Efficiency Measures Research Articles

Measurement of efficiency and its drivers in the Chilean banking industry.

This paper estimates efficiency measures for the banking system in Chile for the period 2000-2019. In contrast to previous studies, we use input-distance functions, introduce the nonparametric slack-based model, and choose the intermediate inputs approach in determining inputs and outputs. Our results suggest that the Chilean system has achieved relatively high levels of efficiency, although with no significant variation over the sample period. Ownership (government, foreign and public) and size had a positive impact on efficiency. On average, mergers and acquisitions seem to have targeted highly efficient banks in order to improve the overall efficiency of the controlling institution in the short run. Other sources of efficiency gains could be an increase in bond funding or a reduction in expenses and capital holdings. The latter could be induced by deepening the local derivatives market.

Phonon-mediated quantum efficiency measurement in semiconductors

Accurate quantum efficiency measurement not only provides crucial information for the photovoltaic cell industry but also supports experiments aimed at directly detecting dark matter and elastic neutrino interactions. The dark matter direct searches paradigm has recently expanded to include particles with masses below 1,MeV/c2, where the expected signal in an electron–recoil interaction is approximately in the eV range, just above the energy gap for silicon and germanium. A robust calibration method for ionization signals in this lower energy region is essential. This paper presents a method for measuring quantum efficiency and yield (q/E) in semiconductors using phonon-mediated calorimetry. The Neganov–Trofimov–Luke phonon amplification method in low-temperature semiconductor crystals has been employed to indirectly measure ionization down to single-electron accuracy. Specifically, at zero bias, the phonon readout directly quantifies the total energy deposited within the detector, independent of the ionization yield. This eliminates a significant source of systematic uncertainty in quantum efficiency estimates associated with total energy uncertainty. The paper includes results from an updated ionization efficiency measurement in a germanium detector.

Design optimization of groundwater circulation well based on numerical simulation and machine learning

The optimal design of groundwater circulation wells (GCWs) is challenging. The key to purifying groundwater using this technique is its proficiency and productivity. However, traditional numerical simulation methods are limited by long modeling times, random optimization schemes, and optimization results that are not comprehensive. To address these issues, this study introduced an innovative approach for the optimal design of a GCW using machine learning methods. The FloPy package was used to create and implement the MODFLOW and MODPATH models. Subsequently, the formulated models were employed to calculate the characteristic indicators of the effectiveness of the GCW operation, including the radius of influence (R) and the ratio of particle recovery (Pr). A detailed collection of 3000 datasets, including measures of operational efficiency and key elements in machine learning, was meticulously compiled into documents through model execution. The optimization models were trained and evaluated using multiple linear regression (MLR), artificial neural networks (ANN), and support vector machines (SVM). The models produced by the three approaches exhibited notable correlations between anticipated outcomes and datasets. For the optimal design of circulating well parameters, machine learning methods not only improve the optimization speed, but also expand the scope of parameter optimization. Consequently, these models were applied to optimize the configuration of the GCW at a site in Xi’an. The optimal scheme for R (Q = 293.17 m3/d, a = 6.09 m, L = 7.28 m) and optimal scheme for Pr (Q = 300 m3/d, a = 3.64 m, L = 1 m) were obtained. The combination of numerical simulations and machine learning is an effective tool for optimizing and predicting the GCW remediation effect.

MSPA-based green space morphological pattern and its spatiotemporal influence on land surface temperature

The frequent occurrence of extreme heat events has notably affected human's living environment, and a considerable number of studies have reported that green space is an efficient measure by investigating the correlation between green space and land surface temperature (LST). However, spatiotemporal effects of green space on LST still remain unclear. In this study, green space patterns (e.g., core, islet, perforation, edge, loop, bridge, and branch) were identified through morphological spatial pattern analysis (MSPA). Moreover, the effects of green space pattern on LST in three periods were investigated through three kinds of models. As indicated by the results: (1) the geographically and temporally weighted regression model exhibited the optimal performance compared with other two models. (2) in general, the core, the edge, the bridge, and the branch significantly contributed to cooling, and the islet hindered cooling. However, the perforation and the loop exerted significant dual nature effects with the similar quantity of the negative and positive coefficients, showing relatively complex impact mechanism. (3) the intensity of the effect of the respective MSPA class varied across the study area. The core had the most substantial effect, which distributed in the south and middle corners. (4) the result suggested that a neighborhood scale in China, which was 960 m in this study, served as a basic unit in green space management. The spatiotemporal non-stationarity of the effects of green space morphological patterns on LST provided important insights into urban thermal environment improvement through urban green space planning and design.

A compromise programming approach for cross efficiency measurement in basic two-stage network system

Data envelopment analysis (DEA) is a technique that allows each decision-making unit (DMU) to calculate efficiency using the most favorable weights for inputs and outputs. The resulting efficiency scores are incomparable and difficult to discriminate. Cross-efficiency is a concept for solving the problem of incomparability among the efficiencies of a set of DMUs that are calculated from different weights and is helpful for ranking. In basic DEA, several cross-efficiency evaluation methods with various secondary purposes have been presented, however, the internal mechanism of the DMUs in cross-efficiency evaluation is often neglected. In this study, we use the composition approach for a basic two-stage structure, so that the efficiencies of the divisions are estimated first, and then the overall efficiency of the system is obtained. To solve the linear bi-objective model in the combination approach, we consider a compromise programming problem to find the solution that is as close as possible to the ideal point. Finally, a secondary objective model is proposed to select a weight among the optimal weights of the compromise model, which also guarantees the efficiency of the optimal weight for the bi-objective problem. We use the optimal solution obtained from this model to evaluate cross-efficiency and rank DMUs for a series two-stage system. The proposed approach enables us to rank the DMUs by assessing the performance of each DMU and each of its separate divisions. The validity of the suggested network cross-efficiency evaluation is demonstrated by a numerical example from the literature.

THE EFFICACY OF VERY LOW CALORIE KETOGENIC DIET (VLCKD) ON CARDIO–METABOLIC PROFILE IN PATIENTS WITH OBESITY

Abstract Background Obesity is associated with alterations in cardiac structure and haemodynamics leading to cardiovascular mortality and morbidity. Very low calorie ketogenic diet (VLCKD) has been proposed as an effective intervention to achieve a significant weight loss in obese patients in a short time period. Furthermore, hyperketonemia induced by VLCKD is associated with beneficial cardiovascular effects. In addition, ketogenic diet is able to prevent mitochondrial fission, improve mitochondrial function, suppress oxidative stress and attenuate cardiac myocytes apoptosis in the heart of mice. Aim To evaluate the role of VLCKD on cardio–metabolic risk factors, cardiac dysfunction and myocardial remodelling in obese patients. Materials and Methods Ten obese patients treated with VLCKD were enrolled. All patients were characterized from an anthropometric, cardio–metabolic and echocardiographic point of view at baseline and 8 weeks after VLCKD treatment. In addition, each patient underwent measurement of global myocardial work efficiency (GWE), a novel indicator that accounts for deformation and afterload, which may provide additional value for assessment of myocardial function. The insulin resistance (IR) was evaluated by HOMA–IR. Results As expected, all the patients showed a significant reduction in body weight and an overall improvement of body composition parameters after VLCKD. Weight (kg) (from 105.1 ± 18.2 to 83.7 ± 16.7, P <0.05), BMI (kg/m2) (from 40.1 ± 4.7 to 31.8 ± 4.8, P= 0.002) and waist circumference (cm) (from 115 ± 13.6 to 101.8 ± 12.4, p < 0.05) were significantly lower after VLCKD treatment. VLCKD treatment improved also significantly fasting glucose levels (P <0.05), fasting insulin levels (P =0.004), HOMA–IR values (P <0.001), lipid profile and systolic and diastolic blood pressure levels. In addition, the echocardiogram evaluation showed an improved in end–diastolic left ventricular volume, end–systolic left ventricular volume, left ventricular mass and left ventricular mass index. Interestingly, a significantly changes in GWE was observed (P<0.05). Conclusion Although preliminary, our data suggest that VLCKD treatment is able to reduce cardio–metabolic risk factors and to improve cardiac dysfunction and myocardial function.

Investigation of dual-ported shroud casing in a centrifugal compressor: Aerodynamic performance and aeroacoustics

The dual-ported shroud casing has two ports over the impeller section in a centrifugal compressor, different from the traditional ported shroud casing. This paper uses numerical simulations and experiments to investigate the effects of the dual-ported shroud on the centrifugal compressor, including aerodynamic performance and aeroacoustics. According to the experimentally measured compressor performance map, the novel finding is that the dual-port casing treatment extends the compressor operating range by improving the instability margin and increasing the compressor choke flow capacity. The mechanism contributing to the choke flow capacity increase is the bypass function. The dual-ported shroud casing bypasses a part of the air to enter the impeller channels at the blade tips without going through the impeller geometry throat. Besides the benefits, the efficiency and aero-acoustic measurements identify the disadvantages of the dual-ports casing treatment: the peak efficiency deterioration at high rotational speeds and louder noise emission at the compressor inlet.

Responsible coordination of municipal health and care services for individuals with serious mental illness: a participatory qualitative study with service users and professionals

BackgroundCare coordination is crucial to ensure the health of individuals with serious mental illness. The aim of this study was to describe and analyze an inclusive innovation process for coordinating municipal health and care services for individuals with serious mental illness.MethodsWe conducted café dialogues with professionals and service users with serious mental illness. The café dialogues engaged participants in conversation and knowledge exchange about care coordination, adressing topics of efficiency, challenges, and improvement. We used a responsible innovation framework to analyze the innovation process.ResultsResponsible coordination requires promoting service users’ health and ensuring communication and mutual awareness between professionals. Individual-level factors supporting responsible coordination included service users knowing their assigned professionals, personalized healthcare services, and access to meaningful activities. Provider-level factors included effective coordination routines, communication, information exchange, and professional familiarity. Results reflect professionals’ and service users’ perspectives on efficient care coordination, existing challenges, and measures to improve care coordination.ConclusionCafé dialogues are an inclusive, participatory method that can produce insights into the responsible coordination of municipal health and care services for individuals with serious mental illness. The responsible innovation framework is helpful in identifying care coordination challenges and measures for responsible coordination.

Carbon Emission Analysis and Reporting in Urban Emissions: An Analysis of the Greenhouse Gas Inventories and Climate Action Plans in Sarıçam Municipality

The urban carbon footprint (UCF) is an important tool for assessing an organization’s ecological impacts and in guiding sustainability efforts. This calculation is usually measured in tons of carbon dioxide equivalent (CO2-eq). Calculations provide important data to determine strategies to reduce the carbon footprint and establish sustainability targets. Various standards and protocols guide UCF calculation, and many organizations aim to make these data transparent to their stakeholders and the public. This study aims to calculate the UCF of Sarıçam Municipality (SM) in the Adana Province of Türkiye. This study includes the greenhouse gas emission inventories resulting from all activities of the SM main service building, guest house, construction site service building, Cultural Center service building, and additional service buildings between 1 January 2022 and 31 December 2022. The calculations include generator fuel consumption, electricity consumption, the refrigerant gas leaks and refills resulting from these activities, the fuel consumed in vehicles owned by the company or whose fuel consumption is under company control, emissions originating from personal travel, emissions originating from customers and visitors, emissions originating from business travel, purchases, etc. Emissions from products purchased and emissions from waste transportation are included. The findings show that, in 2022, the total UCF of SM was equal to 10,862.46 tons of CO2-eq. The Paris Agreement aims to reduce the per capita emissions to approximately two tons of CO2-eq by 2030. The carbon footprint per employee within the municipality was calculated at 12.43 tons of CO2-eq, as derived from the analyzed data. The results reveal the importance of implementing sustainable practices and strategies within SM, such as energy efficiency measures, waste reduction, and the adoption of renewable energy sources, to mitigate its carbon footprint. This study plans to provide a basis for SM’s reduction efforts by keeping greenhouse gas emissions under control.

Semi-Additive Integer-Valued Production Technology for Analyzing Public Hospitals in Mashhad

Conventional Data Envelopment Analysis (DEA) models assume real-valued input-output data and ignore the collaboration among decision-making units (DMUs) in the analysis of efficiency. This paper proposes a novel DEA production technology that is capable of dealing with the collaboration concept and resource sharing for both integer and real-valued data in the efficiency measurement and target setting. This is accomplished by way of a mixed integer linear programming (MILP) efficiency analysis model. We also deal with the computational aspect of the proposed model and invent a MILP with the computational complexity of [Formula: see text] rather than [Formula: see text]. We explain the proposed models by numerical examples and graphical illustrations. We apply our models for efficiency analysis of 15 governmental (public) hospitals in Mashhad City in Iran and demonstrate the practical relevance and advanced future of the proposed methods.

Efficiency measurement of the water recycling system in a fuzzy environment

Efficiency measurement of the water recycling system in a fuzzy environment

The economic impact of E-commerce on the U.S. airports: Cost savings and productivity growth

The rise of e-commerce, fueled by digitalization and shifting in consumer demand, has revolutionized air cargo. While all e-commerce stakeholders are engaged in fierce competition to increase their market share, airports as integral elements of the air cargo supply chain could not be apathetic to this competition. This study examines the economic implication of e-commerce on high cargo volume airports, focusing on cost savings and productivity growth. Utilizing the Farrell measure of input-oriented technical efficiency, we estimate scope economies for the U.S. airports between 2009 and 2019. The results reveal higher scope economies for high cargo volume airports, indicating greater cost savings resulting from e-commerce activities. In addition, the Malmquist index is employed to assess productivity growth. The index is decomposed into technical change, efficiency change, and scale change. The findings show a 3.3% overall productivity growth in the U.S. airport industry, primarily driven by technical change. Besides, high cargo volume airports exhibit higher productivity growth compared to low cargo volume airports, with 4.1% and 2.9% growth rates, respectively. The gap between high cargo volume and low cargo volume airports widened in 2017, aligning with the pre-pandemic peak in e-commerce activity. Furthermore, high cargo volume airports experience higher efficiency gains and technical advancements. While efficiency gains are attributed to improved performance and increased capacity utilization, the technical advancements can be explained by the digitalization and customized operations associated with e-commerce. Overall, the results highlight the significant contribution of e-commerce to cost savings and productivity growth in high-cargo volume airports.

Design approach for carbon-neutral and resilient residential communities: Case study of Tabuk region

In this paper, a systematic analysis approach is outlined to design carbon neutral and resilient residential communities in Tabuk region, Saudi Arabia. The design used cost optimization approach to determine the required capacities for on-site power generation and energy storage using renewable energy resources to achieve desired carbon neutrality and energy resiliency thresholds. Moreover, different energy efficiency levels for the housing units are considered to design grid-connected residential communities based on prevalent grid electricity prices and carbon emissions. The analysis indicates that combinations of energy efficiency measures, PV systems, and storage batteries can be utilized to achieve both desired carbon neutrality and energy resiliency levels. The implementation of proven energy efficiency measures can reduce by over 45 % both the annual electricity demands, and the on-site PV capacities needed to reach carbon neutral designs for the residential communities. The cost-effectiveness of carbon-neutral and resilient designs depends significantly on installation costs of PV systems and wind turbines as well as electricity prices purchased and sold back to the grid. The levelized cost of energy for net-zero energy communities can be as low as 0.06 USD/kWh to reach carbon neutrality.

Analysis of the Operational Efficiency Measurement of Domestic Logistics Enterprises Against the Background of a Low-Carbon Economy

As an indispensable link between low-carbon economic activities, the green development of logistics enterprises determines their market competitiveness and industry development ability. In this paper, 80 domestic logistics enterprises identified in 2022 are selected as objects, and the three-stage data envelope analysis (DEA) method is used to construct the enterprise operation efficiency evaluation index system with the input-output data of 2017–2021. The results show that the overall operating efficiency of domestic logistics enterprises is not high. In 2017, the comprehensive technical efficiency and pure technical efficiency of effective companies reached their peaks, accounting for 22.5% and 35%, respectively. The scale efficiency of effective companies only accounted for 35%. The company's technology and management caliber are negatively impacted by external environmental conditions. There are redundancies in operating input and unreasonable allocations of operating resources. According to the analysis results, this paper puts forward some improvement suggestions for the sustainable development of domestic logistics enterprises from both the government and enterprises.

Environmental stewardship in the oil and gas sector: Current practices and future directions

This paper provides an overview of the current practices and future directions in environmental stewardship within the oil and gas industry, focusing on key areas of concern and strategies for improvement. The oil and gas industry has made significant strides in environmental stewardship in recent years, driven by a combination of regulatory requirements, corporate initiatives, and stakeholder pressure. One of the primary areas of focus has been the reduction of greenhouse gas emissions associated with extraction, refining, and transportation processes. Companies have implemented technologies such as carbon capture and storage to minimize their carbon footprint, alongside investments in renewable energy sources and energy efficiency measures to transition towards cleaner energy alternatives. Furthermore, the industry has placed increasing emphasis on the responsible management of water resources, recognizing the potential environmental impacts of water extraction and usage in oil and gas operations. Strategies for water recycling, reuse, and wastewater treatment have been adopted to mitigate pollution and minimize strain on local ecosystems. Biodiversity conservation has also emerged as a critical aspect of environmental stewardship in the oil and gas sector, with companies undertaking environmental impact assessments and collaborating with conservation organizations to minimize habitat disruption and restore ecosystems affected by their operations. Community engagement and social responsibility are integral components of environmental stewardship, with companies seeking to address the social impacts of their operations through employment opportunities, infrastructure development, and social programs benefiting local communities. However, the industry continues to face challenges and limitations in its efforts to minimize environmental impact. Accidental spills, leaks, and other incidents pose significant ecological risks, highlighting the importance of stringent safety regulations and emergency response protocols. Moreover, the transition to renewable energy presents challenges for traditional oil and gas companies, requiring substantial capital investment and strategic planning. To address these challenges and advance environmental stewardship, several future directions are proposed. These include accelerating the transition to renewable energy, enhancing transparency and accountability in reporting environmental performance, strengthening environmental regulations and enforcement, investing in research and development of innovative technologies, and fostering collaboration among industry stakeholders, governments, NGOs, and local communities. Keywords: Stewardship, Oil, Gas, Sustainability, Climate, Mitigation

The last of the maculineans: can we save the emblematic Alcon Blue butterfly Phengaris alcon under climate change when its habitat continues to deteriorate?

AbstractIn the NW-European region of Flanders (northern Belgium), wet heathlands harbour several threatened species among which the emblematic Alcon Blue butterfly Phengaris alcon is rapidly declining. Since 1990, the number of occupied grid cells in Flanders has decreased from 61 to only six in 2023, a decline of 90%. Due to the loss of many populations, the mean distance between populations tripled from 9 km in the period 1950–1990 to 27 km now. Site-wide egg counts in one of the strongholds of the Alcon Blue in Flanders revealed a strong increase after some initial intensive care conservation measures in the 2000s, but since 2013 a steep decline of 99% has been observed. The standardised egg counts in the remaining six Flemish populations (i.e., monitoring within the framework of the Natura2000 reporting) showed a yearly decrease of 18% since 2016. Despite increased conservation attention and targeted management since the end of the 1990s, the current situation of P. alcon in Belgium is more precarious than ever. Causes of this rapid decline are manifold and they are likely to be amplified by extreme weather conditions caused by climate change. More efficient intensive care measures and more intense cooperation across national borders are now quickly required to regionally preserve this habitat specialist with a unique eco-evolutionary profile.Implications for insect conservation By analysing the causes of the decline of the threatened Alcon Blue butterfly in Flanders, we suggest management and policy measures in an attempt to conserve this and other threatened heathland species in a highly anthropogenic region.

Research on driving factors and efficiency measures of low‐carbon levels in less‐developed regions: A case of Western China

AbstractThe far‐reaching impacts of climate change have further strengthened the determination of governments around the world to pursue low‐carbon development, and low‐carbon efficiency in less developed regions has become a “shortcoming” in realizing low‐carbon aspirations. We analyze the carbon emission efficiency (CEE) and its temporal evolution in less‐developed regions in developing countries, such as Western China. The differentiation of Western China was evaluated in terms of spatial and influencing factors through the Theil index and the logarithmic mean divisia index (LMDI), and the innovative use of GDP gold content (GDPgc) to represent the absolute economic level in the Theil index. Considering the net carbon emissions (NCE) are undesirable outputs, the GDPgc is taken as the desired output. The Un‐Super‐SBM‐CRS method obtained the net carbon emission efficiency (NCEE) values. The results show that: (1) Western regions’ NCE differences can be categorized as high per capita NCE areas (more than 25 tons), medium per capita NCE areas (10–25 tons), and low per capita NCE areas (0–10 tons). (2) The per capita‐based T (Theil index) and the GDPgc are comparable and “intra‐group convergence and inter‐group differentiation” can be used to describe intra‐regional and inter‐regional NCE differences. (3) Both the level of the economy and the level of urban development are drivers of the 11 domains, and the level of the economy is driven more than the level of urban development overall. There are significant regional differences in other factors. (4) The NCEs and their evolutionary trends in each region can be divided into single‐variable and fluctuating‐variable. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

Edges deletion problem of hypercube graphs for some n

Numerous graph-theoretic methods can be used to investigate the efficiency and reliability of networks. The reliability of a network is determined based on its connectivity. At the very least, the system must continue to function in the event of part of its component (node or link) failures. An ideal system remains reliable even when errors occur. Diameter is a measure of network efficiency used to study the effects of link failures in networks. In this paper, we look into the eliminating edges affect to the hypercube graph’s diameter (call it by [Formula: see text]) and calculate the maximum diameter that is denoted by [Formula: see text] after deleting [Formula: see text] edges from hypercube graphs [Formula: see text] for some n.

Novel high-efficiency 2D position-sensitive ZnS:Ag/6LiF scintillator detector for neutron diffraction

Scintillator-based ZnS:Ag/6LiF neutron detectors have been under development at ISIS for more than three decades. Continuous research and development aim to improve detector capabilities, achieve better performance and meet the increasingly demanding requirements set by neutron instruments. As part of this program, a high-efficiency 2D position-sensitive scintillator detector with wavelength-shifting fibres has been developed for neutron-diffraction applications. The detector consists of a double scintillator-fibre layer to improve detection efficiency. Each layer is made up of two orthogonal fibre planes placed between two ZnS:Ag/6LiF scintillator screens. Thin reflective foils are attached to the front and back scintillators of each layer to minimize light cross-talk between layers. The detector has an active area of 192 × 192 mm with a square pixel size of 3 × 3 mm. As part of the development process of the double-layer detector, a single-layer detector was built, together with a prototype detector in which the two layers of the detector could be read out separately. Efficiency calculations and measurements of all three detectors are discussed. The novel double-layer detector has been installed and tested on the SXD diffractometer at ISIS. The detector performance is compared with the current scintillator detectors employed on SXD by studying reference crystal samples. More than a factor of 3 improvement in efficiency is achieved with the double-layer wavelength-shifting-fibre detector. Software routines for further optimizations in spatial resolution and uniformity of response have been implemented and tested for 2D detectors. The methods and results are discussed in this manuscript.

Energy Performance in Residential Buildings as a Property Market Efficiency Driver

Energy consumption plays an important role in contemporary economies. Its significance extends beyond utilitarian value, impacting economic robustness, environmental protection, and residents’ well-being. The escalating global energy requisites necessitate efficient energy utilization and a shift towards renewable sources to address climate change and strengthen energy independence. Developing accurate predictive models to forecast long-term energy costs and savings remains a complex problem. This paper aims to provide a methodology to identify the influence of building energy performance on real estate market efficiency, focusing on property maintenance costs. Real estate plays a crucial role in human life, serving both as a fundamental need and as a vehicle for achieving personal aspirations and secure financial investments, particularly during times of economic and social instability. Through interdisciplinary methodological architecture, this study addresses three key issues: the impact of rising energy costs on market efficiency, the responsiveness of the real estate market to energy price fluctuations, and the significance of property maintenance costs on market value. The research approach includes creating and applying AI algorithms capable of evaluating extensive datasets pertaining to real estate features. Utilizing machine learning methods, the algorithm determines the importance of energy efficiency measures as well as various other inherent and external attributes of properties. The suggested methodology provides a novel approach to improve the effectiveness of market efficiency analysis.