Thermodynamic and electrical performance monitoring of a domestic split-type air conditioner and development of a simulation based R22 permanent replacement

The difficulty that exists in accurately monitoring the performance of air conditioners has made performance prediction an arduous task. Nevertheless, the performance still needs to be monitored and predicted as it helps solve a lot of problems resulting from this technology like effect of the technology on the grid, energy consumption, water utilisation and GHGs emission. With the introduction of regression modelling as a means of system monitoring and prediction some years ago, the accuracy was still a call for concern. It is worth realising that increasing the number of predictors will enhance this method’s accuracy. As such, this document intends to increase the accuracy of this method’s monitoring and predicting ability by increasing the number of predictors to cut across system thermal, environmental and human behavioural variation. These predictors experimentally gotten are used to build an environ-behavioural model that monitors the coefficient of performance and energy consumption of a domestic split-type air conditioner with higher accuracy. Refrigerants have undergone evolution in the past decades in a bid to come up with a refrigerant that has zero ODP, lower – than – R22 GWP and much better than R22 thermodynamic performance. No pure refrigerant has been found to possess these qualities as such mixtures or blends are the best shot at the moment. R410A could stand the test of time to be the long term R22 replacement but for the fact that besides R410A’s higher GWP than that of R22, the former’s system performance is lower than that of the latter’s due to the lower thermodynamic performance of the former. This means the search continues. In this document, a combination of carefully chosen refrigerant components are carefully blended to come up with a simulation based R22 long term replacement, which will be referred to in this document as BTEP

Uncertainty in Digital Platforms and Ecosystems: The Dynamic Interplay Between Knowledge Problems

The information systems literature has long argued that innovation drives uncertainties in organizations. While extant research has extensively studied knowledge problems in the traditional firm setting and their implications on organizing and decision making, an updated understanding is required in relation to uncertainties within digital platforms and ecosystems, where organizational boundaries are blurred and downstream movement is becoming more popular. To address this issue, we explore the different dimensions of uncertainties in the digital platforms and ecosystems by classifying them based on the knowledge problems that dominantly contribute to their formation and the platform actors facing such uncertainties. A higher-level uncertainty emerges as a result of the interactions within these dimensions. In addition, the interactions evolve in longitudinal and dynamic patterns due to the complex nature of digital platforms and ecosystems

Privacy Inequality and IT Identities: The Impact of Different Privacy Laws Adoptions

Protecting consumers’ personal information is no longer a by-product of business operations. Since 2018, adoption of General Data Protection Regulation (GDPR) Regulation EU 2016/679 has pushed countries to revamp their data privacy laws and regulations. However, many countries are still adopting or lack such privacy laws, leading to an inequality in handling users’ data privacy as a fundamental right. We argue that it is possible for users to develop different IT identities with different IT, based on their salient privacy expectations formed by the place where they are interacting with these IT. We plan to apply a mixed methodology for data collection and data analysis. This research will contribute to the current IS literature in a variety of ways by examining how organizations’ compliance and non-compliance to GDPR, as well as better understanding how countries’ adoption and non-adoption of data protection regulations and privacy laws can generate inequality in organizations’ privacy practices. In addition, the study will extend the established IT Identity theory by examining the impact of the data protection regulations in shaping users’ different IT identities and trust

Assessing the Impact of Virtual Health Communities and Environmental Characteristics of Chronic Pain Mobile Health Apps on Users’ Privacy Decisions: A Multilevel Perspective

Chronic pain has been identified as one of the most widespread health-related problems. Potential chronic pain apps users seek health communities for current and previous reviews to assess the quality of the apps and make a decision regarding disclosing their information to these apps. In this study, we present a multilevel perspective on how virtual health communities and environmental characteristics of chronic pain mobile health apps impact users’ privacy decisions. We used Exploratory Data Analysis and Machine Learning (ML) to operationalize the Theory of Multilevel Information Privacy. The results revealed that the most influential factors affecting users’ cost-benefit analysis are Chronic Pain MHA’s characteristics related to user’s information privacy. The ML results indicate that the existence of information privacy policy can be predicted through the ways the apps use to Collect Data, App\u27s Category, Country, and Store Type, which in turn affect users\u27 decisions

Chief Privacy Officer Role and Organizational Transformation in the Digital Economy

With increased digitalization and the evolving digital economy, consumers, regulating agencies, and business partners alike demand more transparency for organizational privacy practices, generating increased pressure on organizations to establish privacy programs and initiatives. The Chief Privacy Officer (CPO) role is central to the development of these privacy initiatives and is becoming more strategic. However, the role of the CPO appears to vary significantly across organizations. This study aims to investigate how an organization\u27s privacy initiatives implementation influences the CPO role and understand how an organization needs to transform to support the emerging CPO roles in the digital economy. We present our initial findings and elaborate on a transformation model that shows the stages an organization follow to support the CPO role strategically

Benchmarking techno-economic performance of greenhouses with different technology levels in a hot humid climate

Greenhouse agriculture is expected to play a critical role in sustainable crop production in the coming decades, opening new markets in climate zones that have been traditionally unproductive for agriculture. Extreme hot and humid conditions, prevalent in rapidly growing economies including the Arabian Peninsula, present unique design and operational challenges to effective greenhouse climate control. These challenges are often poorly understood by local operators and inadequately researched in the literature. This study addresses this knowledge gap by presenting, for the first time, a comprehensive set of benchmarks for water and energy usage, CO2 emissions (CO2e) contribution, and economic performance for low-, mid-, and high-tech greenhouse designs in such climates. Utilising a practical and adaptable model-based framework, the analysis reveals the high-tech design generated the best results for economic return, achieving a 4.9-year payback period with superior water efficiency compared to 5.8 years for low-tech and 7.0 years for mid-tech; however, the high-tech design used significantly more energy to operate its mechanical cooling system, corresponding with higher CO2e per unit area (8.3 and 4.0 times higher than the low- and mid-tech, respectively). These benchmarks provide new insights for greenhouse operators, researchers, and other stakeholders, facilitating the development of effective greenhouse design and operational strategies tailored to meet the challenges of hot and humid climates

Study on the effects of nitrilotriproprionic acid and 4,5-dihydroxy-1,3-benzene disulphonate on the fractionation of beryllium in human serum using graphite furnace atomic absorption spectrometry

<p>Abstract</p> <p>Background</p> <p>Occupational exposure to beryllium may cause Chronic Beryllium Disease (CBD), a lung disorder initiated by an electrostatic interaction with the MHC class II human leukocyte antigen (HLA). Molecular studies have found a significant correlation between the electrostatic potential at the HLA-DP surface and disease susceptibility. CBD can therefore be treated by chelation therapy. In this work, we studied the effect of two complexing agents, nitrilotriproprionic acid (NTP) and 4,5-dihydroxy-1,3-benzene disulphonate (Tiron), on the fractionation of beryllium in human serum analysed by graphite furnace atomic absorption spectrometry (GFAAS).</p> <p>Results</p> <p>We found the average serum beryllium concentration of fourteen non-exposed individuals to be 0.53 (± 0.14) μg l^-1, with 21 (± 3)% of the beryllium mass bound to the low molecular weight fraction (LMW), and 79 (± 3)% bound to the high molecular weight fraction (HMW). The addition of Tiron increased the beryllium mass in the HMW fraction, while NTP was not seen to have any influence on the fractionation of beryllium between the two fractions. NTP was, however, shown to complex 94.5% of the Be mass in the LMW fraction. The beryllium GFAAS detection limit, calculated as three times the standard deviation of 10 replicates of the lowest standard (0.05 μg L^-1), was 6.0 (± 0.2) ng L^-1.</p> <p>Conclusion</p> <p>The concentration of beryllium or its fractionation in human serum was not affected by sex or smoking habit. On average, three quarters of the beryllium in serum were found in the HMW fraction. Of the two ligands tested, only Tiron was effective in mobilising beryllium under physiological conditions, thus increasing the Be content in the HMW fraction.</p