Improved Genetic Programming Algorithm Applied to Symbolic Regression and Software Reliability Modeling

The present study aims at improving the ability of the canonical genetic programming algorithm to solve problems, and describes an improved genetic programming (IGP). The proposed method can be described as follows: the first inves-tigates initializing population, the second investigates reproduction operator, the third investigates crossover operator, and the fourth investigates mutation operation. The IGP is examined in two domains and the results suggest that the IGP is more effective and more efficient than the canonical one applied in different domains.

Post-operative morbidity after neoadjuvant chemotherapy and resection for gallbladder cancer: A national surgical quality improvement program analysis

BACKGROUND Gallbladder cancer is the most common malignancy of the biliary tract.Neo-adjuvant chemotherapy(NACT)has improved overall survival by enabling R0 resection.Currently,there is no consensus of guidelines for neoadjuvant therapy in gallbladder cancer.As investigations continue to analyze the regimen and benefit of NACT for ongoing care of gallbladder cancer patients,we examined American College of Surgeons National Surgical Quality Improvement Program(NSQIP)database to determine if there was higher morbidity among the neo-adjuvant group within the 30-day post-operative period.We hypothesized patients who underwent NACT were more likely to have higher post-operative morbidity.AIM To investigate the 30-day post-operative morbidity outcomes between patients who received NACT and underwent surgery and patients who only had surgery.METHODS A retrospective analysis of the targeted hepatectomy NSQIP data between 2015 and 2019 was performed to determine if NACT in gallbladder cancer increased the risk for post-operative morbidity(bile leak,infection rate,rate of converting to open surgery,etc.)compared to the group who only had surgery.To calculate the odds ratio for the primary and secondary outcomes,a crude logistic regression was performed.RESULTS Of the 452 patients,52 patients received NACT prior to surgery.There were no statistically significant differences in the odds of morbidity between the two groups,including bile leak[odds ratio(OR),0.69;95%confidence interval(95%CI):0.16-2.10;P=0.55],superficial wound infection(OR,0.58;95%CI:0.03-3.02;P=0.61),and organ space wound infection(OR,0.63;95%CI:0.18-1.63;P=0.61).CONCLUSION There was no significant difference in the risk of 30-day post-operative morbidity between the NACT and surgery group and the surgery only group.

Set Programming Method and Performance Improvement of Phase Change Random Access Memory Arrays

A novel slow-down set waveform is proposed to improve the set performance and a 1 kb phase change random access memory chip fabricated with a 13nm CMOS technology is implemented to investigate the set performance by different set programming strategies based on this new set pulse. The amplitude difference （I1 - I2） of the set pulse is proved to be a crucial parameter for set programming. We observe and analyze the cell characteristics with different I1 - I2 by means of thermal simulations and high-resolution transmission electron microscopy, which reveal that an incomplete set programming will occur when the proposed slow-down pulse is set with an improperly high I1 - I2. This will lead to an amorphous residue in the active region. We also discuss the programming method to avoid the set performance degradations.

Genetic programming for predictions of effectiveness of rolling dynamic compaction with dynamic cone penetrometer test results

Rolling dynamic compaction (RDC),which employs non-circular module towed behind a tractor,is an innovative soil compaction method that has proven to be successful in many ground improvement applications.RDC involves repeatedly delivering high-energy impact blows onto the ground surface,which improves soil density and thus soil strength and stiffness.However,there exists a lack of methods to predict the effectiveness of RDC in different ground conditions,which has become a major obstacle to its adoption.For this,in this context,a prediction model is developed based on linear genetic programming (LGP),which is one of the common approaches in application of artificial intelligence for nonlinear forecasting.The model is based on in situ density-related data in terms of dynamic cone penetrometer (DCP) results obtained from several projects that have employed the 4-sided,8-t impact roller (BH-1300).It is shown that the model is accurate and reliable over a range of soil types.Furthermore,a series of parametric studies confirms its robustness in generalizing data.In addition,the results of the comparative study indicate that the optimal LGP model has a better predictive performance than the existing artificial neural network (ANN) model developed earlier by the authors.

Synthesis of refrigeration system based on generalized disjunctive programming model

Refrigeration system holds an important role in process industries. The optimal synthesis cannot only reduce the energy consumption, but also save the production costs. In this study, a general methodology is developed for the optimal design of refrigeration cycle and heat exchanger network(HEN) simultaneously. Taking the heat integration between the external heat sources/sinks and the refrigeration cycle into consideration, a superstructure with sub-coolers is developed. Through defining logical variables that indicate the relative temperature positions of refrigerant streams after sub-coolers, the synthesis is formulated as a Generalized Disjunctive Programming(GDP) problem based on LP transshipment model, with the target of minimizing the total compressor shaft work in the refrigeration system. The GDP model is then reformulated as a Mixed Integer Nonlinear Programming(MINLP) problem with the aid of binary variables and Big-M Constraint Method. The efficacy of the process synthesis model is demonstrated by a case study of ethylene refrigeration system. The result shows that the optimization can significantly reduce the exergy loss as well as the total compression shaft work.

Motor relearning program and Bobath method improve motor function of the upper extremities in patients with stroke

BACKGROUND: In the natural evolution of cerebrovascular disease, unconscious use of affected extremity during drug treatment and daily life can improve the function of affected upper extremity partially, but it is very slow and also accompanied by the formation of abnormal mode. Therefore, functional training should be emphasized in recovering the motor function of extremity. OBJECTIVE: To observe the effects of combination of motor relearning program and Bobath method on motor function of upper extremity of patients with stroke. DESIGN: Comparison of therapeutic effects taking stroke patients as observation subjects. SETTING: Department of Neurology, General Hospital of Beijing Jingmei Group. PARTICIPANTS: Totally 120 stroke patients, including 60 males and 60 females, averaged (59±3) years, who hospitalized in the Department of Neurology, General Hospital of Beijing Jingmei Group between January 2005 and June 2006 were recruited. The involved patients met the following criteria: Stroke attack within 2 weeks; diagnosis criteria of cerebral hemorrhage or infarction made in the 4th National Cerebrovascular Disease Conference; confirmed by skull CT or MRI; Informed consents of therapeutic regimen were obtained. The patients were assigned into 2 groups according to their wills: rehabilitation group and control group, with 30 males and 30 females in each group. Patients in rehabilitation group averaged (59±2)years old, and those in the control group averaged (58±2)years old. METHODS: ① Patients in two groups received routine treatment in the Department of Neurology. When the vital signs of patients in the rehabilitation group were stable, individualized treatment was conducted by combined application of motor relearning program and Bobath method. Meanwhile, training of activity of daily living was performed according to the disease condition changes of patients at different phases, including the nursing and instruction of body posture, the maintenance of good extremity position, bed exercise, bedside sit up and sitting position balance, sit up exercise, dynamic and static balance exercise, walking exercise, active training and passive training. The strength, time and speed of training were increased gradually according to their physical abilities. Patients were trained 45 to 60 minutes once, 5 times a week, within 2 weeks. ② Evaluation criteria of therapeutic effect: The motor function of upper extremity was evaluated by Fugl-Meyer method on the day of beginning and end of treatment. Higher points indicated better function of upper extremity. ③ t test and paired t test were used for comparing the difference of intergroup and intragroup measurement data, respectively. MAIN OUTCOME MEASURES: Changes in Fugl-Meyer scoring of two groups before and after treatment. RESULTS: Totally 120 stroke patients participated in the final analysis. Before treatment, Fugl-Meyer scoring was close between rehabilitation group and control group [(14.47±2.38),(14.16±2.39) points, P > 0.05]; Fugl-Meyer scoring of rehabilitation group after treatment was significantly higher than that before treatment and that of control group[(37.93±2.67),(18.36±2.43) points, t =11.053, 5.408, P < 0.01]; There were no significant differences in Fugl-Meyer scoring between before treatment in the control group and control group (P > 0.05). CONCLUSION: Combined application of motor relearning program and Bobath method can significantly improve the motor function of upper extremity of patients with stroke.

Optimizing the Asset and Liability Management of Telecommunication Company using Goal Programming Model

Since the telecommunications companies experience great competition,high churn rate,data traffic issues during the Covid-19 pandemic and the upgrade to 5G connectivity,the finance management of a telecommunications company should be analyzed to study the volatility and returns in the sector.This paper aims to develop a goal programming model to examine the asset and liability management of a telecommunication company,namely Telekom Malaysia Berhad(TM)in Malaysia.The result of this study shows that TM has achieved all the goals in maximizing assets,equities,profits,earnings and optimum management item while minimizing liabilities over the period of study from 2015 to 2019.Potential improvements on these goals have also been identified through this study.This paper has also contributed to the studies in financial management since past studies have not been done on asset and liability management in telecommunications companies which is rapidly growing and expanding even while the world is suffering from economy crisis during this pandemic.

National Swine Genetic Improvement: An overview of essential program components and organizational structure needed for success

The swine industry in China is a thriving and evolving industry that has shown phenomenal growth over the past 10 years. To insure long term success and viability in a worldwide competitive industry such as pork, there is need for a National Swine Genetic Improvement Program. This program needs to draw on expertise and technology from across the world for its development, but it should be based on the structure of the pig industry in China and be led by Chinese scientists, administrators and producers. National Genetic Improvement requires more than just technology. A successful program of national genetic improvement will require cooperation from the industry and the government. The support for the university system is essential for the success of the pig industry. The university system has a vital role on education (of students, faculty, producers and consumers) as well as research and technology transfer. The government could also have a role in supporting the central test stations and AI stations across the country. An accurate and comprehensive pedigree maintenance system is essential to genetic improvement. And it will be vitally important to be active in the importation of new genetics to sample other populations.

Studying Design and Use of Healthcare Technologies in Interaction: The Social Learning Perspective in a Dutch Quality Improvement Collaborative Program

Designing technologies is a process that relies on multiple interactions between design and use contexts. These interactions are essential to the development and establishment of technologies. This article seeks to understand the attempts of healthcare organisations to integrate use contexts into the design of healthcare technologies following insights of the theoretical approaches of social learning and user representations. We present a multiple case study of three healthcare technologies involved in improving elderly care practice. These cases were part of a Dutch quality improvement collaborative program, which urged that development of these technologies was not “just” development, but should occur in close collaboration with other parts of the collaborative program, which were more focused on implementation. These cases illustrate different ways to develop technologies in interaction with use contexts and users. Despite the infrastructure of the collaborative program, interactions were not without problems. We conclude by arguing that interactions between design and use are not naturally occurring phenomena, but must be actively organised in order to create effects.

Extending Extreme Programming User Stories to Meet ISO 9001 Formality Requirements

For software organizations needing ISO 9001 certification, including those that have adopted agile methodologies, it is important that their software life cycle processes be able to manage the requirements imposed by this certification standard. However, the user stories in the XP agile methodology do not provide auditors with enough evidence that certain steps and activities have been performed in compliance with ISO 9001. This paper proposes an extension to the user story, based on four sub processes related to the CMMI-DEV model: 1) identification of the source of the user story;2) categorization of the non functional requirements;3) identification of the user story relationships;and 4) prioritization of the user stories. These sub processes are aligned with the XP release planning phase, and enhance the ability of user stories to accumulate the information that is mandatory for achieving ISO 9001 certification.

Nurse Mentor Training Program to Improve Quality of Maternal and Newborn Care at Primary Health Centres: Process Evaluation

Quality of maternal and newborn care could be improved if health care providers’ knowledge and competencies as well as system level constraints are addressed. However, due to several barriers staff nurses who form the frontline of health care workforce have limited access to enhancing their clinical knowledge and competencies. To address this gap, a new cadre of nurse mentors (NMs) for the public health system were trained by specialists from a teaching hospital in a special 5-week training course. This included 54 hours of theory and 110 hours of practical in clinical obstetric and newborn care, apart from mentoring, quality improvement and health systems issues. The nurse mentors were assigned to support staff nurses in the primary health care centres (PHCs) in eight northern Karnataka districts. Each NM covered 6-8 PHCs monthly for 2 - 3 days and thus a total of 385 PHCs were reached. They received support in the field through supportive supervision visits done by the specialists who had trained them, as well as by refresher training and clinical postings to the district hospitals. This paper presents impact of the training program on change in immediate and long term knowledge and competency scores of nurse mentors. Their baseline knowledge scores changed from 44.3 ± 12.7 to 72.1 ± 13.8 immediately after the training in obstetric and from 18.2 ± 19.1 to 66.4 ± 14.9 in newborn (p p p > 0.05). Skills score soon after training increased from 62.2 ± 13.2 to 69.6 ± 12.5 in obstetric after a 1 year period and from 52.6 ± 9.3;63.5 ± 14.4 in newborn (p < 0.001) content areas respectively. These findings have implications for those interested in improving quality of maternal and child care through nurse-dependent health delivery systems.

Training Program to Improve NGOs' capacity

Murong Feng, a 31-year-old activist from Hebei Province in northern China, had attended several training workshops for non-governmental organizations （NGOs） related to HIV/AIDS prevention before he came to Beijing last October for another one.

Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm

To obtain a suitable scheduling scheme in an effective time range,the minimum completion time is taken as the objective of Flexible Job Shop scheduling Problems(FJSP)with different scales,and Composite Dispatching Rules(CDRs)are applied to generate feasible solutions.Firstly,the binary tree coding method is adopted,and the constructed function set is normalized.Secondly,a CDR mining approach based on an Improved Genetic Programming Algorithm(IGPA)is designed.Two population initialization methods are introduced to enrich the initial population,and a superior and inferior population separation strategy is designed to improve the global search ability of the algorithm.At the same time,two individual mutation methods are introduced to improve the algorithm’s local search ability,to achieve the balance between global search and local search.In addition,the effectiveness of the IGPA and the superiority of CDRs are verified through comparative analysis.Finally,Deep Reinforcement Learning(DRL)is employed to solve the FJSP by incorporating the CDRs as the action set,the selection times are counted to further verify the superiority of CDRs.

基于GPU加速求解MINLP问题的SQP并行算法

针对确定性算法求解大型复杂混合整数非线性规划的时间不可接受问题,通过对序贯二次规划算法(SQP)和图形处理器(GPU)的架构特点分析,提出了基于GPU加速策略的并行化SQP算法。算法的主要思想是通过枚举法确定二元变量的取值,在保证取值完整的基础上,使用CPU+GPU的并行策略,同时运用大量线程进行非线性规划子问题的求解。算例的数值实验结果表明:本文所提出的算法较之传统串行计算具有较好的加速效果,特别适合求解二元变量较多,约束条件相对少的MINLP问题。

Factors in fluencing farmers' participation in crop intensification program in Rwanda

The crop intensification program（CIP）was introduced in Rwanda in 2007 by the Ministry of Agriculture and Animal Resources（MINAGRI）,Rwanda,as a solution to the land fragmentation,low use of agricultural inputs and low access to extension services.However,due to the voluntary nature of farmers’participation and their reluctance to participate,this study aimed at assessing the factors that influence their participation.Data were collected from 340 respondents through a household survey in Mayange and Rusarabuye sectors.Descriptive statistics and binary logistic regression model were used to analyze the data.Results show that the factors that significantly influenced the farmers’participation in the CIP include gender,non-farm income,farmland size,farming experience,land acquisition means,market access,trust and agro-ecological conditions.In fact,the non-farm income significantly increased the farmers’decisions to participate in the CIP（P〈0.001）as it eases the financial capital needed to invest in the CIP activities.On the land acquisition means,the farmers who inherited or bought the land positively and significantly participated in the CIP（P〈0.05）because they had the land tenure security.However,the participation in the CIP was hindered by inadequate irrigation and mechanization facilities,lack of farmers’participation in the CIP planning process,inadequate extension services,inadequate agricultural inputs and inadequate post-harvest technologies.Closer collaboration between farmers,local leaders,extension agents and agricultural service providers as well as the farmers’practical skills in irrigation and mechanization could enhance the participation to the program.Therefore,there is a need on the part of policymakers to empower farmers with adequate knowledge on better cropping practices and agricultural technologies through appropriate extension services and bottom-up based program.

基于机会约束MINLP模型的多工况氢气网络操作优化技术

随着日益严格的环保标准以及新能源需求的不断增加,氢气已经成为炼油厂的重要资源。针对炼油厂存在多种工况的情况,在氢源产氢量、氢阱耗氢量、市场价格不确定的环境下,以氢气网络运行与CO_(2)排放成本(TOEC)之和为目标,考虑氢源标况流量、氢阱标况流量、氢气含量、压缩机、变压吸附(PSA)装置、燃料和管道约束,建立了多工况机会约束混合整数非线性规划(MCC-MINLP)氢气网络操作优化模型。对某炼油厂涉氢装置运行数据进行拟合,得到不同工况下产氢量与耗氢量的分布情况后,在不同置信水平下求解MCC-MINLP模型,得到了各工况的氢气网络最优操作方案。计算结果表明,通过增加一套PSA装置以及对应管道,可以减少15.17%~16.68%的新氢使用量并优化原氢气网络结构,优化后氢气网络的TOEC降低了2.19%~2.34%。

Optimal synthesis of compression refrigeration system using a novel MINLP approach

The optimal design of a compression refrigeration system(CRS) with multiple temperature levels is very important to chemical process industries and also represents considerable challenges in process systems engineering. In this paper, a general methodology for the optimal synthesis of the CRS, which simultaneously integrates CRS and Heat Exchanger Networks(HEN) to minimize the total compressor shaft work consumption based on an MINLP model, has been proposed. The major contribution of this method is in addressing the optimal design of refrigeration cycle with variable refrigeration temperature levels. The method can be used to make major decisions in the CRS design, such as the number of levels, temperature levels, and heat transfer duties. The performance of the developed methodology has been illustrated with a case study of an ethylene CRS in an industrial ethylene plant, and the optimal solution has been examined by rigorous simulations in Aspen Plus to verify its feasibility and consistency.

Applications of Molecular Markers in Fruit Crops for Breeding Programs—A Review

Selection and use of molecular markers for evaluation of DNA polymorphism in plants are couple of the most important approaches in the field of molecular genetics.The assessment of genetic diversity using morphological markers is not sufficient due to little differentiating traits among the species,genera or their individuals.Morphological markers are not only highly influenced by environmental factors but skilled assessment is also prerequisite to find the variations in plant genetic resources.Therefore,molecular markers are considered as efficient tools for detailed DNA based characterization of fruit crops.Molecular markers provide new directions to the efforts of plant breeders particularly in genetic variability,gene tags,gene localization,taxonomy,genetic diversity,phylogenetic analysis and also play an important role to decrease the time required for development of new and excellent cultivars.The success of molecular markers technology in genetic improvement programs depends on the close relationship among the plant breeders,biotechnologists,skilled manpower and good financial support.The present review describes application and success of molecular markers technology used for genetic improvement in different fruit crops.

解决高维INLP和MINLP问题的混沌差分进化算法

为改进差分进化(Differential Evolution,DE)算法的搜索能力,提出一种新的混沌差分进化算法(CGLSDE).首先,该算法利用混沌序列替换DE参数并采用混沌全局搜索算法来改进DE的全局搜索能力;其次,CGLSDE算法还采用了单维和多维的混沌局部搜索来改进DE的局部搜索能力.仿真结果表明:CGLSDE算法在解决高维整数非线性规划(INLP)问题和高维混合整数非线性(MINLP)问题上,其性能要好于其它3种混沌差分进化算法.