超深勘察钻孔ASR法地应力测试技术应用

宝灵山隧道是某铁路先开段的重难点控制性工程,其中宝灵山DZ-06勘察钻孔深2118.00 m,是该段深度最大的控制性勘察钻孔。在钻孔的2072.53、2084.27 m深度选取合适岩心,采用ASR法(非弹性应变恢复法)开展了地应力测试,并与该钻孔采用水压致裂法获取的地应力结果进行对比,同时验证了ASR法对于估测超深钻孔的三维地应力大小和方向的实用价值。结果表明:在钻孔2072.53~2084.27 m深度范围,ASR法2个测点获取的最大主应力、中间主应力、最小主应力平均值分别为59.70、54.03、30.74 MPa,最大主应力近水平,方向近SN向,说明该区域以水平构造应力为主;ASR法的最大主应力测试结果均值与水压致裂法测试结果回归值一致性很好,最小主应力测试结果均值与水压致裂法测试结果回归值的一致性处于合理范围,两种方法的水平主应力方向测试结果基本一致。

花生ASR基因家族特性及其对干旱和盐胁迫的响应

【目的】探究花生ASR基因家族特性及其在干旱和盐胁迫响应中的作用,为培育花生抗旱抗盐新品种提供潜在基因位点。【方法】通过生物信息学方法在全基因组水平鉴定花生ASR家族并分析其基本特性,借助转录组数据分析其在200 mmol/L NaCl及模拟干旱PEG处理后的表达变化。【结果】(1)鉴定到7个花生ASR基因,pI为5.34~6.98,蛋白脂肪系数为23.77~56.84,GRAVY值均为负值,表明这7个蛋白均是亲水性蛋白;(2)AhASR3与AhASR7基因表达模式相似,转录水平较高,基因结构及蛋白结构域和保守基序的位置和数量较相似,motif 5、6、9仅存在于AhASR3与AhASR7蛋白中;(3)AhASR1、AhASR5及AhASR2的启动子区域有干旱诱导MYB转录因子的结合位点,发现AhASR1、AhASR2及AhASR4的启动子区有ABA响应元件;(4)AhASR2、AhASR3及AhASR7在200 mmol/L NaCl处理后根部出现较明显转录上调;(5)AhASR1、AhASR3、AhASR4及AhASR7分别在PEG处理4 h和8 h后,转录水平出现2倍以上上调。【结论】花生ASR家族蛋白均为亲水性蛋白,各成员之间既有保守结构域也有特异性序列,大部分成员启动子区都具有干旱响应相关元件,并受到盐处理以及模拟干旱处理的诱导表达,可作为耐盐耐旱花生品种培育的重要候选基因。

Classification and Comprehension of Software Requirements Using Ensemble Learning

The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional requirements.To address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human effort.However,existing techniques often struggle with complex instructions and large-scale projects.In our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer trees.Experimental results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT dataset.Both datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse scenarios.These findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

An Investigation on Open-RAN Specifications:Use Cases,Security Threats,Requirements,Discussions

The emergence of various technologies such as terahertz communications,Reconfigurable Intelligent Surfaces(RIS),and AI-powered communication services will burden network operators with rising infrastructure costs.Recently,the Open Radio Access Network(O-RAN)has been introduced as a solution for growing financial and operational burdens in Beyond 5G(B5G)and 6G networks.O-RAN promotes openness and intelligence to overcome the limitations of traditional RANs.By disaggregating conventional Base Band Units(BBUs)into O-RAN Distributed Units(O-DU)and O-RAN Centralized Units(O-CU),O-RAN offers greater flexibility for upgrades and network automation.However,this openness introduces new security challenges compared to traditional RANs.Many existing studies overlook these security requirements of the O-RAN networks.To gain deeper insights into the O-RAN system and security,this paper first provides an overview of the general O-RAN architecture and its diverse use cases relevant to B5G and 6G applications.We then delve into specifications of O-RAN security threats and requirements,aiming to mitigate security vulnerabilities effectively.By providing a comprehensive understanding of O-RAN architecture,use cases,and security considerations,thisworkserves as a valuable resource for future research in O-RAN and its security.

Requirements ranking based on crowd-sourcing high-end product USs

Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.

Autoantibodies against beta cells to predict early insulin requirements in pediatric patients with clinically diagnosed type 2 diabetes

BACKGROUND Autoimmunity has emerged as a probable disease modifier in patients with clinically diagnosed type 2 diabetes mellitus(T2DM),that is,patients who have insulin resistance,obesity,and other cardiovascular risk factors,suggesting that the presence of glutamic acid decarboxylase(anti-GAD65),islet antigen 2(anti-IA2),and zinc transporter 8(anti-Zn8T)antibodies could have deleterious effects on beta cell function,causing failure and earlier requirement for insulin treatment.AIM To evaluate anti-GAD65,anti-IA2 and anti-Zn8T as predictors of early insulin requirement in adolescents with a clinical diagnosis of T2DM.METHODS This was a case–control study in patients with clinically diagnosed with T2DM(68 cases and 64 controls with and without early insulin dependence respectively),male and female,aged 12–18 years.Somatometry,blood pressure,glucose,insulin,C-peptide,glycated hemoglobin A1c,and lipid profiles were assessed.ELISA was used to measure anti-GAD65,anti-IA2,and anti-Zn8T antibodies.Descriptive statistics,Pearson'sχ2 test,Student's t test,and logistic regression was performed.P<0.05 was considered statistically significant.RESULTS There were 132 patients(53.8%female),with a mean age was 15.9±1.3 years,and there was a disease evolution time of 4.49±0.88 years.The presence of anti-GAD65,anti-IA2,and anti-Zn8T positivity was found in 29.5%,18.2%,and 15.9%,respectively.Dividing the groups by early or no insulin dependence showed that the group with insulin had a higher frequency of antibody positivity:anti-GAD65 odds ratio(OR):2.42(1.112–5.303,P=0.026);anti-IA2:OR:1.55(0.859–2.818,P=0.105);and anti-Zn8T:OR:7.32(2.039–26.279,P=0.002).CONCLUSION Anti-GAD65 positivity was high in our study.Anti-GAD65 and anti-Zn8T positivity showed a significantly depleted beta cell reserve phenotype,leading to an increased risk of early insulin dependence.

Towards Improving the Quality of Requirement and Testing Process in Agile Software Development:An Empirical Study

Software testing is a critical phase due to misconceptions about ambiguities in the requirements during specification,which affect the testing process.Therefore,it is difficult to identify all faults in software.As requirement changes continuously,it increases the irrelevancy and redundancy during testing.Due to these challenges;fault detection capability decreases and there arises a need to improve the testing process,which is based on changes in requirements specification.In this research,we have developed a model to resolve testing challenges through requirement prioritization and prediction in an agile-based environment.The research objective is to identify the most relevant and meaningful requirements through semantic analysis for correct change analysis.Then compute the similarity of requirements through case-based reasoning,which predicted the requirements for reuse and restricted to error-based requirements.Afterward,the apriori algorithm mapped out requirement frequency to select relevant test cases based on frequently reused or not reused test cases to increase the fault detection rate.Furthermore,the proposed model was evaluated by conducting experiments.The results showed that requirement redundancy and irrelevancy improved due to semantic analysis,which correctly predicted the requirements,increasing the fault detection rate and resulting in high user satisfaction.The predicted requirements are mapped into test cases,increasing the fault detection rate after changes to achieve higher user satisfaction.Therefore,the model improves the redundancy and irrelevancy of requirements by more than 90%compared to other clustering methods and the analytical hierarchical process,achieving an 80%fault detection rate at an earlier stage.Hence,it provides guidelines for practitioners and researchers in the modern era.In the future,we will provide the working prototype of this model for proof of concept.

How to implement a knowledge graph completeness assessment with the guidance of user requirements

In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.

Research Progress on Nutritional Requirements of Carp

Carp is a temperate freshwater fish native to Asia,distributed in all regions of the world except Australia and South America.With the improvement of comprehensive and healthy breeding technology of carp,the unit yield has been greatly increased mainly due to the exten-sive use of compound feed.In this study,the nutritional requirements of carp were summarized from the aspects of protein,amino acids,fat,carbohydrate,calcium and phosphorus,vitamins and taurine.This study provides a certain theoretical reference for scientific formula of carp feed.

基于改进IVNSA的RGV/ASR仓储系统出入库调度算法

针对自动化立体仓库(AS/RS)中环形穿梭车(RGV)和空中分拣机器人(ASR)协同调度问题,以最小化运输时间为目标,建立了RGV/ASR仓储系统的出入库问题调度模型,并提出改进变邻域搜索算法(IVNSA)对问题模型进行求解。首先,设计双序列编码方式优化搜索空间;其次,针对任务调度顺序设计全局综合搜索算子,扩大了算法搜索空间,同时受生物体激素调控机制启发,提出一种基于生物体激素调控机制的局部深度搜索算子,提高了算法的局部搜索深度;最后,通过对比实验验证了所提算法的优越性和有效性。

Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

改进A^(*)算法在ASR移动机器人路径规划中的应用

针对传统A^(*)算法在ASR移动机器人路径规划中无用节点多、耗时长的问题,提出了基于自适应场景地图改进A^(*)算法,引入转弯惩罚函数策略、扩展方向与优先级搜索、路径平滑策略等,以规避路径的多余转弯问题。经仿真试验,证实改进A^(*)算法能够减少搜索节点次数及缩短路径长度,提高ASR移动机器人的运行效率,实现最优路径。

Macroscopic Traversable Wormholes: Minimum Requirements

While wormholes are just as good a prediction of Einstein’s theory as black holes, they are subject to severe restrictions from quantum field theory. To allow for the possibility of interstellar travel, a macroscopic wormhole would need to maintain sufficiently low radial tidal forces. It is proposed in this paper that the assumption of zero tidal forces, i.e., the limiting case, is sufficient for overcoming the restrictions from quantum field theory. The feasibility of this approach is subsequently discussed by 1) introducing the additional conditions needed to ensure that the radial tidal forces can indeed be sufficiently low and 2) by viewing traversable wormholes as emergent phenomena, thereby increasing the likelihood of their existence.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

A Study on Aligning Nursing Curriculum with Hospital Clinical Competency Requirements

The purpose of this study is to coordinate the alignment between the nursing curriculum and hospital clinical competencies,identify the reasons for the gaps,evaluate the impact of these gaps on the nursing profession,and propose strategies to bridge these gaps.This study will help strengthen nursing education,improve nursing students’skills,and help students adapt to complex clinical environments.

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

Forecasting on success or failure of software has become an interesting and,in fact,an essential task in the software development industry.In order to explore the latest data on successes and failures,this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework?What human factors contribute to success or failure of a software?What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work?In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors,misinterpretation,and miscommunication of requirements and decision-making processes play their roles in software success forecasting.We discussed a potential relationship between forecasting of software success or failure and the development processes.We noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study,and they were more likely to rate software success forecasting linking to the development processes.Our analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success rate.The results of this empirical study also validated that requirements’misinterpretation and miscommunication were themain causes behind software systems’failure.It has been seen that reliable,relevant,and trustworthy sources of information help in decision-making to predict software systems’success in the software industry.This empirical study highlights a need for other software practitioners to avoid such bias while working on software projects.Future investigation can be performed to identify the other human factors that may impact software systems’success.

ASR抑制下高性能混凝土的长期抗卤水腐蚀性

以中国西北地区高浓度盐碱环境为背景,研究了含潜在碱活性细骨料的大掺量矿物掺合料高性能混凝土(HPC)在Na^(+)-Cl^(-)-SO_(4)^(2-)型卤水中的力学性能和损伤演变.结果表明:在卤水浸泡3650 d时,HPC的相对动弹性模量大于90%,抗腐蚀系数大于1,线性膨胀率小于0.12%;较高的当量碱含量在一定程度上加剧HPC的碱硅酸反应(ASR);引气能够提高HPC的抗卤水腐蚀能力,降低ASR引起的膨胀;采用大掺量矿物掺合料和潜在碱活性细骨料制备的强度等级为C50的HPC,在Na^(+)-Cl^(-)-SO_(4)^(2-)型卤水中具有优良的长期耐久性.

粉煤灰抑制水工混凝土ASR长期暴露试验研究

准确评价粉煤灰抑制水工混凝土ASR的有效性是使用粉煤灰预防水工混凝土ASR的关键。采用基于普通混凝土试验建立的标准混凝土棱柱体法(试件尺寸为75 mm×75 mm×275 mm)的评价粉煤灰抑制水工混凝土ASR的效果,忽略了水工混凝土自身的特点,与实际存在着一定的差异。采用全级配大尺寸棱柱体试件(试件尺寸为300 mm×300 mm×1350 mm)可以真实反映水工混凝土中的ASR作用,客观评价粉煤灰抑制ASR的实际效果。长达12 a的自然环境暴露试验结果表明,用掺35%Ⅰ级粉煤灰可以有效地抑制水工混凝土ASR膨胀变形。

Requirement Engineering for E-Coaching in Higher Education

This paper presents a requirement engineering for developing an e-coaching environment in the higher education sector. This research demonstrates that IT experts encounter challenges in establishing a system that matches a university’s expectations, as they are usually uncertain about its goals and system requirements. The paper illustrates a business goal-focused requirement induction technique, which encompasses demonstrating the business procedures through Business Process Modelling Notation (BPMN), assessing the university goals via the tree diagram, and drawing out the system requirements from the university objectives through UML state diagrams. A case study of supporting the development of a new IT course is used as a case study and applied using BPMN.