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Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals.

The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently.

The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present.

The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.

Cesspits are the means for each house to dispose of wastewater in the Bani Kinanah District (BKD) of Jordan, which creates severe environmental complications. This research aimed to find a suitable site for a wastewater treatment plant (WWTP) in BKD.

Geographic Information System (GIS)-based multicriteria decision analysis (MCDA) was used for an optimal site selection for a sewage treatment plant. Several datasets were obtained to prepare the maps of the criteria influencing the choice of the most suitable site for the WWTP. The analytic hierarchy process was used to apply the weights for each factor.

Five classes of suitability were generated: 0.23% very high suitability, 8.49% high suitability, 47.12% moderate suitability, 37.67% low suitability and 6.49% very low suitability. According to Analytical Hierarchy Process (AHP) results, the elevations, slope and groundwater depth have high importance; where their weights 21%, 19% and 17%, respectively. The most suitable site for establishing a WWTP was found in the northern part of the study area, where it is characterized by relatively low elevations (−90 to −93 m), low slope (0–2.5 %), distance from groundwater level (47–82 m) and the space is sufficient for building the plant (25328 m², 8861 m² and 8586 m²).

This research is limited by the availability of data.

The research is invaluable for decision makers involved in urban planning.

Wastewater treatment plants are essential for communities with limited resources such as Jordan. It has also profound impacts on the surrounding environment.

From the present study, it can be concluded that GIS is essential in urban utility establishment, like urban domestic wastewater treatment site selection. Although the study area has adequate potential areas for establishing WWTP, further assessment of flood vulnerability, wastewater amount quantification, population growth and urban expansion must be seriously considered before implementation.

Most teacher preparation programs (TPP) provide little instruction on mitigating the stress-related consequences of teaching (Miller and Flint-Stipp, 2019). This study aims to provide empirical support for including a self-care unit in teacher preparation curricula to address the secondary trauma and stressors inherent to the teaching profession (Essential 2; NAPDS, 2021; Sutcher et al., 2019).

This investigation occurred in an elementary TPP at a private southeastern US university and spanned two years, utilizing a mixed methods approach.

Findings suggest that after experiencing a 5-week self-care unit, preservice teachers exhibited a statistically significant increase in well-being and a newfound recognition of the need to prioritize self-care for effective teaching, suggesting its potential effectiveness in reducing burnout and attrition.

While this study provided valuable insights into the implementation and impact of a self-care unit within the context of elementary education majors at a mid-sized private university in the USA, it is essential to acknowledge its limitations. One notable limitation is the relatively homogenous sample, primarily consisting of White female participants.

The implications of this study are critical for teacher education policy and practice, advocating for including self-care curricula to enhance teacher well-being and, by extension, prepare teachers with a skillset to support their career trajectory (Essential 3; NAPDS, 2021).

This recommendation underscores the collaborative efforts between TPPs and partnership schools to implement such initiatives effectively, representing a pivotal step toward better-preparing teachers to manage the demands of their profession while prioritizing their mental health (Essentials 4 & 5; NAPDS, 2021).

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

Higher productivity in the potato value chain in Rwanda requires good quality seed potatoes. The article analyzes how innovations were introduced in the framework of a development project resulting in a partnership between a firm and two educational institutions to produce better seed potatoes, using the Triple Helix approach.

In the Triple Helix model government, academia and the private sector work together to develop and introduce innovations. This led to producing and introducing improved seed potatoes at an affordable price through a public private partnership (PPP). Interviews with experts and a survey of local producers were carried out to identify factors influencing the success of the partnership.

A Service, Training and Innovation Center (STIC) has been created to produce the first clean potato seeds in Africa on a commercial scale, based on cultivation of in vitro potato plantlets and aeroponics to produce mini-tubers. It is called Seed Potato Advancement Centre, an education–enterprise partnership, using these plantlets to produce mini-tubers through aeroponics. Seed multipliers are responsible for the next three stages of seed multiplication. The final product is the certified potato, sold to ware potato farmers. The availability of disease-free seed potatoes in Rwanda gives a boost to the potato value chains and contributes to food security. The partnership was successful because of the support from the government and donors, with the private sector and the extension services helping to implement the innovations effectively.

The limitation is that the number of experts interviewed is limited and the survey did not only deal with potato-related activities. The focus is on one region only, but the most important potato growing area in Rwanda.

STICs function as a tool for cooperation between government, private sector and the knowledge sector to achieve commercial and development goals. They function as a channel for technology transfer. They allow applied research, including agronomic research; information collection; and dissemination, networking, training, organization of outreach activities. The model can be repeated in other sectors and countries.

The paper looks at a PPP in agriculture with educational institutions. Second, the Triple Helix and value chain literature is used to study the introduction and implementation of appropriate innovations, while factors determining the success of the partnership were identified. This concerns the first production of clean seed potatoes in Africa on a commercial scale.

The purpose of this study was to examine how participants experienced and perceived an M.Ed. program that had a school-based design. In particular, the authors sought to understand: (1) how participants experienced being in a school-based cohort and (2) whether and how participants experienced the three designated tenets of the M.Ed. program: teacher inquiry, social justice and student engagement and motivation.

This qualitative study used semi-structured focus group interviews (n = 7) to examine teachers’ perceptions, using a constant comparative method (Corbin & Strauss, 2008) of open coding to analyze the data and determine emergent themes.

The findings indicate the design of this school-based M.Ed. program provided both social and academic benefits including strengthening teachers’ working relationships and their understanding of students outside their own classroom and a transfer from individual learning to organizational benefit. Teachers positively perceived the three tenets that guided the first year of the program, especially the ability to study social justice and student motivation in depth.

This study has implications for teacher education and retention as well as how boundary spanning roles in PDS schools can impact graduate students’ experiences in schools. Given the current teacher shortage concerns, it is important to understand how M.Ed. programs can be designed with teacher needs at the forefront so learning is relevant and rewarding, both to the individual and the school.

While there are many studies that examine the use of cohorts in education, particularly in doctoral programs, few, if any, studies examine a school-based cohort M.Ed. program for practicing teachers. This study also puts a unique spotlight on how boundary-spanning roles can benefit not only teacher candidates but also practicing teachers in their M.Ed. programs.

Medical schools aspire to graduate doctors who are competent in interpreting, conducting and publishing scientific research. Hence, the purpose of the paper is explore the impact of a structured compulsory community-oriented, project-based research program in the undergraduate medical curriculum on medical graduates’ future careers, publications and motivation for scientific research.

An online questionnaire was sent through the Alumni Association of the Arabian Gulf University (AGU) to medical graduates who have valid email addresses, seeking information on their scientific productivity along with demographic and current employment data. Responses were collated and analyzed using a standard statistical software package. The chi-square test and p-value were calculated. P-value <0.05 was considered statistically significant.

Completed forms were received from 91 medical graduates. In this sample, almost a quarter of the respondents have published a research paper out of their undergraduate research project, and about 50% have published at least one paper (as main or co-author) after graduation. Both demographic and medical specialty was not related to the doctor's perception of the benefits they have attained from the compulsory undergraduate research program. However, medical graduates who are at senior levels in their medical careers and those who are employed in secondary healthcare are significantly more likely to publish research papers.

The compulsory community-oriented, project-based research program in AGU has positively contributed to the research productivity of graduates, and it would be worthwhile to include such programs as an integral part of the undergraduate medical curriculum.

Although proactive fault handling plans are widely spread, many unexpected data center outages still occurred. To rescue the jobs from faulty data centers, the authors propose a novel independent job rescheduling strategy for cloud resilience to reschedule the task from the faulty data center to other working-proper cloud data centers, by jointly considering job nature, timeline scenario and overall cloud performance.

A job parsing system and a priority assignment system are developed to identify the eligible time slots for the jobs and prioritize the jobs, respectively. A dynamic job rescheduling algorithm is proposed.

The simulation results show that our proposed approach has better cloud resiliency and load balancing performance than the HEFT series approaches.

This paper contributes to the cloud resilience by developing a novel job prioritizing, task rescheduling and timeline allocation method when facing faults.

The authors designed a science and engineering curricular program that includes design features that promote student interest and motivation and examined teachers' and students' views on meaningfulness, motivation and interest.

The research approach consisted of mixed methods, including content analyses and descriptive statistics.

The curricular program successfully included all four of the US National Academies of Sciences' design features for promoting interest and motivation through scientific investigation and engineering design. During interviews, teachers and students expressed evidence of design features associated with interest and motivation. After experiencing the program, more than 60% of all students scored high on all four science and engineering meaningfulness and interest survey items.

A curricular program that extends science learning through the engineered design of solutions is an innovative approach to foster both conceptual knowledge development and interest and motivation in science and engineering.