Annual Usage Research Articles

The Epidemiology of Platelet-Rich Plasma Injections From 2010 to 2020 in a Large US Commercial Insurance Claims Database: A Recent Update.

The popularity of platelet-rich plasma (PRP) injections for the treatment of orthopaedic conditions has grown markedly. We sought to better define the trends in the usage of orthopaedic PRP injections across an insured US population over the past decade. The PearlDiver M91Ortho commercial administrative claims database was queried for all patients receiving PRP injections for orthopaedic conditions from 2010 through the first quarter of 2020 (Q1.2020). Trends in PRP use, reimbursement charges, demographics, joints injected, and administering physicians were assessed over time and reported as year-over-year (YOY) changes. Over the study period, 14,096 unique patients had 17,759 orthopaedic PRP injections. The number of PRP injections administered had a YOY increase of 7.1% (144 injections/year, 95% confidence interval [CI] = 89 to 199, Ptrend = 0.0009). A YOY increase of 895% was observed in total nonsurgical charges ($683,974/yr, 95% CI 441,504 to 926,444, Ptrend = 0.0009). The median age of PRP recipients increased (YOY change = +0.6 years, 95% CI 0.4 to 0.8, Ptrend = 0.0005). Injections to the elbow (YOY change = -0.8%, 95% CI -0.10% to [-0.06%], Ptrend = 0.005) and foot/ankle (YOY change = -1.0%, 95% CI -1.4% to [-0.06%], Ptrend = 0.002) decreased, whereas hip (YOY change = +0.4%, 95% CI 0.2% to 0.6%, Ptrend = 0.019), knee (YOY change = +0.9%, 95% CI 0.3% to 1.2%, Ptrend = 0.016), and spine (YOY change = +0.2%, 95% CI 0.0% to 0.4%, Ptrend = 0.033) injections increased. PRP injections given by sports medicine orthopaedic surgeons (YOY change = +0.8%, 95% CI 0.6% to 1.2%, Ptrend <0.0001) increased over time, whereas those by general orthopaedic surgeons decreased (YOY change = -0.9, 95% CI -1.2 to [-0.6%], Ptrend = 0.001). PRP injections quadrupled in prevalence from 2010 to Q1.2020, with a projected increase in annual usage in this data set of 66% by 2030. As greater evidence-based indications for PRP use are identified, more specialists and insurance providers may consider expanding their involvement in this growing field. III, retrospective cohort study.

Tokat İli İkinci El Pazarındaki Traktörlerin Teknik ve Ekonomik Özelliklerinin Belirlenmesi

In this study, it is aimed to determine the technical and economical specifications of the used tractors put to sale in Tokat province and its districts, such as rated engine power, age, usage hours, tractor structure, maintenance and repair requirements and sale price. Also, it is intended to reveal the tendencies of farmers in tractor demand. The technical and economical specifications of used tractors in the second-hand tractor market in Tokat province and its districts has been analysed. For this purpose, all data has been collected from tractor owners through face-to-face interviews for a total of 408 tractors in 7 districts. According to the data, generally the tractors are standard type, and their age range is between 1 and 58. Based on the data collected from tractor owners, the average annual usage time of the tractors for Tokat is 268 hours, and the average rated power is 58.5 HP (43.6 kW). The remarkable sale reasons of used tractors are model obsolescence, insufficient capacity and need for cash respectively. In the second-hand tractor market, the age of the tractors, rated engine power, brand, usage hours and other technical specifications are primarily factors about pricing. Although 41% of the tractors in the sale have almost completed their lifespan, it has been determined that they can be preferred to some extent. It has been also revealed that tractors with very good service network and tractors that tractor owners can find buyers with the price that they want to sale are most common tractor types in the market. In addition, it is thought that the farmers’ awareness should be developed because they tend to make unconscious buying and selling decisions.

Performance characteristics of a waste-heat recovery water-source heat pump system designed for data centers and residential area in the heating dominated region

Data centers (DCs) have been increasingly constructed owing to the increasing demand for data storage. The performance of the cooling system for DCs should be improved for energy saving owing to a large amount of energy consumption for cooling. A residential area (RA) consumes a large amount of energy for heating, especially in the heating dominated region. A novel waste-heat recovery water-source heat pump (WSHP) system is proposed for the combination of the DC and RA to reduce energy consumption by recovering waste heat from the DC and to suppress the freezing risk of water during the heating season. The performance characteristics of the waste-heat recovery WSHP system were analyzed based on various perspectives including energy consumption and environmental impact. Consequently, the annual average power usage effectiveness for the DC and the system coefficient of performance for the RA showed a significant improvement compared to the conventional system; accordingly, the energy consumptions of the DC and RA decreased by 12.3% and 31.2%, respectively. The energy consumption of the DC decreased by 64.4% in March, and that of the RA reduced by 48.2% during the heating season, which led to an 18.8% decrease in total annual energy consumption of the proposed system. Additionally, the risk of freezing in the evaporator of the WSHP was substantially suppressed under cold winter conditions, increasing the system reliability; the water temperature at the evaporator outlet was maintained at 8–12 °C owing to the waste heat absorbed from the DC. Based on the lifecycle climate performance (LCCP) analysis, the proposed system showed a 28.7% reduction in total CO2 emissions compared with the conventional system. The proposed system can be a good option for reducing the energy consumption and for enhancing system reliability through the combination of the DC and RA. • A waste-heat recovery water-source heat pump system is proposed. • The proposed system is applied to the combination of data center and residential area. • The proposed system reduces energy by 12.3% (data center) and 31.2% (residential area). • The proposed system shows a 28.7% reduction in total CO 2 emissions. • The proposed system improved system reliability by suppressing freezing risk.

Rainwater Harvesting for Urban Landscape Irrigation Using a Soil Water Depletion Algorithm Conditional on Daily Precipitation

The supply of various non-potable water usages based on the harvesting and management of rainwater in urban areas allows to save high-quality water resources for strictly potable use and to limit the squandering of precious freshwater resources. A rainwater harvesting system included in a reconversion project of a former military area located in the town of Genova (Italy) is examined. Rainwater is collected and used for the landscape irrigation of public areas. Three rainwater collection scenarios are considered while varying the size of the storage tank, using daily rainfall data from a local long-term record as the reference rainfall climatology. A behavioural model is adopted to simulate the operation of the rainwater harvesting system and improved with a dedicated algorithm to account for the actual soil water availability for the vegetation and its temporal decay, based on the specific soil type and vegetation. For each scenario/tank size combination, reliability indices are calculated and compared, while the detention time and the annual usage volume per unit tank capacity are used as indicators of water quality deterioration in the tank and the economic benefit associated with the exploitation of the resource. The best solution in terms of rainwater collection scenario and tank size is identified.

A methodology to estimate space heating and domestic hot water energy demand profile in residential buildings from low-resolution heat meter data

This article presents a new methodology to disaggregate the energy demand for space heating (SH) and domestic hot water (DHW) production from single hourly smart heat meters installed in Denmark. The new approach is idealized to be easily applied to several building typologies without the necessity of in-depth knowledge regarding the dwellings and their occupants. This paper introduces, tests, and compares several algorithms to separate and estimate the SH and DHW demand. To validate the presented methodology, a dataset of 28 Danish apartments with detailed energy monitoring (separated SH and DHW usage) is used. The comparison shows that the best method to identify energy demand data points corresponding to DHW production events is the so-called “maximum peaks” approach. Furthermore, the best algorithm to estimate the SH and DHW separately is a combination of two methods: the Kalman filter and the Support Vector Regression (SVR). This new methodology outperforms the current Danish compliances typically used to estimate the annual DHW usage in residential buildings.

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. The interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

Selective inventory classification using ABC classification, multi-criteria decision making techniques, and machine learning techniques

The Selective Inventory Classification has popularity in industries due to its virtue of obtaining higher returns by focusing on the small group of inventories than all the thousands and lakhs of components. ABC classification is the most popular traditional technique which utilizes annual usage value for grouping components into A, B and C categories. However, a more accurate classification should be carried out as other parameters are also essential along with cost. So, these other criteria along with usage value are essential while categorizing the components. Hence along with ABC, multi-criteria decision-making techniques and machine learning models are applied on three parameters i.e., usage value, lead time, and unit cost. In the MCDM techniques, the A. Hadi-Vencheh model is applied for the selective classification of inventory. The K-Means clustering algorithm is also applied to cluster the items. The result of the K-Means clustering algorithm is compared to the traditional technique and multi-criteria decision-making techniques. The K-Means showed promising results when compared to MCDM techniques. The percentage accuracy of the comparison showed that K- Means clustering algorithm can be used for millions of items and gives fairly accurate results. The main advantage of the Machine Learning Algorithm is that it can handle large data efficiently. The Classification given by the algorithm also follows the Pareto rule which is the base for ABC Classification. The finding suggests the possibility of K-Means clustering Algorithm for inventory classification and the use of the algorithm will help in skipping the calculations specified in the MCDM technique. The accuracy of the algorithm can be further increased by altering the parameters.

A Study of the Agricultural Water Supply at the Hoengseong Dam Based on the Hydrological Condition of the Basin

Since South Korea relies on dams and agricultural reservoirs for approximately 45% of its annual agricultural water usage, the supply control of agricultural water based on its usage amount is essential for effective water resources management. The objective of the study, therefore, is to suggest an alternative to the agricultural water supply from the Hoengseong Dam using the threshold curve of usage record that was suggested in the previous study. The characteristics of agricultural water usage and Usage Rate compared to the Permission amount (URP) threshold curve of the Seom River basin, which is defined as the thresholds of the maximum usage rate of agricultural water in each hydrological condition, were derived and analyzed using the historical record of runoff and agricultural water usage. The agricultural water supply of the Hoengseong Dam was simulated from 2006 to 2021 according to the URP threshold curve. As a result, it was found that the agricultural water usage rate of the Seom River Basin can be up to 106.5% even with the average hydrological condition compared to normal years. It was also shown that about 1.7 million m3 of agricultural water could be stored by applying the URP threshold curve to the agricultural water supply of the Hoengseong Dam annually.

Cost Economics of Tractor Drawn On-farm Mobile Turmeric Steam Boiler

Turmeric is an important commercial spice crop grown in India since ancient times and named as “Indiansaffron”. In India during 2019-20, about 2.54 lakh ha (6 lakh acre) area and in the State of Telangana about55,443 ha (1.37 lakh acre) was covered under turmeric. The post harvesting operations of turmeric rhizomesare boiling, drying, polishing and pulverization. Among all these operations boiling is more difficult andlabour oriented. The quality of turmeric is depending upon time and method of boiling. The separatedrhizomes must be boiling within two to five days otherwise it will effect on the quality. In the traditionalmethod of boiling, the rhizomes are not cooked uniformly and injuries may be occurred by rubbing andbruising of rhizomes while taking out from the vessel. Due to lack of labour availability, the farm operationscould not be carried out in time and especially for turmeric during harvesting and boiling season. Toaddress all these problems, popular tractor drawn turmeric steam boiler was identified to reduce the cost ofoperation and labour for the benefit of the farmers.The cost economics of the machine and payback periodof turmeric steam boiler was calculated. During the operation, the fuel cost and total operating cost of themachine was estimated as 1575Rs. h-1 and 1898.28 Rs. h-1 respectively. The break-even point of turmericsteam boiler was estimated as 78.17 hour per year with the annual usage of machine was taken as 480 hourper year. From results, the annual utility and payback period were obtained as 720 tonnes per year and 1year respectively.

Evaluation of Environmental Pollution of Housing Industry and Introduction of Modern Methods of Construction

Using data compiled from Powell's and Rosa's research on the CO2 emissions generated by houses at different stages of their lives, the paper examines and analyses the UK's externalities generated by residential properties and their environmental impacts. The paper also estimates that a single house's scale of ecological externalities is equivalent to 270 tonnes of carbon emissions. In the second half of the research, the paper focuses on the MMC construction system, which Innerspace Ltd initially introduced. On average, MMC homes reduce CO2 and annual Kw usage by c60% below current building regulations. By analysing company financial data and market status, research concludes that the sustainability of the MMC system and its accessibility for providing a more environmentally friendly and cost-effective in the UK.

User Perception on Disclosure: A Comparative Analysis of Public and Private Banks in Ethiopia

This study investigates the views and perceptions of users on disclosure and the extent of disclosure by the Ethiopian banking sector. The data collected from 509 respondents in different groups of information users were analyzed using percentage, mean and kruskal-wallis H test. The result shows that most of the user groups regard annual reports as the most important source of information and income statements as an important section of annual reports. The majority of the user groups attached the highest ranking for the relevant attribute for the annual reports and delay in publishing annual reports as the most serious problems. The users of information perceive that a public bank discloses more information with better quality than private banks and the analysis of annual reports also disclose the same results. The Kruskal-wallis H test shows that there was a significant difference among user groups on the frequency of annual report usage, purposes of annual reports, sources of information, the significance of the problems, and sections of annual reports.

Experimental safety analysis of transplanting device of the cam-type semi-automatic vegetable transplanter

A transplanting device is a part of a vegetable transplanter that performs a key role and receives a large load during the transplanting work. The load characteristics affect the static and dynamic safety of the transplanting device. The aim of this research was to experimentally investigate the load and safety of the transplanting device of the cam-type semi-automatic vegetable transplanter commonly used in Korea. A strain-based load measurement system was constructed using 15 strain gauges attached to selected measurement spots on the transplanting device. Field tests were conducted at 4 levels of engine speed and 12 levels of planting distance. Measured strain data were converted into stress values to analyse the static safety factor and fatigue life of the transplanting device. The results showed that the stress acting on the transplanting device tended to increase with the increase in the engine speed or the decrease in the planting distance. The static safety factors of the transplanting device under various working conditions were greater than 1.0 for all the measurement spots. The minimum fatigue life was 66,416 h at the upper side of the hopper which is sufficient lifetime, considering 25.5 h of annual usage time in Korea.

A Scatter Search Algorithm for Multi-Criteria Inventory Classification considering Multi-Objective Optimization

Inventory management requires thousands or millions of individual transactions each year. Classification of the items influences the results of inventory management. Traditionally, this is usually classified with considering an annual dollar usage criterion but maybe other criteria such as lead time, criticality, perishability, inventory cost, and demand type can be affected on that classification. Inventory items that have more than one criterion are discussed under multi-criteria inventory classification (MCIC) methods in the literature. In this paper, the MCIC problem is considered with two objectives as follows: (1) minimization of total inventory relevant cost and (2) minimization of the dissimilarity index. The proposed Mixed Integer Nonlinear Programming (MINLP) model of the MCIC problem is formulated using Scatter Search Algorithm (SSA). The suggested multi-objective optimization problem is solved using LP-metric, ɛ-constraint and weighted sum method. Pareto optimal solutions are obtained according to these different methods and selected best method by using deviation index. Scatter Search Algorithm provides high-quality solutions within reasonable computation times. The proposed model generated a Pareto frontier solution with the maximum satisfaction level and minimum distance from ideal point. Finally, the proposed model is implemented with two numerical datasets to show the performance of its efficiency and compared our results with other studies in the previous literature.

Framework for Plastic Waste Management

Plastic pollution has become a global problem. Around 3.3 million tons of plastic are wasted annually, with an annual plastic product usage growth rate of 15%. The recycling sector is unstructured, policies at the state level are non-existent to address plastic waste management. Pakistan, as a developing country is also turning towards circular economy practices to benefit businesses and the environment. This case study is done with support from SPEL and aims to perform a systematic literature review, analyzing the present frameworks followed by developed countries for the implementation of CE in developing countries, its critical analysis for the gaps to achieve sustainability in view of UN SDGs 2030 along with the study of factors impacting PWM. The findings showed that the current system is primarily focused on garbage collection and transportation with very little focus on its management. Religion, culture, educational awareness, and psychology can play moderating roles in implementing CE practices. It will provide a conceptual framework that can be implemented by SPEL.

The water footprint of hydraulic fracturing under different hydroclimate conditions in the Central and Western United States

The oil and gas (O&G) exploitation via hydraulic fracturing (HF) has augmented both energy production and water demand in the United States. Despite the geographical coincidence of U.S. shale plays with water-scarce areas, the water footprint of HF under drought conditions, as well as its impacts on local water allocation, have not been well understood. In this study, we investigated the water consumption by HF activities under different hydroclimate conditions in eleven O&G-producing states in the central and western U.S. from 2011 to 2020. Our results show that the water consumption under abnormally dry or drought climates accounted for 49.7 % (475.3 billion gallons or 1.8 billion m3) of total water usage of HF, with 9 % (86.1 billion gallons or 325.9 million m3) of water usage occurring under extreme or exceptional drought conditions. The water usage of HF under arid conditions can translate to high densities of water footprint at the local scale, equivalent to >10 % and 50 % of the annual water usage by the irrigation and domestic sectors in 6–29 irrigation-active counties and 11–51 counties (depending on the specific year), respectively. Such water stress imposed by O&G production, however, can be effectively mitigated by the reuse of flowback and produced water. Our findings, for the first time, quantify the water footprint of HF as a function of hydroclimate condition, providing evidence that the water consumption by HF intensifies local water competition and alters water supply threatened by climate variability. This renders wastewater reuse necessary to maintain water sustainability of O&G-producing regions in the context of both a rising O&G industry and a changing climate.

Seasonal Distribution of the Fin Whale (Balaenoptera physalus) in Antarctic and Australian Waters Based on Passive Acoustics

The fin whale is listed as globally vulnerable, with ongoing threats to their population, yet little is known about the distribution and movements of the Southern Hemisphere sub-species, Balaenoptera physalus quoyi. This study assesses fin whale distribution in the Southern Hemisphere analysing acoustic recordings from 15 locations in Antarctic and Australian waters from 2002 to 2019. A seasonal acoustic presence of fin whales in Antarctic waters from late austral summer to autumn (February to June) with long-term, consistent annual usage areas was identified at the Southern Kerguelen Plateau and Dumont d’Urville sites. In comparison, limited vocal presence of fin whales was observed at the Casey site. In Australian waters, fin whales were seasonally present from austral autumn to mid-spring (May to October) on east and west coasts, with a decadal pattern of acoustic presence observed at Cape Leeuwin, WA. Two migratory pathways are identified, from the Indian sector of Antarctica to the west coast of Australia and from the Pacific sector of Antarctica to the east coast of Australia. The identified seasonal distributions and migratory pathways provide valuable information to aid in monitoring the recovery of this vulnerable sub-species. We suggest the identified distribution and dispersal from the Southern Kerguelen Plateau and Dumont d’Urville sites to the west and east coasts of Australia respectively, as well as the spatial separation between Antarctic sites, provide preliminary evidence of separate sub-populations of the Southern Hemisphere sub-species of fin whale.

Power usage effectiveness analysis of a liquid-pump-driven hybrid cooling system for data centers in subclimate zones

Free cooling technology can effectively reduce the cooling energy consumption of data centers, but its energy efficiency is greatly affected by regional and meteorological conditions. This study investigates the liquid-pump-driven free cooling/mechanical refrigeration hybrid cooling system of a data center with 40 racks through a demonstration case and tests. The annual hourly energy efficiency in 20 subclimate zones and 37 typical cities in China of the hybrid cooling system designed with 5 and 10 °C temperature differences was analyzed with different meteorological parameters. The annual power usage effectiveness (PUE) values corresponding to the energy efficiency ratio (EER) in different regions were presented. Results showed that the annual average EER of the liquid-pump-driven free cooling mode was 7.07–14.18, and the annual average EER of the hybrid system was 4.22–14.10 when the temperature difference was 5 °C. The annual average EER range and the design temperature difference of the hybrid system for different climate regions were recommended. The PUE values of other regions, except for Guangzhou and Haikou, were lower than 1.40. The results provide references for the EER and PUE of the hybrid system in different climate regions.

Microplastics from face masks: A potential hazard post Covid-19 pandemic.

The tremendous use of plastic products to averse the infection rate during Covid-19 pandemic has developed great pressure on the management and disposal systems of plastic waste. The compulsory use of face masks to curb the infection and prevent transmission of the virus has led to addition of millions of face masks into the terrestrial and marine environment. The current study attempts to assess and quantify the rate of infection in coherence with the annual usage of face masks in various nations across the globe. The ecological footprint of the plastic waste generated from used and discarded face masks along with their potential impacts have also been discussed. The current study has quantified the total annual face masks across thirty-six nations to be more than 1.5 million ton. The total estimated figure for annual plastic waste and microplastics in all these nations was ∼4.2 million tonnes and 9774 thousand tonnes, which emerges as a great threat to the global efforts towards reduction of plastic usage. The emergence of Covid-19 pandemic has modified the living habits with new enterprises being set up for Covid essential products, but the associated hazard of these products has been significantly ignored. Hence this study attempts to present a quantitative baseline database towards interpretation and understanding of the hazards associated with microplastics and increased dependence on plastic products.

Pediatric VAD Growth in the US: What Factors May Be Driving Growth Jumps?

<h3>Purpose</h3> As the use of pediatric ventricular assist device (VAD) support has grown in the US, the rate of growth has not been linear. Instead, growth has occurred in spurts. We sought to analyze growth spurts in pediatric VAD use to determine what factors may be influencing increases in VAD utilization in the US. <h3>Methods</h3> OPTN data were used to identify all children ≤18 years listed for heart transplant between 2009 and 2019 including the proportion supported with a VAD at some point during the waiting period. VAD growth spurts were identified based on direct inspection of the annual implant volume trends. Factors independently associated with VAD growth spurts were identified using multivariable regression techniques. <h3>Results</h3> Among 6,940 children who met the inclusion criteria, 769 received a VAD. Annual VAD implant growth is depicted in the Figure. Two distinct periods of rapid growth were identified, the first between 2011 and 2012, where annual usage at listing jumped 75% and the second between 2016 and 2017, where annual usage at listing increased by 36% and was sustained. Regression analyses suggest that the 2011-12 jump was driven by increased implants among infants with the Berlin Heart while the 2016-2017 jump was observed in older children, especially ages 4-6 years, and associated with several factors including growth in use of the PediMag/CentriMag system, Heartmate III, introduction of bivalirudin anticoagulation, and UNOS revisions favoring VAD over milrinone to achieve 1A status in cardiomyopathy patients. Minimal change appears related to increase of VAD implants in children with congenital heart disease. <h3>Conclusion</h3> Over the past 10 years, pediatric VAD growth has been non-linear, accelerating more rapidly at specific time periods. The 2012 jump appears driven by Berlin Heart approval and use in infants, whereas the jump beyond 2016 appears related to a variety of factors including expansion of pump options, anticoagulation strategies and potentially the 2016 UNOS allocation revisions.

Techno-economic analysis of rooftop solar power plant implementation and policy on mosques: an Indonesian case study

Indonesia is pushing the implementation of renewable energy to meet its climate action target. Solar energy is abundant, and its utilization is prioritized, including rooftop solar power plant (RSPP). This research presents a techno-economic analysis of an RSPP installed in a mosque in Ngombol subdistrict, Purworejo district, Central Java, Indonesia. This article also introduces and explains the regulation of RSPP and electricity tariffs in Indonesia, which define the economics of RSPP. This study employs an operational and financial model to analyze RSPP in five scenarios. The RSPP design objective is to reduce the annual energy usage of the mosque and yield the highest Net Present Value (NPV). According to the result, RSPP at all configurations based on the type and number of panels yield negative NPVs at the current electricity tariff, costs of components, and regulations implemented concerning RSPP. Proposed policy adjustment modeled through different scenarios provide benefit to some extent, limited by other policies. Hence, a combination of different policy adjustments may be required to achieve the most optimal condition for RSPP implementation on the mosque rooftop. This study could help policymakers to understand the possible directions of policy design for faster PV implementation.