Outbreak response can be viewed as a project for which the window of opportunity for planning is often quite limited. Therefore, regular evaluation for sharing the lessons learned is crucial, especially in the cases of national and global crises. As one of the major global concerns, the novel coronavirus, also known as COVID-19, has infected and killed many people in several countries worldwide. Hence, it is worth analyzing the performance of different countries in this regard. In this paper, the confirmed Case Fatality Rate (cCFR), and the confirmed Case Recovery Rate (cCRR) are considered as the main performance criteria, and the data are analyzed utilizing statistical confidence intervals (CIs) implemented in Python. The results identify the regions with high cCFR and low cCRR, as well as the regions with low cCFR and high cCRR. Finally, it is suggested to systematically transfer the knowledge and lessons learned from the high performing countries to where such information and knowledge is needed.

Climate change creates considerable issues for watershed management, especially in areas prone to erosion and sediment production. The purpose of this study was to examine and map the sediment yield response to future climatic scenarios in the Songwe Watershed. The Soil and Water Assessment Tool (SWAT), which is integrated with Regional Climate Models (RCM) under Representative Concentration Pathways (RCPs) 8.5, was used to evaluate the possible consequences on sediment transport dynamics within the watershed. The simulated results from the four Regional Climate Models (CCLM4, HIRAM5, RACMO22T, and RCA4 RCMs) showed that sediment yields increased for future estimates from 2011 to 2100 under RCP 8.5, owing mostly to increased rainfall and altered hydrological cycles. The results reveal that the average annual sediment yield could increase by 30-50% under RCP 8.5. scenario. Sediment yield mapping highlights crucial hotspots, notably in steep terrain and places with minimal vegetation cover, that are extremely susceptible to erosion, providing useful insights for focused intervention measures. The study emphasized the need for adaptive watershed management methods to counteract the negative effects of climate change on soil erosion and sediment crusade.

Considering accurate constitutive models is of the utmost importance to capture mechanical response of soft tissue and biomedical materials under physiological loading conditions. This paper investigated the behaviour of porcine myocardium of passive rested hearts. This was investigated by applying biaxial loads on the myocardium. The main objective of this research was to investigate the cardiac mechanics of various regions in the healthy passive of a porcine. The biaxial mechanical properties of myocardial tissue samples were captured using a biaxial testing system. The porcine heart was divided into three regions, namely: left ventricle (LV), septum and right ventricle (RV). In these regions, 18×18 mm2 equal samples were cut from six porcine passive hearts. For the LV sample, biaxial elastic modulus in the fibre direction is 33.3% larger than in the cross fibre direction. For the mid-wall sample, biaxial elastic modulus in the fibre direction is 18.8% larger than in the cross fibre direction. For the RV sample, biaxial elastic modulus in the fibre direction is 33.3% larger than in the cross fibre direction. It was concluded that the cardiac mechanics of LV, Septum and RV exhibit different mechanical behaviour. The mechanical behaviour exhibited by various regions (LV, Septum and RV) in the healthy porcine heart differs considerably. To develop adequate computational models, these data could be utilized to estimate the material parameters of the myocardium.

Nowadays, with the increasing number of projects in organizations, managers are enthusiastic about managing and controlling projects, and as projects become more complex and cause unforeseen risks, project management becomes even more critical. Using the earned value management method to control the current status of projects, and predicting the future status of projects has had many advantages. Representing the status of the project, and predicting the project performance by various indicators are some features of this method. As these indicators are deterministic, the risk of the prediction increases when the number of risks goes up in a project. Therefore, statistical methods can be employed to estimate the statistical distribution of risks and notably boost predicting accuracy. The purpose of this paper is to present a method for predicting project duration and cost of the project and selecting the best action plan. Control charts are used along with the earned value management method to increase accuracy. This model also provides the possibility of selecting the best action plan to improve project performance. Moreover, this method can be applied in each project phase separately. Finally, a case study is used to investigate the validity of the proposed method.

In this study, an integrated approach is presented for analyzing the impact of resilience engineering and ergonomics factors in aerospace supply chain using data envelopment analysis (DEA). The proposed approach selects the preferred supplier by considering traditional supply chain factors as well as resilience engineering and ergonomics factors. Also, the relevant performance efficiency of each decision making unit is calculated. The case study of this paper is the supply chain of real commercial airlines. Thus, the aerospace standards as well as resilience and ergonomics factors are considered to be modeled by the mathematical programming approach. 22 suppliers are evaluated by analyzing inputs and outputs through data envelopment analysis, and each supplier is considered as a decision making unit (DMU). In this study, the most effective factors are identified as “reliability”, “Human resource management”, “supplier’s delay” and “availability”. Also, “lead time” shows the highest potential for improvement. This study helps decision makers identify the weaknesses of their supply chain management to establish a performance improvement plan in aerospace industry.

This research paper aims to investigate the effect of Internet of Things (IoT) on Search Engine Optimization (SEO) by considering the mediating role of user behavior on this effect. A conceptual research model was developed in accordance with the UTAUT and based on a thorough analysis of extant research. A self-handled questionnaire survey was administered to a purposely selected sample of employees working in telecommunications companies in Jordan. A dataset of 131 usable questionnaires were subjected to data analysis using SmartPLS 3.0. The main findings showed that IoT affected SEO and user behavior. User behavior was also found to be significantly predicted by IoT and to mediate its effect on SEO. The results revealed the significance of SEO as an emerging effective electronic marketing tool in encouraging consumers' adoption of new technologies. The paper ends with a discussion of findings, conclusions, and areas for future research.

The advent of Industry 4.0 has revolutionized manufacturing, integrating advanced technologies to enhance efficiency and sustainability. However, the transition to sustainable green manufacturing presents numerous challenges. This paper analyzes these challenges using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). By incorporating expert opinions and fuzzy logic, various obstacles are evaluated and prioritized in the implementation of green manufacturing practices in the context of Industry 4.0. The analysis reveals that market uncertainty in the economic landscape ranks as the top challenge, followed by high costs of implementation, maintenance, security, and integration. Uncertain benefits and trade-offs are also found as significant barriers. Key factors include the need for substantial investments, cybersecurity concerns, integration difficulties, and the complexities of predicting returns on investment. From the study, it is also evident that the impact of Industry 4.0 on supply chains and emissions from Electronics manufacturing is also a critical issue. The study provides actionable insights and strategic recommendations for policymakers and industry leaders to facilitate the adoption of sustainable green manufacturing practices in the era of Industry 4.0.

Distinguishing and diminishing risks in today’s projects are crucial for project success. Almost every project is facing several risks throughout the project timeline. Construction projects in Finland are also facing project risks due to the complexity of the project. To minimize the impact of risks, an effective risk management approach must be incorporated into every project which also includes the effectiveness and measurement of its performance. Managing the risks is an important job but measuring the RM performance is crucial. Thus, the objective of this study is to analyze the risk management (RM) and risk management performance measurement (RMPM) through an indepth empirical analysis of two complex construction projects of Finland. To achieve the objective, a qualitative case study is followed by the authors of this article to identify the RM processes, major and minor risks of the projects, RM strategies to mitigate them and RM performance measurement strategies. Overall, this article provides a comparative analysis of RM and RMPM for construction projects and it can be used as a basis for further research into RM perspective in complex construction projects.

The linear elastic analysis of homogeneous, isotropic cracked bodies started in the 1900s. The existence of three dimensional corner point effects in the vicinity of a corner point where a crack front intersects a free surface was investigated in the late 1970s. An approximate solution by Bažant and Estenssoro explained some features of corner point effects but there were various paradoxes and inconsistencies. Results derived from finite element models showed that the analysis is incomplete. The stress field in the vicinity of a corner point appears to be the sum of two different singularities (i.e. stress intensity factors and corner point singularities). In this paper some recent results for the corner point singularities under in and out of plane loadings is reviewed and discussed.

Many entrepreneurs use different ways to offer credit to enhance long term profit as well as relations with their customers. Order-size dependent credit period is one of them that encourage customers to order large lots to grab more credits in payments. Since display of items play positive role in boosting demand, stock dependent demand is assumed in the proposed model. Ordering large lots can create space issue so the proposed model presents a rented warehouse along with owned one. Rented warehouse is used only when owned warehouse is utilized, completely. Here we propose an integrated inventory model with capacity utilization dependent holding cost to optimize joint profit of supplier and retailer. An algorithm is developed to determine the optimal replenishment policies in order to enhance total profit of supply chain under different ordering schemes. Total joint profit for supplier and retailer is optimized using MATLAB 2015. Numerical examples are presented to illustrate the solution procedure and the results. Sensitivity analysis for some key parameters is carried out to demonstrate the influence of different parameters on over-all profit and cycle time. The proposed model is applicable to fast moving consumer goods (FMCG) and home textile industry.