This study aims to develop a performance evaluation system that can facilitate performance evaluation at region, hospital, and department levels to enable better cost management for sustainable development. A multi-level system of performance evaluation informs a hierarchical assessment of cost management from regions to hospitals to departments using diagnosis-related group (DRGs). Various metrics are developed employing the variances between targets and actuals where targets are determined from two perspectives: benchmarking using external regional prices and change management using internal data. Targets for the latter are statistically based and specifically incorporate variability. The model is applied to two hospitals, twenty departments, nine DRGs and 1071 inpatients. The analyses indicate that the approach can provide a practical evaluation tool that allows for particular characteristics at multiple levels. The system provides macro-micro and external-internal perspectives in performance, enabling high-level variances to be decomposed thereby identifying sources of performance variability and financial impact.

In order to evaluate the economy of superhighway, on the basis of the analysis of the cost of the ordinary expressway and high speed railway, the cost of superhighway is estimated. On this basis, the standard of the toll of superhighway at all levels is determined by reference to the standard of the construction cost and the toll collection standard of the ordinary expressway. According to the toll collection standard of superhighway and the fuel consumption cost of superhighway at all levels, the cost of single car and the single person cost of superhighway are calculated. Based on the analysis of highway passenger transport, railway passenger transport and civil aviation ticket price, the single person cost per kilometer of the above travel modes is calculated and compared with the single person travel cost per kilometer of superhighway. The results show that the single person cost of superhighway is between 0.29 and 0.47 yuan /km, which is 0.28 yuan /km higher than the highway bus, 0.18 yuan /km higher than the ordinary expressway self driving and 0.23 yuan /km higher than the express train, but 0.78 yuan/km lower than that of the first class seat of high-speed train, and is 0.92 yuan/km far lower than that of civil aviation flight economy class and 2.42 yuan/km lower than the business class. Therefore, the superhighway trip has certain advantages in economy.

The importance of this study may be defined by using the smart techniques to earned value indicators of residential buildings projects in Republic of Iraq, only one development intelligent forecasting model was presented to predict Schedule Performance Index (SPI), Cost Performance Index (CPI), and To Complete Cost Performance Indicator (TCPI) are defined as the dependent. The approach is principally influenced by the determining numerous factors which effect on the earned value management, that involves Iraqi historical data. In addition, six independent variables (F1: BAC, Budget at Completion., F2: AC, Actual Cost., F3, A%, Actual Percentage., F4: EV, Earned Value. F5: P%, Planning Percentage., and F6: PV, Planning Value) were arbitrarily designated and satisfactorily described for per construction project. It was found that ANN has the capability to envisage the dust storm with a great accuracy. The correlation coefficient (R) has been 90.00%, and typical accuracy percentage has been 89.00%.

This retrospective study aimed to evaluate the performance of the hormone treatment protocols, determine the factors associated with pregnancy success after hormone treatment, and compare the cost-efficiencies of two types of hormone treatment among cyclic and noncyclic anestrous dairy cows. The clinical records of 279 anestrous cows who received hormone treatment for artificial insemination (AI) from 64 herds in the western region of Thailand were obtained from Kasetsart University Veterinary Teaching Hospital from January to August 2017. The performance of the hormone treatment protocols, fixed-time AI (TAI) and estrus detection before AI (EAI), showed that the pregnancy risk for the TAI protocol was higher than for the EAI protocol, but pregnancy per AI did not differ significantly between the two protocols in cyclic and noncyclic cows. Multivariate logistic regression analysis showed that cows receiving the TAI protocol were more likely to be pregnant compared to those treated with the EAI protocol. Cows with a 3.00 body condition score (BCS) <3.75 after treatment and loose-housing cows were more likely to become pregnant. Treatment during winter showed higher pregnancy success than in the summer and rainy seasons. The cost-efficiency analysis showed that the TAI protocol was the most cost-efficient option for noncyclic cows, whereas the EAI protocol was the most cost-efficient option for cyclic cows.

In the last two decades, the continuous ever growing demand for energy has determined a significant development in the production of photovoltaic (PV) modules. Anyway, a critical and very important issue in the module design process is the adoption of suitable encapsulant materials and technologies for cell embedding. Therefore, adopted encapsulants have a significant impact on modules efficiency, stability and reliability, and to ensure the unchanged performance of PV modules in time, the encapsulant materials must be selected properly. The selection of encapsulant materials must maintain a good balance between the encapsulant performance in time and costs, related to materials production and technologies for cells embedding. However, the encapsulants must ensure excellent isolation of active photovoltaic elements by the environment, preserving accurately the PV cells against humidity, oxygen and accidental causes that may compromise the PV modules function. This review provides an overview of different encapsulant materials, their main advantages and disadvantages in adoption for PV production, and also in relation to used encapsulant technologies for cell embedding, additives and the interaction of these materials with other PV components.

Risk management strategies protect the company as a whole as well as employees from unforeseen financial impacts. As in the case of personal finance, preparing for certain scenarios helps to face any difficulties that the company may encounter and allows it to get out of this impasse.For any project to be successful, the way the project executing agency will deal with potential risks must be determined so that it can identify, mitigate or avoid problems when it needs to do so. Successful project managers realize that risk management is important, because the achievement of project objectives depends on planning, preparation, results and evaluation that contribute to the achievement of strategic goals, especially the sustainable development of societies.Risk management strategies work to protect the company as a whole as well as employees from unexpected financial effects, and as is the case in personal finance, preparing for certain scenarios helps to face any difficulties that the company may face and allows it to get out of this impasse.To ensure the success of your project, determine how you will handle potential risks so that you can identify, mitigate or avoid problems when you need to do so. Successful project managers understand that risk management is important, because the achievement of project objectives depends on planning, preparation, results, and evaluation that contribute to the achievement of strategic objectives.

Osteoarthritis (OA) is the degeneration of cartilage in joints that results in bones rubbing against each other, it causes uncomfortable symptoms such as pain, swelling, stiffness, and can lead to disability. It usually occurs in the elderly and causes a large medical burden. The aim of this study is to evaluate cost-effectiveness between the standard treatment for osteoarthritis and the standard treatment with added crystalline glucosamine sulfate at various stages. The Markov analysis modelling was applied to evaluate the effect of both adding glucosamine compared to standard treatment from a societal perspective during whole patients’ lifetimes. Data input was collected by review in previous studies. The outcome was measured in quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) from a societal perspective was ap-plied with 3%-discounted for all cost and outcome. One-way analysis via Tornado diagram was performed to investigate the change of factors in model. In general, the adding glucosamine into the standard treatment proved to be more cost-effectiveness compared to the standard treatment. Particularly, early stage adding glucosamine in the treatment was cost-effectiveness then post-stage adding glucosamine. The addition of supplementing crystalline glucosamine sulfate to whole regimen at any stage was cost-effectiveness at willingness-to-pay (WTP) threshold

There is increasing interest in automating train operations of mainline services, e.g. to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but not implemented on a large scale. Before the general introduction of new or adapted technologies can have a transformative effect on the operation of such a complex system as train operation on mainlines, they have to pass functional, interoperability and performance tests. A virtual preliminary analysis is one way to ensure a smooth as well as safe introduction and implementation. This paper aims to present an approach that applies to the performance testing of ATO systems. Therefore, methods and test standards for technologies enabling automatic operation in other transport sectors are reviewed. The main findings have been adapted, transformed and combined to be used as a general strategy for virtual performance testing in the railway sector. Specifically, universal performance indicators, namely punctuality, accuracy, energy consumption, safety and comfort, are presented. A layer model for scenario description is adapted from the automotive sector, as well as the definition of different scenario types. Lastly, factors that can influence the performance of an ATO algorithm are identified. To demonstrate the developed approach, a straightforward investigation of a case study is conducted using a microscopic train simulator in combination with an ATO algorithm.

This paper introduces an advanced method that integrates contingent valuation and machine learning (CVML) to estimate residents’ demand for reducing or mitigating environmental pollutions and climate change. To be precise, CVML is an innovative hybrid machine-learning model, and it can leverage a limited amount of survey data for prediction and data enrichment purposes. The model comprises of two interconnected modules: Module I, an unsupervised learning algorithm, and Module II, a supervised learning algorithm. Module I is responsible for grouping the data into groups based on common characteristics, thereby grouping the corresponding dependent variable, whereas Module II is in charge of demonstrating the ability to predict and the capacity to appropriately assign new samples to their respective category based on input attributes. Take a survey on the topic of air pollution in Hanoi in 2019 as an example, we found that CVML can predict households’ willingness– to– pay for polluted air mitigation at a high degree of accuracy (i.e., 98%). We found that CVML can help users reduce costs or save resources because it makes use of secondary data that is available on many open data sources. These findings suggest that CVML is a sound and practical method that could be widely applied in a wide range of fields, particularly environmental economics and sustainability science. In practice, CVML could be used to support decision-makers in improving the financial resources to maintain and/or further support many environmental programs in years to come.

Almost all single-family detached house in Canada consume huge electricity for space heating and domestic hot water (DHW) purposes. There are many possibilities to design an energy-efficient house. A solar water heating system can be used for domestic water and space heating. Water temperature can be kept constant always by connecting a heat pump or oil burner because solar energy is intermittent. Proper and optimized solar photovoltaic and collector design, tank design, heat pump selection, house insulation, total demand calculation in each section are essential. Energy-Efficient house design has been proposed with water heating and space heating system and compared with the existing system, solar PV based systems, and solar collector based system. The tracking and non-tracking based solar thermal collector based and the solar photovoltaic based system has been compared in this paper and investigate the suitable one for practically applicable and acceptable by the people. Simulation has been done by using the PolySun software. It found that by implementing the proposed PV based system with tracking is highly suitable considering lower cost, high output power, flexibility, easy installation.

The paper highlights the performance of the seismic isolation devices, installed on retrofitted buildings in reducing the seismic response when subjected to earthquakes. Two buildings from the beginning of the XX-th century in Bucharest are chosen from many more, monitored over the city area. We discuss the response of these base-seismic isolated structures, relying on good quality data acquired from the recent strong earthquake (03.11.2022, MW = 5.0). Elastic response spectra computed from recordings at two levels of each structure are used, placed under and right above the isolating layer. At one building the existence of previous recordings and the particularity of the sensors allow a comparison with other two relatively recent medium intensity earthquakes. The assessment is carried out in terms of maximum acceleration amax, measured at certain levels in each structure, spectral acceleration amplitude SAmax and spectral-peak corresponding period. We find that the base-isolation methodology is effective in reducing the response of the building right above the isolating layer, an observation valid for both structures, all components of the recordings, and spectral acceleration values. Moreover, the outcomes from the modal evaluation performed prior to rehabilitation and seismic isolation process are presented, by pointing out a higher newly acquired fundamental period of the isolated structures.

A lack of trust in Energy Service Company (ESCo) is the most critical factor affecting the development of Energy Performance Contracting (EPC) in China compared with other constraints. One cannot easily estimate the energy-saving performance of an EPC project. Under that condition, lack of trust may cause the Energy-Consuming Unit (ECU) to suspect the energy-saving performance promised by the ESCo, thus leaving potentially profitable projects without necessary funding. Currently, specific studies taking an across-projects viewpoint on annual energy-saving performance of EPC projects in multiple subsectors objectively and quantitatively are lacking. This paper studies the regression relationships of annual energy-saving quantity in terms of revamping cost and the regression relationships of annual cost saving in terms of revamping cost. The regression results show that there are statistically significant correlations in the above relationships in the nine subsectors investigated. This is significant for ESCos and ECUs because knowledge on energy-saving performance could contribute to EPC investment decisions and trust relationships between ESCos and ECUs. Then a multiple linear regression model of revamping cost is set up to analyze its influencing factors. The model indicates that the subsector the sample belongs to, financing, registered capital of the ESCo, and contract period have significant effects on revamping cost. Thus, policy implications regarding innovation of EE promotion technology, clarifying ESCos’ exit mechanism, innovation of financing mechanism, and improving the market credit environment for promoting investment in EPC projects are provided.

The stormwater drainage problem is one of the major challenges facing in Shire Endaslasse town, Ethiopia. In a town, Street flooding and overtopping drainage system problems are occurring during the rainy season. This causes ponding which poses difficulties in ease of transportation and it hinders the day-to-day activity of the people. So, the study focuses on the performance of the stormwater drainage system in Shire Endaslasse town using Arc GIS and SWMM5.1. For this study, the primary data were collected by field surveys and interviews with the council body. Simulation results for storm events show that in some of the drainage systems in different regions of Shire Endaslasse town have flooded. During the field observation, the drainage structures are filled with solid wastes, inadequate inlet and outlet structures and some of the top element of the manhole have been broken this may cause a problem of aesthetic and healthy at large it may increase flood risk. The flooding risk in the drainage systems is very high due to the drainage system is undersized to cope with the current rainfall rates, but also is very limited to face the upcoming predicted rainfall.

Using the World Bank Global Findex Database for 91 countries in 2014, 2017, and 2021, we examine whether fintech levels influence bank performance and whether fintech’s interaction with GDP per capita causes differential effects on bank performance globally. Since fintech levels were already very high for rich countries when the World Bank started providing fintech development statistics in 2014, we estimate AbFintech by regressing fintech levels on GDP per capita by year. AbFintech is the difference between the fintech level and its fitted values. Then, using multiple regression analyses, we investigate the impact of AbFintech on bank performance worldwide, focusing on the differential effects of AbFintech and GDP levels on bank performance. We find AbFintech significantly increases bank performance, primarily in less developed countries. Specifically, AbFintech increases banks’ ROA in the least developed countries and net interest margin in the 75th percentile countries. Also, AbFintech decreases the cost-to-income ratio in the 75th percentile countries, while it increases the ratio in the most developed countries. AbFintech does not affect the ratio of noninterest income to total income, regardless of the level of economic development.

Everyone should therefore consistently get access to enough and safe water. The operation of the existing distribution network as well as the proper optimization and implementation of the new distribution systems are required for a sufficient and safe water supply. In Sekota town sufficient amount of water was not reached to the beneficiaries due to shortage of water at the source. The primary goal of this study was to evaluate the performance and optimize the existing Sekota water supply distribution system using Bentley Water GEMS.The system's hydraulic modeling is carried out by considering as a continuous supply system, and the evaluation procedure used the extended period simulation approach after calibration was done. Calibration is used to ensure the performance of the model using the observed pressure values. The output of the existing system shows pressure is very high means above the maximum pressure and velocity is very low at peak hour demand. The results of velocity and pressure before optimization have negative effect on the performance of the system. The number of pipes and junctions their velocities and pressures which were in admissible ranges are 15 and 42 pipes for velocities and zero and 59 junctions for pressure before and after optimization were evaluated respectively.

The airline sector is critical in today's globalized society, supporting the efficient movement of people and products worldwide. Airlines are continuously looking for methods to enhance their operational performance to remain competitive in the face of increased competition. This study focuses on the application of Multi-Criteria Decision Making (MCDM) techniques to improve low-cost carrier (LCC) also known or low-cost (budget) airlines' ground operational performance. MCDM techniques have gained considerable attention in recent years to address complex decision problems with multiple conflicting goals. This research aims to bridge this gap by proposing a comprehensive framework that combines MCDM techniques to enhance airline operational strategies to increase performance. The study utilizes qualitative and quantitative data, drawing on previously published materials on MCDM techniques in the aviation sector. It utilizes fuzzy Analytic Hierarchy Process (AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies. A case study is conducted to evaluate the ground operational performance of three airline companies based in Türkiye, considering five main criteria and 18 sub-criteria. The findings of this research will contribute to a comprehensive understanding of operational performance in the airline sector. It also highlights the implications and limitations of the research and suggests future research directions.

The Australian Bureau of Meteorology offers a national operational 7-day ensemble streamflow forecast service covering regions of high environmental, economic and social significance. This semi-automated service generates streamflow forecasts every morning and is seamlessly integrated into the Bureau's Hydrologic Forecasting System (HyFS). Ensemble rainfall forecasts, European Centre for Medium-Range Weather Forecasts (ECMWF) and Poor Man's Ensemble (PME), available in the Numerical Weather Prediction (NWP) suite, are used to generate these streamflow forecasts. The NWP rainfall undergoes pre-processing using the Catchment Hydrologic Pre-Processer (CHyPP) before being fed into the GR4H rainfall-runoff model, which is embedded in the Short-term Water Information Forecasting Tools (SWIFT) hydrological modelling package. The simulated streamflow is then post-processed using the Error Representation and Reduction In Stages (ERRIS). We evaluated the performance of the operational rainfall and streamflow forecasts for 96 catchments using four years of operational data between January 2020 and December 2023. Performance evaluation metrics included CRPS, relative CRPS, CRPSS, and PIT-Alpha for ensemble forecasts and NSE, PCC, MAE, KGE, PBias and RMSE and three categorical metrics CSI, FAR and POD for deterministic forecasts. The skill scores CRPS, relative CRPS, CRPSS and PIT-Alpha, gradually decreased for both rainfall and streamflow as the forecast horizon increased from Day 1 to Day 7. A similar pattern emerged for NSE, KGE, PCC, MAE and RMSE as well as the categorical metrics. Forecast performance also progressively decreased with the higher streamflow regime. Most catchments showed positive performance skills, meaning the ensemble forecast outperformed climatology. Both streamflow and rainfall forecast skills varied spatially across the country – and were generally better in the high runoff generating catchments, and poorer in the drier catchments situated in the western part of the Great Dividing Range, South Australia and mid-west of Western Australia. We did not find any association between model forecast skill and the catchment area. Our findings demonstrate that the 7-day ensemble streamflow forecasting service is robust and draws great confidence from agencies that use these forecasts to support decisions around water resources management.

Pacing strategy refers to the distribution of effort and speed throughout the race to achieve optimal performance. The study aims to understand whether the choice of pacing strategy in swimming depends on the length of competitions and how sex, age, and performance level influence this strategy. Participants were the finalists of the 800-meter and 1500-meter freestyle events at the elite and junior world championships in 2022-2023. Race outcomes and pacing parameters were compared between the two distances and across different groups of swimmers. Swimmers in both distances did not break world records. Pacing strategy generally followed a U-shape with significant differences in the frequency and duration of speed changes between the two distances. The 800-meter exhibited more frequent changes in acceleration while the 1500-meter events generally followed a more consistent time series pattern. There were differences in pacing strategies between males and females and between junior and elite swimmers. Swimmers closer to world records showed more consistent pacing patterns compared to those farther from records. The study suggests that pacing strategies are influenced by race distance, sex, age, and performance level. The research highlights the complex interplay between physiological and psychological factors that shape a swimmer's decision-making during a race.

The building and construction sector has a significant impact on CO2 emissions and pollutants released into the atmosphere, which contribute to climate change. The EPDB Directive mandates the achievement of a minimum energy class E for all residential buildings by 2030 and an energy class D by 2033. Particularly, in Italy, about 86% of the existing building stock predates the enactment of any energy laws and regulations, making it imperative to apply the energy efficiency interventions. This paper provides a support decision tool for the identification of standardized interventions on the envelope, air conditioning system and domestic hot water production. The study is focused on a specific construction period class (1976 - 1990) in six different climatic zones. The methodological approach is based on a cataloguing phase and definition of Ante Operam energy classes, on the case study identification, the energy requalification interventions identification, solutions simulations, cost estimation. By simulating standardized interventions for each climatic zone, a range of possible combinations will be identified. The most advantageous ones will be determined based on a cost-benefit analysis, considering the potential class jump achieved. The research result is a matrix of energy efficiency interventions that is applicable to each climatic zone and can be extended to the existing housing stock.

Legacy IPv4 networks are strenuous to manage and operate. Network operators are in need to minimize the capital and operational expenditure of running network infrastructure. The implementation of Software-defined networking (SDN) addresses those issues by minimizing the expenditures in the long run. Legacy networks need to integrate with the SDN networks for the smooth migration towards the fully functional SDN environment. In this paper, we compare the network performance of the legacy network with the SDN network for IP routing in order to determine the feasibility of the SDN deployment in the Internet Service provider (ISP) network. The simulation of the network is performed in the Mininet test-bed and the network traffic is generated using distributed Internet traffic generator. Open network operating system is used as a controller for the SDN network in which SDN-IP application is used for IP routing. Round trip time, bandwidth, and packet transmission rate from both SDN and legacy networks are first collected and then the comparison is done. We found that SDN-IP performs better in terms of bandwidth and latency as compared to legacy routing. The experimental analysis of interoperability between SDN and legacy networks shows that SDN implementation in production level carrier-grade ISP network is viable and progressive.

The efficiencies of conventional triple organic Rankine cycle (TORC) configurations are restricted by the low critical temperatures of common working fluids (＜320 °C). This paper proposes a high-temperature TORC system. A near-azeotropic mixture biphenyl/diphenyl oxide (BDO), which has stellar track record in the high-temperature ORC applications, is innovatively adopted as the top and middle ORC fluid simultaneously. The top cycle evaporation temperature is up to 400 °C in view of BDO’s high stability. Five conventional organic fluids are chosen for the bottom ORC. Fundamentals of the TORC system are illustrated, and mathematical models are built. Thermo-economic performance is investigated. The results hint that the optimal thermodynamic property is achieved on the use of benzene as the bottom fluid. The maximum thermal and exergy efficiencies are respectively 40.86% and 74.14%. The largest irreversible loss occurs inside the heat exchanger coupling the middle and bottom ORCs, accounting for above 30% of the total entropy generation. The levelized energy cost (LEC) is 0.0284 $/kWh. Given the same heat source condition, the TORC system can boost efficiency by 1.02% and drive down LEC by 0.0024 $/kWh compared with a BDO mixture-based cascade ORC.

This paper formulates the performance evaluation of cloud services as a multicriteria group decision making problem, and presents a fuzzy multicriteria group decision making method for evaluating the performance of cloud services. Interval-valued intuitionistic fuzzy numbers are used to model the inherent subjectiveness and imprecision of the performance evaluation process. An effective algorithm is developed based on the technique for order preference by similarity to ideal solution method and the Choquet integral operator for adequately solving the performance evaluation problem. An example is presented to demonstrate the applicability of the proposed fuzzy multicriteria group decision making method for solving the multicriteria group decision making problem in real world situations.

Bitumen is produced from non-renewable natural resources, continuously deplete and intrigues researchers to look for alternative binders. Annually, tons of waste engine oil (WEO) and crumb rubber (CR) are discarded unsustainably and pose a significant environmental threat. Adding these industrial waste products to asphalt provides a safe and cost-effective way for their disposal and improves the bitumen's performance in parallel. This study uses various combinations of waste engine oil and crumb rubber with 60/70 penetration grade bitumen to produce a partially synthetic bitumen. Adhesion being one of the critical characteristics of the bituminous binder has been assessed using the bitumen bond strength test along with physical and rheological properties. Results showed that waste engine oil with crumb rubber inclusion increases penetration and decreases the softening point, viscosity, complex modulus, and bonding strength. Additionally, polyphosphoric acid (PPA) in smaller dosages was also incorporated into the optimum percentage of CR + WEO to improve the properties of the binder. The results confirm that binder modification with waste engine oil and crumb rubber can be more effective with PPA. It is concluded that 35% of waste can replace the virgin binder giving a cost-effective and environmentally friendly solution.

Like the most of crops, especially sugarcane needs to be kept upright until it is harvested. Because, lodging of sugarcane has a significant negative effect on cane yield and sugar content of sugarcane. To keep sugarcane upright earthing up is an utmost intercultural operation. In Bangladesh, most of the operations for sugarcane cultivation including earthing up are generally done in traditional method using human labor which increases production costs as well as reduces the income of sugarcane growers. So, a cost effective two-wheeled tractor (2WT) mounted earthing up machine was developed in Bangladesh Sugarcrop Research Institute (BSRI), Pabna to reduce drudgery and cost of sugarcane production. Field tests were conducted in experimental sugarcane field at BSRI and technical and economic performances of the developed earthing up machine were also carried out based on the field test. Average effective field capacity and field efficiency were found 0.16 ha/hr and 77.41 %, respectively for the developed earthing up machine. The earthing up machine was not found economically viable when it is used only for earthing up operation. Besides, when the 2WT was being used as the main driver for other activities including earthing up operation, then the earthing up machine becomes economically beneficial with net cash flow, net present value, internal rate of return, benefit-cost ratio and payback period of BDT 148497/ha, BDT 23184, 3%, 3.81:1 and approximately 1 year, respectively. On the contrary, considering cost of only earthing up tool without 2WT, then it was found economically beneficial with net cash flow, internal rate of return, net present value, benefit-cost ratio and payback period of BDT 16428/ha, BDT 3053, 4.7%, 2.71:1 and approximately 2 years, respectively. Since 2WT is commonly used for versatile farming purposes. Therefore, versatile use of 2WT as prime mover for other machines including earthing up machine can make earthing up machine economically viable and beneficial for sugarcane growers.

Literature revealed the potential of using guayule resin for asphalt cement replacement from the binder’s perspective. However, monitoring guayule resin through binder-aggregate mixture could disclose its performance through field. In this study, designated binders were employed to investigate the applicability of such an innovative replacer through mixture, which were neat asphalt and guayule-based binders (neat guayule, asphalt-rubber-guayule, guayule-rubber binders). Consecutively, field-simulated lab mixtures were prepared to investigate the major distresses. Moisture damage, rutting, fatigue cracking, and thermal cracking resistances were investigated using the modified Lottman (TSR) test, rut test by asphalt pavement analyzer (APA), semi-circular bending (SCB) test, and disk-shaped compact tension (DCT) test, respectively. Additionally, the Hamburg wheel-tracking (HWT) test was employed to evaluate moisture susceptibility and rutting resistance. Outcomes revealed that the neat guayule was susceptible to moisture damage at a 7% air content (V_a) when the TSR test was employed. In contrast, all investigated mixtures yielded perfect performances against moisture susceptibility under the HWT test. Guayule-based mixtures perfectly resisted rutting, as analyzed by the rut test and HWT test. Generally, changing parameters (e.g., V_a, rubber addition, and partial asphalt replacement by guayule and rubber) enhanced the guayule-based mixture resistance to rutting and moisture damage resulting in acceptable performances. Guayule-based mixture had a high fracture toughness at low temperatures, hence fatigue fracture resistance at intermediate temperatures. Neat guayule mixture with or without rubber addition did not entirely resist thermal fracture. However, partial asphalt replacement by guayule and rubber resisted the thermal fracture to a great extent.

The performance evaluation of the Internet of Things (IoT) based supply chain is challenging due to the involvement of multiple decision makers, the multi-dimensional nature of the evaluation process, and the existence of uncertainty and imprecision in the decision making process. To ensure effective decisions are made, this paper presents a fuzzy multicriteria analysis model for evaluating the performance of IoT based supply chain. The inherent uncertainty and imprecision of the performance evaluation process is adequately handled by using intuitionistic fuzzy numbers. A new algorithm is developed for determining the overall performance index for each alternative across all criteria. The development of the fuzzy multicriteria group decision making model provides organizations with the ability to effectively evaluate the performance of their IoT based supply chains for improving their competitiveness. An example is presented for demonstrating the applicability of the model for dealing with real world IoT-based performance evaluation problems.

Supplements in fish nutrition can help alleviate pressure on the wild stock; however, there is limited information on the benefits of rooibos tea extract in aquafeed. This study aimed to determine the effect of rooibos tea extract inclusion in the commercial diet on the growth performance of larval fish. Fish were reared on three diets: a commercial diet with 30% fermented or green rooibos extract and a commercial tilapia diet (control). Fish (initial weight of 0.54 ± 0.008 g and length of 2.22 ± 0.01 cm) were randomly distributed into recirculating aquaculture systems in triplicates at 100 fish per tank. Fish was hand-fed thrice daily for eight weeks at 2% body weight. After that, samples were withdrawn to measure growth parameters. Fish-fed fermented, and green tea extracts exhibited a significantly (p ˂ 0.05) higher weight gain than the controls. The feed conversion ratio was higher in the control group, fermented (1.50 ± 0.25 cm) and green tea (1.41 ± 0.07 cm). Similarly, the control group exhibited the highest condition factor (K=13.14 ± 4.87). The two treatment groups were comparable (p >0.05) in growth performance. Overall, the evidence indicates that adding rooibos tea extracts to the basal diet can improve fish growth.

Disease detection and prediction have been one of the most frequent uses of machine learning models in the last decade, and Parkinson's disease is no exception. It is common for people in their old age to have one form of disease or another depending on the circumstances in which they find themselves. This study analyzed and evaluated various supervised machine learning models to detect the presence of Parkinson's disease in elderly individuals. An extreme gradient boosting model, along with other models, such as naïve Bayes, random forest, K-nearest neighbor, and support vector machine (SVM), was implemented to determine the best outcome. The extreme gradient boosting (XGBoost) model is a powerful boosting machine learning technique, particularly in terms of speed and accuracy. The results showed that the XGBoost model, which is an optimized version of the other boosting models, is capable of projecting the presence of Parkinson's disease with very high accuracy compared to other algorithms. The implemented classification algorithm extreme gradient boosting method achieved approximately 98 % accuracy, 97.5 % precision, 100.0 % recall, and 98.7% f1-score which are high compared with the results found in the existing literature.

Background: The duration of the vaccine's protective efficacy against SARS-CoV-2 is unknown. Evaluation of the clinical performance of available tests is required. Objectives: To evaluate the clinical performance of three immunoassays for the detection of IgG antibodies generated by mRNA vaccines against SARS-CoV-2. Methods: Two automated immunoassays (Euroimmun Anti-SARS-CoV-2 ELISA IgG and Abbott SARS-CoV-2 CLIA IgG) and one lateral flow immunoassay (LFIA Test Livzon IgG) were tested. 300 samples distributed in 3 groups were analyzed: 100 subjects over 18 years old and under 45 years old, 100 subjects between 45-65 years old and another 100 over 65 years old. collected before vaccination, at 21 days, 1, 2, 3 and 6 months post-vaccination. Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, and agreement (I. Kappa) were calculated for each serological test. Results: Maximum sensitivity for IgG was 98.7%, 98.1%, and 97.8% for the ELISA Euroimmun, CLIA Abbott, and Livzon LFIA assays and maximum specificity for IgG was 99.4%, 99.9%. % and 98.4% ELISA, CLIA and LFIA respectively at 3 months after vaccination with a decrease in antibody levels from the sixth month. The best agreement was observed between ELISA and CLIA 100%; (k = 1.00). The agreement between ELIA, CLIA and LIFIA was 99% (k = 0964) at the second and third month after vaccination. Seroconversion was faster and longer lasting in the younger age groups. Conclusion: Our study showed an equivalent and homogeneous clinical performance for IgG of three immunoassays after vaccination and that the LIFIA assay is the most cost-effective, reliable and accurate for routine use in population studies of seroconversion and seroprevalence.

Background: The purpose of this study was to evaluate and compare the performance of health, safety and environmental management of civil, traffic and urban services contractors in the 18th district of Tehran municipality in 2015-2016. Methods: This is an applied, longitudinal, descriptive-comparative study. The statistical population of this study was construction contractors, urban services and traffic in the municipality of district 18 of Tehran in the years 2015-2016. from 52 contractors, 18 construction contractors, 21 utilities contractors and 13 traffic contractors, respectively, were selected using census method. the research instrument consisted of periodic direct observation and completion of the HSE standard checklist by researchers. Data were analyzed using Kruskal-Wallis nonparametric test by SPSS software.Results: The HSE performance of all contractors (civil, utilities and traffic) was acceptable and the results of Kruskal-Wallis test showed that the HSE performance of contractors at the second visit of 2015 and the first visit of 2016 was significantly different in favor of civil contractors )p <0.01), but there was no significant difference between the first and third visits of 2015 and the second and third visits of 2016 (p> 0.05). visits in six periods indicate HSE Civil Contractors status increased from 100% unfavorable to 88.88% acceptable level and 11.11% good level, and in the case of civil service contractors who initially had 95.23% in an unfavorable situation and 4.76% in a favorable situation achieved 100% acceptable performance, and finally, the traffic contractors, who were 100% unfavorable, were upgraded to 100% acceptable. Conclusion: According to the findings of the study, it seems that the supervision of municipality inspectors on HSE performance of contractors can be effective in improving and strengthening the commitment to HSE requirements, therefore, it is suggested that periodical visits be made to the municipal contractors.

Nowadays, energy saving is considered a key issue worldwide, as it brings a variety of benefits: reducing greenhouse gas emissions, reducing demand for energy imports, and lowering costs on a household and economy-wide level. Researchers and building designers are looking to optimize building efficiency by means of new energy technologies. Changes in existing buildings can also be made to reduce energy consumption and costs. These may include the usage of new heat transfer fluids based on nanofluids. In this work, an extended experimental campaign (from February 2020 to March 2021) has been carried out on an educational building in the Campus of University of Salento, Lecce – Italy, in order to evaluate the increase in performance of the HVAC system, due to the usage of a nanofluid. The results show that, under optimal operating conditions, plant performance improves more than 10%, with average daily peaks of about 15%.

This experimental study examined the application effect of polycaprolactone (PCL), an organic resin material with excellent elasticity and ductility, on improving the mechanical performance of cellulose nanocrystal (CNC) cement composites. To analyze the effect, a test specimen containing CNC and PCL mixed, containing only CNC, and a control (plain) specimen containing nothing were compared. PCL was compared according to its shape, and in the case of Granules, which is the basic shape, interfacial adhesion with cement was not achieved, so a DCM solution was used to dissolve and use the Granules form. As a method for bonding PCL to the CNC surface, the CNC surface was modified using 3-aminopropyltriethoxysilane (APTES), and surface silylation was confirmed through Fourier transform infrared spectroscopy(FT-IR) analysis. To evaluate the dispersibility according to the application of PCL to the modified CNC, particle size analysis (PSA) and zeta potential analysis were performed according to the PCL mixing amount (0.1, 0.3, 0.5, and 1 vol.% compared with those of CNC) and size distribution. Through the zeta potential value, the highest dispersion stability was shown at 1 vol.%. The cohesive force of CNC was low and the dispersion stability was high according to the application of PCL. According to the results of the dispersion stability evaluation, the degree of hydration of the dissolved PCL 1 vol.%, CNC-only specimens, and plain specimens were analyzed. Hydration products increased by increasing the degree of hydration in the unhydrated area. However, the incorporation of PCL showed a low degree of hydration, and the analysis of strength characteristics also showed a decrease of approximately 27% compared with that of plain specimens. This was because the bonding with SiO2 was not smooth owing to the solvent, thus affecting internal hydration. To investigate the effect of the PCL shape, the compressive and flexural strength characteristics were compared using PCL powder as an additional parameter. The compressive and flexural strength values were improved by approximately 54% and 26%, respectively, compared with those of the plain specimen. Scanning electron microscopy (SEM) analysis determined that the filler effect that made the micropore structure denser, affected the mechanical performance improvement.

The detrimental consequences of soil pollution caused by crude oil or petroleum products are immense, leading to land degradation, property damage, and rendering agricultural practices ineffective. Extensive research has been conducted in the field of soil remediation, but further studies are still required to explore additional details of the remedial process. As a result, this study focuses on evaluating the effectiveness of Vernonia Galamensis and Vernonia Amygdalina, commonly known as bitter leaf, in remediating hydrocarbon-contaminated soil. In the analysis of micro-organisms, it was found that the bitter leaf extracts contained three types of bacteria: Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli. The leaf extracts were prepared using different methods, including sun drying, room drying, and using them in their wet form, which were then blended into the contaminated soil. The study also took into consideration three different types of soil: sandy-loamy soil, clay soil, and swamp soil. These advanced techniques and considerations are relevant to the topic of revolutionizing soil remediation, as they explore the potential of bitter leaf extracts and different soil types in effectively mitigating the effects of hydrocarbon contamination.The findings revealed that the wet blended extracts of Vernonia performed exceptionally well in the remediation process, surpassing a 50% reduction in the initial contamination levels. The study involved utilizing a quantity of bitter leaf ranging from 10g to 40g, which was added to the contaminated soils and monitored for a duration of 40 days. Remarkably, this approach led to a significant decrease in the concentration of contaminants within the soil, indicating the effectiveness of the bitter leaf extracts in the remediation process. Towards the conclusion of the study, predictive models were constructed to forecast the impact of hydrocarbon content, as well as the levels of lead, zinc, and chromium in the soil. These variables served as the dependent variables in the models, while the mass of bitter leaf, the duration of treatment, and the pH of the soil were considered as independent variables. Significantly, the models achieved a level of significance of less than 0.05, indicating their statistical validity. Furthermore, the r2 value, which represents the goodness of fit, demonstrated an appreciable level of accuracy in predicting the remediation effects. These results highlight the potential of the developed models in assessing and predicting the remedial outcomes of hydrocarbon contamination using bitter leaf extract.

Hermetia illucens is a very promising insect due to its ability to convert low-value substrates in highly nutrient feed. Its feeding and nutrition are important issues. This work aimed to study the effect of different substrates composed of coffee silverskin, by-product of the roasting process, enriched with different inclusion of microalgae (5%, 10%, 20%, 25%), Schizochytrium limacinum and Isochrysis galbana, coupled with the assessment of environmental sustainability by LCA. In general, the inclusion of microalgae caused an increase in the growth performance of the larvae, although S. limacinum showed the best results. Higher prepupal weight were observed in larvae fed on 20% and 25% of S. limacinum, shorter development times in larvae fed on 25% of both S. limacinum and I. galbana and higher growth rate were observed in larvae fed on 25% of S. limacinum. Anyway, the inclusion of 10% of S. limacinum showed a small difference with the higher inclusions. Moreover, the 10% of S. limacinum achieved the best waste reduction index. Therefore, considering the greater inclusion of microalgae, the higher the environmental impact of larvae production, the addition of 10% of S. limacinum seems to be the best compromise for the larval rearing.

Solar radiation is closely related to the energy buildings consume for cooling, heating, and lighting purposes. Glazing is the only material of the building envelope that transmits solar radiation and needs to be appropriately designed to reduce energy cㅈonsumption. Currently, smart glass technology is being actively investigated and developed for effective solar radiation control. Among the various types of smart glass, electrochromic glazing is one of the most promising technologies, as it can adjust transmittance on its own, has a wider transmittance range in both the clear and darkened states, and consumes less electricity. Considering the importance of solar radiation adjustment in electrochromic glazing technology, this study attempted to develop an optimal control method for electrochromic glazing. Toward this goal, the solar radiation incident on vertical surfaces and outdoor temperature conditions were controlled in three regions with different climatic characteristics, and the annual cooling, heating, and lighting loads, discomfort glare, and interior illumination were analyzed. This approach enabled the optimal conditions with respect to visual comfort to be determined. Subsequently, the EDPI (Energy and daylight performance index) was used to optimize control conditions for each region, thereby producing integrated evaluations from results with different units and properties. The proposed control method will be utilized to develop a control algorithm and a control system to reduce building energy consumption.

The paper presents the results of energy and environmental analysis of geothermal CHP plant operation in Polish conditions. As the most favorable, for the geothermal conditions prevailing in Poland, the variant of CHP plant based on Organic Rankine Cycle (ORC) has been taken into consideration. As the case study the existing geothermal well located in the town of Konin in the Wielkopolska voivodship has been chosen. The conceptual design of CHP plant has been proposed and evaluated from energy and environmental point of view. As energy performance criteria the non-renewable primary energy consumption has been chosen. In case of environmental performance carbon dioxide emission has been taken as evaluation criteria. The analysis has been performed for different operating conditions and three working fluids.

When drilling oil and gas wells, hole cleaning efficiency is crucial, particularly in the curved or severely deviated sections. Although many hole-cleaning procedures and models have been developed, most of them have substantial limitations or are difficult to apply in real time. This study aimed to develop a model for the hole cleaning index (HCI) that could be integrated into the drilling operations to provide an automated and real-time evaluation of deviated drilling hole cleaning. The new model herein was developed based on the mechanical drilling parameters, enhanced estimated drilling fluid properties, and cuttings characteristics. This HCI model was validated and tested in the field, as it was applied when drilling 12.25”-intermediate directional sections in two wells with a total length of approximately 2000 ft each. The integration of the HCI helped to attain a much better well drilling performance (50% enhancement) and mitigation of potential problems like pipe sticking and the slower rate of penetration. Since the developed index incorporates the changes in wellbore geometry and other spontaneous field data, the new model could be utilized for real-time optimization and intermediate interventions by drilling teams, unlike commercial software tools which are only useful during the planning phase. For this reason, the HCI can be linked to the driller's control panel to provide timely evaluation and corrective measures related to hole cleaning.

Purpose: This research aims to model a police agency ordering problem based on criteria that measure the performance of operational and logistical variables, using a multicriteria method. Design/methodology/approach: The multicriteria method PROMETHEE II was used, which with the aid of the Visual PROMETHEE software, emulated the systematized data in the impact matrix and produced the final ordering of the most efficient police agencies in equalizing the operational, logistical, financial, and human resources applied in the combating crime and reducing criminal indices. Findings: The results confirmed that the resources made available to police agencies located in different municipalities in the metropolitan region of the state of Rio de Janeiro are better applied by managers compared to police units in the capital of Rio de Janeiro. Research limitations/implications: As implications of the research, it can be inferred that the use of multicriteria methods in modelling problems in ​​public security can contribute to the rationalization of the use of available resources to fight crime in large cities. Research has shown that it is possible to use the multicriteria methodology in ordering police agencies that best equalize the available resources. Practical implications: The practical impact of this research lies in optimizing the resources available to law enforcement agencies in the fight against crime in general. Social implications: The results can influence the decision making of the local government in the allocation of resources, as well as offering sectors of the economy information relevant to local development. Originality/value: The results of the MCDA analysis can be used to help police agencies in Rio de Janeiro, Brazil to be more efficient. In addition, the application of MCDA can be a new approach to measuring the efficiency of police services.

The presented research focused on the evaluation of the novel concept of overmolding technique using self-reinforced composite prepregs and recycled polymer blends. In order to evaluate the effectiveness of the proposed manufacturing technique, several series of materials based on polycarbonate/polyethylene terephthalate (PC/PET) and polycarbonate/polyethylene terephthalate glycol (PC/PETG) blends were prepared. The reinforcing component in the form of overmolded prepreg was made from polyester-based self-reinforced composite (srPET). The prepared materials were compared in terms of mechanical properties and heat resistance; the study was supplemented by thermal analysis measurements (DMTA, DSC). Considering the mechanical characteristics, the overmolding technique turns out to be an effective method of improving the properties of composites, and the increase in impact strength turns out to be particularly beneficial. The increase of the impact strength for overmolded PC/PET blend reached 430 % for PC/PETG sample 330% , while for PC-based composite, only 100%. The expected improvement in thermomechanical properties turned out to be difficult to achieve due to the rapid softening of the srPET prepreg at around 70 °C. However, technological tests and analysis of properties clearly indicated that the use of PC-based blends makes it possible to create a permanent connection with reinforcement based on srPET prepregs, which can significantly expand the potential of applications of this type of materials.

Most people living in Europe's cities are still exposed to levels of air pollution deemed harmful by the World Health Organization. In the modern world, air pollution is the foremost concern because of its impact in human health and economy. This strong connection appears gaining a lot of concern, driven by new installed low-cost electrochemical sensors monitoring systems. Highly accuracy, real-time monitoring, daily and yearly statistics, data access from experts or simple users, low-cost equipment and forecasting needs, enforce the market to develop new air quality monitoring systems using advanced technologies and protocols. In this study, a comparison via low-cost electrochemical sensors and of static, fixed site measurement monitoring station, is taking place in Athens, Greece, along with the data quality and Air Quality Index (AQI) including data accuracy and quality of data concerning adverse health effects due to air pollution. The findings presented in this work, relate to different flexible and affordable alternatives adopted during the evaluation and calibration of low-cost gas sensors for the monitoring. The significance of the positive results is particularly useful, especially considering the founding for interference, environmental conditions affections and air quality information including indexes and health recommendations for a specific location.

Background: Significant national and global costs were incurred from recent emerging infectious disease outbreaks, notably H1N1 highly pathogenic influenza, Zika and Severe Acute Respiratory Disease (SARS), both in the medical sphere and within the socioeconomic context around it. With forecasts expecting an increase in direct and indirect burden of novel infectious disease events, costs of future outbreak events are likely to be exacerbated. In this scope, it is critical for countries to identify this trend and work towards minimizing costs while continuing to improve prevention, treatment and mitigation. Objectives: The impacts of the West Africa Ebola crisis have largely focused on the response to the outbreak abroad. The aim of this paper was to determine the direct and indirect domestic costs of the Ebola Virus Disease (EVD) introduction into the United States (U.S.), compare the economic consequences of the epidemic with other disease outbreaks and identify the primary drivers of such costs to leverage more global health preparation to prevent, prepare for, and respond to disease threats more effectively. Methods: I conducted a literature review of 1) EVD cases documented by the U.S. Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO), 2) scientific articles identifying the costs of Ebola for the U.S. and countries around the world and 3) grey literature on treatments and public reactions. Extrapolating data from these sources, I then performed a cost-analysis of direct costs (preparation, treatment and contact tracing) and indirect costs (loss of productivity owing to disease, death, and risk avoidance behaviors) of the disease. Findings: The country spent between $300-$700 million in direct costs. Additionally, roughly $200-$340 million were forgone as results of loss of productivity from to disease, death or social risk avoidance behaviors. The cost-per-case for the United States was vastly higher than for any other country. Conclusions: High direct costs suggest that either the United States took disproportionate preparative measures to mitigate a potential American outbreak or were unprepared for a potential outbreak of this magnitude. The significant risk avoidance behavior estimates hint that forces having the ability to shape social attitudes and norms – namely traditional and online media – played a significant role in driving social behavior towards fear of exposure to others. The findings reinforce that outbreaks occurring in a single part of the world can have dramatic economic effects globally, even in areas with existing public health capacity and other preventive measures, highlighting the need for change in global health systems to shift from a passive responder and incorporate other societal actors to effectively reduce the ever-increasing costs of disease threats.

. Identifying students who might have difficulty in their course of studies ahead of time is crucial. There can be many reasons for performance issues, such as personality, family, social, and/or economic. We advocate that educational systems should use machine learning to predict students’ performance based on performance factors. This would allow educational professionals and institutions to put in place a preventive plan to help students towards achievements of their educational goals and success. In this chapter, we propose a student performance prediction method and evaluate its performance. We provide a taxonomy of performance factors that help to gauge students performance from different perspectives and give insights on the categories and features that have more significant impact on students’ performance. The results of this work can be used by education institutions to put in place a student-centric approach to tackle performance issues before they create long-term effects on student’s life. In addition, it will help education policymakers to introduce a tailored approach for the population in specific areas.

Supplier selection/replacement strategies and optimized purchasing policies play a key role in efficient supply chain management in today’s dynamic market. Here we study supplier replacement in a one-level assembly system (OLAS) producing one type of finished product. To assemble the product, we need to provide multi-type components, but assembly will be interrupted if any single component is missing, and incoming units will get hoarded until the missing component arrives. The assembly process can be interrupted by various sources of uncertainty, including delays in component deliveries. There is consequently a non-negligible risk that the assembly process may get stopped any moment. This brings inventory-related costs, which should be minimized. Here we consider discrete lead-time distributions to mimic industry-world reality. We present a model that takes into account not only optimal assignment of component order release dates but also replacement of a critical supplier. For a given unit, we model several alternative suppliers with alternative pricing and lead-time uncertainties, and we evaluate the impact on the total assembly system. For a more general case where several suppliers may be replaced, we propose a genetic algorithm.

This study addresses the pressing energy constraints in nations like Bangladesh by proposing the implementation of photovoltaic (PV) microgrids. Given concerns about environmental degrada-tion, limited fossil fuel reserves, and volatile product costs, renewable energy sources are gaining momentum globally. Our research focuses on a grid-connected solar PV system model at Char Jazira, Lalpur, Natore, Rajshahi, Bangladesh. Through PVsyst simulation software, we assess the performance ratio (PR) and system losses, revealing an annual solar energy potential of 3375 MWh at Standard Test Condition (STC) efficiency. After considering losses, the system generates 2815 MWh annually, with 2774 MWh exported to the grid. We analyze an average PR of 78.63% and calculate a levelized cost of energy (LCOE) of 2.82 BDT/kWh [1 USD = 110 BDT]. The financial assessment indicates a cost-effective LCOE for the grid-connected PV system, with an annual gross income of 27744 BDT from selling energy to the grid and operating costs of 64060.60 BDT/year. Remarkably, this initiative can prevent 33074.061 tCO2 emissions over the project’s 25-year lifespan.

Emotion detection from the text is an important and challenging problem in text analytics. The opinion-mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions. However, most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets, resulting in performance degradation. To overcome this issue, this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset. The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision, recall ad f-measure. Finally, a classifier with the best performance is recommended for the emotion classification.

The stinging nettle caterpillar, Darna pallivitta (Lepidoptera: Limacodidae) is a serious invasive pest of agricultural products and a health hazard on the Hawaiian Islands first discovered in 2001. Nursery workers and homeowners have been stung by the caterpillars while handling their plants, especially rhapis palms (Rhapis sp.). Throughout its invaded range, it causes widespread damage including the many cultivated and native palm species grown in Hawaii. Of medical importance are the stinging spines of the larva, which cause dermatitis on contact with the skin. Horticulture and nursery products impacted by the limacodid pest are estimated at $84.3 million (2018 value). An eradication attempt with pesticides and lure traps was made but proved unsuccessful and the moth population continued to spread to major Hawaiian Islands (Hawaii, Kauai, Maui, Oahu). The introduction of specific biological control agents from the native region was thought to be the long-term solution for this invasive pest. Initial exploration in Indonesia and Thailand resulted in the introduction of a pupal ectoparasitoid, Nesolynx sp. (Hymenoptera: Eulophidae: Tetrastichinae), that was not specific. The oriental wasp, Aroplectrus dimerus Lin (Hymenoptera: Eulophidae: Eulophinae), idiobiont gregarious ectoparasitoid of the stinging nettle caterpillar, was introduced from Taiwan in 2004 for host specificity studies and biocontrol in Hawaii. Host range testing showed the parasitoid attacked only limacodid species and it was approved for field release in 2010. The parasitoid identity, host specificity under containment facility conditions, reproductive performance, colonization on the major infested sites were assessed. A total of 13379 parasitoids were colonized on162 release sites on four Hawaiian Islands. Evaluations were conducted using field surveys of larvae, pupal counts, and male lure traps. Field parasitism was thoroughly investigated on Oahu Island averaging 18.9 ± 5.6 % of 3923 collected larvae during 2010 – 2023. The numbers of male moths caught/trap/month were significantly reduced on Oahu Island (P

Elliptic curve cryptography (ECC) over prime fields relies on scalar point multiplication realized by point addition and point doubling. Point addition and point doubling operations consist of many modular multiplications of large operands (256 bits for example), especially in projective and Jacobian coordinates which eliminate the modular inversion required in affine coordinates for every point addition or point doubling operation. Accelerating modular multiplication is therefore important for high-performance ECC. This paper presents the hardware implementations of modular multiplication algorithms, including 1) Interleaved modular multiplication (IMM), 2) Montgomery modular multiplication (MMM), 3) Shift-sub modular multiplication (SSMM), 4) SSMM with advance preparation (SSMMPRE), and 5) SSMM with CSAs and sign detection (SSMMCSA) algorithms, and evaluates their execution time (the number of clock cycles and clock frequency) and required hardware resources (ALMs and registers). Experimental results show that SSMM is 1.76 times faster than IMM, and SSMMCSA is 3.21 times faster than IMM. We also present the ECC hardware implementations based on the Secp256k1 protocol in affine, projective, and Jacobian coordinates using the IMM, SSMM, SSMMPRE, and SSMMCSA algorithms, and investigate their cost and performance. Our ECC implementations can be applied to the design of hardware security module systems.

Air quality and environmental fairness have always been an area of prime interest across the globe. The significance low-cost air quality sensing and practices spikes during the time of pan-demic and epidemics when the air becomes a threat to living beings especially human beings. The gradual innovation and enrichment in low-cost air quality sensing sensors, nodes or devices, and systems are exponentially increasing for the last three decades. This work reviews the major contributions in a) low-cost scalable air quality assessment; b) low-cost air quality sensors, sensing approaches and technologies; c) low-cost state-of-the-art gas sensors fabrication methods (MEMS and CMOS); d) low-cost gas sensors measurement configurations and assemblies; and e) low-cost air quality sensors calibration and testing systems. A systematic review of past work with a goal to assist end-users, public health facilities, state agencies, researchers, scientists and air quality protection agencies has been rendered in this work. Starting from sensors electrodes to IoT based mobile smart nodes; all have been introduced in this article.

The aim of this study was to measure one-year total cost of stroke and to investigate the value of stroke care, defined as cost per QALY. The study population included 892 patients with first ever acute stroke, hemorrhagic and ischemic, (ICD-10 codes: I61, I63 and I64) admitted within 48 hours of symptoms onset to nine public hospitals located in six cities. We conducted a bottom-up cost analysis from the societal point of view. All cost components including direct medical costs, productivity losses due to morbidity and mortality and informal care costs were considered. We used an annual time horizon, including all costs for 2021 irrespective of the time of disease onset. The average cost (direct and indirect) was extrapolated in order to estimate the national annual burden associated with stroke. We estimated the total cost of stroke in Greece at €343.1 mil a year in 2021, (€10,722/patient or €23,308 per QALY). Out of €343.1 mil., 53.3% (€182.9 mil) consisted direct healthcare cost representing 1.1% of current health expenditure in 2021. Overall, productivity losses were calculated at €160.2 mil. The mean productivity losses were estimated to 116 work days with 55.1 days lost due to premature retirement and absenteeism from work, 18.5 days lost due to mortality and 42.4 days lost due to informal caregiving by family members.This study highlights the burden of stroke and underlines the need for stakeholders and policy makers to re-organize stroke care and promote interventions that have been proved as cost-effective

For the majority of the contractual arrangements used in construction projects, the owner is not responsible for the cost deviations due to the variability of labor productivity or material price, amongst many other aspects. Consequently, the cost performance of a project may be entirely distinct for the owner and the contractor. Since the majority of the quantitative research on cost estimation and deviation found in the literature adopts the owners’ perspective, this research provides a contribution towards modelling costs and cost deviation from a contractors’ perspective. From an initial sample of 13 residential building and 10 office building projects, it was possible to develop models for cost estimation at the early stage of development including both endogenous and exogenous variables. Although the sample is relatively small, the authors were able to fully analyze all the cost data, using no secondary sources of data (very frequent in cost modelling studies). The statistically significant variables in the cost estimation models were the areas above and below ground and the years following the 2008 financial crisis, including the international bailout (2011-2014) period. For estimating the unit cost, a nonlinear model was obtained with the number of underground and total floor, the floor ratio and the years following the 2008 financial crisis, including the international bailout (2011-2014) period as predictors. For the office buildings, it was also found a statistically significant correlation between the cost deviation and the number of underground floors.

Banking sector is generally taken out of sample while the sustainability performance, and the financial performance are compared with each other. The core aim of this study is to analyze the effect of the declarations made in the cope of sustainability reports on the financial performance in the banking sector. Seven banks were included in the study which were placed at least one time in BIST Sustainability Index in between 2010-2017 years. Environment, human resources, product liability and community involvement were determined as sustainability criteria and return on assets, return on equity and net interest margin were determined as financial performance criteria. Non-Parametric Statistic Tests and Panel Data Analysis were used for analysis and types, and the sizes of banks were selected as dummy variables. As a result, it is found that the declarations of sustainability reports have a significant effect only on return on assets and have no significant effect on return on equity and net interest margin. And also, when we analyzed the relationship of sustainability criteria and return on assets, we found that the declarations about environment and human resources have negative effects on return on assets.

The Internet of Healthcare Things (IoHT) is an essential IoT domain that encompasses the necessary capabilities to transform the current healthcare system. IoHT generates, transfers, manages, stores, and processes highly confidential medical data and sensitive personal information. Thus, IoHT is a critical application from a security perspective and is most favorably targeted by attackers. Several security-breaching attempts can be carried out due to the vulnerabilities of the IoHT that put classified data at constant risk. Henceforth, this work aims to inspect the performance of 6LoWPAN-RPL-based `Patient-Centric IoHT’ in the presence of malicious intruders conducting blackhole, rank, and DoDAG attacks in both normal and emergency operational modes of the mentioned resource-constraint network. PC-IoHT is simulated on the Cooja simulator and Contiki-OS for each attack with two and four intruders (out of 10 motes) for both operation modes. Several performance evaluation parameters are used to assess the overall performance of the considered PC-IoHT. The attacks’ impact on PC-IoHT is analyzed by comparing blackhole, rank, and DoDAG attacks with the no-attack scenario.

This paper presents a theoretical evaluation of the prices of mixed briquettes produced from co-conut shells (CCS), banana peels (BNP), rattan waste (RWT), and sugarcane bagasse (SGC), and, on the other hand, an analysis of the economic viability of their use as a replacement for conventional household fuels (Liquefied Petroleum Gas, fuelwood, and wood charcoal) in house-holds in Cameroon. The investigation was carried out using the Life Cycle Cost method on a typical household over a ten-year period with annual cooking energy requirements of 950 kWhth. The SGC-CCS and SGC-RWT mixed briquettes with a ratio higher than 7.75% and 11.1%, respectively, have prices lower than 0.063 €/kWhth. The Present Value of the Net Benefit is posi-tive for the use of SGC-CCS and SGC-RWT mixed briquettes. The results show that by making the right mixes of residues, it is possible to obtain biomass briquettes that are less expensive than conventional fuels.

Partial shading on solar photovoltaic (PV) arrays is a prevalent problem in photovoltaic systems that impair the performance of PV modules and is responsible for reduced power output as compared to that in standard irradiance conditions thereby resulting in the appearance of multiple maximas on panel output power characteristics. These maxims contribute to mismatch power losses among PV modules. The mismatch losses depend on shading characteristics together with different interconnected configuration schemes of PV modules. The research presents a comparative analysis of partial shading effects on a 4 x4 PV array system connected in series(S), parallel (P), serries-parallel (SP),total-cross-tied (TCT),central-cross-tied(CCT),bridge-linked(BL),bridge-linked total cross-tied (BLTCT) ,honey-comb(HC), honey-comb total-cross-tied (HCTCT) and ladder (LD) configurations using MATLAB/Simulink. The PV module SPR-X20-250-BLK was used for modeling and simulation analysis. Each module is comprised of 72 number of PV cells and a combination of 16 PV modules was employed for the contextual analysis. Accurate mathematical modeling for the HCTCT configuration under partial shading conditions (PSCs) is provided for the first time and is verified from the simulation. The different configuration schemes were investigated under short-narrow,short-wide,long-narrow,long-wide, diagonal, entire row distribution, and entire column distribution partial shading condition patterns with mathematical implementation and simulation of passing clouds. The performance of array configurations is compared in terms of maximum power generated ), mismatch power loss (∆), relative power loss ) and the fill factor (FF). It was inferred that on average, TCT configuration yielded maximum power generation under all shading patterns among all PV modules interconnection configurations with minimum mismatch power losses followed by hybrid and conventional PV array configurations respectively.

This study empirically analyzes the effectiveness of resource optimization utilizing artificial intelligence (AI) within cloud computing environments. It compares systems that have been transitioned from a Monolithic structure to Microservices Architecture (MSA) with those adopting a simple Rehost strategy, to validate the operational efficiency of two systems whose resource efficiency has been enhanced compared to traditional legacy systems. The research is based on systems that determined resource efficiency post-cloud migration using APM tools. It points out the limitations of traditional heuristic operation methods in resource optimization, which lead to issues such as application performance degradation, resource over-allocation, and increased operational costs. This study aims to overcome the conventional resource optimization standards that depended on the average peak usage of CPU and memory infrastructure, by introducing AI-based optimization tools, and applying on-premise standards to cloud and container environments to achieve resource optimization. The paper emphasizes the importance of resource optimization through AI-based automation tools, exploring the possibilities of resolving real-world application performance issues in cloud environments, reducing unnecessary resource usage costs, and cutting down on labor risks and operational expenses. Through this, it presents strategic directions on how AI technology can offer financial and operational advantages in managing cloud resources.

This study assessed the relationship between body posture displacements and cardiopulmonary function test (CPET) and skill related physical fitness tests. One hundred male (60%) and female collegiate athletes (22.2 ± 4yrs) with a normal body mass index (BMI up to 24.9) were assessed via the PostureScreen Mobile app to quantify postural displacements as head, thorax and pelvis rotations and translations. CPET and physical performance tests including the agility T-test, the vertical jump test, the stork static balance test (SSBT) and the dynamic Y-balance test (YBT) were performed. Spearman correlation (r) and p-values are reported. Postural parameters were found to have moderate-to-high associations with CPET and the agility test, moderate correlations with the vertical jump test and the SSBT (head and pelvic postures only), and weak correlations with the YBT. As postural parameters were more asymmetric, both CPET and performance skills scores were worse. For examples: 1) a medium positive correlation was found between cranio-vertebral angle (CVA) and vertical jump test (r = 0.54; p-value &lt; 0.001) and SSBT (r = 0.57; p-value &lt; 0.001), while a strong negative correlation was found between CVA and agility test (r = -0.86; p-value &lt; 0.001). 2) A strong positive correlation was found between CVA and oxygen uptake efficiency slope, load watts VO2 at VT, VO2 / kg, load watts at respiratory compensation point (RCP), (r = 0.65 and r = 0.71; p &lt; 0.001). Conversely, a significant negative correlation was found between CVA and VE / VO2 at VT (r = -0.61; p &lt; 0.001). Postural rotations and translations of the head, thorax and pelvis were statistically correlated with physical performance skills and CPET in young collegiate athletes. There were moderate-to-high associations with cardiopulmonary functions and agility tests, moderate correlations with the vertical jump test, and weak correlations with the YBT. Postural alignment may be important for optimal physical performance and optimal cardiopulmonary function. Further research is necessary to elucidate reasons for these correlations as found in our sample of young and healthy athletes.

The purpose of this research is to determine if the tradeoffs that Kissick proposed among cost containment, quality, and access remain as rigidly interconnected as originally conceived in the contemporary health care context. Although many have relied on the Kissick model to advocate for health policy decisions, to our knowledge, the model has never been empirically tested. Some have called for policy makers to come to terms with the premise of the Kissick model tradeoffs, others have questioned the model given the proliferation of quality enhancing initiatives, automation, and information technology in the health care industry. One wonders whether these evolutionary changes alter or disrupt the originality of the Kissick paradigms themselves. Methods: Structural Equation Modeling (SEM) was used to evaluate the Kissick hypothetical relationships among the unobserved constructs of cost, quality, and access in hospitals for the year 2018. Hospital data were obtained from Definitive Healthcare a subscription site which contains Medicare data as well as non-Medicare data for networks, hospitals, and clinics (final n= 2,766). Results: Reporting significant net effects as defined by our chosen study variables, we find that as quality increases costs increase, as access increases quality increases, and as access increases, costs increase. Policy and Practice Implications: Our findings lend continued relevance to a balanced approach to health care policy reform efforts. Simultaneously bending the health care cost curve, increasing access to care, and advancing quality of care is as challenging now as it was when the Kissick model was originally conceived.

Long-term storage may reduce the nutritional quality of brown rice, so the present study was aimed to evaluate the nutritive values and application in pig diets. In Exp.1, 18 Landrace × Yorkshire (L × Y) barrows with initial body weight (IBW) of 25.48 ± 3.21 kg were randomly assigned to three treatments, which included corn diet, one-year stored brown rice (BR1) diet and six-year stored brown rice (BR6) diet, to determine the digestible energy (DE) and metabolisable energy (ME) value of stored brown rice. In Exp. 2, 24 barrows (L × Y; IBW: 22.16 ± 2.42 kg) fixed with ileal T-cannula were randomly allotted to four dietary treatments, including corn diet, two stored brown rice diets and nitrogen-free diet, to evaluate the amino acid (AA) digestibility of stored brown rice. In Exp. 3 and 4, 108 crossbred weaned piglets (L × Y; IBW: 9.16 ± 0.89 kg) and 90 crossbred growing pigs (L × Y; IBW: 48.28 ± 3.51 kg) were allotted to 3 treatment diets, including control diet and two stored brown rice diets, respectively, to investigate the application of stored brown rice in weaned piglet and growing-finishing pig diets. Results showed that: 1) The DE and ME of corn and stored brown rice showed no significant differences (P > 0.05), while the apparent ileal digestibility (AID) of arginine, histidine, aspartic acid, and the standardized ileal digestibility (SID) of arginine and histidine were higher in stored brown rice compared to corn (P < 0.05). 2) Compared with the control diet, the stored brown rice diets showed no significant effects on growth performance, nutrient apparent total tract digestibility (ATTD) and serum biochemical indices (P > 0.05), but decreased digestive enzymes activities in duodenum, jejunum and ileum of piglets (P < 0.05). 3) Compared with the control diet, the stored brown rice diets showed no significant effects on growth performance, carcass traits, meat quality, fatty acids profiles in the longissimus dorsi muscle of growing-finishing pigs (P > 0.05). In conclusion, the brown rice stored for 6 years under good conditions has no obvious changes in available energy and nutrient values. Although it may reduce digestive enzyme activity in small intestine of the piglets, the stored brown rice showed no obvious adverse effect on growth performance and meat quality, and can be effectively used in pig diet.

Aquaculture is an important source of food for the growing global population. To meet the increasing demand for fish, intensive aquaculture methods are commonly used. However, these methods can lead to stress and disease in fish, which can result in significant economic losses. Gamma-aminobutyric acid (GABA) is a non-protein amino acid that is found in the brain and central nervous system of animals as inhibitory neurotransmitter. It has been shown to have a variety of physiological functions, including stress reduction and immune enhancement. This study investigated the effects of dietary supplementation of GABA on growth, serum biochemistry, innate immunity and disease resistance in juvenile olive flounder (Paralichthys olivaceus) challenged with Edwardsiella tarda under high stocking density. A control diet and three experimental diets were prepared, with 150 mg/kg (GABA150), 200 mg/kg (GABA200), and 250 mg/kg (GABA250) of GABA added to each diet, respectively. The actual GABA content of the experimental diets was analyzed and found to be 63.9 mg/kg (CON), 231.3 mg/kg (GABA150), 291.6 mg/kg (GABA200), and 323.9 mg/kg (GABA250). Each experimental diet was fed to olive flounder with an initial weight of 12.75 g ± 0.3 g in 40 L tanks at two stocking densities: normal density (20 fish/tank) and high density (40 fish/tank). The experiment was conducted in triplicate for each diet and stocking density. The water temperature was maintained at 17.5 ± 1℃ and the salinity at 33 ± 1 ppt. After 8 weeks of feeding trial, growth, feed utilization, whole-body proximate composition, blood analysis, non-specific immune response, and challenge test were performed. There were no significant difference in weight gain and specific growth rate among the GABA concentrations and density × GABA concentration interaction groups. However, the low-density groups showed significantly higher values than the high-density groups (P &lt; 0.05). There was no significant difference in feed efficiency and protein efficiency ratio among all groups. Moreover, there was no significant difference in the whole-body general composition analysis (P &gt; 0.05). In the hematological analysis, there was no significant difference in cortisol in terms of diet and density × GABA concentration interaction, but the high-density experimental group showed a significantly higher value. Blood GABA significantly increased in proportion to the addition amount regardless of the density group (P&lt;0.05). Superoxide dismutase activity in the non-specific immune response showed that the GABA-added experimental group had a significantly higher value than the control group, but there was no significant effect of the density densities or density × GABA concentration interaction (P&lt;0.05). Myeloperoxidase activities in fish fed the GABA200 and GABA250 diets showed significantly higher values, and a density × GABA concentration interaction effect was observed (P&lt;0.05). Lysozyme activity was significantly higher in the GABA150 group than in the CON, GABA200, and GABA250 groups (P &lt; 0.05). After 15 days of challenge test by intraperitoneal injection of Edwardsiella tarda, the cumulative survival rates of the GABA150, GABA200, and GABA250 groups were significantly higher than that of the CON group (P &lt; 0.05). The results suggested that the optimal dietary GABA level for juvenile olive flounder culture is 150 mg/kg, regardless of rearing density, to enhance growth, immune function and disease resistance.

The Ames/quantitative structure-activity relationship (QSAR) International Challenge Projects held during 2014–2017 and 2020–2022, evaluated the performance of various predictive models. Despite the significant insights gained, the rules allowing participants to select prediction targets introduced ambiguity in model performance evaluation. This reanalysis identified the highest-performing prediction model, assuming a 100% coverage rate (COV) for all prediction target compounds and an estimated performance variation due to changes in COV. All models from both projects were evaluated using balance accuracy (BA), Matthews correlation coefficient (MCC), F1 Score (F1), and the first principal component (PC1). After normalizing the COV, a correlation analysis with these indicators was conducted, and the evaluation index for all prediction models in terms of the COV was estimated. In total, 109 models, the highest estimated BA (76.9) at 100% COV was MMI-VOTE1, reported by Meiji Pharmaceutical University (MPU). The best models for MCC, F1, and PC1 were all MMI-STK1, also reported by MPU. All models reported by MPU ranked in the top four. MMI-STK1 was estimated to have F1 scores of 59.2, 61.5, and 63.1 at COV levels of 90%, 60%, and 30%, respectively. These findings highlight the current state and potential of the Ames prediction technology.

There is a paucity of data on the progression of track cycling sprinters, and the evolution of training and performance over a training cycle. Following prior research showing relationships between sprint cycling power and endurance cycling power, we compared these relations over a 3-month period. Our hypothesis is large improvements in power would come from training either for sprint power or sprint capacity, and this would be reflected in the data. A total of publicly available 25 datasets. These data were plotted against the line of best fit for 30-s and 2-min power to assess if training towards the line led to better 30-s power. We observe the best performances came from riders who start below the 30-s vs 2-min power line of best fit, with greater capacity and ability to ride fast over a sprint series, and progressing towards focusing on specific power in the final block leading into a competition. These results support the hypothesis of combined capacity and power training based on rider-specific relationship to the line of best fit between these measures versus a strictly maximal power training focus.

In this paper, it is defined that how the IPOs are affected by the underwriter reputation. What will happen to IPOs who are backed by reputed underwriter and who is not? And evaluate the IPOs short-run and long-run performance. Also try to explain the relationship between IPOs and underwriter. Also tried to compare some of the international return and Pakistani returns. Also determine the relation of the investor to the underwriter. There is a set of investors who have there own relationship with the underwriters how they will affect on the IPOs in the market.

Derivatives products have become essential in portfolio diversification, price discovery and risk hedging. Derivatives are complex instruments; their role is twofold, risk management and speculation, and their actual Impact on the underlying assets’ behaviours are not well understood. Little is documented empirically on how these instruments’ two-edged roles influence firms’ financing decisions, firm risk exposures, and stability. Given the growing interest in using derivatives in risk management and portfolio engineering, this study examines the practical impact of derivatives usage on the underlying firm’s financing policy and stability. The paper uses data from South African listed non-financial firms for the period 2000 to 2019. The study employs a dynamic panel model estimated with System Generalised Methods of Moments (GMM). The initial analysis shows that derivatives use reduces the cost of capital and increases firm stability. However, further in-depth analysis provides evidence that extensive use of derivatives increases firms’ capital costs and negatively impacts financial stability. These findings imply that the risk embedded in derivatives’ speculation dominates their risk management function. The results are subjected to numerous controls for robustness, including financial leverage, firm size, cashflows and asset tangibility.

Legacy risks from infrastructures and industrial installations often reveal themselves when a potential for failure has been discovered much later than at the stage of the design and construction of a structure. In which case, there might already be a problem with the legacy installation, or even a crisis, without having had an accident. When the hazard cannot be taken away, the question arises as to how much effort, if any, should be spent on improving the situation. The usefulness of the three archetypical approaches to this problem: setting a standard, the As Low As Reasonably Practicable approach and a case-by-case discourse approach are discussed for their applicability for these legacy risks. Although it would be desirable to retrofit legacy risks to previously set legal requirements as is the case when acceptability limits are set in law or demonstration of ALARP is demanded, it may be impossible to reduce the residual risk to an otherwise acceptable level without taking away or replacing the infrastructure, which is not acceptable either. Therefor in conclusion the only available solution to persistent legacy risk problems seems to be to have a thorough discussion with all relevant stakeholders until an agreement is in some way found.

Estimation of the worth of continuity of electricity supply is of interest of industry, authorities and research society. There are numerous methods to calculate the Customer Interruption Costs (CICs). Each method has its advantages and disadvantages. This paper approaches the problem from Distribution System Operators’ (DSOs) point of view and adopts two existing analytical models. One model is used by the Finnish Energy Market Authority and the second one was proposed by the authors at a previous study. The model suggested by the authors as an alternative to the one used by the Finnish Energy Market Authority proposes a simple and straightforward methodology which will provide credible and objective estimations by only utilizing publicly available analytical data. We made use of cost and reliability indices data of 78 DSOs in Finland from the year 2016. In addition to cost estimations, this paper highlights regional differences in CIC estimations in different parts of Finland and critically overviews the existing standard customer compensation scheme in Finland.

In recent years, with the increasing prominence of environmental and social issues, investors have been paying more attention to the ESG performance of enterprises, highlighting the importance of ESG factors in the financial field. This study is based on the theories of banking business models, stakeholder theory, risk management theory, and ESG investment theory. It uses the financial data and ESG scores of Chinese listed banks to deeply analyze the ESG factors and explore their impact on the liquidity risk of commercial banks. The research found that (1) good ESG performance can reduce the liquidity risk commercial banks face by improving bank value and financial performance. (2) ESG factors can also enhance the liquidity management level of commercial banks through standardization and sustainable business principles, thereby reducing the occurrence and impact of liquidity risk. Therefore, it is necessary to reduce the liquidity risk of banks and promote the sustainable development of commercial banks from four aspects: ESG performance and management, bank value, financial performance, and policy regulation.

The purpose of this study is to examine the match-related performance (scores and penalties) of the athletes in the Junior EJC (European Judo Championship) and U23 EJC categories before and immediately after the Covid-19 quarantine, according to gender and weight category groups. Our sample was based on the junior and U23, male and females, 2019-2020 Junior European Judo Championships and 2019-2020 U23 European Judo Championships. A total of 1431 matches in these tournaments were analyzed: male (n=812) and female (n=619). The main findings of this study showed that most matches in both the male and female categories resulted in ippon (2019-2020 average: 64,35% for Junior male, 70,55% for U23 male and 69,3% for Junior female, 64,4% for U23 female). No significant differences (p &gt; 0.05) were observed between gender and age groups concerning the match scores. In the formation phase of the technique, considerations of high- and low-intensity actions, and analysis of the speed of athletes during matches in official competitions can help to better understand the dynamics of the variability of movements in judo matches. In addition, suggestions are presented to be applied to athletes in different age categories who are on the way to become Olympic athletes.

Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2 (PLF) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM2.5), 10 μm or less (PM10), and nitrogen dioxide (NO2), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r<0.4). Moderate correlation was observed for one PLF unit at indoor location and two units at roadside location, when measuring PM2.5, but not for PM10 and NO2 concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R2 values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.

In this age of global warming, academics and policymakers are increasingly concerned about firm environmental sustainability success. Therefore, this study aims to investigate whether Environmental, Social and Governance (ESG) performance impacts sustainability performance through the mediating effect of firm innovation. To this end, Structural Equation Modeling (SEM) was deployed to analyze data collected from the employees of manufacturing industries in an emerging economy like Bangladesh. The results revealed that ESG performance significantly enhances the innovation and sustainability performance of manufacturing industries, indicating that the higher the ESG performance of a firm, the greater its innovation and sustainability performance. Furthermore, the results confirmed that firm innovation performance fully mediates the relationship between ESG initiatives and sustainability performance. The findings of this study provide policymakers and industry authorities with valuable insight into the role of ESG and innovation performance in improving sustainability performance. Specifically, the study sheds knowledge on how firm ESG initiatives and innovation performance impact sustainability performance in the manufacturing sector of an emerging economy like Bangladesh.

The objective of this paper was to give an overview of the expressed preference (EP) techniques of environmental valuation. These methods offer estimation of the value of a resource not necessarily willingness to pay (WTP) or willingness to Accept (WTA) compensation rather upper and lower values. The method of measuring individuals’ willingness to pay is usually based on contingent valuation method (CVM). This research focuses on defining, categorizing, and applicability of various environmental valuation techniques that have been and can be applied in attaching value to a given resource using expressed/Revealed preference methods. The study serves as a supplementary synthesis and discussion to the board of knowledge of resource valuation methods. More specifically, selected methods to discussed herein include; contingent valuation method, hedonic pricing model, travel cost method, trade-off game method, the costless-choice method, Delphi method, Replacement Cost Method, Relocation Cost Method, Opportunity cost method, and Cost-benefit Method. In the last part, applicability of the methods is fully illustrated to support future studies on resource valuation.

Ice and snow on roads in winter endanger traffic safety. The existing methods of snow and ice removal have various drawbacks, which need further research. Aiming at solving limitations about high labor intensity, low efficiency, serious environmental pollution of traditional snow and ice removal methods, the anti-icing coating technology of high-voltage conductors is used for reference, and in view of the characteristics of asphalt pavement deicing, an ice-suppressing material that can effectively reduce the adhesion between snow, ice and pavement is successfully developed. As there is no perfect evaluation index and method for ice-suppressing materials at present, this paper further evaluates the performance of ice-suppressing materials from the aspects of deicing performance, durability, adhesion and the impact of ice-suppressing materials on pavement performance. The test results show that the ice-suppressing material can effectively reduce the adhesion between the ice layer and the specimen, making it easier to remove. The ice-suppression material has good slow-release performance, and the specimens still have good deicing performance after 7 cycles of tests.

In the current study, we assessed the effects of conventional and Ultra High Dose Rate (UHDR) irradiation on behavioral and cognitive performance one month following exposure and assessed whether these effects were associated with alterations in the number of immune cells in the hippocampus using flow cytometry. Conventional- and UHDR-irradiated mice showed impaired novel object recognition. During fear learning, conventional- and UHDR-irradiated mice moved less during the inter-stimulus-interval (ISI) and UHDR-irradiated mice also moved less during the baseline period (prior to the first tone). In irradiated mice, reduced activity levels were also seen in the home cage; conventional- and UHDR-irradiated mice moved less during the light period and UHDR-irradiated mice moved less during the dark period. Following behavioral and cognitive testing, infiltrating immune cells in the hippocampus were analyzed by flow cytometry. The percent Ly6G+ CD45+ cells in the hippocampus was lower in conventional- and UHDR-irradiated than sham-irradiated mice, suggesting that neutrophils might be particularly sensitive to radiation. The percent of Ly6G+ CD45+ cells in the hippocampus was positively correlated with the time spent exploring the novel object in the object recognition test, suggesting that the reduced percent Ly6G+ CD45+ cells in the hippocampus might mediate some of the detrimental radiation-induced cognitive effects.

The Inefficient water use, varying and low productivity in Kenya public irrigation schemes is a major concern. It is therefore necessary to periodically monitor and evaluate the performance of public irrigation schemes. The performance of public irrigation in western Kenya was assessed by combining benchmarking methodology and principal component analysis. The aim was to quantify and rank the performance of pumped public irrigation schemes in Kenya. Eleven benchmarking indicators were computed for the period from 2012 to 2016 and compared to global benchmark values. The indicators used fall under agricultural productivity, water supply and financial performance categories. The computed agricultural productivity was 36%–51% in Ahero, 23%–42% in West Kano and 26%–50% Bunyala irrigation scheme. Water supply performance in Ahero, West Kano and Bunyala irrigation schemes varied from 24% to 58%, 3% to 49% and 19% to 43% respectively. Financial performance varied from 46% to 54% in Ahero, 25% to 32% in West Kano and 54%–56% in Bunyala irrigation scheme. An average overall performance efficiency of 46%, 39% and 31% was obtained in Ahero, Bunyala and West Kano irrigation schemes respectively. The performance of the irrigation schemes is very poor and measures on improving performance are needed.

Tropical rock lobsters (Panulirus ornatus) are a highly cannibalistic species with intermoult animals predominantly attacking animals during ecdysis (moulting). Rapid, positive characterisation of pre-ecdysis lobsters may open a pathway to disrupt cannibalism. Ecdysial suture line development is considered for pre-ecdysis recognition with suture line definition compared for lobsters emerged and immerged, using white, near ultraviolet (365 nm), near infrared (850 nm) and spe-cialty Osram SFH 4737 broadband IR LEDs against a reference of intermoult lobsters with no suture line development. An alternative pre-ecdysis recognition strategy used a novel low-cost spectral camera composed of the Sony IMX219, AMS AS7265x spectral sensors and Osram SFH 4737 broadband infrared LEDs. Images and data using the novel low-cost spectral camera was acquired from intermoult, pre-ecdysis, and post-ecdysis lobsters. Compared with the white light appear-ance, suture line definition was enhanced under 850 nm, 365 nm, and SFH 4737 LEDs for immerged lobsters, while the 850 nm LED achieved the best suture line definition of emerged lobsters. The spectral camera was unable to characterise pre-ecdysis. A least squares regression for binary classification decision boundary successfully separated 86.7% of post-moult lobsters. Achieving post-moult characterisation validated the speculative exploratory approach in developing this novel low-cost spectroscopy tool.

GNSS is nowadays a standard tool for monitoring and studying the Earth’s dynamic environment. However, the development of dense GNSS measurements remains limited in many experiments by the cost of geodetic-class equipments allowing to achieve the high precision required by many applications. Recently, multi-constellation, multi-frequency, low-power and, above all, less expensive GNSS electronic chips have become available. We present a prototype of a low-cost, open-source multi-GNSS station. Our prototype comprises a dual-frequency GNSS chip, a calibrated antenna, a Raspberry Pi card and a 4G key for data transmission. The system is easy to deploy in the field and allows precise positioning in real time and post-processing. We assess the performance of our prototype in terms of raw data quality, and quality of the obtained high rate and daily position one-year-long time series. Our results demonstrate a quality equivalent to geodetic-class equipment and better quality than other low-cost systems proposed so far.

Peste des Petits Ruminants (PPR), a highly contagious viral disease, causes significant economic losses in sheep and goats. Laboratory diagnosis is crucial to disease control and eradication. Since PPRVs have recently adopted new hosts, genetic diversity within isolates of the same lineage is more likely than if they were host-specific, sheep and goats most often. ELISA detects antibodies and antigens in serology. However, mishandling, environmental conditions (temperature and humidity), storage, and sensitivity issues of commercially available ELISA kits prevent rapid PPR virus detection in third-world countries like Pakistan. In the 2020-21 outbreaks in Pakistan, 325 blood samples, 19 swabs, and 6 virus tissue samples of sheep and goats were collected from Gilgit, Islamabad, and Fateh Jang. These virus isolates were submitted to NCBI for partial N gene sequencing. Antigen was prepared from indigenous virus Using semi-purified antigen from PPRV, an indirect ELISA for the detection of PPR antibodies in goat and sheep serum was developed using MW600922 grown in Vero cells. Dilutions of 1:200 serums and 1:32 antigens improve antibody detection. The N-gene-based analysis revealed a better understanding of PPRV genetic characterization. This study develops an RT-PCR assay to detect PPRV by targeting the N-protein gene. This assay offers an accurate and affordable diagnostic tool for PPRV and partial genome sequencing. Results described that PPRV isolates from the current study have 99.73% and 99.4% similarity to previously published Lahore and Faisalabad isolates from Pakistan, respectively. Compared to previous isolates from NCBI data, the virus showed high divergence rates with the Turkish strain. The comparative analysis between Commercial kit (c-ELISA) and I-ELISA revealed that the former had a high sensitivity of 90.60% and specificity of 85.23% compared with the cELISA kit. By comparing I-ELISA and VNT, we find that the current assay is 100% specific and 82.14 % sensitive. Based on these results, serological surveys for PPR antibodies, on a larger scale, in small ruminants can be conducted with indirect ELISA rather than competitive ELISA. Furthermore, the cost and storage efficiency was highly significant because the currently developed method has a low production cost, which is much lesser than the commercially available kit. Our findings demonstrated a significant breakthrough in terms of cost-effectiveness and storage efficiency, and they are highly recommended for developing countries.

This paper presents high-resolution digital measurements at low cost, combining oversample and averaging. Experiments of processing data between samples and between multiple temperature sensors in the same environment are conducted. They provide results with effective increase in the analog to digital converter bits, in correspondence with the minimization on the effects of noise. It is shown that averaging a set of small, low-cost sensors at a small microcontroller can give flexible access to improved measurement accuracy.

We review some semantical aspects of probability bounds from Boole’s “conditions on possible experience” violated by quantum mechanics. We also speculate about emerging space-time categories as an epiphenomenon of quantization and the resulting breakdown of relativity theory by non-unitary and non-linear processes.

OBJETIVES: During the COVID-19 pandemic, the risk of collapse of the health system created great difficulties. We will demonstrate that Intermediate Respiratory Care Units (IRCU) provide adequate management of patients with non-invasive respiratory support, which is particularly important in patients with SARS-CoV-2 pneumonia. METHODS: A prospective observational study of patients with COVID-19 admitted to the ICU of a tertiary hospital. Sociodemographic data, comorbidities, pharmacological, respiratory support, laboratory and blood gas variables were collected. The overall cost of the unit was subsequently analyzed. RESULTS: 991 patients were admitted, 56 to the IRCU (of the 81 a critical care unit). Mean age was 65 years (SD 12.8), Barthel Index 75 (SD 8.3), Charlson 3.1 (SD 2.2), HTN 27%, COPD 89% and obesity 24%. Significant relationship (p <0.05) with higher mortality of the following: fever greater than or equal to 39oC [OR 5.6; 95% CI (1.2-2.7); p = 0.020], protocolized pharmacological treatment [OR 0.3; 95% CI (0.1-0.9); p = 0.023] and IOI [OR 3.7; 95% CI (1.1-12.3); p = 0.025]. NIMV showed less of a negative impact [OR 1.8; 95% CI (0.4-8.4); p = 0.423] than IOI. The total cost of the IRCUs amounted to €66,233. The cost per day of stay in the IRCU was €164 per patient. The total cost avoided was €214,865. CONCLUSION: The pandemic has highlighted the importance of IRCUs in facilitating the management of a high patient volume. The treatment carried out in IRCUs is effective and efficient, reducing both admissions to and stays in the ICU.

The domain of Information and Communication Technology (ICT) education has garnered significant consideration in recent times. However, several challenges are inherent to this area of study, including monetary expense, temporal factors, pedagogical environment, teacher training programs, incentive, syllabus design, and health-related concerns. This paper presents an analysis of the difficulties encountered in the realm of ICT education in Japan, taking into account ten different perspectives.

The aim of this article is to propose a core game theory model of transaction costs wherein it is indicated how direct costs determine the probability of loss and subsequent transaction costs. The existence of optimum is proven, and the way in which exposure influences the location of the optimum is demonstrated. The decisions are described as a two-player game and it is discussed how the transaction cost sharing rule determines whether the optimum point of transaction costs is the same as the equilibrium of the game. The dispute between actors regarding changing the share of transaction costs to be paid by each party is modeled by a non-cooperative bargaining game. Requirements of efficient transaction cost sharing rules are defined, and it is posited that solution exists which is not unique. Policy conclusions are also devised based on principles of design of institutions to influence the nature of transaction costs.

The present work studies the concept of productivity in shipbuilding and how it should be measured. The existing metrics, shipbuilding process and shipyard organization were studies in order to choose the most adequate metrics which would allow the measuring of a shipyard productivity in a systematic and holistic way. This is achieved by gathering the man-hours spent in each ship organized by cost centre and using Compensated Gross Tonnages as the measure of output from the shipyard. Data was gathered for thirty ships built in the same European yard organized by cost centre. From the data collected it was found that the ratio of hours spent in outfitting to the hours spent in structures is proportional to the complexity of the ship. There was also opportunity to study the work reduction resulting from building ships in series and the shares of labour for ships series and across ship types.

The present work aimed to validate a low-cost passive monitoring procedure. For its validation, the monitoring of atmospheric organic pollutants - polycyclic aromatic hydrocarbons (PAH) was carried out in a capital of the central-western region of Brazil. The sensors were fixed on poles intended for electrification during the dry season. After 15 days, samples were extracted by solvent extraction and analysed by High-Resolution Gas Chromatography with Flame Ionization Detector (HRGC-FID). For the validation of the procedure, PAHs monitored and standardised by the American Environmental Agency (EPA), a benchmark for environmental monitoring of air quality by several countries, were analysed. The results demonstrated that the low-cost passive monitoring method was effective in the quantification of PAH in the environment-air, capable of being used by countries that do not have many resources for monitoring air quality.

This study aimed to analyze the effect of a flow training program based on mindfulness applied to young and adult elite handball athletes. A quantitative, quasi-experimental, descriptive data analysis approach was carried out. The sample included 105 athletes (51 female and 54 male). The athletes were divided into two groups: i) experimental (n = 53) and ii) control (n = 52). The results of the repeated ANOVA indicated that the experimental group achieved significant improvements compared to the control group in decision making (n2p=.086), mental well-being (n2p=.045), dispositional flow state (n2p=.103), non-judgment (n2p=.040), refocusing (n2p=.052) and mindful trait in daily life (n2p=.058). In the linear regression test, the factor non-judgment was identified as a predictor of decision making (F(103)=7.99, p=.006) and the predictor for the mental well-being were dispositional flow state (F(102)=29.2, p

Covid-19 is a disease caused by SARS-CoV-2, which has spread worldwide since the beginning of 2020. Several pharmaceutical and non-pharmaceutical strategies were proposed to contain the virus dissemination, including vaccination and lockdowns. One of the consequences of the pandemic was the denial or delay of access to convenient health care services, but also potentially the increase of adverse events within those services, like the number of hospital infections. Therefore, the main question here is: What happened to the performance and sustainability of hospitals? The main goal of this work was to test if the Portuguese public hospitals' performance has been affected by the SARS-CoV-2 pandemic. We used the Benefit-of-Doubt method integrated with the Malmquist Index to analyze the performance evolution over time. Then, we employed a multiple regression model to test whether some pandemic-related variables could explain the performance results. We considered a database of 40 Portuguese public hospitals evaluated from January 2017 to May 2022. The period 2017 to 2019 corresponds to the baseline (pre-pandemic), against which the remaining period will be compared (during the pandemic). We also considered fourteen variables characterizing hospital quality, divided into three main performance definitions (efficiency and productivity; access; safety and care appropriateness). As potential explanatory variables, we consider seven dimensions, including vaccination rate and the need for intensive care for Covid-19 infected people. Results suggest that Covid-19 pandemic features help explain the drop on access after 2020, but not the evolution of safety and appropriateness of care, which surpris-ingly increased the whole time.

The paper deals with the design of a systematic procedure for implementing strategy changes into internal business processes for a project-oriented production type of organization. In the first part of the contribution, a summary of the theoretical starting points for the field of strategic management and change management is presented. In the second part, the contribution deals with the analysis of the current situation in the area of the impact of the change of strategy on the management of business processes. In the last part, the proposal of the procedure for implementing strategy changes into internal business processes and the verification results are presented. The proposed procedure includes steps where the selection and verification of key performance indicators at individual levels of management plus the quantification of the impact of the change in strategy on the processes takes place. The management can thus monitor and evaluate the chosen processes in accordance with the fulfilment of the chosen strategy of the company. The last chapter presents the verification of the proposal for the systematic introduction of changes into the processes.

This paper presents preliminary operational performance results of a pilot grid-connected photovoltaic (PV) system designed and installed on the rooftop of the Ministry of Petroleum, Energy and Mining headquarter in Nouakchott (latitude of 18.1°N and the longitude of 16.0°W), Mauritania. The aim is for the government to demonstrate the relevance of using solar energy and to encourage the uptake of solar PV technology for commercial and residential building applications in Mauritania.. In this study, the grid-connected PV system has a peak power of 48 kW and the performance monitoring was carried out during one year, with a system that allow to measure DC power, inverter and system conversion efficiency, energy generated by the PV arrays, solar radiation in the inclination plane of panels, ambient temperature and module temperature. During this period, the PV plant was found to supply 65,668 kWh to the grid. The final yield ranged from 3.91 to 5.09 kWh/kWp/day. The performance ratio was found to vary from 69.69% to 89.35% and the annual capacity factor was found to be 19%. Finally, performance parameters were compared with other PV plants installed in the same region of Northern Africa. The outcome of this work is deemed important in assisting accurate PV system design and decision-making.

Thailand has formulated her climate change policy and updated relevant plans and policies to align with the goal of achieving carbon neutrality and net zero GHG emissions. This study investigates the optimal level of GHG mitigation in Thailand, taking into account the marginal abatement cost (MAC) and social cost of carbon (SCC). It evaluates how energy efficiency and renewable energy technologies influence GHG reduction in the power and industrial sector and illustrates policy recommendations that align with the 2020 to 2050 policy and plan period. The findings indicate that there may be instances where GHG mitigation potential is insufficient to reach the national mile-stone. In such cases, it becomes imperative to leverage all technologies within the marginal abatement cost curve (MACC) and also utilization of the social cost of carbon for policy decision making and meeting the desired goals. In certain scenarios, the adoption of additional technologies or measures may be necessary, such as flexible power generation and deploying carbon capture and storage or hydrogen which are high-cost technologies. Furthermore, preparations should be made for multiple levels of climate change policies and plans beyond 2030.

This paper aims at trying to answer the question of whether a low cost drone equipped with a regular camera can serve as a simple device to estimate the size of objects. Ad-ditionally, it assesses if the accuracy of measurement is good enough for using a drone for measurements, relying solely on GPS position and camera. A review of the literature pertaining to ground object measurements was conducted. The availability of such in-struments was evaluated in terms of purchase and rental costs, the number of instru-ments on the market, and the time to obtain them. The most common measurement methods were considered and their unit costs were reviewed. The cost of professional surveying and measuring equipment was compared to the possibility of using low-cost, non-commercial drones to measure objects and surfaces. The quality of the images ob-tained was compared with high-resolution satellite systems. Is an ordinary drone with a standard camera suitable for length measurement without professional measuring equipment? Should the results be considered only in the category of size estimation?

This study investigated the impact of sustainability reporting on financial performance, with a focus on companies in the Turkish food, beverage and tobacco and textile, wearing apparel and leather sectors. The sustainability reports of 48 companies listed on the Istanbul Stock Exchange for 2022 were studied, and the quality of sustainability practices was determined by using a general index (Sustainability Reporting Disclosure Quality Index (SRDQI)) and three partial indices (Environmental Disclosure Quality Index, Social Disclosure Quality Index, and Corporate Governance Disclosure Quality Index (CGDQI)). To analyze the relationships between financial performance and sustainability practices two types of regression models were developed, based on which eight models were directly examined. The results indicate the complete absence of a statistically significant impact of SRDQI on all financial performance measures used. Among the partial indices, only CGDQI has a significant positive effect on the Assets Turnover Ratio. An analysis of the influence of control variables shows a multidirectional dependence of individual financial performance measures on the size of companies, their age, industry affiliation, as well as on the structure of capital used. Finally, this study provides directions for improving the institutional environment of sustainability reporting for Turkish companies.

Asphalt binder is a temperature sensitive material, whose performance is greatly affected by the climate change of the environment. Improper selection of asphalt will cause a lot of damage and affect the durability of the road. The establishment of asphalt pavement performance zoning in Xinjiang, a vast area with great temperature difference, will provide reference for the selection of asphalt suitability, the refinement of pavement design and the sustainable development of road engineering. In this study, 11 years of temperature data in Xinjiang region were collected and analyzed, and 98% reliability of pavement design temperature was used to draw a performance grading map of asphalt pavement in Xinjiang region based on ArcGIS platform. Finally, Xinjiang region was divided into 9 performance zones. At the same time, the performance grade (PG) of five kinds of asphalt binders in Karamay were explored. The result shows that there is little difference in continuous PG span between different matrix asphalt binders, the lower penetration grade, the better high temperature performance, the worse low temperature performance. After adding SBS modifier, the continuous PG span can be higher than the matrix asphalt in 20 ℃. All these provide the basis for reasonable selection of asphalt binders in different areas of Xinjiang.

Performance appraisal is a fundamental indicator in public accountability to achieve the good governance principles. Hence, this study aims to analyze the performance measurement that can improve performance on government agencies in South Sulawesi, Indonesia. The study was conducted in qualitative approach. The research found that non-integrated models of performance measurement in South Sulawesi are inefficient and ineffective. Inefficiency happens because it uses time and cost resources separately, while being ineffective is because both models focuses on each goal instead on performance goals and the process is not supported by the actual management.

Clustering is an important task in data mining that has become more challenging due to the ever-increasing size of available datasets. To cope with these big data scenarios, a high-performance clustering approach is required. Sparse grid clustering is a density-based clustering method that uses a sparse grid density estimation as its central building block. The underlying density estimation approach enables the detection of clusters with non-convex shapes and without a predetermined number of clusters. In this work, we introduce a new distributed and performance-portable variant of the sparse grid clustering algorithm that is suited for big data settings. Our compute kernels were implemented in OpenCL to enable portability across a wide range of architectures. For distributed environments, we added a manager-worker scheme that was implemented using MPI. In experiments on two supercomputers, Piz Daint and Hazel Hen, with up to 100 million data points in a 10-dimensional dataset, we show the performance and scalability of our approach. The dataset with 100 million data points was clustered in 1198s using 128 nodes of Piz Daint. This translates to an overall performance of 352TFLOPS. On the node-level, we provide results for two GPUs, Nvidia's Tesla P100 and the AMD FirePro W8100, and one processor-based platform that uses Intel Xeon E5-2680v3 processors. In these experiments, we achieved between 43% and 66% of the peak performance across all compute kernels and devices, demonstrating the performance portability of our approach.

This review examines the quality of capital investment. It explores the essential components and analysis involved in financially assessing an engineering project, including an assessment of various associated risks. Additionally, the review delves into the historical progression of current capital budgeting practices and surveys academic research in the field. The evaluation of investments has been a recognized challenge for the past thirty years, but it has recently gained renewed attention from both management and scholars. Investments constitute a significant and growing portion of organizations’ capital expenditures. However, assessing the impact of investments on pursued goals is challenging. Consequently, there is a strong demand for methods and techniques that can aid in evaluating investments during the proposal stage. This paper explores several investment strategies and Examines the criteria for investment.

Background: The clinical impact of withdrawal of sodium-glucose cotransporter 2 inhibitor (SGLT2i) on the all-cause readmission in patients with heart failure remains unknown. Methods: Consecutive 212 patients who were hospitalized for heart failure and received SGLT2i during the index hospitalization between February 2016 and July 2022 were evaluated. Of these, 51 patients terminated SGLT2i during or after their index hospitalization. The primary outcome was defined as an all-cause readmission rates/times. Results: Over a median of 23.2 months, an all-cause readmission occurred in 38 of 51 patients (74.5%) withdrawn from SGLT2i and 93 of 161 patients (57.8%) with continuation of SGLT2i (p = 0.099). The total number of all-cause readmissions per year was 0.97 [0-1.50] in patients withdrawn from SGLT2i and 0.50 [0-1.03] in patients with continuation of SGLT2i (p = 0.030). There was no significant difference in total medical cost (62,906 [502-187,246] versus 29,236 [7,920-180,305] JPY per month, p = 0.866) between both patient groups. Conclusions: Termination of SGLT2i may be associated with incremental all-cause readmission and no benefit in reducing total medical costs.

Background: Alopecia areata is a skin disease that affects patients’ quality of life and social participation. Objective: To quantify the economic burden of alopecia areata and to map health services utilization among patients with alopecia areata.Materials and methods: Prospective and retrospective data sources, using both top-down and bottom-up approaches to estimate direct and indirect costs and to map health service utilization associated with alopecia areata in Romania in 2022.Results: In our study, the total cost of alopecia areata in Romania for 2022 was estimated at 46.289 million EUR for adult patients and 1.89 million EUR for pediatric patients, encompassing both mild and severe cases. The breakdown reveals that both mild and severe cases incurred the highest costs due to associated expenses, medical services, and treatment. As for children, the highest alopecia-related expenses were represented by associated expenses and treatment costs (for both severity levels).Conclusion: This is the first study to quantify the burden of alopecia areata in Romania. Additional studies are needed due to a low sample size. However, considering our estimations based on external data sources, alopecia areata should be considered when planning health service distribution.

With the global supply of LNG experiencing unprecedented growth, the industry is on the brink of a programmed glut, further exacerbated by the challenges posed by weaker energy pricing. In light of this, it is expected that marginal programs will be deferred temporarily, yet continuously assessed to enhance their economic potential in the future. Moreover, recent setbacks in LNG programs, such as cost overruns and delays, highlight the critical need for a unique conceptual design master plan. This plan will serve as a powerful tool to evaluate and optimize new programs, ensuring improved economic viability and boosting rates of return. By leveraging advanced analytical frameworks, innovative technologies, and comprehensive risk assessments, this study aims to develop a transformative approach that drives sustainable growth and profitability in the dynamic landscape of LNG program development." "This paper centers around the development of a comprehensive conceptual design master plan aimed at optimizing the total program economics across various areas, including sub-sea, offshore, and onshore advancements. The master plan serves as a crucial framework for identifying opportunities to reduce costs and enhance program definition, drawing insights from selective benchmarks derived from recent successful LNG programs. The ultimate objective is to boost the program rate of return while improving overall program definition, thereby mitigating the risks of cost overruns and schedule delays that have plagued the industry. By implementing this master plan, marginal programs stand a greater chance of becoming economically viable, fostering sustainable growth and enabling stakeholders to make informed decisions in the highly dynamic LNG landscape.

Forest harvesting generates variable amounts of residue that represent a fire hazard and a hindrance to regeneration and must be managed accordingly. In South Africa, burning is the most common residue management method, but there is an interest in introducing safer and more effective techniques, such as mulching. For that reason, a productivity study was conducted in the Eastern Cape province to gather information on the productivity, cost, and work quality of the three main alternatives: manual broadcasting, manual broadcasting followed by mulching with an adapted farm tractor and mulching with a purpose-built mulcher. Manual broadcasting required 16 h/ha, mulching with a farm tractor 3.6 h/ha, and mulching with a purpose-built mulcher 0.9 h/ha (one pass). Manual broadcasting was the cheapest option, at a cost of 400 ZAR/ha. Mulching with a farm tractor and a purpose-built mulcher incurred a cost of 3 267 ZAR/ha and 4 083 ZAR/ha, respectively. Manual broadcasting achieved a minimal reduction of residue size, with 50% of the slash (branches and stem wood) having a mean length above 40 cm. When mulching with a farm tractor was applied, 49% of the slash (branches and stem wood) length reduced to about 30 cm. When a purpose-built mulcher was used, only 10% of the slash elements exceeded 40 cm length.

Regulatory monitoring networks are often too sparse to support community-scale PM2.5 exposure assessment while emerging low-cost sensors have the potential to fill in the gaps. Recent advances in air quality monitoring have produced portable, easy-to use, low-cost, sensor-based monitors, which has given a new dimension to the air pollutant monitoring and has democratized the air quality monitoring process by making monitors and results directly available at community level. This study used PurpleAir(c) sensors for PM2.5 assessment in California, USA. Evaluation of PM2.5 from sensors included Quality Assurance &amp; Quality Control (QAQC) procedures, assessment with respect to reference monitored PM2.5 concentrations, and formulation of a decision support system integrating these observations using geostatistical techniques. The hourly and daily average observed PM2.5 concentrations from PurpleAir monitors followed the trends of observed PM2.5 at regulatory monitors. PurpleAir monitored PM2.5 also captured the peak PM2.5 concentrations due to incidents like forest fire. In comparison with reference monitored PM2.5 levels, it was found that PurpleAir PM2.5 concentrations were mostly higher. The most important reason for PurpleAir higher PM2.5 concentrations was the inclusion of moisture or water vapor as aerosol in contrast to measurements of PM2.5 excluding water content in FEM/FRM and non-FEM/FRM monitors. On long term assessment (2016-2020), R2 was between 0.54 and 0.86 at selected collocated PurpleAir and regulatory monitors for hourly PM2.5 concentrations. Past research studies have been conducted for mostly shorter time periods (&lt;3-4 months) that resulted in higher R2 values between 0.80 to 0.98. This study aims to provide reasonable estimations of PM2.5 concentrations with high spatiotemporal resolutions based on statistical models using PurpleAir measurements. The methods of Kriging and IDW, geostatistical interpolation techniques, showed similar spatio-temporal patterns. Overall, this study revealed that low-cost, sensor based PurpleAir sensors could be effective and reliable tools for episodic and long-term ambient air quality monitoring.

The COVID-19 pandemic has expanded globally and caused serious consequence in both health system and the economy. MPV is one of two oral antivirals for COVID-19 with mild-to-moderate symptoms that have received FDA approval so far. This study aims to evaluate the cost-utility of using MPV in COVID-19 treatment. To compare the utility costs of MPV and non-MPV treatments for COVID-19 patients, we used a decision tree model. Data on clinical efficacy, cost, and quality of life were gathered from previous studies. The incremental effective cost ratio (ICER) calculated based on costs incurred and quality-adjusted life years (QALY), was considered as primary out-come. The total cost of MPV treatment and not using MPV was 15,362,516 VND (618 USD) and 15,771,262 VND (634 USD), respectively. The estimated QALY with using-MPV was 28.33, while without MPV was 19.72. The ICER was dominant, resulting in savings of 47,453 VND/QALY (1.9 USD). MPV is a cost-effective medication used to treat COVID-19. In mild-to-moderate COVID-19 patients, MPV considerably lowers costs and improves quality of life. However, several clinical factors of the drug still need to be taken into account.