Production and Application of Organic Waste Compost for Urban Agriculture in Emerging Cities

Composting is one of the conventional techniques adopted for organic waste management but the practice is very limited in emerging cities despite that most of the waste generated is organic. This paper aims to examine the viability of composting for organic waste management in the emerging city of Addis Ababa, Ethiopia by addressing the composting practice, quality of compost and application of compost in urban agriculture. The study collects data using compost laboratory testing and urban farm households’ survey and uses descriptive analysis on the state of compost production and application, physicochemical analysis of the compost samples, and regression analysis on the urban farmer’s willingness to pay for compost. The findings of the study indicated that there is composting practice at a small scale, most of the producers use unsorted feedstock materials, aerobic composting is dominantly used and the maturation period ranged from four to 10 weeks. The carbon content of the compost ranges from 30.8 to 277.1 due to the type of feedstock applied and this surpasses the ideal proportions for C:N ratio. The total nitrogen, pH, organic matter and moisture content are relatively optimal. The levels of heavy metals measured for Mn, Cu, Pb, Cd and Cr6+ in the compost samples are also insignificant. In the urban agriculture sector, chemical fertilizer is the dominant type of soil input in crop productions but vegetable producers use a combination of both fertilizer and other organic inputs including compost. The willingness to pay for compost depends on income, household size, gender, type of soil inputs, monitoring soil fertility, the main product of the farm, farming method and farm ownership. Finally, this study recommends the need for collaboration among stakeholders along the value chain of waste, awareness creation on the benefits of composting and addressing challenges faced by both compost producers and users.

How International College Students Understand Entrepreneurial Readiness and Business-Related Skills: A Qualitative Study

The free-market economy provides many opportunities for entrepreneurship or starting one’s own business, attracting many students to study business at for-profit colleges in the United States. This is also true for international students, many of whom are filled with the hope of making a better life for themselves and their families through entrepreneurial endeavors. This qualitative research showed that not all graduates business students start their own business. In investigating this phenomenon, the effectiveness of entrepreneurship curricula at international colleges needs to be examined in order to adjust, improve and reform entrepreneurship curricula. This qualitative study will explore how business skills learned in college for-profit play a role in the entrepreneurial readiness of undergraduate business students in the south Florida. Business curricula helps international students achieve goals and transform their actions to understand challenges in a corporate society. Students will be interviewed to gain information about the students’ experience with entrepreneurship curricula in a for-profit college in south Florida.

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.

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.

Fuzzy Uncertainty Theory for Stealth Fighter Aircraft Selection in Entropic Fuzzy TOPSIS Decision Analysis Process

The purpose of this paper is to present fuzzy TOPSIS in an entropic fuzzy environment. Due to the ambiguous concepts often represented in decision data, exact values are insufficient to model real-life situations. In this paper, the rating of each alternative is defined in fuzzy linguistic terms, which can be expressed with triangular fuzzy numbers. The weight of each criterion is then derived from the decision matrix using the entropy weighting method. Next, a vertex method is proposed to calculate the distance between two triangular fuzzy numbers. According to the TOPSIS concept, a closeness coefficient is defined to determine the ranking order of all alternatives by simultaneously calculating the distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). Finally, an illustrative example of selecting stealth fighter aircraft is shown at the end of this article to highlight the procedure of the proposed method. Correlation analysis and validation analysis using TOPSIS, WSM, and WPM methods were performed to compare the ranking order of the alternatives.

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.

Bedouin Weaving Techniques: Source of Textile Innovation

Nomadic tribes have always had the need to relocate and build shelters, moving from one site to another in search of food, water, and natural resources. They are affected by weather and seasonal changes and consequently started innovating textiles to build better shelters. Their solutions came from the observation of their natural environment, material, and surroundings. ‘AlRahala’ Nomadic Bedouin tribes from the Middle East and North African region have used textiles as a fundamental architectural element in their tent structure, ‘Bayt AlShar’ (House of Hair). The nomadic tribe has innovated their textile to create a fabric that is more suited to change in climatic and weather conditions. They used sheep, goat, or camel hair to weave the textiles to make their shelters. The research is based on existing literature on the weaving technicalities used by these tribes, based on their available materials encountered during travel. To conclude how they create the traditional textiles and use in the tents are a rich source of information for designers to create innovative solutions of modern-day textiles and environmentally responsive products.

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.

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.

Circular Economy: Relationship of the Natural Water Collection System, Afforestation and Country Park towards Environmental Sustainability

The government and community have raised their awareness of the benefits of water reuse. Deforestation has a significant effect to climate change as it causes the drying out of the tropical rainforest and hence increases the chance of natural threaten the storage and supply of clean water. This paper focuses on discussion of the relationship of the natural water collection system, afforestation and country parks towards environmental sustainability and circular economy, with a case study of water conservation policy and strategy in Hong Kong and Singapore for further research.