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Predicting Drug Resistance in Gastric Cancer with Mutation in the Human Epidermal Growth Factor Receptor 2 (HER2) And Machine Learning Technique 通过人表皮生长因子受体 2(HER2)突变和机器学习技术预测胃癌的耐药性
Q1 Engineering Pub Date : 2024-05-15 DOI: 10.52783/pst.391
Elham Soltanian
Gastric cancer with mutations in the human epidermal growth factor receptor (HER2) can be regarded as one of the leading causes of cancer mortality in the world. Targeted tyrosine kinase inhibitors (TKIs) developed against HER2 yielded optimistic results in improving patients' survival rates and life quality. Nevertheless, drug resistance can influence the critical supportive documents of treatment plans and decrease the treatment effectiveness after about one year. Predicting the efficacy of HER2-TKI drugs or therapies for patients with HER2-mutated gastric cancer is a critical research field. In the present study, a personalized drug response prediction model based on molecular dynamics simulations and machine learning is presented to predict response to first-generation drugs approved by the Ministry of Health in patients with gastric cancer. In the molecular dynamics simulation, the patient's mutation status is considered. The patient's unique mutation status was modeled using molecular dynamics simulations to extract geometric features at the molecular level.Furthermore, additional clinical features are incorporated into the machine learning model to predict drug response. The complete features encompass demographic and clinical characteristics, geometrical properties of the drug-target binding site, and binding free energy (RBFE) of the drug-target complex from molecular dynamics simulations. Drug response prediction utilizes the XGBoost classifier, which achieved leading-edge performance for a 4-level drug response prediction task (PDRP) with 97.5% accuracy, 93% sensitivity, 96.5% specificity, and 94% F1 score.The present research has demonstrated that modeling the binding cavity geometry, in tandem with the binding free energy, can effectively predict drug response. Interestingly, the clinical information, while significant, did not significantly influence the model's performance. This exciting finding opens up new avenues for testing the proposed model on various types of cancers, potentially revolutionizing drug development strategies.DOI: https://doi.org/10.52783/pst.391
人类表皮生长因子受体(HER2)发生突变的胃癌可被视为全球癌症死亡的主要原因之一。针对 HER2 开发的靶向酪氨酸激酶抑制剂(TKIs)在提高患者生存率和生活质量方面取得了令人乐观的结果。然而,耐药性会影响治疗计划的关键支持文件,并在大约一年后降低治疗效果。预测HER2-TKI药物或疗法对HER2突变胃癌患者的疗效是一个关键的研究领域。本研究提出了一种基于分子动力学模拟和机器学习的个性化药物反应预测模型,用于预测胃癌患者对卫生部批准的第一代药物的反应。在分子动力学模拟中,考虑了患者的突变状态。利用分子动力学模拟对患者独特的突变状态进行建模,以提取分子水平的几何特征。完整的特征包括人口统计学和临床特征、药物-靶点结合位点的几何特性以及分子动力学模拟中药物-靶点复合物的结合自由能(RBFE)。药物反应预测使用了 XGBoost 分类器,该分类器在 4 级药物反应预测任务(PDRP)中取得了领先的性能,准确率达 97.5%,灵敏度达 93%,特异性达 96.5%,F1 得分达 94%。有趣的是,临床信息虽然重要,但对模型的性能影响不大。这一令人兴奋的发现为在各种类型的癌症上测试所提出的模型开辟了新的途径,有可能彻底改变药物开发策略。DOI: https://doi.org/10.52783/pst.391
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引用次数: 0
Botnet detection based on Markov chain and Fuzzy rough set 基于马尔可夫链和模糊粗糙集的僵尸网络检测
Q1 Engineering Pub Date : 2024-05-15 DOI: 10.52783/pst.390
Aziz Ezzatneshan
Botnets now make up a wide range of cyber-attacks, which are a network of infected computers connected to the Internet, with remote control. So far, a lot of research has been done in this field, the proposed methods are based on the signatures of discovered botnets, anomalies, traffic behavior, and addresses. Each method has both advantages and disadvantages. This research proposes a structure for performing identification operations, which is presented in this research based on the Markov chain and is based on behavioral analysis. A disadvantage of the past methods is the inability to receive network information at a very high speed. In this research, it has tried using a solution to receive traffic at a very high speed of about 40 Gbps and analyze it. To be able to perform the analysis with a lower overhead. The proposed method can investigate the behavior of botnets by examining the area of behavior better than the previous solutions, and as a result, during the solutions used by botnets to hide their behavior, it can counter and identify suspicious flows. The accuracy of the proposed method was found to be 96.170%.DOI: https://doi.org/10.52783/pst.390
僵尸网络是由连接到互联网的受感染计算机组成的网络,具有远程控制功能。迄今为止,这一领域已经开展了大量研究,提出的方法都是基于已发现的僵尸网络的特征、异常情况、流量行为和地址。每种方法都各有利弊。本研究提出了一种执行识别操作的结构,该结构基于马尔可夫链,并以行为分析为基础。以往方法的缺点是无法以极高的速度接收网络信息。本研究尝试使用一种解决方案,以大约 40 Gbps 的极高速度接收流量并进行分析。为了能够以较低的开销进行分析。与之前的解决方案相比,所提出的方法能更好地通过检查行为区域来调查僵尸网络的行为,因此,在僵尸网络用来隐藏其行为的解决方案中,它能反击和识别可疑流量。该方法的准确率为 96.170%。DOI: https://doi.org/10.52783/pst.390
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引用次数: 0
Light Weight Concurrent Scheduling of Mobile Sink routing protocol towards Minimization of Propagation Delay against Spatial and Temporal Uncertainties of Cluster based Wireless Sensor Network 移动 Sink 路由协议的轻量级并发调度,针对基于集群的无线传感器网络的空间和时间不确定性实现传播延迟最小化
Q1 Engineering Pub Date : 2024-05-15 DOI: 10.52783/pst.387
Manjula G. Hegde, Dr. E. Kavitha, Professor and Head Research Supervisor
                 Wireless Sensor Network highly exposed to certain security attacks due to various uncertainties of the network which lead to node compromise.  Hence considerable attention has been made by researcher during scheduling of the mobile sink to data collection of sensed information from the sensor nodes. Many secure data aggregation mechanism has been proposed to withstand the network against these kind of attack. Despite of many advantageous, those architectures will lead to several limitations such as large propagation delay and high energy consumption and spatial and temporal uncertainties. In order to mitigate those challenges, Light Weight Concurrent Scheduling of Mobile Sink routing protocol towards Minimization of Propagation Delay against Spatial and Temporal Uncertainties of Wireless Sensor Network is designed. It should be capable achieving energy efficiency and collision avoidance due to uncertainty in transmission and reception. Proposed model eliminates the packet collision and poor channel utilization challenges. Initially, node is partitioned and cluster head is selected based on the highest energy density of the node in the particular location.  Employing Full duplex channel easily examines the spatial and temporal characteristic of the node through utilization cache information of routing table. It further helps to build the light weight scheme with behavioral strategies of the nodes for secure propagation of the sensed data to the mobile sink. Light weight scheme deployed in mobile sinks estimate the node trustworthiness and simultaneously collects the secure aggregated data packets of the sensor node through cluster head against dynamic time slots concurrently .Comparing with traditional secure routing architecture, simulation results demonstrates that proposed architecture can reduce the propagation delay against various uncertainties and maximizes the life time of the network on increasing the networking performances with respect to packet delivery ratio, throughput and propagation delay. Finally proposed model obtains the cooperative communication of sensor node information to the base station through mobile sink on heterogeneous wireless sensor network environment. DOI: https://doi.org/10.52783/pst.387
由于网络的各种不确定性导致节点受损,无线传感器网络极易受到某些安全攻击。 因此,研究人员在调度移动汇收集传感器节点传感信息的过程中给予了极大关注。人们提出了许多安全数据聚合机制,以抵御此类网络攻击。尽管这些架构有很多优点,但也存在一些局限性,如传播延迟大、能耗高、时空不确定性大等。为了缓解这些挑战,我们设计了轻量级并发调度移动 Sink 路由协议,以最小化无线传感器网络在空间和时间不确定性条件下的传播延迟。该协议应能实现能源效率,并避免因传输和接收的不确定性而造成的碰撞。所提出的模型消除了数据包碰撞和信道利用率低的难题。最初,根据节点在特定位置的最高能量密度对节点进行分区并选择簇头。 采用全双工信道可以通过路由表的利用缓存信息轻松检查节点的空间和时间特性。它还有助于利用节点的行为策略建立轻量级方案,以便将感知到的数据安全地传播到移动汇。与传统的安全路由架构相比,仿真结果表明,所提出的架构可以减少各种不确定性带来的传播延迟,并最大限度地延长网络的使用寿命,同时提高数据包交付率、吞吐量和传播延迟等方面的网络性能。最后,所提出的模型在异构无线传感器网络环境中通过移动水槽实现了传感器节点信息与基站的合作通信。DOI: https://doi.org/10.52783/pst.387
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引用次数: 0
Design and Development of a Hybrid Cooperative- Based Routing Protocol avoiding the void nodes in WSNs using the Concepts of Minimum Energy Consumption with good Data Security features 设计和开发一种基于合作的混合路由协议,利用最小能耗概念避免 WSN 中的空节点,并具有良好的数据安全特性
Q1 Engineering Pub Date : 2024-05-11 DOI: 10.52783/pst.374
Manjula G. Hegde, Dr.E.Kavitha
This paper presents a novel cooperative-based routing protocol designed for underwater Wireless Sensor Network Cloud Applications (uWSNCA). The protocol aims to minimize energy consumption by avoiding void nodes, which are areas without sensor coverage. The proposed approach consists of two main steps: first, avoiding void nodes using an adaptive hop-by-hop vector method, and second, applying a cooperative rule-based adaptive hop-by-hop vector method to create a hybrid algorithm that is more efficient than existing approaches, such as the watch-dog protocol. The research focuses on developing an energy-efficient distributed cooperative routing protocol for wireless sensor networks, specifically tailored for cooperation-based uWSNCA. This is achieved by preventing data packets from being forwarded through void nodes.  The proposed routing protocol utilizes cooperation-based adaptive hop-by-hop vector-based forwarding concepts, where sensor nodes forward data packets in a multi-hop fashion within a virtual pipeline. In the developed algorithm for the underwater WSN cloud application, data packets are forwarded in a multi-hop manner using a virtual pipelining mechanism.Nodes outside the virtual pipeline do not forward data packets, thereby reducing flooding in the cooperative WSN. To prevent data packets from being forwarded towards void areas in the WSN, 2-hop information is used at each hop. This approach improves the performance of the wireless sensor network in terms of various performance criteria compared to existing routing protocols.  The simulation tool NS2 is used to observe the simulation results of the energy packets being transferred from the source to the sink. The simulation results demonstrate the effectiveness of the proposed methodology. Overall, this paper contributes to the field of underwater WSNs by introducing a novel routing protocol that improves energy efficiency and performance for cloud applications.
本文介绍了一种为水下无线传感器网络云应用(uWSNCA)设计的基于合作的新型路由协议。该协议旨在通过避免无效节点(即没有传感器覆盖的区域)来最大限度地降低能耗。提出的方法包括两个主要步骤:首先,使用自适应逐跳向量方法避开无效节点;其次,应用基于合作规则的自适应逐跳向量方法创建一种混合算法,该算法比现有方法(如看门狗协议)更高效。研究重点是为无线传感器网络开发一种高能效的分布式合作路由协议,特别适合基于合作的 uWSNCA。这是通过防止数据包通过无效节点转发来实现的。 提出的路由协议利用基于合作的自适应逐跳向量转发概念,传感器节点在虚拟管道内以多跳方式转发数据包。在针对水下 WSN 云应用开发的算法中,数据包是利用虚拟管道机制以多跳方式转发的。为了防止数据包被转发到 WSN 中的空白区域,在每一跳都使用了 2 跳信息。与现有的路由协议相比,这种方法在各种性能标准方面提高了无线传感器网络的性能。 仿真工具 NS2 用于观察能量包从源传输到汇的仿真结果。仿真结果证明了所提方法的有效性。总之,本文通过引入一种新型路由协议,提高了云应用的能效和性能,为水下 WSN 领域做出了贡献。
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引用次数: 0
Detect Gear Fault in Wind Turbine Gearbox based on Time Synchornous Averaging Without Phase Signal. 基于无相位信号的时间同步平均法检测风力涡轮机齿轮箱中的齿轮故障。
Q1 Engineering Pub Date : 2024-05-03 DOI: 10.52783/pst.352
Nguyen Trong, Du, Nguyen Huu, Nguyen Cuong, Van Minh, Hoang Nguyen, Phong Dien
Wind energy is increasingly recognized as a worldwide sustainable and environmentally friendly power source. Nevertheless, an important barrier to further investment in wind energy is the large rate of failure that occurs to turbines. The gearbox, a crucial component, has a major effect on the performance of wind turbines. It consists of complex planetary and cylindrical gear systems, making it prone to failure and causing major defects in wind turbines. Therefore, there is an urgent need to minimize downtime and improve productivity in wind turbine gearbox operations. Recent decades have witnessed growing interest in fault diagnosis of gearboxes due to their widespread use and industry significance. The time synchronous averaging (TSA) method is widely used as a fundamental approach to detect faults in wind turbine gearboxes from mechanical vibration signals. Usually, applying this method requires a device to measure the vibration phase. Nevertheless, there are certain circumstances where installing a phase-measuring device might pose challenges. For instance, if the gearbox operates, it cannot be paused for installation. Additionally, if the gearboxes are enclosed, it becomes difficult to insert the device. The present paper presents an innovative technical approach to improve the time synchornous averaging method without requiring information about phase vibration. It also evaluates the effectiveness of the proposed method using feature values. An experimental test rig was set up to evaluate the algorithm's effectiveness, simulating different gear faults and load conditions.
风能越来越被认为是一种世界范围内可持续的环保能源。然而,风机故障率高是进一步投资风能的一个重要障碍。齿轮箱是一个关键部件,对风力涡轮机的性能有重大影响。它由复杂的行星和圆柱齿轮系统组成,容易发生故障,导致风力涡轮机出现重大缺陷。因此,迫切需要尽量减少停机时间,提高风力涡轮机齿轮箱运行的生产率。近几十年来,由于齿轮箱的广泛应用和行业重要性,人们对齿轮箱故障诊断的兴趣与日俱增。时间同步平均法(TSA)被广泛用作从机械振动信号中检测风力涡轮机齿轮箱故障的基本方法。通常,应用这种方法需要一个测量振动相位的装置。然而,在某些情况下,安装相位测量装置可能会带来挑战。例如,如果齿轮箱在运行,就不能暂停安装。此外,如果齿轮箱是封闭的,则很难插入装置。本文提出了一种创新的技术方法,在不需要相位振动信息的情况下改进时间同步平均法。本文还利用特征值评估了所提方法的有效性。为评估该算法的有效性,建立了一个实验测试平台,模拟不同的齿轮故障和负载条件。
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引用次数: 0
Next-Generation Protection: Leveraging Federated Learning and Blockchain for Intrusion Detection in Smart Vehicle Network 下一代保护:利用联盟学习和区块链进行智能车联网入侵检测
Q1 Engineering Pub Date : 2024-05-03 DOI: 10.52783/pst.353
J. Malik, Sagheer Abbas, Altaf Hussain, Muhammad Saleem, Rahat Qudsi
Smart Car's era ushers in new challenges, some of which are in the field of information security such as wise cyber-attack prevention. Traditional IDS systems would lose everything in such a dynamic environment with their centralized architectures, and this approach could create single points of failure and privacy issues.  Along with interconnectedness, cyber security becomes an inevitable problem as smart vehicles are incorporated into a daily life. Traditional security mechanisms usually lack scalability and privacy, which brings about the need to develop alter-nate or innovative methods. This research demonstrates a mixed security system that combines both federated learning and blockchain technologies to improve intrusion detection in smart vehicular networks. We evaluated the effectiveness of this framework using four machine learn-ing models as respectively; Support Vector Machine (SVM), Decision Tree, Neural Network, and Random Forest. Empirical results show that SVM had the highest accuracy of both 93.88% in training and 91.84% in validation, which is higher than Decision Tree, Neural Network, and Random Forest models. These findings evidently demonstrate that the federated learning and blockchain are a strong solution for the plausible security of smart vehicle networks; with SVM being employed mostly in complex security scenarios.DOI: https://doi.org/10.52783/pst.353
智能汽车时代带来了新的挑战,其中一些是信息安全领域的挑战,如明智的网络攻击防范。传统的 IDS 系统采用集中式架构,在这样一个动态环境中会失去一切,而且这种方法可能会造成单点故障和隐私问题。 随着智能汽车融入人们的日常生活,网络安全也成为一个不可避免的问题。传统的安全机制通常缺乏可扩展性和私密性,因此需要开发新的或创新的方法。本研究展示了一种混合安全系统,该系统结合了联合学习和区块链技术,以改进智能车辆网络中的入侵检测。我们分别使用支持向量机(SVM)、决策树、神经网络和随机森林四种机器学习模型评估了该框架的有效性。实证结果表明,SVM 的训练准确率和验证准确率分别为 93.88% 和 91.84%,均高于决策树、神经网络和随机森林模型。这些研究结果清楚地表明,联合学习和区块链是智能汽车网络可信安全的有力解决方案;其中 SVM 主要应用于复杂的安全场景。DOI: https://doi.org/10.52783/pst.353
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引用次数: 0
Experimental Evaluation of Mechanical Properties, Micro Structure and Post-Fire Strength of Fiber Reinforced Geopolymer Concrete 纤维增强土工聚合物混凝土力学性能、微观结构和火烧后强度的实验评估
Q1 Engineering Pub Date : 2024-05-02 DOI: 10.52783/pst.349
Abbasali Saffar, Mohammad Ehsanifar, Seyed Mohammad Mirhosseini, Mohammad Javad Taheri
Geopolymer mixtures offer an enhanced alternative to implement an eco-friendly solution in construction industry. These mixtures exhibit similar or better mechanical and structural properties in comprising of cement and can use recycling and by-product materials. Against this background, an eco-friendly advantageous were achieved from the engineers and researchers by using waste materials to replace cement and attention to reduce CO2 emission during its procedure. This study attempted to evaluate compressive and tensile strength, micro structure and post-fire characteristic of the geopolymer mixtures. For this aim, the geopolymer mixtures were exposed to elevated temperature between 200, 500 and 800 0C. Then, the post-fire and mechanical behaviour were investigated. The proposed research supported the slight decrease in the GPC's compressive stress by fibres, and the 1.25% PP fibres displayed the least performance, indicating nearly 13% decrease than the unreinforced mixtures. As exhibited by the post-fire behaviour of mixtures, the GPC's compressive strength increased first for all mixes but in the range of 400 - 800°C it decreased at a higher rate because of the geopolymer matrix-related dehydration. Besides, fiber melting under high temperatures and the thermal reaction procedure related to free water evaporation reduce the mechanical properties under temperatures ranging from 400°C to 800°C.DOI: https://doi.org/10.52783/pst.349
土工聚合物混合物为建筑业提供了一种更好的生态友好型解决方案。与水泥相比,这些混合物具有相似或更好的机械和结构特性,并且可以使用回收材料和副产品。在此背景下,工程师和研究人员通过使用废料替代水泥,实现了生态友好的优势,并注意在使用过程中减少二氧化碳的排放。本研究试图评估土工聚合物混合物的抗压和抗拉强度、微观结构和火灾后特性。为此,将土工聚合物混合物置于 200、500 和 800 摄氏度的高温下。然后,对着火后的机械性能进行了研究。研究结果表明,纤维可使 GPC 的压缩应力略有降低,其中 1.25% 的聚丙烯纤维性能最低,比未增强的混合物降低了近 13%。从混合物着火后的表现来看,所有混合物的 GPC 抗压强度都会首先增加,但在 400 - 800°C 范围内,由于土工聚合物基质脱水,抗压强度的下降率较高。此外,高温下的纤维熔化以及与自由水蒸发有关的热反应过程降低了 400°C 至 800°C 温度范围内的机械性能。DOI: https://doi.org/10.52783/pst.349
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引用次数: 0
The Effect of Electromagnetic Waves of the Terahertz Range on the Frequency of Molecular Oxygen (129.0 Ghz) On the Processes of Lipid Peroxidation in Experimental Animals Under Chronic Stress 太赫兹范围的电磁波对分子氧频率(129.0 Ghz)对慢性应激下实验动物脂质过氧化过程的影响
Q1 Engineering Pub Date : 2024-04-17 DOI: 10.52783/pst.289
Victoria Zaborova Et.al
The aim of this scientific research is to study the effect of electromagnetic waves of the terahertz range on the frequency of molecular oxygen (129.0 GHz) on the processes of lipid peroxidation in experimental animals under chronic stress.Overtraining is a psychological and/or physiological condition that manifests itself as impairment in athletic performance. This condition may be based on prolonged competitive stress and stressful psychological factors that can lead to the activation of lipid peroxidation processes (LPO). Moreover, the activation of the processes of lipoperoxidation is the main pathogenetic link of many socially significant diseases, especially cardiovascular disease. These circumstances require the development of modern and relevant methods of prevention and treatment of post-stress disorders. In the last ten years, a new method has been used to assess the effect of stress on the pro-oxidant activity of blood plasma and the concentration of antioxidants by exposure to electromagnetic radiation. In this paper electromagnetic waves of terahertz range, at frequencies of active cellular metabolites, were used to correct the processes of lipoperoxidation (LPO) changes at chronic stress. The innovative device "Оrbit" was used to emit Terahertz (THz) radiation at frequencies of molecular oxygen 129,0 GHz in fractional mode. From the marked activation of lipid peroxidation processes and inhibition of antioxidant activity of blood, it is possible to observe a partial normalization, in the conditions of long-term immobilization or through cold water swimming of animals (rats), by using THz waves 5 days for 15 minutes; moreover, if the same procedure was applied for 30 minutes, a complete normalization of lipid peroxidation and antioxidant levels in the blood of stressed animals occurred. The study shows the high efficiency and expediency of using the device for terahertz therapy "Orbit" in the correction of altered processes of lipid peroxidation and it encourages future application for humans.DOI: https://doi.org/10.52783/pst.289 
这项科学研究的目的是研究分子氧频率(129.0 GHz)太赫兹范围的电磁波对处于慢性应激状态下的实验动物脂质过氧化过程的影响。过度训练是一种心理和/或生理状况,表现为运动成绩受损。过度训练是一种心理和/或生理状况,表现为运动成绩受损。这种状况可能是由于长期的竞争压力和紧张的心理因素导致脂质过氧化过程(LPO)被激活。此外,脂质过氧化过程的激活是许多社会重大疾病,尤其是心血管疾病的主要致病环节。在这种情况下,需要开发现代的相关方法来预防和治疗应激后紊乱。近十年来,一种新的方法被用于评估压力对血浆促氧化剂活性的影响,以及通过暴露于电磁辐射对抗氧化剂浓度的影响。本文利用太赫兹范围的电磁波,以细胞活性代谢物的频率,对慢性压力下的脂过氧化(LPO)变化过程进行校正。创新装置 "Оrbit "以分数模式发射分子氧频率为 129,0 GHz 的太赫兹(THz)辐射。在动物(大鼠)长期固定或通过冷水游泳的条件下,通过使用太赫兹波 5 天 15 分钟,可以观察到血液中脂质过氧化过程的明显激活和抗氧化活性的抑制部分恢复正常;此外,如果使用同样的程序 30 分钟,受压动物血液中脂质过氧化和抗氧化水平会完全恢复正常。这项研究表明,使用太赫兹治疗设备 "Orbit "在纠正脂质过氧化改变过程中具有高效性和便捷性,并鼓励未来将其应用于人类。DOI: https://doi.org/10.52783/pst.289
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引用次数: 0
Presenting a Systematic Framework of Factors Influencing the Policy of University Governance Transformation 提出大学治理转型政策影响因素的系统框架
Q1 Engineering Pub Date : 2024-04-17 DOI: 10.52783/pst.290
Saeed Mirnejati, Hosein Aslipour, Seyed Mehdi Alvani
Objective: This article uses the ultra-compound method to provide systematic framework of effective factors.Method: Meta-composition method is choosing 470 related articles and research in 2000-2024 from Web of Science citation index. This research is qualitative and interpretive paradigm aiming to discover the characteristics of  development policy governance. Also, in terms of research time, it is cross-sectional.Results: The characteristics of this new approach to transition of governance can be seen in four categories; The role of the state, university, society and the market. Each of these four groups also has parts below.Conclusion: The issues of "power and policy developments, policy processes improvement" and "Information exchange,trust and diverse", the researchers have had more and more different research on issues of "qualitative and quantitative development" and "raising of the student's generation" and have not been studied in different dimensions. On this basis and regarding the importance of policy issues, implementation of policies, future research can pay more attention to the recent two dimensions. The findings of this study can be useful for applying new approaches to improve governance transformation in different policy fields.DOI: https://doi.org/10.52783/pst.290
目的本文采用超复合方法提供有效因素的系统框架:方法:采用元组合方法,从 Web of Science 引文索引中选取 2000-2024 年间的 470 篇相关文章和研究。本研究采用定性和解释范式,旨在发现发展政策治理的特点。同时,在研究时间上,本研究为横断面研究:从国家、大学、社会和市场的作用这四个方面可以看出这种新的治理转型方法的特点。这四类中的每一类也都有以下部分:在 "权力与政策发展、政策流程改进 "和 "信息交流、信任与多样化 "等问题上,研究人员对 "质与量的发展 "和 "学生一代的培养 "等问题的研究越来越多,但并没有从不同的维度进行研究。在此基础上,考虑到政策问题、政策实施的重要性,今后的研究可以更多地关注最近的两个维度。本研究的结论有助于在不同政策领域应用新方法来改善治理转型。DOI: https://doi.org/10.52783/pst.290
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引用次数: 0
Circular Economy Strategies in Supply Chain Management: Towards Zero Waste. 供应链管理中的循环经济战略:实现零废弃物。
Q1 Engineering Pub Date : 2024-04-17 DOI: 10.52783/pst.291
Dr. Elma Sibonghanoy Groenewald, María Teresa Espinosa-Jaramillo, Apeksha Garg, Kartik D Pipalia, Dr. Vijayakumar Umasekar, Dr. Coenrad Adolph, Groenewald
The pursuit of a circular economy has emerged as a viable solution to address the environmental and economic challenges posed by traditional linear production and consumption models. In this context, the integration of circular economy principles within supply chain management has garnered attention as a means to achieve zero waste and enhance sustainability. [1],[2] This paper explores the application of circular economy strategies in supply chain management, focusing on the transition towards zero waste. Through a comprehensive analysis of existing literature, case studies, and best practices, the paper examines key principles, challenges, and opportunities associated with adopting circular economy strategies in supply chains. It highlights the importance of design for circularity, resource optimization, collaboration, and integration across supply chain tiers. Furthermore, the paper discusses the role of stakeholders, policy frameworks, and technological advancements in facilitating the transition to a circular economy. By synthesizing insights from various sources, this paper provides a holistic understanding of the implications and benefits of integrating circular economy strategies in supply chain management. Ultimately, it underscores the importance of businesses embracing sustainability and innovation to create more resilient and efficient supply chains while minimizing environmental impact.
追求循环经济已成为应对传统线性生产和消费模式所带来的环境和经济挑战的可行解 决方案。在此背景下,将循环经济原则融入供应链管理,作为实现零浪费和增强可持续性的一种手段,已引起人们的关注。[1],[2] 本文探讨了循环经济战略在供应链管理中的应用,重点关注向零废弃物的过渡。通过对现有文献、案例研究和最佳实践的综合分析,本文探讨了在供应链中采用循环经济战略的主要原则、挑战和机遇。论文强调了循环设计、资源优化、协作以及供应链各环节整合的重要性。此外,本文还讨论了利益相关者、政策框架和技术进步在促进向循环经济过渡中的作用。通过综合各种来源的观点,本文全面阐述了将循环经济战略纳入供应链管理的意义和好处。最终,它强调了企业拥抱可持续发展和创新的重要性,以创建更具弹性和效率的供应链,同时最大限度地减少对环境的影响。
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