Time Savings Research Articles

Clinical Impact of 3- versus 5-Minute Delay and 30- versus 60-Second Intervals on Unattended Automated Office Blood Pressure Measurements.

Guidelines advise automated office blood pressure (AOBP) with an initial 5-minute delay and multiple measurements at least 60 seconds apart. Recent studies suggest that AOBP may be accurate with shorter delays or intervals, but evidence in clinical settings is limited. Patients referred to one hypertension (HTN) center underwent 24-hour ambulatory blood pressure monitoring (ABPM) and one of four non-randomized, unattended AOBP protocols: a 3- or 5-minute delay with a 30 or 60-second interval, i.e., 3min/30sec/30sec, 3/60/60, 5/30/30 and 5/60/60 protocols. HTN was defined as systolic blood pressure ≥140 or diastolic blood pressure ≥90 mmHg. We compared differences in mean blood pressure and HTN classification between average AOBP and awake-time ABPM by t-tests and Fisher's exact test. Among 212 participants (mean 58.9 years, 61% women, 25% Black), there was substantial overlap in the probability distributions of awake-time ABPM and each of the three AOBP measures. Systolic blood pressure means were similar between the 5/60/60 and 3/30/30 protocols and 5/30/30 and 3/60/60 protocols. The 5/30/30 was associated with a higher proportion of systolic HTN, while the 3/60/60 protocol was associated with a higher proportion of diastolic HTN. There were no significant differences in systolic or diastolic HTN between 5/60/60 and 3/30/30 protocols with respect to awake-time ABPM. In this quality improvement study, the shortest AOBP protocol did not differ significantly from the longest protocol. The time savings of shorter protocols may improve AOBP adoption in clinical practice without meaningfully compromising accuracy.

Mechanization in Cotton Farming: Addressing Labor Shortages and Enhancing Productivity in India

Cotton is a globally significant crop, playing a vital role in both the agricultural and industrial economy. Cotton is a crucial raw material for the textile and apparel industries, driving international trade and commerce. Its global demand influences market dynamics, trade policies, and economies worldwide. The cotton industry provides livelihoods for millions of people, particularly in developing countries, from farming to manufacturing, making it a key source of employment globally. In India, approximately 59% of the raw material for India's textile industry comes from cotton. However, cotton cultivation is challenged by lower yields and high costs associated with various operations such as sowing, weed management, pest control, and harvesting. Mechanization significantly improves cotton yield and profitability by enhancing efficiency, reducing labor, and enabling the cultivation of larger areas with better resource utilization. Precision tools like seed-cum-fertilizer drills and mechanized planters ensure optimal seed placement and spacing, boosting plant health and yield potential. Additionally, mechanized harvesting reduces labor costs, minimizes harvest losses, and ensures better-quality cotton, leading to higher market returns and overall profitability. The innovative concept of High Density Planting Systems (HDPS) shows great potential for improving yields, particularly in rainfed cotton. This system involves planting five to ten plants per square meter, which enhances yield and is compatible with mechanized operations for seeding, weeding, pest management, and harvesting. The key objective of using improved sowing equipment is to achieve precise seed distribution within the row, facilitating operations like weeding and fertilizing at predetermined distances and depths. Proper seed placement by planters is critical to achieving optimal germination. Implementing efficient mechanical weeders could motivate small-scale farmers, boosting production and reducing poverty. A power weeder, a mechanized tool commonly used for preparing soil beds, offers significant savings in time, labor, and fuel. Furthermore, the adoption of mechanical cotton pickers would help ensure timely harvesting operations, increasing yields and contributing to higher cotton production. India’s low cotton productivity can be attributed to the limited adoption of modern agronomic practices and the low level of mechanization. Embracing these innovations could lead to significant improvements in the cotton sector Cotton pickers and strippers play a vital role in modern, large-scale cotton cultivation by significantly reducing harvesting time and labor costs, making them indispensable for efficient operations. These machines increase productivity by enabling faster harvesting across larger areas, minimizing the reliance on manual labor, which can be costly and scarce. Additionally, they reduce harvest losses and enhance yield by ensuring more cotton is collected with minimal waste. Cotton pickers, being gentler, help preserve fiber quality, while strippers are ideal for bulk harvesting in regions growing lower-grade cotton. Overall, mechanized harvesting ensures timely and efficient cotton collection, improving both yield and quality.

Evaluating the barriers to adoption of improved biomass cookstoves in Benue state, Nigeria

The prevalent use of inefficient traditional stoves for biomass cooking energy in Nigeria contributes to high rates of biomass consumption, deforestation, and harmful pollutant emissions. This study aimed to assess the constraints hindering the adoption of improved biomass cookstoves (IBCS) in Benue State, Nigeria. Data were randomly collected from 135 households and analyzed using descriptive (frequency, mean and percentage) as well as inferential statistics (binary probit regression). Findings revealed that 88% of households rely on fuelwood for cooking, with approximately 35% still using traditional stoves. However, 46% of households have adopted IBCS and recognized its advantages, including improved cooking speed, fuel economy, time savings in fuelwood collection, cost savings, and reduced smoke emissions. Additionally, various factors such as age, household size, access to credit, location, distance to market, membership of women's associations, fuelwood collection distance, and fuelwood sources were identified as constraints to IBCS adoption. To promote IBCS adoption, we recommend that development planners and extension officers raise awareness among households and provide them credit incentives through government and NGO support. This research significantly contributes to pertinent knowledge by shedding light on the challenges and opportunities associated with IBCS adoption in Nigeria, thereby informing policy and development initiatives in the country.

Navigating STEM careers with AI mentors: a new IDP journey.

Mentoring is crucial to the success of STEM higher education. The Individual Development Plan (IDP) is a common career development tool in STEM graduate education that facilitates structured mentor-mentee interactions and goal setting. This study examined the integration of AI mentors into the myIDP framework to provide real-time support and career insights. Using Google Gemini as an AI mentor, this study developed and assessed AI prompts within the myIDP framework. Eighteen STEM graduate students, primarily from underrepresented groups, were trained to engage with the AI mentor. Their interactions, feedback, and comments were analyzed using sentiment and thematic analysis. Participants reported positive experiences with AI mentors, noting benefits, such as immediate responses, up-to-date information, access to multiple AI mentors, enhanced ownership of career development, and time savings. However, concerns about misinformation, bias, privacy, equity, and algorithmic influences have also been raised. The study identified two hybrid human-AI mentoring models-Sequential Integration and Concurrent Collaboration-that combine the unique strengths of human and AI mentors to enhance the mentoring process. This study underscores the potential of AI mentors to enhance IDP practices by providing timely feedback and career information, thereby empowering students in their STEM career development. The proposed human-AI mentoring models show promise in supporting underrepresented minorities, potentially broadening participation in STEM fields.

YOLOrot2.0: A novel algorithm for high-precision rice seed size measurement with real-time processing

We present YOLOrot2.0, an automated algorithm for measuring the dimensions of rice seeds, which holds significant importance in evaluating grain quality and genetic breeding research. The current methods for rice seed measurement exhibit various limitations, such as the need for seed preprocessing and selection, specialized equipment for measurement, and prolonged measurement time. To address these issues, YOLOrot2.0 introduces the following improvements: Firstly, it utilizes an anchor-free detection algorithm to optimize the detection of rotated targets. Secondly, the utilization of the Kalman Filter IoU loss function, which combines the horizontal bounding box and smooth L1 loss function, accelerates the convergence speed of the network. Moreover, the YOLOv8 architecture was adjusted by modifying certain convolutional layers and the Context to Fusion module to enhance the detection capabilities for smaller targets. Finally, YOLOrot2.0 enables direct processing of the entire image, eliminating the need for image partitioning and resulting in substantial time and processing savings. Experimental results demonstrate that YOLOrot2.0 achieves an mAP (mean average precision) score of 0.95, surpassing other comparative algorithms. Additionally, YOLOrot2.0 provides highly accurate measurements of seed length and width, closely aligned with ground truth values. Notably, YOLOrot2.0 achieves real-time detection by achieving an average detection time of only 11.5 ms for images sized 3000×4000 pixels.

Quantitative Analysis Toward Guidance for Implementing E-Ticketing for Asphalt Paving Operations

Previous research efforts into e-ticketing for asphalt paving operations have qualitatively identified benefits and concerns. However, there is minimal academic literature detailing the quantitative impact of e-ticketing in the post-COVID-19 pandemic era. This research addresses this gap by gathering information from the Kentucky Transportation Cabinet (KYTC) about e-ticketing practices to aid in determining potential implementation steps. Quantitative project information was collected from KYTC projects to compare the traditional weigh ticket collection process with e-ticketing processes for both project engineers and inspectors. The analysis shows statistically significant time savings for field employees but not project management personnel. Further, factors affecting e-ticketing implementation for both project engineers and inspectors were also investigated. For inspectors, the dataset was analyzed to determine how the project type and quality assurance responsibilities of the inspector altered the e-ticketing impact. For engineers, the dataset was analyzed to determine how the project type altered e-ticketing impacts and how e-ticketing affected the engineer reviewing and storing project data. Cluster analysis was completed for both project engineers and inspectors to group project types where e-ticketing impact was maximized, and a decision matrix was created to aid agencies in creating implementation plans. The primary contributions to the body of knowledge include a modified action research methodology applied to electronic bulk material tickets to incorporate practitioner expertise into implementation guidelines and quantitative findings indicating that state transportation agencies should first implement e-ticketing on large asphalt-resurfacing projects, such as interstate rehabilitations, where inspectors have strenuous quality assurance responsibilities to maximize benefit.

Unattended noise measurements: use of new technologies to automatically qualify noise events for greater efficiency, precision and time savings

For more than 40 years, the noise assessment in the environment has consisted of measuring and storing the time history typically every second, then marking the events using post-processing software or automatically or manually by coding. Technological advances now make it possible to enrich the simple measurement of the time history thanks to additional data allowing a better evaluation of the measured phenomena: audio recording and AI analysis of the type of noise, analysis of the predominant direction during a noise event. We propose to present an innovative solution based on a 3D sound intensity probe allowing the determination of the azimuth and the elevation every time a noise event occurs. The results are expressed by frequency bands and A weighted filter. The influence of the type of field (active and reactive intensity) will be developed. Particular attention will be paid to the accuracy and the validity of the measurement as well as the limits of the principle.

Expanding the tool box for native structural biology: 19F dynamic nuclear polarization with fast magic angle spinning.

Obtaining atomic-level information on components in the cell is a major focus in structural biology. Elucidating specific structural and dynamic features of proteins and their interactions in the cellular context is crucial for understanding cellular processes. We introduce 19F dynamic nuclear polarization (DNP) combined with fast magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy as a powerful technique to study proteins in mammalian cells. We demonstrate our approach on the severe acute respiratory syndrome coronavirus 2 5F-Trp-NNTD protein, electroporated into human cells. DNP signal enhancements of 30- to 40-fold were observed, translating into over 1000-fold experimental time savings. High signal-to-noise ratio spectra were acquired on nanomole quantities of a protein in cells in minutes. 2D 19F-19F dipolar correlation spectra with remarkable sensitivity and resolution were obtained, exhibiting 19F-19F cross peaks associated with fluorine atoms as far as ~10 angstroms apart. This work paves the way for 19F DNP-enhanced MAS NMR applications in cells for probing protein structure, dynamics, and ligand interactions.

Evaluating large language models in analysing classroom dialogue

This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue—a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using datasets from middle school mathematics and Chinese classes, classroom dialogues were manually coded by experts and then analysed with a customised GPT-4 model. The study compares manual annotations with GPT-4 outputs to evaluate efficacy. Metrics include time efficiency, inter-coder agreement, and reliability between human coders and GPT-4. Results show significant time savings and high coding consistency between the model and human coders, with minor discrepancies. These findings highlight the strong potential of LLMs in teaching evaluation and facilitation.

Development of high-efficient asphalt pavement modeling software for digital twin of road infrastructure

To develop digital twin (DT) of road infrastructure, one critical element is computation of pavement responses (strains, stresses, and deflections) under traffic and environmental loading. This study aims to develop high-efficient asphalt pavement modeling software based on semi-analytical finite element method (SAFEM) for DT application. The algorithms address important aspects in vehicle-tire-pavement interaction modeling, such as dynamic vehicular loading, three-dimensional (3-D) non-uniform tire contact stress, viscoelastic behavior of asphalt material, and interface bonding condition. The simulation accuracy is verified by comparison with full-scale test and field measurements, and the relative differences are around 5 % to 20 %. Techniques including optimized discrete Fourier transform, parallel computing, graphics processing unit (GPU) acceleration, and sparse matrices are implemented for computation efficiency. As compared to the traditional 3-D FEM, SAFEM shows significant savings in computation time and storage usage. The high efficiency and accuracy make the software full of potential to be applied for DT of roadway infrastructure.

No man’s hand: artificial intelligence does not improve police report writing speed

Abstract Objectives This study examines the potential of artificial intelligence (AI) to reduce the time police officers spend writing reports, a task that consumes a significant portion of their workday. Methods In a pre-registered randomized controlled trial, we test this claim within the patrol division of a medium-sized police department (n = 85) at the individual report level (n = 755). Analyses utilize mixed-effects regression accounting for the nested structure of report-writing. Results AI assistance did not significantly affect the duration of writing police reports. Alternative specifications beyond those specified in the pre-registration, including a difference-in-differences approach observing report duration over a full year (n = 6084), confirm the null findings are robust. Conclusions Our findings contradict marketing expectations for the effect of this technology, suggesting no time savings in report-writing can be expected when using AI-assisted report-writing. Several other potential effects remain possible and untested.

Patient-Centered Cost Saving and Positive Environmental Impact With the Introduction of Telehealth Services at a Single Center.

To establish the patient-specific cost and time savings associated with telemedicine with the secondary environmental benefits of virtual visits within a tertiary referral center sub-specialty urology clinic. An electronic health record query was made of all urology telehealth visits that have occurred between October 4, 2020 and October 10, 2020 at a single academic center. We evaluated the cost of travel for an in-person visit based on zip code data. To adjust for productivity loss, the cost of missed work was added as either full day or half day-based distance and average compensation per day based on zip code data. Environmental impact was calculated using average CO2 emissions per mile not traveled. There were 6444 patients seen in the urology clinic via telehealth during the 6-month period. Urology patients traveled on average 69 ± 148 miles round-trip for an appointment. The average cost savings per patient including the cost of the gas and time away from work was $152.78 ± $105.90. Overall, over a 6-month period, the total cost savings was $984,534.73 for the 6444 patients seen via telemedicine. There was also a significant environmental impact of the decreased travel burden with 153.36 metric tons of CO2 emissions eliminated. With the implementation of telehealth during the COVID-19 pandemic, patients have been able to save a substantial amount of time and money primarily driven by the decreasing work hours lost and cost of travel.

A-124 Sustainable Transport: Assessing Environmental Impact in Medical Sample Transit via Drones and Vehicles

Abstract Background This research explores the ecological implications associated with different methods of transporting medical samples, specifically focusing on drones, combustion cars, and electric cars within two laboratories in central European countries. With the primary goal of assessing and comparing CO2 consumption, delivery time, and overall environmental impact, the study aims to provide a basis for adopting sustainable practices in healthcare logistics. Methods The transportation of medical samples occurred between two laboratories in the Principality of Liechtenstein and Switzerland, utilizing authorized aerial and road routes. Various weather conditions and distances were considered for sample transports using different vehicles (8 combustion cars, two electric cars, and one drone model). Energy consumption was documented, and the CO2 footprint was calculated based on data from the Swiss Federal Office for the Environment (FOEN) for both imported and renewable electricity. Comparative analyses were conducted to quantify the environmental impact of each transportation method. Results In terms of CO2 footprint, combustion cars exhibited a CO2 release of 159.5 g/km, while electric cars showed 3.43g (2.15 to 4.08% of combustion cars). Drones demonstrated a minimal 0.09g CO2 emission per kilometer (0.066% of combustion car CO2 emission; 2.6% of electric car CO2 emission). The distance traveled by drones was significantly shorter (16.7% to 50%). Additionally, the efficiency of drone transport was emphasized by its ability to avoid traffic jams and associated detours, resulting in time savings ranging from 31.25 to 50% per delivery when comparing transport times during rush hour and regular hours in the selected setting. Conclusions The integration of drone technology emerges as a crucial strategy for establishing a “green laboratory.” The substantial reduction in CO2 emissions and enhanced delivery efficiency position drone transport as a sustainable and operationally effective solution for medical sample logistics, offering shorter delivery times. These findings highlight the potential for transformative change in healthcare logistics, aligning with the global shift towards sustainability and green practices.

Leveraging machine learning to minimize experimental trials and predict hot deformation behaviour in dual phase high entropy alloys

In recent time, high entropy alloys (HEAs) are widely used due to their wide design space and remarkable properties allowing a vast range of property variations with myriads of possible combinations of constituent elements. This research utilizes machine learning techniques, including Random Forest (RF), K-Nearest Neighbors (KNN), XGBoost (XGB), Decision Tree (DT), and Support Vector Regressor (SVR), to predict the flow stress behavior of the dual FCC phase CoCrCu1.2FeNi high entropy alloy (HEA) at new temperature and strain rates to reduce the experiments dependency. The RF and KNN models were identified as top performers, with R² values of 0.987 and 0.986, respectively. These models successfully predicted flow stresses, aligning closely with actual measurements. A new flow stress-strain curve was generated at new temperature of 1123K, demonstrating good performance metrics for RF and KNN. with R² values of 0.97 and 0.958 respectively. This approach has the potential to significantly reduce the need for extensive experimental work in determining the mechanical behaviour of HEA, offering substantial savings in time, cost, and energy, and marks a significant advancement in the development of such alloys.

Creating Positive Customers Evaluation: The Impact of Efficient CRM Processes on Increasing Client Satisfaction

Commodity creation took precedence over endurance as the industrial revolution of the first half of the twentieth century led to the digitization of industrial techniques. Subsequently, the focus shifted to promotional elements that gave priority to consumer satisfaction. The technological advancements of the 20th century and globalization have brought humans to the highest levels of the asset organization, which has had a profound impact on employment. Ancient Hindu texts such as demonstrate the importance of human resources and demonstrate that structured management of human personnel dates back thousands of years. However, the first signs of the evolution of Hrd (human capital administration) approaches date back to the 1780 factory insurrection. During this time, technological breakthroughs necessitated improved work practices, productivity, and quality. The financial advantages of splitting of labor were discussed by Smith (1776) in his work “An Enquiry into the Causes and Nature of Wealth of Nations.” He suggested that specialization could increase the efficiency of labor. He perceived three benefits from a separation of labor: skill growth, time savings, and the ability to use specialized instruments. The creative endeavor of Owen (1825) demonstrates the significance of individuals in the operation of businesses. He maintained that one of the most effective expenditures managements can make is money invested in personnel development. Babbage (1832) investigated and developed the concept of specialization of labor in an even more thorough matching of individual expertise and abilities with particular tasks, based on his work, he came to that conclusion. As the work of Taylor (1911) tried to codify worker situations, procedures, methods, and tacit talents into concrete norms and formulae, a revolutionary shift occurred in the realm of interpersonal management practices. Research on the connection among productivity and the workplace was first undertaken by Mayo and his colleagues in 1927–1932. Barnard (1938) and other researchers followed up on these groundbreaking studies, which completely changed the realm of hiring and firing methods. The controversy about if effective human resources management is just jargon or a real concept is still up for debate, despite the fact that there has been a sizable body of literature on the subject. By analyzing the level of strategic HRM implementation and its effects on organizational performance in Nigeria’s manufacturing sector, this report aimed to expand the scope of previous research. The stated goal of the multi-respondent survey, which included 21 manufacturing organizations in the nation of Nigeria, had been to find a fit among corporate success and strategic staffing practices. The data obtained was evaluated using descriptive statistics, regression analysis, and correlational analysis. Results indicate that production enterprises in Nigeria employed moderate amounts of tactical HRM. Findings also show this path The main tactical human resources procedures that affect the effectiveness of organizations in Nigeria’s manufacturing sector are management devolution, creative hiring and hiring methods, ongoing workers education and training, based on shares compensation, performance appraisal, professional development, and active employee involvement in decisions and actions. It follows that businesses involved in production should focus more on these procedures in order to enhance their use throughout the sector.

Towards a Sustainable Financial Future: Exploring the Influence of E-Wallet Adoption Among Gen Z in Malaysia

The COVID-19 pandemic has prompted a shift in payment approaches, with a preference for e-wallets. Despite their potential, Malaysians lag in adopting e-wallets. It is necessary to gain a deeper understanding of the factors influencing e-wallet adoption, especially through Gen Z. Therefore, we conducted this study using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to explore the factors influencing e-wallet adoption among Gen Z. Interviews with eight members of Gen Z reveal that advantages like time savings and the ability to manage and monitor transactions drive the adoption of the e-wallet payment method. Emergent themes, such as government incentives and the convenience of donating, further delineate the adoption of e-wallets. The adoption of e-wallets will eventually promote sustainable consumption by replacing cash transactions and reducing carbon emissions due to the reduced physical transit of financial resources. This study enhances the UTAUT and suggests prospective avenues for the growth of e-wallets in Malaysia. Practically, the findings are advantageous for financial service providers that are enhancing their e-wallets, as well as for government initiatives to transition to a cashless society and ultimately achieve sustainable development goals.

Towards integrated multi-risk reduction strategies: A catalog of flood and earthquake risk mitigation measures at the building and neighborhood scales

The integration of risk reduction measures for earthquakes and floods is a promising concept in the field of multi-hazard disaster risk reduction. However, existing studies mostly discuss it conceptually, often missing a focus on decision-making. This paper introduces a novel approach by examining synergies and trade-offs between earthquake and flood risk reduction measures. The paper first conducts a detailed analysis of selected measures for these two hazards. It then explores how these individual risk mitigation measures can be strategically integrated at the building level to maximize synergies, potentially resulting in time and cost savings. Furthermore, it discusses the limitations of current decision-making procedures for single-hazard risk mitigation selection when applied to multi-hazard risk (MHR) scenarios. To address these challenges, the study proposes new decision variables to be incorporated into existing Multi-Criteria Decision-Making frameworks with the aim of facilitating strategic risk reduction prioritization for MHR scenarios, ensuring sustainability and community resilience. To aid implementation (i.e., the phase in which the measure would be selected and tested in a series of case study buildings), a catalog of analyzed risk reduction measures is developed and provided as Supplementary Material. In future developments, this catalog will facilitate the integration of these measures into decision-support tools for evidence-based multi-hazard disaster risk reduction.

Microwave-Assisted vs. Conventional Extraction of Moringa oleifera Seed Oil: Process Optimization and Efficiency Comparison.

This study aims to evaluate the effectiveness of microwave-assisted and conventional extraction using ethanol, hexane, and petroleum ether as solvents, and to optimize the process for extracting oil from Moringa oleifera Lam. seeds, with a focus on improving food-grade oil production. Response surface methodology (RSM) was applied to enhance the extraction process of the oil. Central composite rotational design (CCRD) was used to analyze the impact of solid-liquid ratio (x1), power (x2), and temperature (x3) on oil yield. The optimization identified the optimal conditions as a solid/liquid ratio of 1:38, power of 175 W, and temperature of 50 °C, achieving a 42% oil yield. Notably, the microwave-assisted extraction reduced the processing time from 8 h (using conventional Soxhlet extraction) to just 1 h. Conventional extraction with hexane and petroleum ether was also performed for comparison, resulting in similar oil content and fatty acid profiles, predominantly, oleic acid. FTIR analysis confirmed that the microwave-extracted oil contained fatty acids and had similar characteristics to the conventionally extracted oil. Thus, the use of ethanol as a green solvent in the microwave has shown significant improvement in terms of time and energy savings compared to the Soxhlet method with toxic solvents. This study concludes that microwave-assisted extraction with ethanol provides a more energy efficient, environmentally friendly, and time-saving alternative for food-grade oil production, aligning with advancements in food engineering and production.

The Captive Insurance Opportunity in Alberta: Drivers of Success in Captive Domiciles

The annual economic impact from captive insurance companies in Alberta could range as high as C$139 million, but changes to the province’s current policies are necessary for the industry ideally to grow to 210 captives by 2033, up from the 20 licensed captives as of July 2024. Alberta’s Captive Insurance Companies Act came into force in July 2022, making it the second province after British Columbia to permit captive insurance companies. Diversifying Alberta’s economy and building the province’s financial sector are important parts of the rationale behind Alberta’s captive insurance legislation, but much remains to be done. To determine how Alberta can build on its early success, this paper extracts lessons from studies on captive insurance in Bermuda, Delaware, North and South Carolina, Vermont and Hawaii that measured captives’ economic benefits. Economic impact estimates per captive are as high as C$564,400 annually, demonstrating how a healthy captive market positively impacts a domicile. For example, in 2016, Delaware’s 1,081 captives generated US$360 million in economic activity, US$109 million in labour income and 2,573 jobs. Alberta already has a sound foundation for success. The province’s speed of licensing means companies’ applications are approved within six weeks of being submitted. Alberta allows limited partnerships as a corporate structure for captives as well as the ability for companies to insure risks in other provinces. Being located in Alberta means time and cost savings for captives that can then avoid the expense of offshore travel for setup, board meetings and administration, aided by easy access to the regulator. Allowing for non-resident captive managers has proved attractive to companies from other domiciles, but fine-tuning these and other regulations is key if the industry is to flourish in Alberta. For example, while four of Alberta’s 20 captives have established operations in the province, if Alberta were to require captive managers to be based in the province, this would generate a higher impact from employment and greater economic benefits. To successfully compete with Barbados and Bermuda, Alberta needs to lower its minimum capital requirements for captives — $250,000 for pure captives and $500,000 for association and sophisticated insured captives. The Alberta government should also permit inter-company loans as an acceptable form of capital, as Bermuda and Barbados already do. Alberta needs to expand its policy of not requiring collateral for reinsurance so that Alberta’s captives can access the Bermuda and Swiss reinsurance markets, which account for 27 per cent of the global property and casualty reinsurance industry. Successful domiciles for captive insurance also allow for protected cell captives (PCC), which attract smaller entities because their operating costs can be up to 50 per cent lower than pure single-parent captives and the cells can be set up in days. The domiciles examined in this paper also have no insurance premium tax (IPT), engage with regulators and the industry via trade associations and hire experienced captive regulators — something it could take years for Alberta to achieve unless managers are recruited from elsewhere. Alberta needs PCC legislation targeted at captive insurers, while examining the feasibility of creating an annual dollar IPT maximum and lowering IPT rates for captives. The province ought to also encourage the creation of an industry association whose members would engage with government on legislation and hire senior regulators to bring their expertise to the province. By learning from the experiences of other domiciles and implementing their best practices, Alberta can quickly begin benefiting economically from the growth and vitality of the captive insurance industry.

Rapid evaluating caking tendency of nonspherical crystals by developing a shape-based crystal bridge growth model

Crystal caking is a decisive factor affecting the quality of high-end fine chemicals, whereas lack of shape-to-caking understanding results in considerable waste of time, severely delaying high-end fine chemical development. On this basis, a morphology-based caking evaluation model is developed with 74% and 96% time savings compared to previous modeling and non-modeling experiments, respectively, while guaranteeing superior accuracy. The crystal morphology is expressed as a function of the aspect ratio and the particle size distribution. The quantitative relationships between these parameters and the caking tendency are deduced, firstly achieving morphology anti-caking criterion establishment. For D-allulose crystals, considering humidity, and particle size, an aspect ratio is below 3 is the standard for combating caking, which has not been reported previously. Herein, the specific effect of crystal morphology on caking behavior is quantitatively described. The knowledge obtained can be applied to rapidly and quantitatively design anti-caking storage systems for products in warehouses.