Experimental Investigation of Natural Frequency and Forced Vibration of Euler-Bernoulli Beam under Displacement of Concentrated Mass and Load

This work aims to evaluate the free and forced vibration of a beam with two end joints subjected to a concentrated moving mass and a load using the Euler-Bernoulli method. The natural frequency is calculated for different locations of the concentrated mass and load on the beam. The analytical results are verified by the experimental data. The variations of natural frequency as a function of the location of the mass, the effect of the forced frequency on the vibrational amplitude, and the displacement amplitude versus time are investigated. It is discovered that as the concentrated mass moves toward the center of the beam, the natural frequency of the beam and the relative error between experimental and analytical data decreases. There is a close resemblance between analytical data and experimental observations.

Sustainable Engineering Paradigm Shift in Digital Architecture, Engineering and Construction Ecology within Metaverse

In the post COVID 19 pandemic, the demand for virtual world and digital economy accelerated and became more popular and the term Metaverse is now a hot topic in different sectors in the community and society. Digital technology development in augmented reality (AR), virtual reality (VR), and networks has become more mature in recent years, the racing of the application of Metaverse in different aspects is more vigorous. Metaverse in digital architectural, engineering and construction being one of the major players in future should not be overlooked. More understanding of Metaverse which includes the Architecture, Engineering and Construction (AEC) industry is crucial and this is important for stakeholders in the AEC industry to start early development to match with the quick development, expansion and global trend of Metaverse.

Development of the Maturity Sensor Prototype and Method of Its Placement in the Structure

Maturity sensors are used to determine concrete strength by the non-destructive method. The method of placement of the maturity sensors determines their number required for a certain frame of a monolithic building. This paper proposes a cheap prototype of an embedded wireless sensor for monitoring concrete structures, as well as an alternative strategy for placing sensors based on the transitional boundaries of the temperature distribution of concrete curing, which were determined by building a heat map of the temperature distribution, where unknown values are calculated by the method of inverse distance weighing. The developed prototype can simultaneously measure temperature and relative humidity over a smartphone-controlled time interval. It implements a maturity method to assess the in-situ strength of concrete, which is considered an alternative to the traditional shock impulse and compression testing method used in Kazakhstan. The prototype was tested in laboratory and field conditions. The tests were aimed at studying the effect of internal and external temperature and relative humidity on concrete's strength gain. Based on an experimentally poured concrete slab with randomly integrated maturity sensors, it the transition boundaries form elliptical forms were determined. Temperature distribution over the largest diameter of the ellipses was plotted, resulting in correct and inverted parabolas. As a result, the distance between the closest opposite crossing points of the parabolas is accepted as the maximum permissible step for setting the maturity sensors. The proposed placement strategy can be applied to sensors that measure various continuous phenomena such as relative humidity. Prototype testing has also revealed Bluetooth inconvenience due to weak signal and inability to access multiple prototypes simultaneously. For this reason, further prototype upgrades are planned in the future work.

Military Use of Artificial Intelligence under International Humanitarian Law: Insights from Canada

As artificial intelligence (AI) technologies can be used by both civilians and soldiers; it is vital to consider the consequences emanating from AI military as well as civilian use. Indeed, many of the same technologies can have a dual-use. This paper will explore the military uses of AI and assess their compliance with international legal norms. AI developments not only have changed the capacity of the military to conduct complex operations but have also increased legal concerns. The existence of a potential legal vacuum in legal principles on the military use of AI indicates the necessity of more study on compliance with International Humanitarian Law (IHL), the branch of international law which governs the conduct of hostilities. While capabilities of new means of military AI continue to advance at incredible rates, this body of law is seeking to limit the methods of warfare protecting civilian persons who are not participating in an armed conflict. Implementing AI in the military realm would result in potential issues including ethical and legal challenges. For instance, when intelligence can perform any warfare task without any human involvement, a range of humanitarian debates will be raised as to whether this technology might distinguish between military and civilian targets or not. This is mainly because AI in fully military systems would not seem to carry legal and ethical judgment which can interfere with IHL principles. The paper will take, as a case study, Canada’s compliance with IHL in the area of AI and the related legal issues that are likely to arise as this country continues to develop military uses of AI.

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.

An Empirical Assessment of Sustainability of an Urban Water Supply Service Delivery

Urban population is rapidly increasing in Ilorin, (the capital of Kwara State of Nigeria) along with related increased water demand. The inadequacies of water supply services have forced the populace to depend on dug wells, boreholes, water tankers, street vendors etc. for their water needs. People spend hours daily carrying jerry can all around to collect and queue for water at the public water tap with high opportunity cost both in time and economic wastage. This situation motivated this study to assess the sustainability of an urban water supply services to unravel the factors undermining the effective delivery of services. Contingent Valuation Method was used to place value on water supply services using the Double Bounded Dichotomous Choice format for willingness to pay elicitation. A database was created with Microsoft Excel and Stata 12 Software to model and evaluate the variables that affect household willingness to pay. The results of the study reveal that about 92% of the total households surveyed were connected to the Government water supply out of which 87% reported that they were not satisfied with the existing services. The results furthered revealed that respondents are willing to pay ₦2500 monthly to enjoy sustainable water supply service delivery.

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.

Development of a Quantitative Material Wastage Management Plan for Effective Waste Reduction in the Building Construction Industry

Combating climate change is becoming a hot topic in various sectors. Building construction and infrastructure sectors contributed a significant proportion of waste and greenhouse gas (GHG) emissions in the environment of different countries and cities. However, there is little research on the micro-level of waste management, “building construction material wastage management,” and fewer reviews about regulatory control in the building construction sector. This paper focuses on the potentialities and importance of material wastage management and reviews the deficiencies of the current standard to take into account the reduction of material wastage in a systematic and quantitative approach.

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.

Simulation on Influence of Environmental Conditions on Part Distortion in Fused Deposition Modelling

Fused Deposition Modelling (FDM) is one of the additive manufacturing techniques that has become highly attractive in the industrial and academic sectors. However, parts fabricated through FDM are highly susceptible to geometrical defects such as warpage, shrinkage, and delamination that can severely affect their function. Among the thermoplastic polymer feedstock for FDM, semi-crystalline polymers are highly prone to part distortion due to polymer crystallization. In this study, the influence of FDM processing conditions such as chamber temperature and print bed temperature on the induced thermal residual stress and resulting warpage are investigated using 3D transient thermal model for a semi-crystalline polymer. The thermo-mechanical properties and the viscoelasticity of the polymer, as well as the crystallization physics which considers the crystallinity of the polymer, are coupled with the evolving temperature gradient of the print model. From the results it was observed that increasing the chamber temperature from 25 °C to 75 °C leads to a decrease of 3.3% residual stress and increase of 0.4% warpage, while decreasing bed temperature from 100 °C to 60 °C resulted in 27% increase in residual stress and a significant rise of 137% in warpage. The simulated warpage data are validated by comparing it with the measured warpage values of the samples using 3D scanning.

Logistics Support as a Key Success Factor in Gastronomy

Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, foodservice is strongly related to logistics processes, and areas of foodservice that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support, occurring in the catering business, and affecting the scope of the logistic processes implemented. The aim of the paper is implemented through a plural homogeneous approach, based on direct observation, text analysis of current documents, and in-depth free targeted interviews.

Effects of Virtual Reality on the Upper Extremity Spasticity and Motor Function in Patients with Stroke: A Single Blinded Randomized Controlled Trial

Background: Stroke is a disabling neurological disease. Rehabilitative therapies are important treatment methods. This clinical trial was done to compare the effects of virtual reality (VR) beside conventional rehabilitation versus conventional rehabilitation alone on the spasticity and motor function in stroke patients. Materials and methods: In this open-label randomized controlled clinical trial, 40 consecutive patients with stable first-ever ischemic stroke in the past three to 12 months that were referred to a rehabilitation clinic in Tehran, Iran in 2020 were enrolled. After signing the informed written consent form, subjects were randomly assigned by block randomization of five in each block as cases with 1:1 into two groups of 20 cases; conventional plus VR therapy group: 45-minute conventional therapy session plus 15-minute VR therapy, and conventional group: 60-minute conventional therapy session. VR rehabilitation is designed and developed with different stages. Outcomes were Modified Ashworth scale, Recovery Stage score for motor function, range of motion (ROM) of shoulder abduction/wrist extension, and patients’ satisfaction rate. Data were compared after study termination. Results: The satisfaction rate among the patients was significantly better in combination group (P = 0.003). Only wrist extension was varied between groups and was better in combination group. The variables generally had statistically significant difference (P < 0.05). Conclusion: VR plus conventional rehabilitation therapy is superior versus conventional rehabilitation alone on the wrist and elbow spasticity and motor function in patients with stroke.

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.

Modeling of Silicon Solar Cell with Anti-Reflecting Coating

In this study, a silicon solar cell has been modeled and analyzed to enhance its performance by improving the optical properties using an anti-reflecting coating (ARC). The dynamic optical reflectance, transmittance along with the net transmissivity absorptivity product of each layer are assessed as per the diurnal variation of the angle of incidence using MATLAB 2019. The model is tested with various anti-reflective coatings and the performance has also been compared with uncoated cells. ARC improves the optical transmittance of the photon. Higher transmittance of ⁓96.57% with lowest reflectance of ⁓ 1.74% at 12.00 hours was obtained with MgF2 coated silicon cells. The electrical efficiency of the configured solar cell was evaluated for a composite climate of New Delhi, India, for all weather conditions. The annual electricity generation for anti-reflective coated and uncoated crystalline silicon PV Module was observed to be 103.14 KWh and 99.51 KWh, respectively.

Extracting Attributes for Twitter Hashtag Communities

Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.