Virtual Reality for PostCOVID-19 Stroke: A Case Report

COVID-19 has been associated with stroke and neurological complications. The patient was a 59-year-old male presented with sudden left hemiparesis and diplopia due to cavernous sinus thrombosis (CST) on 28/03/2020. The COVID-19 test was positive. Multislice computerized tomography (MSCT) showed ischemic infarction. He underwent surgical sinectomy 9 days after admission. Physiotherapy began for him on August 2020. Our game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and function for stroke. After 6 weeks of VR therapy plus conventional physiotherapy exercises (18 sessions, three times per week, 60 minutes each session), there were significant improvements in Brunnstrom Motor Recovery Stage (from “4” to “5”), Fugl-Meyer Scale score of upper extremity section (from 49 to 54), and Modified Barthel Index (from 15 to 18). There were no adverse effects. This case with stroke post COVID-19 due to the CST showed the usefulness of VR therapy used as an adjunct to conventional physiotherapy in improving affected upper extremity.

Rehabilitation of Contaminated Surface and Groundwater for Selected Sites in the Illawarra and Sydney Regions Utilising Nanotechnology

A comprehensive study was conducted to examine the removal of inorganic contaminants that exist in surface and groundwater in the Illawarra and Sydney regions. The ability of multi-walled carbon nanotubes (MWCNT), as a generation of membrane technology, was examined using a dead-end filtration cell setup. A set of ten compounds were examined in this study that represent the significant inorganic cations and anions commonly found in contaminated surface and groundwater. The performance of MWCNT buckypaper membranes in excluding anions was found to be better than that of its cation exclusion. This phenomenon can be attributed to the Donnan exclusion mechanism (charge repulsion mechanism). Furthermore, the results revealed that phosphate recorded the highest exclusion value reaching 69.2%, whereas the lowest rejection value was for potassium where no removal occurred (0%). The reason for this is that the molecular weight of phosphate (95.0 g/mol) is greater than the molecular weight of potassium (39.10 g/mol).

Using Statistical Significance and Prediction to Test Long/Short Term Public Services and Patients Cohorts: A Case Study in Scotland

Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found  that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.

Creating a Profound Sense of Comfort to Stimulate Workers’ Innovation and Productivity: Exploring Research and Case Study Applications

Purpose: The aim of this research is to explore and discuss innovation-workspaces, and how the design of the workspace has the potential to boost the work process and encourage employees’ satisfaction, leading to inventive and creative results. Background: The relationship between the workers and the work environment has a strong potential to enhance work outcomes when optimized for work goals. Innovation-work environment can benefit employees’ satisfaction, health, and performance. To understand this complex relationship, this research explores innovation-work environments. Methods: A review of 26 peer-reviewed articles, seven books, and 23 companies’ websites was conducted; in addition, five case studies were analyzed to deduce appropriate examples for the study. Results: The research found all successful five innovation environments focused on two aspects: first, workers’ satisfaction and comfort, which includes a focus on physical, functional, and psychological comfort; second aspect, all five centers were diverse work environments that addressed workers’ needs, design for individuals and teamwork, design for workers’ freedom, and design for increasing interaction. Conclusion: understanding individuals' needs and creating work environments that enhance interaction between workers and with the space are key aspects of successful innovation-work environments.

Clustering for Detection of Population Groups at Risk from Anticholinergic Medication

Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. This work evaluates the association between the average risk score and measures of socioeconomic status (index of multiple deprivation) and health (index of health and disability). The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, suggesting that females are more at risk from this kind of multiple medication. The risk may be monitored and controlled in a healthcare management system that is well-equipped with tools implementing appropriate techniques of artificial intelligence.

Governance, Risk Management, and Compliance Factors Influencing the Adoption of Cloud Computing in Australia

A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. Collecting, managing, and retaining large amounts of data in cloud environments make information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Performance Evaluation and Plugging Characteristics of Controllable Self-Aggregating Colloidal Particle Profile Control Agent

In low permeability reservoirs, the reservoir pore throat is small and the micro heterogeneity is prominent. Conventional microsphere profile control agents generally have good injectability but poor plugging effect; however, profile control agents with good plugging effect generally have poor injectability, which makes it difficult for agent to realize deep profile control of reservoir. To solve this problem, styrene and acrylamide were used as monomers in the laboratory. Emulsion polymerization was used to prepare the Controllable Self-Aggregating Colloidal Particle (CSA), which was rich in amide group. The CSA microsphere dispersion solution with a particle diameter smaller than the pore throat diameter was injected into the reservoir to ensure that the profile control agent had good inject ability. After dispersing the CSA microsphere to the deep part of the reservoir, the CSA microspheres dispersed in static for a certain period of time will self-aggregate into large-sized particle clusters to achieve plugging of hypertonic channels. The CSA microsphere has the characteristics of low expansion and avoids shear fracture in the process of migration. It can be observed by transmission electron microscope that CSA microspheres still maintain regular and uniform spherical and core-shell heterogeneous structure after aging at 100 ºC for 35 days, and CSA microspheres have good thermal stability. The results of bottle test showed that with the increase of cation concentration, the aggregation time of CSA microspheres gradually shortened, and the influence of divalent cations was greater than that of monovalent ions. Physical simulation experiments show that CSA microspheres have good injectability, and the aggregated CSA particle clusters can produce effective plugging and migrate to the deep part of the reservoir for profile control.

Effect of Different Types of Highly Consumed Beverages on the Surface Structure of Orthodontic Restorative Material

Orthodontic restorative materials are widely used for the direct restoration of teeth or for cosmetic dentistry purposes. These materials have helped to solve many dental problems, providing healthy and beautiful smiles for many patients. In this study, we aimed to investigate whether the pH value has an effect on the surface structure of a nanohybrid composite material. Five different types of highly consumed beverages were selected to examine their effect on the surface structure of the nanohybrid composite material. The beverages had different pH values in the range of 3–6, i.e., they were all acidic. The material was investigated under the hardest conditions of surface exposure to the drinks by immersing the material for a long period. The specimens were examined using scanning electron microscopy (SEM) at different magnifications to investigate the effect of these beverages on the morphology of the nanohybrid composite material discs. All specimens showed an effect including pores, cracks, protrusions, and surface roughness as a result of the beverages. The degree of effect differed from one experimental group to another, but there was no relationship between the pH (acidity) value and the degree of effect on the surface structure of the specimens.

Experiences and Coping of Adults with Death of Siblings during Childhood in Chinese Context: Implications for Therapeutic Interventions

The death of a sibling in childhood leads to significant impacts on both personal and family development of the surviving siblings, however, both short-term and long-term effects of sibling loss in Chinese societies such as Hong Kong have been inadequately documented in the literature. This paper explores the experience of encountering siblings’ death during childhood with the use of semi-structured interviews. Through thematic analysis, the author explores the impacts on surviving siblings’ emotions, coping styles, struggles and challenges and personal development. Furthermore, the influences on family dynamics are explored thoroughly, including the changes in family atmosphere, family roles, family relationship, family communication and parenting styles. More importantly, the author identifies (i) existing continuing bonds; (ii) crying; (iii) adequate social support; (iv) hiding own emotions as a gesture of protecting parents as the crucial elements pertinent to surviving siblings’ successful adaptation in the face of sibling loss. In addition, “child-centered” and “family-centered” service implications of families with a sibling's death in a Chinese context are discussed.

Perceptions of Chinese Top-Up Students Transitioning through a Regional UK University: A Longitudinal Study Using the U Curve Model

This article argues an urgent need to better understand the personal experiences of Chinese top-up students studying in the UK since the number of Chinese students taking year-long top-up programmes in the UK has risen rapidly in recent years. This lack of knowledge could potentially have implications for the reputation of some UK institutions and also the attractiveness of the UK higher education sector to future international students. This longitudinal study explored the academic and social experiences of 12 Chinese top-up students in a UK institution in-depth and revealed that the students felt their experiences were influenced significantly by their surrounding contexts at the macro and meso levels, which, however, have been largely overlooked in existing research. This article suggests the importance of improving the communications between the partner institutions in China and the UK, and also providing sufficient pre-departure and after arrival support to Chinese top-up students at the institutional level.

Multi-Sensor Target Tracking Using Ensemble Learning

Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Gas Generator Pyrotechnics Using Gun Propellant Technology Methods

This research article describes the gas generator pyro-cartridge using gun propellant technology methods for fighter aircraft application. The emphasis of this work is to design and develop a gas generating device with pyro-cartridge using double base (DB) propellant to generate a high temperature and pressure gas. This device is utilised for dropping empty fuel tank in an emergency from military aircraft. A data acquisition system (DAS) is used to record time to maximum pressure, maximum pressure and time to half maximum pressure generated in a vented vessel (VV) for gas generator. Pyro-cartridge as a part of the gas generator creates a maximum pressure and time in the closed vessel (CV). This article also covers the qualification testing of gas generator. The performance parameters of pyro-cartridge devices such as ignition delay and maximum pressure are experimentally presented through the CV tests.

Microservices-Based Provisioning and Control of Network Services for Heterogeneous Networks

Microservices architecture has been widely embraced for rapid, frequent, and reliable delivery of complex applications. It enables organizations to evolve their technology stack in various domains. Today, the networking domain is flooded with plethora of devices and software solutions which address different functionalities ranging from elementary operations, viz., switching, routing, firewall etc., to complex analytics and insights based intelligent services. In this paper, we attempt to bring in the microservices based approach for agile and adaptive delivery of network services for any underlying networking technology. We discuss the life cycle management of each individual microservice and a distributed control approach with emphasis for dynamic provisioning, management, and orchestration in an automated fashion which can provide seamless operations in large scale networks. We have conducted validations of the system in lab testbed comprising of Traditional/Legacy and Software Defined Wireless Local Area networks.

Indian Women’s Inner -World and Female Protest in Githa Hariharan’s Novel ‘The Thousand Faces of Night’

Gender statuses are inherently unequal; it is difficult to establish equality between men and women in the light of traditional inequalities across the world. This research focuses on the similarities and differences among women from different generations, different kinds of educational backgrounds and highlights the conflict experiences of the characters in Githa Hariharan’s novel “The Thousand Faces of Night”. The purpose is to show how women are suffering and are being humiliated in a male-dominated society. The paper depicts how women in India grapple from male domination aggressiveness as well as the cultural, social and religious controlling in the society they live in. The paper also seeks to explore the importance of knowledge as a powerful component which produces positive effects at the level of desire. The paper is based on the theories of Simone Beauvoir, Pierre Bourdieu, Edward Said, Rene Descartes and Amy Bhatt. Finally, the research emphasizes survival against hegemonic regimes and hope of Indian women for better life.

A Simulation Study into the Use of Polymer Based Materials for Core Exoskeleton Applications

A core/trunk exoskeleton design has been produced that is aimed to assist the raise to stand motion. A 3D model was produced to examine the use of additive manufacturing as a core method for producing structural components for the exoskeleton presented. The two materials that were modelled for this simulation work were Polylatic acid (PLA) and polyethylene terephthalate with carbon (PET-C), and the central spinal cord of the design being Nitrile rubber. The aim of this study was to examine the use of 3D printed materials as the main skeletal structure to support the core of a human when moving raising from a resting position. The objective in this work was to identify if the 3D printable materials could be offered as an equivalent alternative to conventional more expensive materials, thus allow for greater access for production for home maintenance. A maximum load of lift force was calculated, and this was incrementally reduced to study the effects on the material. The results showed a total number of 8 simulations were run to study the core in conditions with no muscular support through to 90% of operational support. The study presents work in the form of a core/trunk exoskeleton that presents 3D printing as a possible alternative to conventional manufacturing.

The CommonSense Platform for Conducting Multiple Participant Field-Experiments Using Mobile-Phones

This paper presents CommonSense, a platform that provides researchers with the infrastructure and tools that enable the efficient and smooth creation, execution and processing of multiple participant experiments taking place outside the laboratory environment. The platform provides the infrastructure and tools to accompany the researchers throughout the life cycle of an experiment – from its inception, through its execution, to its processing and termination. The approach of our platform is based on providing a comprehensive solution, which puts emphasis on the support for the entire life-cycle of an experiment, starting from its definition, the setting up and the configuration of the platform, through the management of the experiment itself and its post processing. Some of the components that support those processes are constructed and configured automatically from the experiment definition.

The COVID-19 Pandemic: Lessons Learned in Promoting Student Internationalisation

In higher education, a great degree of importance is placed on the internationalisation of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks, and connections and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment, through learning approaches, assessment methods and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country either to study, to work, to volunteer or to gain cultural and social enhancement has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience and adopting collaborative on-line projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learnt and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways, and that they will persist beyond the present to become part of the "new normal" for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.

3D Modeling Approach for Cultural Heritage Structures: The Case of Virgin of Loreto Chapel in Cusco, Peru

Nowadays, Heritage Building Information Modeling (HBIM) is considered an efficient tool to represent and manage information of Cultural Heritage (CH). The basis of this tool relies on a 3D model generally obtained from a Cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired Level of Development (LOD), Level of Information (LOI), Grade of Generation (GOG) as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models’ families respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources, since the BIM software used has a free student license.

Knowledge, Attitude and Practice of Pregnant Women toward Antenatal Care at Public Hospitals in Sana'a City-Yemen

Background: Antenatal care can be defined as the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure the best health conditions for both mother and baby during pregnancy. The components of Antenatal Care (ANC) include risk identification; prevention and management of pregnancy-related or concurrent diseases; and health education and health promotion. The aim of this study: to assess the knowledge, attitude, and practice of pregnant women regarding ANC. Methodology: A descriptive knowledge, attitude, and practice (KAP) study was conducted in public hospitals in Sana'a City, Yemen. The study population included all pregnant women that intended to the prenatal department and clinical outpatient department; the final sample size was 371 pregnant women. A self-administered questionnaire was used to collect the data, statistical package for social sciences SPSS was used to data analysis. The results: Most (79%) of pregnant women had correct answers in total knowledge regarding ANC, and about two-thirds (67%) of pregnant women had performance practice regarding ANC and two-third (68%) of pregnant women had a positive attitude. Conclusions: More than three quarter of pregnant women had good knowledge level, most of pregnant women had moderate practice level, and more than two-thirds of pregnant women had a positive attitude regarding antenatal care. There was a statistically significant association between overall knowledge and practice level toward ANC and demographic characteristics of pregnant women, at P-value ≤ 0.05. Recommendations: we recommended more education and training courses, lecturers, and education sessions in clinical facilitators focused on ANC, which relies on evidence-based interventions provided to women during pregnancy by skilled healthcare providers such as midwives, doctors, and nurses.

Aircraft Selection Problem Using Decision Uncertainty Distance in Fuzzy Multiple Criteria Decision Making Analysis

Aircraft have different capabilities and specifications according to the required strategic goals and objectives in operations. With various types on the market with different aircraft characteristics, it becomes difficult to select a suitable aircraft for certain operations and requirements. The entropy weighting method (EWM) is a useful, highly consistent, and reliable method for obtaining the weights of the criteria and is worth integrating with the decision uncertainty distance (DUD) method, which is more applicable and requires less computation than other methods. An illustrative example is presented to demonstrate the validity and usability of the proposed methodology. Comparing the ranking results matches the distance-based approach, which is the technique for order preference by similarity to ideal solution (TOPSIS) method, which shows the robustness of the entropy DUD hybrid method. Validity analysis shows that the proposed hybrid multiple criteria decision-making analysis (MCDMA) methodology is quantitatively stable and reliable.