Renal allograft procurement from living unrelated donors in Iran: What falls under the eclipse

Renal transplantation is the treatment of choice for end stage kidney disease.However,despite all the efforts to expand the donor pool,the shortage of donors is increasing and as a consequence,there has been a significant increase in the number of patients on transplant waiting lists globally.Societies worldwide have employed different methods to address this,each with specific ethical concerns surrounding them.Over three decades ago,a governmentally regulated program of kidney transplantation from living unrelated donors was introduced in Iran and since practiced which has been the subject of hot debate in the literature.Nevertheless,despite all these extensive discussions and publications,several key aspects of the program have still not been properly elucidated and addressed.In this article,the author aims to illuminate some dark corners related to this issue that have largely escaped the notice of ethicists.

Design and Comparison of Simulated Annealing Algorithm and GRASP to Minimize Makespan in Single Machine Scheduling with Unrelated Parallel Machines

This paper discusses design and comparison of Simulated Annealing Algorithm and Greedy Randomized Adaptive Search Procedure (GRASP) to minimize the makespan in scheduling n single operation independent jobs on m unrelated parallel machines. This problem of minimizing the makespan in single machine scheduling problem with uniform parallel machines is NP hard. Hence, heuristic development for such problem is highly inevitable. In this paper, two different Meta-heuristics to minimize the makespan of the assumed problem are designed and they are compared in terms of their solutions. In the first phase, the simulated annealing algorithm is presented and then GRASP (Greedy Randomized Adaptive Search procedure) is presented to minimize the makespan in the single machine scheduling problem with unrelated parallel machines. It is found that the simulated annealing algorithm performs better than GRASP.

Production of Poly（3-hydroxybutyrate-co-3-hydroxyhexanoate） by Recombinant Pseudomonas stutzeri 1317 from Unrelated Carbon Sources

Synthetic biology promises to simplify the construction of metabolic pathways by assembling the de- tached modules of the whole pathway. This gives new approaches for the microbial production of industrial products such as polyhydroxyalkanoates （PHA）. In this study, to produce poly（3-hydroxybutyrate-co-3-hydroxyhexanoate） （PHBHHx） by Pseudomonas stutzeri 1317 from unrelated carbon sources such as glucose, the phaCl-phaZ-phaC2 operon of P. stutzeri 1317 was knocked out to generate the PHA deficient mutant P. stutzeri 1317LF. Then three modules containing phaCahAReBRe, phaCahBReGep and phaCAhPah were introduced into P. stutzeri 1317LF separately The shake flask results indicated that the precursor supply and PHA synthase activity were the vital factors for the PHBHHx accumulation of P. stutzeri 1317LF. Furthermore, the PHBHHx accumulation of the recombinants from different carbon resources were performed. The highest PHBHHx content was 23.7% （by mass） with 58.6% （by mole） 3HB fraction. These results provide basis for further improving the PHBHHx accumulation of P. stutzeri from unrelated carbon sources.

A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine

The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.

A Hybrid Estimation of Distribution Algorithm for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times

A hybrid estimation of distribution algorithm (EDA) with iterated greedy (IG) search (EDA-IG) is proposed for solving the unrelated parallel machine scheduling problem with sequence-dependent setup times (UPMSP-SDST). For makespan criterion, some properties about neighborhood search operators to avoid invalid search are derived. A probability model based on neighbor relations of jobs is built in the EDA-based exploration phase to generate new solutions by sampling the promising search region. Two types of deconstruction and reconstruction as well as an IG search are designed in the IG-based exploitation phase. Computational complexity of the algorithm is analyzed, and the effect of parameters is investigated by using the Taguchi method of design-of-experiment. Numerical tests on 1640 benchmark instances are carried out. The results and comparisons demonstrate the effectiveness of the EDA-IG. Especially, the bestknown solutions of 531 instances are updated. In addition, the effectiveness of the properties is also demonstrated by numerical comparisons. © 2014 Chinese Association of Automation.

Living related and living unrelated kidney transplantations:A systematic review and meta-analysis

AIM To compare the outcomes between related and unrelated kidney transplantations.METHODS Literature searches were performed following the Cochrane guidelines. We conducted a systematic review and a meta-analysis, which included 12 trials that investigated outcomes including the long-term(ten years), midterm(one to five years), and short-term(one year) graft survival rate as well as the acute rejection rate. Metaanalyses were performed using fixed and random-effects models, which included tests for publication bias and heterogeneity.RESULTS No difference in graft survival rate was detected in patients who underwent living related kidney transplantations compared to unrelated(P = 0.44) transplantations after ten years. There were no significant differences between the graft survival rate in living related and unrelated kidney transplantations after a short-and midterm follow-up(P = 0.35, P = 0.46). There were no significant differences between the acute rejection rate in living related and unrelated kidney transplantations(P = 0.06).CONCLUSION The long, mid and short term follow-up of living related and unrelated kidney transplantation showed no significant difference in graft survival rate. Also, acute rejection rate was not significantly different between groups.

Efficient Heuristic to Minimize Makespan in Single Machine Scheduling Problem with Unrelated Parallel Machines

This paper discusses an efficient heuristic to minimize the makespan of scheduling n independent jobs on m unrelated parallel machines. The problem of scheduling the jobs on the unrelated parallel machines is combinatorial in nature. Hence, the heuristic approach is inevitable for quicker solution. In this paper, a simple and efficient heuristic is designed to minimize the makespan of scheduling n independent jobs on m unrelated parallel machines. A mathematical model is also presented for this problem. A factorial experiment is used to compare the results of the proposed heuristic with that of a mathematical model by taking “Method” (Heuristic and Model) as the first factor and “Problem Size” (No. of machines X No. of Jobs: 2X5, 2X6, ……, 2X9, 3X5, 3X6, ……, 3X9, ……., 5X5, 5X6, …5X9) as the second factor. It is found that there is no significant difference between the results of the proposed heuristic and that of the mathematical model. Further, the mean percent error of the results obtained by the heuristic from the optimal results obtained by the model is 2.336 %. The heuristic gives optimal solution for 76.67 % of the problems.

IgG4-Unrelated Type 1 Auto Immune Pancreatitis Manifesting with Pancreatic Head Mass Mimicking Cancer

Auto immune pancreatitis (AIP) is an uncommon form of chronic pancreatitis that has been divided into type 1 and type 2 which have distinct histopathology and clinical features. Type 1 AIP seems to be the pancreatic manifestation of an IgG4-related systemic disease, characterized by elevated IgG4 serum levels, infiltration of IgG4-positive plasma cells and extrapancreatic lesions. When manifesting as a focal disease in the pancreas, it can be challenging to differentiate it from pancreatic cancer (PC). Because AIP is typically responsive to steroid therapy without the need for resection, differentiation between these two diseases is critical. We report the case of a 56-year-old man with initial suspect of PC, and final diagnosis of type 1 AIP according to the International Consensus Diagnostic Criteria (ICDC) without elevated levels of serum IgG4 or need for a histology sample. We take a review of literature in order to improve the diagnostic accuracy of AIP and describe clinical and imaging features to differentiate it from PC and avoid unnecessary surgery due to misdiagnosis.

Unrelated Parallel-Machine Scheduling Problems with General Truncated Job-Dependent Learning Effect

In this paper, we consider scheduling problems with general truncated job-dependent learning effect on unrelated parallel-machine. The objective functions are to minimize total machine load, total completion (waiting) time, total absolute differences in completion (waiting) times respectively. If the number of machines is fixed, these problems can be solved in time respectively, where m is the number of machines and n is the number of jobs.

Improved Estimation of Distribution Algorithm for Solving Unrelated Parallel Machine Scheduling Problem

Scheduling problem is a well-known combinatorial optimization problem.An effective improved estimation of distribution algorithm(IEDA) was proposed for minimizing the makespan of the unrelated parallel machine scheduling problem(UPMSP).Mathematical description was given for the UPMSP.The IEDA which was combined with variable neighborhood search(IEDA_VNS) was proposed to solve the UPMSP in order to improve local search ability.A new encoding method was designed for representing the feasible solutions of the UPMSP.More knowledge of the UPMSP were taken consideration in IEDA_ VNS for probability matrix which was based the processing time matrix.The simulation results show that the proposed IEDA_VNS can solve the problem effectively.

A Multi-Criteria Decision Making for the Unrelated Parallel Machines Scheduling Problem

In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single machine scheduling problem, of which the objective is a weighted sum of the three objectives, is constructed. Such a model will be repeatedly solved by the CPLEX in the proposed Multi-Objective Simulated Annealing (MOSA) algorithm. In the second phase, the MOSA that integrates job clustering method, job group scheduling method, and job group – machine assignment method, is employed to obtain a set of non-dominated group schedules. During this phase, CPLEX software and the bipartite weighted matching algorithm are used repeatedly as parts of the MOSA algorithm. In the last phase, the technique of data envelopment analysis is applied to determine the most preferable schedule. A practical example is then presented in order to demonstrate the applicability of the proposed decision making method.

The Pre－test Principal Components Estimator in the Two Seemingly Unrelated Regression System

For the two seemingly unrelated regression system, this paper proposed a new type of estimator called pre-test principal components estimator (PTPCE) and discussed some properties of PTPCE.

Two Stage Estimation and Its Covariance Matrix in Multivariate Seemingly Unrelated Regression System

Multivariate seemingly unrelated regression system is raised first and the two stage estimation and its covariance matrix are given. The results of the literatures[1-5] are extended in this paper.

数字化变革背景下技术多元化对企业韧性的影响

基于资源基础理论,聚焦企业韧性的稳定性和灵活性特征,探讨数字化变革背景下技术多元化与企业韧性的关系。利用2018~2022年新冠疫情冲击前后中国上市高新技术企业的数据,采用OLS回归和生存分析法进行实证分析。结果表明:非相关技术多元化和相关技术多元化均与企业受到冲击后的稳定性呈倒U型关系;非相关技术多元化负向影响企业受到冲击后的灵活性,而相关技术多元化正向影响企业受到冲击后的灵活性;数字化变革加强了相关技术多元化与企业受到冲击后稳定性间的倒U型关系,并削弱了非相关技术多元化对企业受到冲击后灵活性的抑制作用。研究结论丰富和拓展了技术多元化与企业韧性的相关研究,为企业制定合适的技术多元化战略以增强韧性提供参考。

考虑运输时间的混合流水车间绿色生产调度

针对运输时间对混合流水车间绿色生产调度的影响这一问题,以最大完工时间、生产能耗及生产成本为优化目标,提出一种改进的多目标麻雀搜索算法(Improved Multi-Objective Sparrow Search Algorithm,IMOSSA)进行求解,参考非支配排序将种群适应度值进行划分、引入正余弦策略提高解集质量、加入多项式变异算子和Levy飞行,提高解集的收敛速度和全局搜索能力,避免陷入局部最优。而后设计16种测试算例,将IMOSSA与其他多目标优化算法进行对比,验证了IMOSSA求解的优越性。最后,以某实际生产车间为例,将其生产调度划分为4种模式,证明算法求解的实用性。

基于混合效应模型的相容性削度-材积方程研究

为构建一个能够准确估计树干从地面到任意部位高度的直径和材积的相容性削度-材积方程,以吉林省汪清林业局金沟岭林场的冷杉解析木数据为例,选择基于材积比方程和基于积分方法这2种方法来构建相容性削度-材积方程系统。在模拟时,采用3种参数估计方法来估计2个系统中的削度方程、全树干材积和商品材材积方程的参数,并考虑样木间的随机效应。选择均方根误差和平均绝对残差等指标,对精度进行比较。最后发展出一个能够准确预测树干任意高度的直径、全树干材积和商品材材积的相容性削度-材积方程系统。结果表明,在2个相容性削度-材积系统中,采用削度方程参数估计方法提供了商品材材积和全树干材积的最差预测,似乎不相关参数方法在材积比方程方法构建的相容性削度-材积方程系统中的精度最高,商品材材积参数方法在积分方法构建的相容性削度-材积方程系统中的精度最高。2个相容性削度-材积系统中无论采用商品材材积参数估计方法还是削度方程参数估计方法,在考虑单木的随机效应后,模型的模拟和验证效果都得到很大的提高。基于积分方法的相容性削度-材积方程系统的模拟和验证精度要高于基于材积比方程方法的相容性削度-材积方程系统的模拟和验证精度。总体来说,相容性削度-材积方程系统可以保证削度方程、商品材材积方程和全树干材积方程在形式和算法上相容。

含不相关机的多目标混合流水车间调度

考虑不相关机和传送等因素的多阶段混合流水车间问题,以最小化最大完工时间和总能耗为优化目标建立整数规划模型。针对该问题,提出一种多目标离散灰狼优化算法来求解。设计基于机器分配码和速度选择码的编码方式和基于最短处理时间原则的解码方案;采用反向学习策略改进初始灰狼种群质量;将基于多点变异的自走模式和基于均匀两点交叉与多点交叉的跟随模式结合构成搜索模式以协调开发和搜索能力;引入精英保留策略确保优良个体不丢失。通过一系列的仿真实验验证了该算法的有效性。

本地-流动儿童的义务教育结果公平与教育财政投入、家庭教育支出的研究

本地-流动儿童的义务教育结果公平涉及流动人口的社会融入与以人为核心城镇化进程,故值得学术研究深入探讨的议题。本文利用中国教育追踪调查数据,实证检验了教育财政投入、家庭教育支出对不同儿童义务教育结果表现的影响,结果发现:(1)基准估计揭示了教育财政投入、家庭教育支出与本地-流动儿童的学业表现间可能存在负相关性的关系,但未有明显证据表明本地儿童的学业表现优于流动儿童,稳健性检验则发现似不相关回归更富估计效率;(2)利用分样本回归的异质性分析,发现生均财政经费拨款有利于提高流动儿童和贫困家庭子女的义务教育结果表现;(3)利用分位数回归发现本地儿童在各分位点上的学业表现高于流动儿童,但估计结果并不显著,进一步利用MM分解发现本地-流动儿童的义务教育结果不平等具有“天花板效应”的鲜明特征。

油松人工林相容性生长联立方程组模型构建

以西宁市周边山地人工林为研究对象,利用近2年森林资源更新调查数据,构建油松林相容性生长联立方程组模型,采用似乎不相关回归法求解模型参数,并对模型进行异方差修正,最后检验所构建的相容性生长联立方程组模型预测精度及适应性。结果表明:相容性生长联立方程组模型对平均胸径、平均树高和每公顷断面积的预估精度均在93%以上,MSE和TRE值均在±2%以内,卡方检验结果远远小于临界值,预测效果优于独立拟合模型。在油松中幼龄林阶段,胸径、树高和断面积生长均与林分密度指数和地位级指数正相关;胸径、树高生长对地位级指数更敏感,而断面积生长对林分密度指数更敏感。基于模型预测结果,油松林分胸径快速增长期在5~25 a,年均生长量为0.33 cm;树高快速增长期在5~30 a,年均生长量为0.23 m;断面积在15 a之前增速最快,年均生长量为0.13 m2/hm2。本研究所构建的油松林相容性生长联立方程组模型预测精度高,可用来预测西宁市及相似生态区油松林分胸径、树高和断面积生长,为林分生长及收获预估、科学合理经营提供参考。