Core Requirements Research Articles

Evaluation of the Early Impact of COVID-19 on Physiotherapy Clinical Placement Learning Models and Client Case-Mix

Clinical placements are fundamental to entry-level physiotherapy education and provide an opportunity for students to translate theory into practice within authentic clinical environments. Student success during clinical placement is a core requirement of physiotherapy programs and a critical component of the pathway to graduation, registration, and then employment. The registration of a physiotherapist confirms that as a student, they have met the profession’s rigorous accreditation requirements. COVID-19 has significantly disrupted physiotherapy clinical placements across Australia, with many placements postponed or cancelled in the early public health response. These placement disruptions may preclude students from demonstrating mandatory pre-registration accreditation requirements, ultimately reducing the number of eligible new-graduate physiotherapists. Creating sustainable clinical placements whilst upholding the professional standard of entry level graduates during the pandemic, calls for innovative solutions to monitor student placement experiences. A Clinical Portfolio was implemented to improve monitoring processes and enable dynamic responses to potentially altered student learning experiences as COVID-19 public health measures evolved. In doing so, the aim of this study was to evaluate the impact of COVID-19 on physiotherapy student placements between May and June 2020 through examining client case-mix, demographics and learning model documented in each student’s Clinical Portfolio. These data sets allowed for comparison of learning model and case-mix during the pandemic with previous literature monitoring typical physiotherapy clinical placement experience, and providing support for ensuring the registration of the cohort impacted.

The Role of PD Biomarkers in Biosimilar Development - To Get the Right Answer One Must First Ask the Right Question.

The potential for pharmacodynamic (PD) biomarkers to improve the efficiency of biosimilar product development and regulatory approval formed the premise for the virtual workshop Pharmacodynamic Biomarkers for Biosimilar Development and Approval hosted by the US Food and Drug Administration (FDA) and Duke Margolis, September 2021. Although the possibility of PD biomarkers replacing the to-date routine comparative phase III confirmatory study currently expected by the FDA was discussed, the motivation and feasibility for biosimilar sponsors developing such markers and the regulatory risks entailed largely were not. Even more fundamental is the already established greater comparative value of the pharmacokinetic (PK) study as the most sensitive clinical assay for detecting subtle differences between two products. Consequently, the comparative analytical assessment and the head-to-head PKs will have already answered the core questions as to the biosimilarity of the candidate product to its reference. No further actionable information is obtained with either a PD study or a comparative clinical phase III study even as they may provide some reassurance of what is already known. When a suitable PD biomarker is available for the originator reference product they have already been used for biosimilar development. We must carefully consider the core requirements and timelines inherent in biosimilar development and how they occur in parallel rather than in the series we see for originator products. In order to improve the efficiency of biosimilar development, we need to ask the right questions based on a full understanding of how biosimilars have been developed to date and can be in the future.

Efficient Speed Planning for Autonomous Driving in Dynamic Environment With Interaction Point Model

Safely interacting with other traffic participants is one of the core requirements for autonomous driving, especially in intersections and occlusions. Most existing approaches are designed for particular scenarios and require significant human labor in parameter tuning to be applied to different situations. To solve this problem, we first propose a learning-based Interaction Point Model (IPM), which describes the interaction between agents with the protection time and interaction priority in a unified manner. We further integrate the proposed IPM into a novel planning framework, demonstrating its effectiveness and robustness through comprehensive simulations in highly dynamic environments.

Investigation of Optimum Scale-Up of Media Stirred Mill Using the Discrete Element Method

Media stirred mills have been used in various fields to efficiently produce fine products. The scale-up of such mills is required to increase efficiencies and applications for industrial processes. Despite such circumstances, established scale-up laws remain unavailable, and scale-up has been conducted empirically. This study aims to propose essential requirements for the scale-up of a media stirred mill according to experiments and discrete element method (DEM) simulations. The experimental results were evaluated qualitatively by using particle size distributions of ground products and fitted using grinding kinetic theory as a quantitative evaluation. The grinding performance in the laboratory model was equivalent to the results using the scaled-up model (SU-model) with the modified Froude number, regardless of the rotation speed. DEM simulations identified the main factor that contributed to the agreement. The average collision energy of the media particles was almost identical. To set optimal conditions to fulfill this core requirement, the SU-model operation conditions need to follow the modified Froude number, and the intervals of each arm should be fixed to the same distance. These insights encourage the application of scaled-up media stirred mills.

Characteristics of animal models for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is the causative agent of coronavirus disease 2019 (COVID‐19), the most consequential pandemic of this century, threatening human health and public safety. SARS‐CoV‐2 has been continuously evolving through mutation of its genome and variants of concern have emerged. The World Health Organization R&D Blueprint plan convened a range of expert groups to develop animal models for COVID‐19, a core requirement for the prevention and control of SARS‐CoV‐2 pandemic. The animal model construction techniques developed during the SARS‐CoV and MERS‐CoV pandemics were rapidly deployed and applied in the establishment of COVID‐19 animal models. To date, a large number of animal models for COVID‐19, including mice, hamsters, minks and nonhuman primates, have been established. Infectious diseases produce unique manifestations according to the characteristics of the pathogen and modes of infection. Here we classified animal model resources around the infection route of SARS‐CoV‐2, and summarized the characteristics of the animal models constructed via transnasal, localized, and simulated transmission routes of infection.

Take on transplant: human-centered design of a patient education tool to facilitate informed discussions about lung transplant among people with cystic fibrosis.

Lung transplant (LTx) saves lives in cystic fibrosis (CF). However, many potential candidates express uncertainty about LTx and die before receiving this treatment. CF guidelines recommend LTx education and clinical discussions well before the need for LTx arises, but limited patient resources exist. We engaged people with CF and CF physicians in human-centered design of "Take On Transplant" (TOT), a web-based education tool to prepare patients for LTx discussions. Across 3 phases, needs assessment, design groups, and iterative user testing of TOT, we refined TOT from wireframe prototypes, to an interactive website, to a fully functional intervention ready for clinical trials. Fifty-five people with CF and 105 physicians identified information needs to prepare for LTx discussions. Design groups (n = 14 participants) then established core requirements: didactic education ("Resource Library"), patient narratives ("CF Stories"), frequently asked questions ("FAQ"), and self-assessment to tailor content ("My CF Stage"). Iterative usability testing (n = 39) optimized the design of CF Stories and prototype layout. We then developed the TOT website and demonstrated feasibility and preliminary efficacy of use through 2-week field testing (n = 9). Our human-centered design process provided guidance for educational tools to serve the evolving needs of potential LTx candidates. Our findings support the process of patient deliberation as a foundation for shared decision-making in CF, and inform educational tools that could potentially translate beyond LTx. TOT fills a critical gap in preparing people with CF for shared decision-making about LTx and may serve as a model for educational tools for other preference-sensitive decisions.

“Modern-Age Centaurs”: A Proposal for Case Study Based Integrative Ethics Education in Chemistry

This work is a course proposal for a stronger ethics education component for chemistry undergraduates. We propose that this course should integrate different approaches in ethics with the value-laden and scientifically complex issues that arise in chemistry. Although some programs require that students take some ethics as a core requirement, for many it is just an option among many humanities courses. Alternatively, ethics may arise passively during courses devoted primarily to chemistry. For our proposed course to be maximally effective, we believe it should integrate both ethics and chemistry, inviting students to think about complex real-world problems. This allows students to identify ethical considerations in the context of cases they might encounter as part of their careers in chemistry. It would also provide them with resources to identify the best course of action.

Early Detection of Obstacle to Optimize the Robot Path Planning

Robot path planning is one of the core issues in robotics and its application. Optimizing the route discovery becomes more important while dealing with the robot-based application. This paper proposes the concept of early detection of the obstacle present in the workspace of the robots. To early detect the obstacle, this paper proposes the concept of a snake algorithm along with the traditional path planning algorithms. The contour detection part is merged with the different path planning algorithms to optimize the robot traversing and benefit it in producing good results. Obstacle-free optimized path is one of the core requirements for robots in any application. With the help of path planning algorithms, robots are enabled to derive those paths in a specific environment. The presence of an obstacle makes it difficult for any path planning algorithms to derive a smooth path. The purpose of using the snake algorithm is to detect an obstacle early. This method not only perceives the obstacle but also catches out the complete boundary of the obstacle, it, thus, provides the details of obstacle coordinates to the path planning algorithm. Conceiving the complete periphery of obstacles can have multiple advantages in many application areas. A*, PRM, RRT, and RRT Smooth algorithms are considered along with the snake algorithm to validate our work in three different experimental scenarios: Maze, Random Obstacles, and Dense case. Path length, Time-taken, and Move count are parameters taken to observe the results. The result obtained using the snake algorithm with four path planning algorithms is analyzed and compared in detail with the core A*, PRM, RRT, and RRTS. Finally, the result obtained using the proposed methodology gives some encouraging results and also predicts the exploration of the robot’s path planning for more applications and fields.

First-year nursing students’ digital literacy: A cross-sectional study

Background: The digital world is rapidly changing, and so do the required digital skills. As physical devices and software are adapted to meet new possibilities and demands, individuals’ skills must adapt to technological advancement. Digital literacy is increasingly used in the public discourse, becoming a core requirement of students, academics, patients and healthcare professionals. Assessing nursing students’ digital literacy at the entry-level is vital to ascertain their abilities to use digital technologies. This study aimed to assess basic digital literacy among first-year nursing students at a selected university in South Africa.Methods: This cross-sectional study was conducted from 1st March 2019 to 31st May 2019 at a university in South Africa. The population consisted of 82 nursing students from the first-year students in the 4-year nursing programme. The convenience sampling technique was used to determine the participants of this study, and 76 respondents completed a structured questionnaire. Data were analysed descriptively using the Statistical Package for Social Sciences (SPSS®) software (version 25) from the International Business Machines Corporation (IBM®). A reliability test of the instrument was conducted, and Cronbach Alpha was 0.85.Results: The students’ digital literacy included: (i) basic computer skills — performing basic computer operations, MS Word and PowerPoint; (ii) internet skills — using e-mail, Moodle®, social media platforms, accessibility to the internet; and internet searches (iii) digital device usage — desktop, laptops, tablets and smartphones. Overall, the mean for internet skills was 3.61 (SD = ±0.62), 3.11 (SD = ±0.85) for computer skills, and 3.00 (SD = ±0.47) for digital device usage. Computer skills was positively correlated with internet skills (r = 0.278, p = .012) and computer skills corrected with digital device usage (r = 0.384, p < .001). The overall score for internet skills was higher in the female group than in males, with the mean of 4.00 (SD = ±0.62) and 3.61 (SD = ±0.54), respectively (t74 = -0.405, p = .019). Furthermore, the overall score for digital device usage was higher in the age group of 20 years and above with a mean of 3.19 (SD = ±0.38) than in the age group under 20 with a mean of 2.90 (SD = ±0.48), and those differences were statistically significant (t74 = -2.420, p = .018).Conclusions: An adequate digital literacy at the entry-level of the nursing programme is a foundation and a critical factor to academic success and future use of technology in nursing education and practice. Having adequate digital literacy among nursing students would positively impact their ability to perform electronic documentation, communicate and collaborate, and search for information to support evidence-based practice.

Developing a Quality 4.0 Implementation Framework and Evaluating the Maturity Levels of Industries in Developing Countries

Industry 4.0 implementations integrate people, machines, data, technology, and processes and allow organizations to connect through digitization and cloud-based systems. The purpose of the present research is to realize the need and sustainability of digitization and connectivity within the quality management domain in developing countries, which is now called Quality 4.0. In previous research, several Quality 4.0 frameworks have been proposed. However, most of the frameworks are based on philosophy or require vast resources to implement. Hence, this research work proposes a framework for the implementation of Quality 4.0 in different industries. This framework is based on eleven dimensions that are the core requirements of the Quality 4.0; key variables are evaluated to gauge the maturity of the implementation of the framework. A research instrument is developed based on the variables to acquire the industry data, which are statistically analyzed to determine the maturity of implementation. It was found that scalability, culture, and app development require the most immense attention from industry to completely implement the requirements of Quality 4.0. Finally, recommendations are suggested that address the strengths, weaknesses, opportunities, and threats in transforming traditional quality management systems to the Quality 4.0 framework.

업무상 재해의 요건과 인과관계의 증명책임

The recent Supreme Court en banc decision (2017du45933) maintained the legal principle of the existing precedents of the Supreme Court as they were. That is, the legal principle that workers must prove a proximate causal relation between their duty and the accident in order for an accident to be recognized as an accident on duty in cases related to industrial accident compensation insurance was reconfirmed. However, it is difficult to agree with the conclusion as such. As mentioned by the majority opinion in the judgment above, the main purpose of the enactment of the proviso to Article 37 Paragraph 1 of the Industrial Accident Compensation Insurance Act was to make it clear that a proximate causal relation between the duty and accident is necessary for all types of accidents but since the reason for the revision in the report on the review of the system and wordings of the National Assembly Legislation and Judiciary Committee at the time had the explicit written intent that, in cases where the Corporation proves that there is no proximate causal relation between the duty and the accident, the accident cannot be regarded as an accident on duty in the criteria for recognition of accident on duty, it is clear that the intention of the legislator is to have the Korea Workers' Compensation & welfare Service, not the employee, prove that there is no proximate causal relation between the duty and the accident. This is also the case even when the proviso is analyzed from the position of the legal requirement classification theory for the distribution of burden of proof. In addition, when the purpose of the Industrial Accident Compensation Insurance Act is examined, it can be seen that it is a law to protect people who are engaged in work at the industrial site. Therefore, unilaterally imposing the burden of proof, which is a core requirement for the recognition of accident on duty, does not fit the intent of the industrial accident compensation insurance as a social security system and the purpose of granting the authority to investigate accidents to the Corporation. Therefore, as the four Supreme Court judges argued in this judgment, it is reasonable to have the Korea Workers' Compensation & welfare Service prove the proximate causal relation between the duty and the accident, not the workers.

Basis-Anforderungen einer Fachabteilung für Herzchirurgie.

The evolution and progress in cardiovascular medicine and substantial changes in the German health care system require both a reflection of the principles of patient-centered care in general and an update of the criteria that define a department of cardiac surgery in Germany. This position paper lists the core requirements for a cardiac surgical department with regard to infrastructure, facilities, necessary staff, and standard of care (processes). This standard may be used by hospitals and health care providers to ensure the safety and quality of cardiac surgical departments in Germany.

Deep graph neural network optimized with fertile field algorithm based detection model for uplink multiuser massive multiple‐input and multiple‐output system

AbstractThe core requirements are generated for sixth generation (6G) wireless communication with low‐latency and ultra‐high speeds to increase the count of ultra scale intelligent factors, like smart cars, mobile root users. The advancement of 6G communication can lead the interference exploitation. To manage the exploitation of uplink multiuser massive (UMM), the multiple‐input and multiple‐output (MIMO) is very difficult to detect the mechanisms, particularly, quadrature amplitude modulation (QAM) signals. To overcome these issues, a novel deep graph neural network optimized with fertile field algorithm based detection model (DGNNO‐FFA) is proposed in this article for uplink multiuser massive MIMO System. The proposed DGNNO‐FFA approach minimizes the channel estimation errors under low signal to noise ratio (SNR) with better bit error rate (BER). Finally, the proposed DGNNO‐FFA approach attains 11.02%, 12.22%, and 25.27% lower BER value, 14.55%, 18.66%, and 29.49% higher energy efficiency, 15.59%, 19.06%, and 29.59% lower NMSE, and 15.59%, 19.06%, and 29.59% lower computational complexity compared with other existing approaches, like deep neural network based semi definite relaxation (DNN‐SDR), QR based zero forcing algorithms (QR‐ZF), and QAM based 2‐dimensional double successive projection model (QAM‐2D‐DSP).

Infrastructural Development of Smart Cities as the Background of Digital Transformation of Territorial Units

The Interoperability, continuous data and technology flow are core requirements of a proper smart city. Smart cities take on the characteristics of innovative, competitive and attractive megalopolises, which is strategically important for residents and investors. The aim of the article was to identify the current state and current issues of the Smart City concept implementation in Ukraine in the context of the experience of developed countries. The main methodological tools included the observation, statistical and comparative analysis. The study found that the effective development of digital transformation of territorial units in Ukraine requires focusing on certain factors during the implementation of the Smart City concept. Such factors conditionally include: technology-based infrastructure; environmental comments; constructive level of public transport; progressive city plans; opportunities for citizens to use appropriate resources. It was found reasonable to introduce infrastructural development of smart cities in Ukraine as a foundation of digital transformation of territorial units. Smart Cities were substantiated as an important tool for effective prevention and control of the pandemic without the introduction of restriction policies. A comparative analysis of the practice of Ukraine and developed countries in the implementation of infrastructural development of Smart Cities is a promising area of further research.

The sum of its parts: Analysis of federated byzantine agreement systems

Federated Byzantine Agreement Systems (FBASs) are a fascinating new paradigm in the context of consensus protocols. Originally proposed for powering the Stellar payment network, FBASs can instantiate Byzantine quorum systems without requiring out-of-band agreement on a common set of validators; every node is free to decide for itself with whom it requires agreement. Sybil-resistant and yet energy-efficient consensus protocols can therefore be built upon FBASs, and the “decentrality” possible with the FBAS paradigm might be sufficient to reduce the use of environmentally unsustainable proof-of-work protocols. In this paper, we first demonstrate how the robustness of individual FBASs can be determined, by precisely determining their safety and liveness buffers and therefore enabling a comparison with threshold-based quorum systems. Using simulations and example node configuration strategies, we then empirically investigate the hypothesis that while FBASs can be bootstrapped in a bottom-up fashion from individual preferences, strategic considerations should additionally be applied by node operators in order to arrive at FBASs that are robust and amenable to monitoring. Finally, we investigate the reported “open-membership” property of FBASs. We observe that an often small group of nodes is exclusively relevant for determining liveness buffers and prove that membership in this top tier is conditional on the approval by current top tier nodes if maintaining safety is a core requirement.

Comprehensive evaluation of land reclamation schemes in mining areas based on linguistic intuitionistic fuzzy group decision-making.

Schemes to protect the geological environment and reclaim land are core requirements for an application for mining rights and complying with mining regulations. Mining enterprises must be supervised to ensure they fulfill their obligations. To guide oversight of such schemes and to provide references for their compilation and review, this study evaluates land reclamation schemes in mining areas using a multi-attribute group decision-making method. First, linguistic intuitionistic fuzzy numbers are used to describe the evaluation information. Considering the authority and preferences of experts, methods for determining expert weights in four cases are established. Max-min deviation then determines the attribute weights, and a method for linguistic intuitionistic fuzzy group decision-making is proposed. Finally, the practicability of this method is verified through a comparative analysis of land reclamation schemes for four mining areas in Sichuan Province, China. The results show the proposed method to give simple and effective evaluation, making it reasonably applicable to the compilation and review of land reclamation schemes.

Implementing an interprofessional user-centered design approach to develop a bedside leg exercise device.

Early mobilization is important to improve critically ill patients' outcomes, but barriers to its implementation are common. A suitable in-bed device to exercise patients' legs might facilitate early mobilization. The aim of this study was to develop an in-bed leg press that would facilitate early mobilization and enhance strength training of patients in acute care settings. A user-centered design approach was applied to develop the device. The process was assessed by different instruments: the system usability scale (SUS) questionnaire, the Kano model questionnaire and interviews with end-users. Through several iterations of a user-centered design process, the prototype of an in-bed leg press was developed and tested. The assessment, based on SUS, Kano and interviews, indicates high usability and demonstrates the advantages of a user-centered design process. An interprofessional user-centered design approach was successfully implemented to develop a medical device. The early involvement of end-users resulted in a design that already shows a high degree of production readiness. The resulting device fulfilled all core requirements from a therapeutic point of view and included key features related to its practical use.

Edge computing for Vehicle to Everything: a short review

Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.

Актуальность создания коллаборативной учебной среды в профессиональной подготовке будущих учителей

The importance of this study is linked to the topic of increasing the quality of future teacher professional training by creating a collaborative learning environment. The purpose of this research is to conduct a theoretical analysis of the effectiveness of creating a collaborative learning environment in university and demonstrate its impact on the successful professional activity of future teachers. The paper presents the data of the experimental research in the form of Action Research, conducted among 1st and 2nd year students of pedagogical specialties in the natural sciences (chemistry, biology, physics, computer science). The core requirements of the personality-oriented, activity-based, systemic, environmental, axiological and competence-based approaches form the methodological foundation for building a collaborative learning environment. Students who are immersed in a collaborative learning environment have the opportunity to reflect on the level of formation of their own professional skills, the success of achieving educational goals, and the processes of self-realization, self-development, and self-actualization on a regular basis. This study examines the impact of collaborative learning on students’ communication skills, knowledge quality, assessment of educational achievements, and study time savings. The research findings are linked to the use of Action Research in the educational process, involving students in the process of professional self-improvement. The novelty of the research is characterized by the identification of developmental effect of a collaborative learning environment based on the concept of a zone of actual student professional growth. The practical significance of the research is the development of positive experience in structuring the educational process, with the prospect of applying this experience in future professional activities, such as working with students.

Towards a resource efficient and privacy-preserving framework for campus-wide video analytics-based applications

Video surveillance and analytics solutions based on Artificial Intelligence (AI) are increasingly being deployed across industries, including academia. There are a number of use-cases for campus-wide video analytics applications. Detecting events of interest in real-time and generating alerts is a core requirement for such applications, making them both network and compute intensive. Thus, the underlying framework needs to be resource optimized in terms of latency, compute and storage requirements for a multitude of video applications. Increasingly privacy concerns have been voiced against the pervasive deployment of video analytics-based applications. Thus, protecting the privacy of students and staff in a campus setting shall be a major design consideration for such systems going forward. This paper presents a resource optimized and privacy preserving framework for campus-wide video analytics applications. Several use-cases are presented and early results from the deployment of the proposed framework establish its feasibility and effectiveness.