration in humans. We recently reported that the Y₆₈₂ mutation in the ₆₈₂YENPTY₆₈₇ domain of APP affects its binding to specific adaptor proteins and leads to its anomalous trafficking, to defects in the autophagy machinery and to neuronal degeneration. In order to identify adaptors that influence APP function, we performed pull-down experiments followed by quantitative mass spectrometry (MS) on hippocampal tissue extracts of three month-old mice incubated with either the ₆₈₂YENPTY₆₈₇ peptide, its mutated form, ₆₈₂GENPTY₆₈₇ or its phosphorylated form, ₆₈₂pYENPTY₆₈₇. Our experiments resulted in the identification of two proteins involved in APP internalization and trafficking: Clathrin heavy chain (hc) and its Adaptor Protein 2 (AP-2). Overall our results consolidate and refine the importance of Y₆₈₂ in APP normal functions from an animal model of premature aging and dementia. Additionally, they open the perspective to consider Clathrin hc and AP-2 as potential targets for the design and development of new therapeutic strategies.     

Two stage stochastic bilevel programming model of a pre-established timberlands supply chain with biorefinery investment interests

This work studies the supply allocation problem, using a Stackelberg game, for an established timberlands supply chain with an additional decision of new biorefinery investments. In a timberlands system, harvester and manufacturer decision makers have separate objectives to maximize their respective profits. This interaction is represented with a turn based Stackelberg game. The harvesters decide first on the quantity harvested, and the manufacturers decide on how much to utilize. This game is modeled with a bilevel mathematical program. The novel feature of this paper's bilevel formulation is the inclusion of parametric uncertainty in a two stage model. The first stage problem involves logistical decisions around biorefinery investments, such as location and capacity, while the second stage problem involves a bilevel timberlands model with parameter uncertainty. Studying this problem formulation revealed interesting insights for solving multiperiod problems with bilevel stages as well as the decision maker's behavior for the timberlands model.     

A bi-objective integrated procurement,production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA

Efficient management of supply chain (SC) requires systematic considerations of miscellaneous issues in its comprehensive version. In this paper, a multi-periodic structure is developed for a supply chain network design (SCND) involving suppliers, factories, distribution centers (DCs), and retailers. The nature of the logistic decisions is tactical that encompasses procurement of raw materials from suppliers, production of finished product at factories, distribution of finished product to retailers via DCs, and the storage of raw materials and end product at factories and DCs. Besides, to make the structure more comprehensive, a flow-shop scheduling model in manufacturing part of the SC is integrated in order to obtain optimal delivery time of the product that consists of the makespan and the ship time of the product to DCs via factories. Moreover, to make the model more realistic, shortage in the form of backorder can occur in each period. The two objectives are minimizing the total SC costs as well as minimizing the average tardiness of product to DCs. The obtained model is a bi-objective mixed-integer non-linear programming (MINLP) model that is shown to belong to NP-Hard class of the optimization problems. Thus, a novel algorithm, called multi-objective biogeography based optimization (MOBBO) with tuned parameters is presented to find a near-optimum solution. As there is no benchmark available in the literature, the parameter-tuned multi-objective simulated annealing algorithm (MOSA) and the popular non-dominated sorting genetic algorithm (NSGA-II) are developed to validate the results obtained and to evaluate the performance of MOBBO using randomly generated test instances.