Productivity Gain Research Articles

Artificial Intelligence in Endourology: Maximizing the Promise Through Consideration of the Principles of Diffusion of Innovation Theory.

Introduction: Diffusion of Innovation Theory explains how ideas or products gain momentum and diffuse (or spread) through specific populations or social systems over time. The theory analyzes primary influencers of the spread of new ideas, including the innovation itself, communication channels, time, and social systems. Methods: The current study reviewed published medical literature to identify studies and applications of artificial intelligence (AI) in endourology and used E.M. Rogers' Diffusion of Innovation Theory to analyze the primary influencers of the adoption of AI in endourological care. The insights gained were triaged and prioritized into AI application-related action items or "tips" for facilitating the appropriate diffusion of the most valuable endourological innovations. Results: Published medical literature indicates that AI is still a research-based tool in endourology and is not widely used in clinical practice. The published studies have presented AI models and algorithms to assist with stone disease detection (n = 17), the prediction of management outcomes (n = 18), the optimization of operative procedures (n = 9), and the elucidation of stone disease chemistry and composition (n = 24). Five tips for facilitating appropriate adoption of endourological AI are: (1) Develop/prioritize training programs to establish the foundation for effective use; (2) create appropriate data infrastructure for implementation, including its maintenance and evolution over time; (3) deliver AI transparency to gain the trust of endourology stakeholders; (4) adopt innovations in the context of continuous quality improvement Plan-Do-Study-Act cycles as these approaches have proven track records for improving care quality; and (5) be realistic about what AI can/cannot currently do and document to establish the basis for shared understanding. Conclusion: Diffusion of Innovation Theory provides a framework for analyzing the influencers of the adoption of AI in endourological care. The five tips identified through this research may be used to facilitate appropriate diffusion of the most valuable endourological innovations.

3D View Factor Power Output Modelling of Bifacial Fixed, Single, and Dual-Axis Agrivoltaic Systems

This study investigates the performance of agrivoltaic systems employing bifacial photovoltaic modules. A comparison between yield in Sweden and Italy was carried out. Three agrivoltaic system designs were evaluated: vertical fixed, single-axis tracker, and dual-axis tracker. The results showed that the specific production varied between 1090 to 1440 kWh/kWp/yr in Sweden and 1584 to 2112 kWh/kWp/yr in Italy, where the lowest production was obtained with the vertical fixed agrivoltaic system while the highest production was obtained with the dual-axis tracking agrivoltaic system. The vertical fixed design had a higher electricity production during low solar elevation angles, while the single-axis and dual-axis tracking designs had significantly higher power production during mid-day. The electricity production gain using a dual-axis tracker design was mostly during mid-day, but the increase compared to the single-axis tracker was only 1-2%. The study concludes that low-height, fixed agrivoltaic systems without tracking are well-suited for high-latitude countries like Sweden, while elevated systems with tracker solutions are more suitable for locations like Italy. The findings suggest that the performance of agrivoltaic systems with bifacial photovoltaic modules is highly dependent on geographical location and the specific characteristics of the crops grown beneath them.

Unifying Forces: Harnessing Blockchain and Artificial Intelligence Integration for Enhanced Innovation

Blockchain and artificial intelligence have now become the emerging technologies of our time. However, both strategies induce a change in the market but differ in terms of how creative and complex they are. While block chain is decentralized; distributed ledger technology that the one stores information in multiple locations with no centralized monitoring system, on the other hand, Artificial Intelligence (AI) emulates human problem-solving ability as well as decision-making abilities using software, data or even robots. These two technologies combined together to bring about new opportunities such as productivity gain from both advantages of blockchain and AI security and transparency. Businesses can transform significantly through integration of AI with blockchain technology for data protection, clear data trails and general efficiency. Cyber security is one of the most important concepts linked to these two technologies. The possibility to combine AI’s capabilities with blockchain’s reliable and decentralized nature can be used to manage resources as well as decision making at educational institutes or within healthcare agencies; it may also be employed by society to influence agriculture outputs, planning urban dwellings among others. Artificial intelligence (AI) can help identify risks at an early stage whereas information security and integrity might vanish.

Turbulent flow characteristics over rough permeable and impermeable gravel-bed stream- an experimental study

Abstract The study aims to presents flow heterogeneity over rough permeable and impermeable gravel-bed stream. The rough permeable stream is prepared by laying multiple layers of gravel, whereas its impermeable counterpart is presented by a resin-casted gravel-bed. In general, a common approach can be found in literature to mimic an impermeable bed by laying single layer of gravels, therefore some results are compared with single layer gravel-bed stream keeping the hydraulic conditions same. An acoustic Doppler velocimeter was used for flow measurements whereas; double averaging (DA) methodology was adopted for data analysis. The larger flow penetration depth and intense flow mixing in permeable gravel-bed infer sufficient impetus for organized flow turbulence and damping of DA Reynolds shear stresses whereas; the wall-blocking in resin-casted gravel-bed prevents fluid infiltration which leads to follow the linear stress profile away from the crest level. The damping of DA Reynolds shear stress (RSS) is compensated by enhanced DA form-induced shear stress (FISS). The results are further analysed under the light of the energy budget to characterize the mass-momentum exchange as it penetrates the subsurface layers. The energy budget indicates negative pressure energy diffusion rates corroborating gain in turbulence production in the permeable gravel-bed stream.

PSIV-A-13 The relationship between breed-wide expected progeny differences, genomic predictors, and phenotypic values in mature Angus cows

Abstract For many years, selection for improved beef production centered on heavier weaning weights and more rapid post-weaning gain. More recently, measurement of post-weaning feed intake has facilitated direct improvement in feed efficiency in the feedlot. However, intake on a high concentrate diet is controlled by different biological mechanisms than intake on a high roughage diet. For this reason, the question remains whether an animal that efficiently converts calories from a high-quality concentrate-based ration similar to that of a feedlot diet where the expected progeny differences (EPDs) and genomic predictors (GPs) are developed would also be an efficient forage utilizer as a mature cow. To evaluate this relationship, we compared breed-wide EPDs and predictors to performance on a roughage diet and on a concentrate diet in mature cows. The objective of this study was to determine if EPDs and GPs developed and used in feedlots are applicable to commercial cow/calf producers utilizing forages and other roughages as the main diet ingredient. Data for this study were collected at Oklahoma State University from the fall of 2018 to the spring of 2021. Tissue samples from 64 mature Angus cows were submitted to Neogen for profiling according to genetic potential for 16 different traits. In each trial, retained energy (RE), dry matter intake (DMI), milk production (MILK), mature weight (MW), and average daily gain (ADG) were recorded and compared with the corresponding EPD and GP. Pearson correlations were determined between phenotypic values, GPs, and EPDs for both diets on each trial. No EPD or GP was significantly correlated to any measured trait on the forage diet. The DMI EPD was strongly correlated with DMI on a concentrate-based diet, however, did not predict DMI on a forage diet in mature cows. Based on the evaluations performed in this study, selecting for animals that perform well in the feedlot may be inadvertently selecting for mature cows that perform poorly on a typical mature cow diet of medium to low-quality forages.

Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs

BackgroundWith the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs. Behavior was recorded for 70 days after on-test at about 10 weeks of age and ended at off-test for 2008 female purebred pigs, totaling 119,812 day-wise records. Behavior traits included time spent eating, drinking, laterally lying, sternally lying, sitting, standing, and meters of distance traveled. A quality control procedure was created for algorithm training and adjustment, standardizing recording hours, removing culled animals, and filtering unrealistic records.ResultsProduction traits included average daily gain (ADG), back fat thickness (BF), and loin depth (LD). Single-trait linear models were used to estimate heritabilities of the behavior traits and two-trait linear models were used to estimate genetic correlations between behavior and production traits. The results indicated that all behavior traits are heritable, with heritability estimates ranging from 0.19 to 0.57, and showed low-to-moderate phenotypic and genetic correlations with production traits. Two-trait linear models were also used to compare traits at different intervals of the recording period. To analyze the redundancies in behavior data during the recording period, the averages of various recording time intervals for the behavior and production traits were compared. Overall, the average of the 55- to 68-day recording interval had the strongest phenotypic and genetic correlation estimates with the production traits.ConclusionsDigital phenotyping is a new and low-cost method to record behavior phenotypes, but thorough data cleaning procedures are needed. Evaluating behavioral traits at different time intervals offers a deeper insight into their changes throughout the growth periods and their relationship with production traits, which may be recorded at a less frequent basis.

An integrated simulation and optimization tool for short-term mining planning problems with different prioritization among competing plant targets

This work proposes a tool that integrates a hierarchical mixed-integer linear programming (MILP) model with a discrete event simulation (DES) model to simulate an annual mining plan discretized in shift-by-shift periods. The hierarchical MILP model has ten objectives and optimizes the shift schedule according to the available materials in the free faces at each simulation moment. The DES model simulates the realization of this schedule considering the uncertainties and interactions between the mine’s equipment. Four scenarios from a Brazilian mining company were analyzed. These differ regarding the prioritization order of the MILP goals and the plants’ grade tolerance. The results report that prioritizing the plant with the highest value-added product results in a 7.0% production gain. Additionally, prioritizing the particle size target of the plants leads to a 2.5% production gain compared to prioritizing the element grade targets.

Energy requirement for primiparous Holstein × Gyr crossbred dairy cows

Our objective was to estimate the requirements of metabolizable energy (ME) and net energy for the maintenance (NEm) of lactating and dry cows, the efficiency of ME utilization for milk production (kl) and tissue gain (kg), and the use of body energy mobilization for milk production (kt) throughout the lactation of primiparous crossbred Holstein × Gyr cows, using open-circuit respiration chambers. Twenty-nine primiparous Holstein × Gyr crossbred cows with an initial BW averaging 563 ± 40.1 kg and 2.5 ± 0.09 years old were used throughout lactation and dry periods. The cows were kept non-pregnant throughout the study to eliminate possible confounding factors. Apparent digestibility assays, followed by calorimeter measurements, were performed 6 times throughout the lactation period. In the dry-off period, the cows were also evaluated but fed with restricted intake (DMI = 1.1% BW/d) to achieve heat production close to maintenance. After 21 d of diet adaptation, an apparent digestibility assay followed by calorimeter measurements was performed. Parameter estimates for lactation period were obtained by mixed models including lactation stage as repeated measures. For restricted feeding at dry-off and fasting period assays, the requirements were estimated by exponential regression. For whole lactation, the values of MEm and NEm were 0.588 and 0.395 MJ/BW0.75, respectively. The efficiencies klkgkt were 0.672, 0.771, and 0.814, respectively. However, MEm and NEm were higher in early and mid-lactation than late, while kl was higher in early than other lactation stages. Dry and non-pregnant cows had MEm of 0.434 MJ/BW0.75 and NEm of 0.351 MJ/BW0.75 for maintenance level, and MEm of 0.396 MJ/BW0.75 and NEm of 0.345 MJ/BW0.75 for fasting metabolism level and efficiency of ME utilization for maintenance was 0.80. Our findings confirmed that F1 crossbred Holstein × Gyr dairy cows have differences in energy requirement and efficiency throughout the lactation stages, suggesting the use of different values in each stage. The estimated values of energy requirement for maintenance and efficiencies for primiparous lactating crossbred Holstein × Gyr were similar to those reported in the literature in specific studies and requirements systems.

Potential health and economic impact of achieving Kenya’s overweight and obesity reduction target: a modelling study

IntroductionKenya has adopted the WHO target of halting the rise of overweight, including obesity, by 2025. This paper assesses the potential impact of achieving the set target on health, healthcare...

Restoring degraded landscapes and sustaining livelihoods: sustainability assessment (cum-review) of integrated landscape management in sub-Saharan Africa

IntroductionLand degradation is a significant environmental challenge across sub-Saharan Africa. In recent decades, efforts have been undertaken, with varying successes, to rehabilitate degraded rural landscapes. However, there needs to be more evidence on the outcomes regarding enhanced productivity, environmental management, and socio-economic benefits.MethodsThis study uses a case study approach, using contrasting sites from Ethiopia and Mali to appraise restoration innovations implemented through various programs. Two distinct sites were chosen from each of the study cases, and an extensive literature search was conducted to document the evidence, focusing on the sustainability gains derived from integrated landscape management (ILM). For this, the sustainable intensification assessment framework (SIAF) was used, encompassing five domains, namely productivity, economic, environmental, social, and human condition, and featuring scales from plot to landscape, all facilitated by simplified yet robust indicators such as yield, soil loss, net income, land access, and food availability.ResultsResults highlighted a higher productivity gain (35% to 55%) and an improved socio-economic benefit (>20%). The ILM in the Ethiopian highlands enabled a significant improvement in wheat and barley yield (p < 0.01). Introducing new crop varieties integrated with the in-situ and ex-situ practices enabled diversifying crops across the landscape and significantly reduced runoff and soil loss (p < 0.05). By increasing the cultivable land by 44%, household income was increased by selling potatoes and agroforestry products. In Mali, ILM practices reduced soil loss to 4.97t/ha from 12.1t/ha. In addition to the improvements in the yield of sorghum and maize (33% and 63%, respectively), rehabilitating the once marginal and abandoned landscape in Mali enabled landless and female-headed households to work together, improving the social cohesion among the groups. The introduction of irrigation facilities enabled widowed women to increase household vegetable consumption by 55% and increase their income by 24%.DiscussionThe study showed positive evidence from ILM practices in the two contrasting landscapes. However, there is a need to address challenges related to the absence of timely data monitoring and documentation of successful practices. For this, the generation of evidence-based data and the use of advanced geo-spatial tools such as Remote Sensing and GPS-installed drones are recommended.

Energy Use Pattern and Economic Analysis of Fluted Pumpkin (Telfairia occidentalis) Production in Tillage Methods

The study investigates the energy use pattern and economic analysis of fluted pumpkin production in tillage methods (traditional, reduced-conventional and conventional). Human power, machinery, diesel fuel, fertilizers, seed and pesticides energy inputs were used during the cultivation of fluted pumpkin. Input and output energy analysis method was used to estimate the input and output energy in each of the tillage methods during the production of fluted pumpkin. The energy indices of fluted pumpkin production determined were; energy efficiency, energy productivity, specific energy, net energy and energy efficiency index. The economic analysis of fluted pumpkin production in terms of total cost of production, gross monetary return, net monetary return and cost benefit ratio for the three tillage methods used were determined. The total energy required per hectare in traditional, reduced-conventional and conventional tillage methods were 6899.90, 9206.16 and 10176.84 MJ/ha, while the output energy were found to be 8912.48, 12297.8 and 12297.8 MJ/ha, respectively. The energy efficiency, energy productivity and net energy gain of 3.97, 1.50 and 1.20; 0.76, 0.86 and 0.71 MJ/kg; 1.32, 1.20 and 1.40 MJ/ha, respectively were estimated while energy efficiency index were found to be 27, 47 and 20% for traditional, reduced-conventional and conventional tillage methods, respectively. The highest net monetary return and cost benefit ratio of ₦382,000.00k and 3.05 were estimated for reduced-conventional, ₦351, 600.00 k and 2.31 for conventional tillage, while the least values of ₦220, 000.00 k and 2.11 were recorded for traditional tillage method. The result revealed that reduced-conventional tillage was better than both traditional and conventional tillage methods in terms of energy productivity, net energy gain and energy efficiency index. Economically, production of fluted pumpkin under reduced-conventional tillage shows the highest net monetary return and cost benefit ratio compared to the other two tillage methods considered.

Air pollutant emissions caused by receiving international industrial transfer in Southeast Asian developing countries from 1990 to 2018

Receiving international industrial transfer (mainly foreign direct investment, FDI) is extremely important for economic development but also brings negative environmental impacts for Southeast Asian developing countries (SEADCs). Due to relatively low labor costs and large market potential, SEADCs have become an attractive destination for industrial transfer after China, while studies were far from sufficient on the associated air pollutant emissions that would worsen air quality and threaten human health. We develop an exploratory framework to estimate the long-term trends of relevant air pollutant emissions in eight major SEADCs, including Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. During 1990–2018, the emissions generally show a fluctuating upward trend and increased significantly in Cambodia, Laos, Philippines, and Vietnam. The total emissions of CO, NMVOC, SO2, NOX, PM2.5, and NH3 from the eight SEADCs increased from 19.0, 4.3, 3.6, 1.5, 0.5, and 0.4 kilotons (kt) to 391.6, 260.9, 271.1, 182.4, 48.4, and 12.2 kt, respectively. The emission growth in almost all SEADCs accelerated after 2008 and faster than FDI growth. The disparities in emissions among SEADCs basically grew first and then declined to a level lower than that of 1990, but generally exceeded the disparities in FDI. Productivity gain and emission intensity decrease primarily caused the emission growth and reduction, respectively. Relatively small reductions in emission intensity are found for NOX and SO2. In general, most SEADCs have utilized FDI for economic development without sufficient efforts on air pollutant emission controls. Our outcomes can inform the formulation and optimization of relevant policies reconciling economic development and air quality improvement in SEADCs.

Analysis of the Public Transport Efficiency, Productivity and Economies of Scale: The Case of Sfax – Tunisia

Abstract This study aimed to determine the efficiency and productivity of the production factors in the case of public transport in Sfax – the second most important agglomeration in Tunisia–. The analysis of factor productivity enabled identifying the shortcomings in the supply of this service and advocating certain strategies to boost supply. We use an estimation of the trans-logarithmic costs function with different restrictions while relying on the foundations of the microeconomic theory. We relied on annual statistical data from the Regional Transport Company in Sfax over the period preceding the COVID 19 crisis spanning from 1985 to 2018. The estimation results showed the presence of scale diseconomies, the gain in productivity over the years is too slow. The technical progress of public transport in Sfax is very low and the technical efficiency is also very limited. The results revealed that there is a decline in productivity growth due to a growing inefficiency throughout the study period. The underutilization of production capacities in the transport sector was judged as a consequence of excess of capacity and lack of efficiency attributed mainly to the lack of competition. The study identified some external factors that have an impact on the measured efficiency but are outside the company control. Public authorities should act on these factors to help companies improve their performance. A deregulation of the public transport sector by redefining the most important objectives has become urgent.

Integration of Floating Photovoltaic Panels with an Italian Hydroelectric Power Plant

The potential of applying a floating PV (FPV) system in an Italian context (namely, Cecita dam and Mucone hydroelectric power plants) is studied. The additional PV energy production, as well as the effect of non-evaporated water on the productivity of the hydropower plant, is analyzed by varying the basin surface coverage. The simulations highlight that the amount of additional hydroelectricity is quite small if compared to the non-FPV system, reaching about 3.56% for 25% basin surface coverage. However, the annual PV energy production is noticeable even at low coverage values. The expected gain in electricity production in the case of 25% basin surface coverage with the FPV plant rises to 391% of that of the actual hydropower plant. This gain becomes even larger if a vertical axis tracking system is installed and the increase is about 436%. The economic analysis confirms that the production costs (USD/kWh) of FPV systems are comparable to those of land-based PV (LBPV) plants, becoming smaller in the case that a tracking system is installed. In particular, the best solution is the one with 15% coverage of the lake. In this case, the levelized cost of electricity for the LBPVs is 0.030 USD/kWh and for the FVPs, with and without tracking, it is equal to 0.032 and 0.029 USD/kWh, respectively.

The sacred and profane in design: Exploring the transcendent nature of ordinary products

This paper explores how specific products transcend their utilitarian purposes, evoking profound consumer fascination. These objects, characterized by an elusive quality surpassing practicality, acquire deeper meaning and allure. At the core is the concept of the sacred, intertwining the ordinary with the extraordinary, resonating profoundly on a personal level. Despite historical religious associations, the sacred in design extends beyond religion, inviting exploration of inherent sanctity in everyday products. It unravels the complex interplay between the sacred and the profane in design, examining how ordinary products gain heightened significance and become secularly revered by consumers. By assessing dimensions contributing to design object sacredness, particularly in fostering product loyalty, it seeks to delineate criteria defining sacred properties using precise user comments and product examples. Ultimately, this exploration of the secular sacred aims to inspire designers to delve into objects’ profound potential, fostering a comprehensive understanding surpassing traditional religious associations in design.

The impact of the metaverse on e-commerce business models – A delphi-based scenario study

Despite the current buzz for the metaverse, its evolution has yet to be determined, and there is still a great deal of ambiguity, resulting in difficulties to forecast future opportunities. A deeper comprehension of the metaverse ecosystem is crucial to facilitate long-term planning and the dynamic adaptation of business models in the closely related e-commerce sector. Consequently, the main objective of this paper is to explore how the metaverse impacts e-commerce business models. A two-round Delphi-based scenario study (time horizon 2035) was conducted with 26 participating experts to achieve the objective. Based on the expert responses, twenty projections were clustered into three possible future scenarios: (1) immersive and emotional commerce, (2) altered digital landscape, and (3) game changer. The scenarios indicate that the metaverse development will strongly influence e-commerce business models at the customer interface and core strategy. New business models will emerge, and existing business models will adopt the metaverse as an additional channel. As purely digital products gain increased importance, the digital landscape will be altered to fulfill new customer requests. Although improbable by 2035, the game-changing scenario entails a complete transition to digital products and the replacement of present e-commerce with metaverse commerce.

Integrated Microbiome and Serum Metabolome Analysis Reveals Molecular Regulatory Mechanisms of the Average Daily Weight Gain of Yorkshire Pigs.

The average daily weight gain (ADG) is considered a crucial indicator for assessing growth rates in the swine industry. Therefore, investigating the gastrointestinal microbiota and serum metabolites influencing the ADG in pigs is pivotal for swine breed selection. This study involved the inclusion of 350 purebred Yorkshire pigs (age: 90 ± 2 days; body weight: 41.20 ± 4.60 kg). Concurrently, serum and fecal samples were collected during initial measurements of blood and serum indices. The pigs were categorized based on their ADG, with 27 male pigs divided into high-ADG (HADG) and low-ADG (LADG) groups based on their phenotype values. There were 12 pigs in LADG and 15 pigs in HADG. Feces and serum samples were collected on the 90th day. Microbiome and non-targeted metabolomics analyses were conducted using 16S rRNA sequencing and liquid chromatography-mass spectrometry (LC-MS). Pearson correlation, with Benjamini-Hochberg (BH) adjustment, was employed to assess the associations between these variables. The abundance of Lactobacillus and Prevotella in LADG was significantly higher than in HADG, while Erysipelothrix, Streptomyces, Dubosiella, Parolsenella, and Adlercreutzia in LADG were significantly lower than in HADG. The concentration of glutamine, etiocholanolone glucuronide, and retinoyl beta-glucuronide in LADG was significantly higher than in HADG, while arachidonic acid, allocholic acid, oleic acid, phenylalanine, and methyltestosterone in LADG were significantly lower than in HADG. The Lactobacillus-Streptomyces networks (Lactobacillus, Streptomyces, methyltestosterone, phenylalanine, oleic acid, arachidonic acid, glutamine, 3-ketosphingosine, L-octanoylcarnitine, camylofin, 4-guanidinobutyrate 3-methylcyclopentadecanone) were identified as the most influential at regulating swine weight gain. These findings suggest that the gastrointestinal tract regulates the daily weight gain of pigs through the network of Lactobacillus and Streptomyces. However, this study was limited to fecal and serum samples from growing and fattening boars. A comprehensive consideration of factors affecting the daily weight gain in pig production, including gender, parity, season, and breed, is warranted.

Techno-economic analysis and tri-objective optimization of a novel HDH desalination with PVT and vapor-compression chiller for sustainable water supply in remote areas

Desalination is a powerful tool for addressing freshwater scarcity. This study introduces a stand-alone desalination unit based on humidification-dehumidification, photovoltaic-thermal, and vapor-compression chiller technologies for providing sustainable water supply in remote areas. The system is evaluated from both technical and economic perspectives, and three refrigerants (R22, R134a, and R407C) are tested to determine the best option for the vapor-compression chiller. The system is comprehensively modeled using an artificial neural network trained for tri-objective optimization by employing a genetic algorithm. The optimization aims to maximize the freshwater production rate and gain output ratio while minimizing the cost rate. The results indicate that the photovoltaic-thermal unit comprises about 97% of the cost rate. At the optimum point, the freshwater production rates are 43.81 m3/day for R22, 40.56 m3/day for R407C, and 36.65 m3/day for R134a. The cost rates are highest for R407C at 48.04 $/h, followed by R134a at 45.72 $/h and R22 at 43.74 $/h. Similarly, the gain output ratio follows the same order, with R407C having the highest ratio of 1.28, followed by R134a with 1.27 and R22 with 1.24. The study concludes that R407C is the best option in terms of technical, economic, and environmental factors.

Implementing KAIZEN for Continuous Improvement in Manufacturing Processes: A Quantitative Analysis of Efficiency and Productivity Gains

Implementing KAIZEN for Continuous Improvement in Manufacturing Processes: A Quantitative Analysis of Efficiency and Productivity Gains

Is information and communication technology a productivity drain or gain? Evidence from the health services sector in China

This contribution investigates the impact of information and communication technology (ICT) on health service performance and considers the issue of income inequality. It provides empirical evidence that the development of ICT helps to mitigate the negative impact of income inequality on health and thereby providing support for the vigorous development of ICT. Specifically, by using the Driscoll-Kraay standard error estimation, Generalized Method of Moments, and a panel threshold model, a nonlinear relationship is detected, and the results show that: (1) ICT can significantly promote the performance of the health service sector. As income inequality increases, the effects of ICT on health care performance become larger. (2) With the increase from a lower to a higher income inequality level, the positive impact of ICT development on health service enables productivity to increase significantly. Finally, policy recommendations for promoting health service productivity, based on our theoretical contribution and empirical results, are provided.