Virtual OSCE: Experience and challenges with a large cohort of pharmacy students

In response to the inability to conduct conventional face-to-face objective structured clinical examination (OSCE) due to the COVID-19 lockdown, this study explored options to design virtual OSCE (vOSCE) that meets the objectives and standards of effective competency-based assessment for a large cohort of pharmacy students. The vOSCE required advanced planning of the actual assessment and technical conduct. The development of a master plan consisting of the types of competencies to test, topics and number of cases, and assessment rubrics, guided the team members to develop an adequate OSCE assessment module. Technical aspects included recruitment of examiners, simulated patients (SP), technical support, and a platform for vOSCE. The main challenges were to ensure well-ordered vOSCE and a stable internet connection for examiners, SP, and students. Google Meet was utilised due to its functionality, familiarity, and low internet consumption to all parties involved. Feedback was obtained from stakeholders to improve future OSCE conduct.

Rahman, Mohammad Habibur

Mohammad Habibur Rahman taught social work in two public universities in Bangladesh. He was the founder of a social work program in a science and technology university, the first of its kind in the country. Despite social work being a less familiar academic discipline, especially in a science and technology university, Rahman, a professor of social work, was for the first time appointed as the vice chancellor of the same university. Apart from teaching, he wrote a number of books on social work and social development, community development and community organization, and urbanization and urban social services and also conducted research on the socioeconomic and psychological causes of suicide, rural development and social services in Bangladesh, and urban community development. He presented social work-related papers in national and international conferences and also attended training courses and seminars on social work methods, social welfare policy formulation, and advanced planning in different countries.

Investigation synchronous planning methods efficiency in small-batch make-to-order production

Lack of effective planning methods is one of the reasons for uneven use of production capacity, the occurrence of unplanned downtime and various types of losses. Small-scale make-to-order productions are characterized by weak workplaces specialization, by the versatility of the equipment used with a wide range of used components. They differ in the presence of repeated processing of part at the same workplaces and in occurrence of “a return flow” in a production system. The article discusses the features of planning due to technological specifics in such enterprises and a significant number of applicable incoming nomenclature items. Existing systems of production planning such Manufacturing Execution System and Advanced Planning & Scheduling System are compared, variants of their algorithmic implementation are proposed. The authors investigated the effectiveness of the application of the developed algorithms for different planning levels - interdepartmental and shop, depending of the size of order book and number of technological operations. The analysis of the conducted research allows us to assert that to provide synchronous scheduling in make-to-order small-scale productions it is necessary to apply combined planning approach using APS-and MES-technologies together.

Climate driven spatiotemporal variations in seabird bycatch hotspots and implications for seabird bycatch mitigation

Bycatch in fisheries is a major threat to many seabird species. Understanding and predicting spatiotemporal changes in seabird bycatch from fisheries might be the key to mitigation. Inter-annual spatiotemporal patterns are evident in seabird bycatch of the U.S. Atlantic pelagic longline fishery monitored by the National Marine Fisheries Service Pelagic Observer Program (POP) since 1992. A newly developed fast computing Bayesian approximation method provided the opportunity to use POP data to understand spatiotemporal patterns, including temporal changes in location of seabird bycatch hotspots. A Bayesian model was developed to capture the inherent spatiotemporal structure in seabird bycatch and reduce the bias caused by physical barriers such as coastlines. The model was applied to the logbook data to estimate seabird bycatch for each longline set, and the mid-Atlantic bight and northeast coast were the fishing areas with the highest fleet bycatch estimate. Inter-annual changes in predicted bycatch hotspots were correlated with Gulf Stream meanders, suggesting that predictable patterns in Gulf Stream meanders could enable advanced planning of fishing fleet schedules and areas of operation. The greater the Gulf Stream North Wall index, the more northerly the seabird bycatch hotspot two years later. A simulation study suggested that switching fishing fleets from the hindcasted actual bycatch hotspot to neighboring areas and/or different periods could be an efficient strategy to decrease seabird bycatch while largely maintaining fishers’ benefit.

Building Cultural Heritage Resilience through Remote Sensing: An Integrated Approach Using Multi-Temporal Site Monitoring, Datafication, and Web-GL Visualization

In the American West, wildfires and earthquakes are increasingly threatening the archaeological, historical, and tribal resources that define the collective identity and connection with the past for millions of Americans. The loss of said resources diminishes societal understanding of the role cultural heritage plays in shaping our present and future. This paper examines the viability of employing stationary and SLAM-based terrestrial laser scanning, close-range photogrammetry, automated surface change detection, GIS, and WebGL visualization techniques to enhance the preservation of cultural resources in California. Our datafication approach combines multi-temporal remote sensing monitoring of historic features with legacy data and collaborative visualization to document and evaluate how environmental threats affect built heritage. We tested our methodology in response to recent environmental threats from wildfire and earthquakes at Bodie, an iconic Gold Rush-era boom town located on the California and Nevada border. Our multi-scale results show that the proposed approach effectively integrates highly accurate 3D snapshots of Bodie’s historic buildings before/after disturbance, or post-restoration, with surface change detection and online collaborative visualization of 3D geospatial data to monitor and preserve important cultural resources at the site. This study concludes that the proposed workflow enhances the monitoring of at-risk California’s cultural heritage and makes a call to action to employ remote sensing as a pathway to advanced planning.

Application of the Dsr - Design Science Research method for the development of an APS - Advanced Planning and Scheduling software

The APS Advanced Planning System is a tool that brings competitive advantages in the optimization and manufacturing planning, allowing the efficient use of human and material resources, and in logistical integration, covering all production cycles. These points are fundamental in the manufacturing industry and represent a field of improvement opportunities. This work addresses the use of the Design Science Research methodology in the development of an advanced production and scheduling system, suggesting some improvements such as flexibility, reduction of human and other systems dependencies, and also the application of intelligent algorithms, aligned with the latest advances related to industry 4.0 and digital transformation.,

Multiple peg-in-hole compliant assembly based on a learning-accelerated deep deterministic policy gradient strategy

Purpose As complex analysis of contact models is required in the traditional assembly strategy, it is still a challenge for a robot to complete the multiple peg-in-hole assembly tasks autonomously. This paper aims to enable the robot to complete the assembly tasks autonomously and more efficiently, with the strategies learned by reinforcement learning (RL), a learning-accelerated deep deterministic policy gradient (LADDPG) algorithm is proposed. Design/methodology/approach The multiple peg-in-hole assembly strategy is designed in two modules: an advanced planning module and a bottom control module. The advanced module is completed by the LADDPG agent, which is used to derive advanced commands based on geometric and environmental constraints, that is, the desired contact force. The bottom-level control module will drive the robot to complete the compliant assembly task through the adaptive impedance algorithm according to the command set issued by the advanced module. In addition, a set of safety assurance mechanisms is developed to safely train a collaborative robot to complete autonomous learning. Findings The method can complete the assembly tasks well through RL, and it can realize satisfactory compliance of the robot to the environment. Compared with the original DDPG algorithm, the average values of the instantaneous maximum contact force and contact torque during the assembly process are reduced by approximately 38% and 74%, respectively. Practical implications The entire algorithm can also be applied to other robots and the assembly strategy can be applied in the field of the automatic assembly. Originality/value A compliant assembly strategy based on the LADDPG algorithm is proposed to complete the automated multiple peg-in-hole assembly tasks.

An Innovative VMAT Technique for Left-sided Breast Cancer Patients With Postmastectomy Radiotherapy (PMRT) Evaluated by Ratio of Heart Volume in Tangent Line (RHVTL)

For patients with left-sided breast cancer (LBC), postmastectomy radiotherapy (PMRT) has been shown to improve the overall survival and many advanced planning techniques was adopted in PMRT. We aim to use an innovative VMAT technique to enhance the conformity of PTV and reduce the scattering dose of surrounding OARs, thereby reducing the long-term toxicity of the heart as well as ipsilateral lung (IL). The study further analyzes the more appropriate treatment planning techniques for personalized LBC patients with PMRT. 35 LBC patients were retrospectively selected undergoing PMRT. The PTV included lymph nodes, chest walls, excluding internal mammary nodes, where 95% of PTV receiving the prescription dose of 50Gy (2Gy/fraction) with three different techniques, VMAT, IMRT, Hybrid VMAT. Furthermore, the ratio of Heart Volume in Tangent line and heart volume (RHVTL) was proposed to evaluate the relative antonymy position between patient's heart and PTV, which hypothetically represents the complexity of treatment planning. The data from this study showed that for LBC patients undergoing PMRT, the CI from VMAT was 0.85 (IMRT and H-VMAT were 0.77 and 0.83), the heart D mean was 502.9cGy (IMRT and H-VMAT were 675.6cGy and 687cGy) and the V20 of IL was 21.3 as the lowest of the three techniques, but the dose of the contralateral breast (CB) and contralateral lung increased noticeably. In H-VMAT and IMRT, the mean heart dose was significantly related to RHVTL, with R-values of 0.911 and 0.892 respectively, while the values in VMAT was 0.613, thus the VMAT technique was relatively unaffected by the difficulty of treatment plan. For RHVTL values exceed than 0.06, the mean heart dose under VMAT technique raised by 98.7cGy compared to the RHVTL value of less than 0.06, but H-VMAT and IMRT increased by 233cGy and 261.58cGy individually. This study illustrates that separated fields and adjacent fields in VMAT technique obtained the optimal conformality and lowest doses of heart in three techniques for LBC with PMRT. Thus, based on the results of our preliminary study, the VMAT technique is highly recommended when RHVTL is exceeded 0.06.

Hospital Preparedness, Mitigation, and Response to Hurricane Harvey in Harris County, Texas

Objective: This case study documents Harris County hospitals’ flood preparedness and mitigation efforts before Hurricane Harvey, their collective response experience during Hurricane Harvey, and their lessons learned in the storm’s aftermath. Methods: The case study was constructed using a survey of hospital emergency managers, semi-structured interviews with local agencies involved in public health, emergency management, and health care, and an analysis of news reports and other documents from a variety of government agencies, local organizations, and hospitals themselves. Results: Harris County hospitals learned their most valuable lessons through their direct and repeated experience with flooding over the years, leading to improved preparedness before Hurricane Harvey. Hospital emergency response successes included infrastructure improvements, staff resilience, advanced planning, and pre-established collaboration. However, hospitals still experienced challenges with staff burnout, roadway flooding, and patient evacuation. Conclusions: Although the current state of hospital flood preparedness and mitigation is rather advanced and mature, it is advisable that Harris County takes steps to strengthen emergency management efforts in hospitals with fewer financial and staffing resources and less direct flood experience.

Present and Future Spinal Robotic and Enabling Technologies

Enabling technologies include surgical planning software, computer-assisted navigation, intraoperative three-dimensional (3D) imaging, and robotic systems. Presently, these technologies are in various stages of refinement. Spinal robots in particular are currently limited to the positioning of an alignment guide for pedicle screw placement. Current generation spinal robots, therefore, play a more limited role in spinal surgery. In contrast to spinal robots, intraoperative imaging technology has been developed further, to a stage that allows accurate 3D spinal image acquisition that can be readily utilized for spinal navigation. The integration of these various technologies has the potential to maximize the safety, consistency, reliability, and efficacy of surgical procedures. To that end, the trend for manufacturers is to incorporate various enabling technologies into the spinal robotic systems. In the near-term, it is expected that integration of more advanced planning software and navigation will result in wider applicability and value. In the long-term, there are a variety of enabling technologies such as augmented reality that may be a component of spinal robots. This article reviews the features of currently available spinal robots and discusses the likely future advancements of robotic platforms in the near- and long-term.