Directional Distance Research Articles

Optimizing Supply Chain Efficiency Using Cross-Efficiency Analysis and Inverse DEA Models

Our study employs cross-efficiency analysis (CEA) and machine learning techniques to optimize supply chain performance. By integrating inverse DEA models with directional distance functions, we measure operational efficiency across various decision-making units (DMUs), accounting for undesirable outputs such as excess costs and emissions. Our results indicate a 20% improvement in market recognition efficiency and a 15% increase in earnings persistence efficiency after model application. Additionally, machine learning classifiers, including Random Forest and Support Vector Machines, further enhanced predictive accuracy, with Random Forest achieving the lowest mean absolute error of 0.07. These findings underscore the effectiveness of advanced analytical models in improving supply chain resilience and decision-making accuracy, contributing to sustainable operational performance.

Simulated GP clinic closure: effects on patient access in the Irish Mid-West.

Rural communities can experience more barriers to accessing health care than their urban counterparts, largely due to fewer healthcare staff and services, and geographical isolation. The purpose of this study is to examine the availability of GP practices in rural communities across the Mid-West of Ireland and the potential impact of practice closure on patient access. GP clinic locations were identified in Ireland's Mid-West, specifically counties Limerick and Clare. Administrative subdivisions of both counties, Small Areas (SAs), were identified and their XY geographic centre coordinates recorded. SAs were indexed into six levels of rurality according to Irish Central Statistics Office urban/rural classifications (1, cities; 2, satellite urban towns; 3, independent urban towns; 4, rural areas with high urban influence; 5, rural areas with moderate urban influence; 6, highly rural/remote areas). The direct linear distance from the centre of each SA to its respective closest GP clinic was calculated. Simulated closure of each GP clinic was assessed programmatically by removing practices from the overall dataset and calculating the new direct linear distance from each SA to the next closest GP clinic. The majority of the SAs in County Clare (63%) and County Limerick (66%) are classified as rural (rurality index ≥4), with the exception of Limerick City, where all SAs were defined as urban. Rural SAs have longer travel distances to GP clinics than their urban counterparts, and these distances are greater with increasing rurality of a population. Simulated closure of GP clinics revealed increasing travel distances to the next closest clinic with increasing level of rurality in a stepwise fashion (r2=0.31). Rural community dwellers across the Mid-West of Ireland face longer travel distances to GP clinics than their urban counterparts. Thus rural communities will be, on average, more adversely affected should their local GP clinic close. While these findings are unsurprising, our methodology calculates a discrete number that can be used to rank vulnerability of local communities. Rural areas are particularly vulnerable to GP clinic closure, and maintaining a solid foundation of primary care in these areas will require careful service and workforce planning.

Reading and Writing Research Based on Surname Group

This study examines the influence of surname on academic performance in higher education. It includes an in-depth analysis of comprehensive book circulation data from the library of Nanjing Normal University, covering the period from 2012 to 2023. The study uses Kendall coefficients to assess the consistency in book circulation and renewal among the top 300 surnames of readers, employs multidimensional scaling analysis to identify differences or similarities between categorical variables through direct distance assessment, uses chi-square tests to measure the correlation between surnames above and below the mean line and various categorical variables, and conducts survival analysis to examine circulation activities related to the top 300 surnames. Results are interpreted in the context of female-dominated education and teacher preparation. The results reveal a consistent pattern in the 12-year borrowing and renewal habits of the top 300 surnames of readers. A hierachical mismatch between the reader, book category, and author reflects complex reading interests beyond academic authority. In the wake of the COVID-19 pandemic, readers with surnames above the average have shown less interest in using the book renewal service. The borrowing and renewal activity for the disappeared surnames changed within two years for foreign language books and six years for Chinese books.

Soft Tissue Facial Morphology in Growing Patients with Different Occlusal Classes.

The study of facial profiles in the dental field is very important for the diagnosis and the dental and orthodontic treatment plan. The aim of this study is to analyze the three-dimensional morphology of the faces of 269 growing patients with Class I and II occlusions, focusing on children aged between 6 and 9 years old. The analysis was conducted using a non-invasive computerized system, which allowed for the automatic collection of facial landmarks and the subsequent reconstruction of three-dimensional coordinates. The sample comprised 269 children within the specified age range. Each child's facial features were captured using the non-invasive computerized system, which utilized two infrared CCD cameras, real-time hardware for label recognition, and software for three-dimensional landmark reconstruction. Sixteen cutaneous facial landmarks were automatically collected for each participant. From these landmarks, 10 angular and 15 linear measurements, as well as five direct distance rates, were derived. The mean values for each age class were calculated separately for children with bilateral Angle Class I occlusion and compared with those for children with bilateral Class II occlusion. In all children, the left and right occlusal classes were measured as suggested by Katz. The analysis revealed notable differences, primarily in the three-dimensional angular measurements between children with Class I and II occlusions. Specifically, Class II children exhibited more convex faces in the sagittal plane and a less prominent lower jaw compared to Class I children. However, no significant differences were observed in linear measurements, except for the lower facial height rate, which varied inconsistently across age groups between the two occlusion types. the findings of this research highlight distinct three-dimensional facial morphological differences between children with Class I and II occlusions. While Class II children tended to have more convex facial profiles and less prominent lower jaws, linear measurements showed minimal variation between the two occlusion types. These results underscore the importance of three-dimensional analysis in understanding facial morphology in growing patients with different occlusal patterns.

The impact of big fund on the operational efficiency of semiconductor companies: Corporate social responsibility as a non-economic output

This study contributes to research on the total factor operational efficiency of the semiconductor company considering corporate social responsibility (CSR) by proposing a novel integer-valued nonparametric frontier method. This method adopts an endogenous directional distance function, which first selects the benchmark and then endogenously determines the directional vector. Avoiding the issue of non-integer slack adjustment increases the convenience of formulating incentive plans and calculating efficiency. We apply this method to the input–output data of 185 listed Chinese semiconductor companies from 2010 to 2022, considering integer-valued CSR as non-economic output. Global Malmquist productivity index analysis shows that the average total factor operational efficiency of companies that received investment from the National Integrated Circuit Industry Investment Fund (Big Fund) increased by 6.9%. Using the econometric technique, we verify that the total factor operational efficiency of semiconductor companies receiving Big Fund investment increased by 0.084 compared to those without Big Fund investment. Heterogeneity analysis showed that the effect of Big Fund was more significant in improving the total factor operational efficiency of state-owned, new, and non-integrated circuit semiconductor companies, implying the necessity of purposeful investment policies for the Big Fund.

Heterogeneous strategy and performance decomposition of regional industries in China: From the perspective of resource misallocation

AbstractThe rapid expansion of China's industrial sector has been accompanied by energy consumption and environmental pollution. Accurately identifying the sources of inefficiency of industrial sector is crucial for achieving sustainable development. To address this issue, this study develops a novel decomposition approach that combines the concepts of natural and managerial disposability with an aggregate directional distance function approach to measure the performance of regional industries in China from 2006 to 2019. In the proposed approach, the overall inefficiency is decomposed into technical inefficiency and structural inefficiency. The latter component, which captures inefficiency associated with resource misallocation within a country, is further divided into mix and scale elements. The results show that there remains much room for potential improvement in both the operational and environmental performance of China's industrial system, particularly in the central area. Furthermore, structural inefficiency is the primary contributor to the overall inefficiency of Chinese industry under natural disposability, whereas technical inefficiency appears as the main source of the inefficiency under managerial disposability. The results also reveal great disparities in terms of the overall inefficiency and the sources of inefficiency of Chinese industrial sector among regions between different mitigation strategies. Given the substantial structural effect on the performance of Chinese industries across regions, it is necessary to accelerate the establishment of market mechanisms to promote efficient allocation of resources.

Lessons from the Pilot Project of Korean ETS on the Local Landscape of Economy

For a sustainable landscape of local economies, many researchers have emphasized the importance of field-oriented differentiation in government policies. In particular, the Paris Agreement, based on the bottom-up approach, aims to maximize the participation of all economic agents, in contrast to the top-down approach of the Tokyo Protocol. In response to these global paradigm shifts in the local landscape, local governments in Korea have made significant efforts to adapt to sustainable development during the pilot phase of emission trading scheme (ETS), during the period from 2015 to 2020. This study evaluates the performance of these local government policies in the transition to a carbon-zero economy. Using the general non-radial directional distance function (GNDDF), we found that Gyeongsang Province demonstrated enhanced environmental total factor productivity (TFP) during the pilot project, whereas the Seoul metropolitan area lagged behind due to a lack of governance. As the economic center of Korea, Seoul showed poor environmental performance because of the arbitrary elimination of green belt areas and unchecked land development, resulting in environmental degradation, a trend common in many developing countries facing climate adaptation challenges. To address these urbanization issues, this study concludes that a balanced approach combining stricter regulations with market-oriented promotional incentives is essential for optimizing the transition of local economies to a sustainable landscape.

Decreased diaphragm moving distance measured by ultrasound speckle tracking reflects poor prognosis in amyotrophic lateral sclerosis

ObjectiveDecreased cephalocaudal diaphragm movement may indicate respiratory dysfunction in amyotrophic lateral sclerosis (ALS). We aimed to evaluate diaphragm function in ALS using ultrasound speckle tracking, an image-analysis technology that follows similar pixel patterns. MethodsWe developed an offline application that tracks pixel patterns of recorded ultrasound video images using speckle-tracking methods. Ultrasonography of the diaphragm movement during spontaneous quiet respiration was performed on 19 ALS patients and 21 controls to measure the diaphragm moving distance (DMD) in the cephalocaudal direction during a single respiration. We compared respiratory function measures and analyzed the relationship between the clinical profiles and DMD. ResultsDMD was significantly lower in ALS patients than in the control group (0.6 ± 1.4 mm vs 2.2 ± 2.2 mm, p < 0.01) and positively correlated with phrenic nerve compound motor action potential amplitude (R = 0.63, p = 0.01). DMD was negatively correlated with the change in the ALS Functional Rating Scale-Revised scores per month after the exam (R = −0.61, p = 0.02), and those with a larger rate of decline had a significantly lower DMD (p = 0.03). ConclusionsDiaphragm ultrasound speckle tracking enabled the detection of diaphragm dysfunction in ALS. SignificanceDiaphragm ultrasound speckle tracking may be useful for predicting prognosis.

Layout Optimization of Wave Energy Park Based on Multi-Objective Optimization Algorithm

Abstract In this paper, both semi-analytical method and numerical simulation is applied to investigate the hydrodynamic behavior of large arrays of point-absorber wave energy converters (WECs). To analyze wave interactions among multiple WECs within an array, a semi-analytical model is developed based on the potential flow theory and the matched eigen-function expansions method. The fluid domain is divided into two kinds of regions: interior regions underneath the cylinders and an exterior region surrounding all the cylinders. The matched eigenfunction expansions method is employed to solve the radiation potential problem in each domain, and the hydrodynamic coefficients and motion response of the cylinders in the array are evaluated. To validate the accuracy of the semi-analytical method, WAMIT is adopted to simulate the wave energy park numerically and compared with the results by the semi-analytical model. The hydrodynamic characteristics and power absorption performance of the WECs within the wave energy park are analyzed. The power performance of a wave energy park is studied as functions of layout geometry, incident wave direction and separation distance between WECs respectively. Finally, MOPSO based on a surrogate model is used to optimize the layout of wave energy array.

Assessing performance of water supply operation of water companies in China: A union dynamic multi-activity network data envelopment analysis

Urban growth and the increasing urban water demand highlight the importance of performance analysis in the water supply industry. Both water supply companies (WSCs) and water supply and sewage companies (WSSCs) produce and deliver potable water for city dwellers. Water authorities use benchmarks to monitor the two types of companies’ operations. The internal operation process and heterogeneities of observations were not considered for relative performance evaluation by conventional DEA models. To overcome these limitations, this study proposes a union dynamic multi-activity network data envelopment analysis (DMANDEA) model to extend static network DEA to a more general case for dynamic efficiency assessment of the water supply operations of water companies. For the first time, the model allows for the decomposition of the water supply operation into water production (WP) and water consumption (WC) substages and performance comparisons for water companies by considering their heterogeneity simultaneously. Specifically, by using a non-radial directional distance function (DDF), the inefficiencies for substages and the entire system can be both assessed dynamically. This model is applied to a sample of 246 water companies in China in 2016–2018. The overall, period, and substages’ group efficiencies, meta efficiency, and technology gap ratio (TGR) for 179 WSCs and 67 WSSCs are all provided. The empirical results reveal that: (1) the average group efficiencies of WSCs and WSSCs are 0.4567 and 0.6611, respectively. The meta efficiencies of WSCs and WSSCs are 0.4523 and 0.4703, respectively. The TGR of WSCs (0.994) is greater than that of WSSCs (0.7067). (2) WSSCs perform better than WSCs do, which suggests that economies of scope do exist in WSSCs. However, WSCs possess the best technology for water supply operations because of their high TGR. (3) The average meta efficiency for all the observed water companies (0.4572) is not optimistic, which correlates more with inefficiency in the WP stage. The causes stem from the natural monopoly, lack of competition, and relatively lower water tariffs. The Chinese water supply industry requires diversification of ownership and operation modes, and gradual increases in water tariffs. (4) Water companies in the eastern region outperform those in other regions. Regional cooperation, such as technology sharing, the transfer of managerial experience, and information exchange, needs to be emphasized.

The performance of alternative GPS tracking devices: a case report on wild boars (Sus scrofa)

BackgroundTelemetry studies on terrestrial mammals have been carried out almost exclusively using neck collar-mounted devices. However, collars are not suitable for all species and all age classes and may therefore compromise animal welfare and data quality requirements. Here, we evaluate the use of non-collar tracking devices on wild boars (Sus scrofa), a species for which collars may be problematic due to neck shape and seasonal body mass variation. We tested pelt-glued tags and three types of GPS ear tags. In addition, animals were marked with plain cattle ear tags.ResultsThe tested GPS tags exhibited various technical challenges related mostly to satellite coverage of the study area and tag loss. However, GPS devices enabled moderate movement monitoring of weeks to months, whereas plain cattle ear tags offered information on displacement over longer time intervals. The longest direct dispersal distance (163 km) by a wild boar sounder was discovered by cattle tags.ConclusionsData volume and quality obtained from small tags are inferior to data provided by GPS collars, but low-fix rate tags may enable monitoring of individuals with reduced invasiveness. Moreover, these tags enable tracking in cases where the collar is not an option. The low price and small size of the devices together with technical developments may offer cost-effective tools for future studies on dispersal and survival.

Seeking sustainable efficient global agricultural production with nexus approach

This study aims to estimate the shadow prices of water and carbon dioxide (CO2) in global agriculture under three scenarios: pursuing economic efficiency, sustainable development goals (SDGs), and environmental protection. It assesses the social cost of environmental impacts compared to actual prices. This study also evaluates substitutability among water, labor, and capital in the three scenarios for developing relevant agricultural policies depending on distinct agricultural conditions. Social costs tend to be underestimated because they are not directly observed. Our society has faced an overproduction of agriculture in terms of CO2 emissions and the exploitation of water. This study employs a method of a directional technology distance function for global agricultural production based on Food and Agriculture Organization data on agricultural inputs and outputs. The following three critical findings were obtained: First, the average shadow price of water under the economic scenario was close to the current actual water prices, and water prices would increase if agricultural production accomplished the three SDGs (Goal 2, 6, and 13). Second, labor is substituted for water under the environmental scenario because water prices increase rapidly. In contrast, water is complementary to labor under the SDGs scenario, implying that labor becomes more important for increasing food production. Third, the current CO2 prices are lower than those in the economic scenario. These values are significantly lower than those under the SDGs and environmental scenarios. Based on these results, we conclude that agricultural products are often undervalued because the appropriate value of water is overlooked in real markets. The contribution to reducing CO2 in agriculture is insufficient, owing to current low carbon taxes.

Analysing cost-effectiveness in dynamic network DEA: a directional distance function approach

Analysing cost-effectiveness in dynamic network DEA: a directional distance function approach

Three-dimensional moisture transport fabric for enhanced moisture management in protective clothing

Effective moisture management within the microenvironment of protective clothing is crucial for maintaining garment performance and wearer comfort. The inherent properties of fabrics and the structural of protective garments often hinder the discharge of sweat to the external environment. Here, we present a novel 3D moisture transport fabric, engineered with gradient wetting properties along both the thickness and length dimensions. This fabric can transport moisture from the inner to the outer surface within approximately 5 s, achieving a maximum accumulative one-way transport capability of 1189.1 in the thickness direction. Additionally, by further directing moisture along the constructed wetting gradient on the fabric's outer surface, the moisture diffusion distance in the gradient direction was up to 2.6 times greater than in other directions. This approach will enhance moisture transport and management within protective clothing and can be further extended to the development of materials for oil-water separation, wound dressings, flexible microfluidics, and fuel cell membranes.

Effect of DG penetration on hybrid relay coordination using user-defined dual-setting directional overcurrent relays and distance relays

ABSTRACT The efficient coordination of the distance and directional overcurrent relays (DOCRs) is jeopardized by the massive deployment of renewable distributed generation (DG) into electrical power networks. The two key aspects influencing the relay coordination are the bidirectional flow of current and increased short-circuit currents due to DG integration. This study investigates the consequences of variable DG penetration on the distance and dual-setting DOCRs (DS-DOCRs) coordination. As a result, common optimal relay settings have been obtained that can be utilized for variable DG penetration levels in modified IEEE-14 bus test system. For the distance relays (DRs), a fixed zone 1 and variable zone 2 operation have been considered. The proposed combined protection scheme is tested on a modified IEEE-14 bus test system using DS-DOCRs and DRs. The relay coordination problem is formulated as a constrained non-linear optimization problem and solved by genetic algorithm (GA) and gray wolf optimization (GWO). In this paper, DS-DOCRs with user-defined relay characteristics have demonstrated superior performance in line protection compared to conventional DOCRs with normal inverse (NI) characteristics. In addition, a comprehensive comparative analysis of optimization algorithms has been performed between GA and GWO algorithms.

Economic sanctions and energy efficiency: Evidence from Iranian industrial sub-sectors

Improving energy efficiency is vital for reducing energy consumption and can have substantial impacts on reducing carbon emissions. This study investigates the impact of sanctions on Iran's energy efficiency across different industrial sub-sectors from 2015 to 2019. We compute a sanction intensity index for each industrial sub-sector using principal component analysis. This index measures how much each sub-sector has been affected by sanctions. Additionally, energy efficiency is measured using the directional distance function method, considering the emission impacts as undesirable outputs. We use fixed effects regression analysis, adjusting for various manifestations of cross-sectional (spatial) and temporal dependence and controlling for other sectoral drivers of energy efficiency. We find a significant negative effect of sanction intensity on energy efficiency at the industrial sub-sector level in Iran. The negative effect of sanctions on energy efficiency is significantly larger for industrial units with higher import dependency.

Directional aspects of crop yield correlation: Implications for insurance rating and contract design

AbstractWe estimate directional anisotropic models of linear correlation for crop yields. We find that directional distances (i.e., the degree to which yield correlation decays depending on direction) tend to differ from one another, with east to west distances being “longer” than north to south distances (i.e., correlation tends to decline slower in the east to west direction), at least for the major crops of corn and soybeans. Results for wheat are somewhat ambiguous. However, in all cases, average yield aggregates made up of east to west linked counties tend to be more accurate than is the case for north to south linkages. Implications for rating and contract design in the US area yield federal crop insurance program are offered.

Inter-annual variability and health risk assessment of summer VOCs in a Plain City of China

This study investigated the inter-annual variations, transport pathways, pollution sources, and health implications of volatile organic compounds (VOCs) in Zhengzhou, China, a city notably affected by ground-level ozone (O3) pollution. Analyzing VOCs data from the summers of 2017–2021 revealed an average summer VOCs concentration of 61.8 ± 18.2 μg/m3, predominantly consisting of alkanes (55.0%), aromatics (22.5%), and alkenes (16.9%). The study identified significant year-to-year disparities in VOC abundances and compositions, which were closely linked to meteorological conditions, including temperature, wind speed, and relative humidity. Additionally, factors like air mass origin, direction and transport distance critically influenced the VOCs characteristics, with local air masses exhibiting higher VOC concentrations than those from distances of 100–500 km to the northwest, west and east. Positive Matrix Factorization (PMF) analysis identified major sources of VOCs as vehicle exhaust, oil and gas evaporation, solvent use, and biogenic emissions, with their contributions varying annually influenced by regional transport, environmental policies, and the COVID-19 pandemic. Health risk assessments, following U.S. Environmental Protection Agency guidelines, indicated negligible non-carcinogenic and carcinogenic risks from VOCs exposure, except for a potential carcinogenic risk from ethylbenzene. Solvent use sources were found to have the highest risks, with non-carcinogenic risks at 4.1 × 10−3 (negligible) and carcinogenic risks at 7.8 × 10−7 (with potentially carcinogenic in 2017 but negligible in subsequent years). This research underscored the complex dynamics of VOCs pollution and provided insights for developing effective pollution control strategies and enhancing public health in urban settings.

Advanced Fuzzy-Based Decision-Making: The Linear Diophantine Fuzzy CODAS Method for Logistic Specialist Selection

This study addresses the inherent uncertainty in human decision-making by leveraging fuzzy sets, which were introduced to better capture the imprecision associated with human thoughts and judgments. As an extension to traditional fuzzy sets, the Linear Diophantine Fuzzy Set (LDFS) was developed, offering a more flexible approach by relaxing existing limitations on grade values. The LDFS has found applications across various fields, demonstrating its versatility and effectiveness. In this study, we explore the application of the Linear Diophantine Fuzzy Set within the framework of the Combinative Distance-based Assessment (CODAS) method. The CODAS method stands out because it incorporates Euclidean and Taxicab distances. Decision-making should consider not only the direct distances between ideal solutions and alternatives but also the indirect distances. The foremost objective of this research is to propose a novel approach by integrating the CODAS method with the LDFS to address complex decision-making problems characterized by uncertainty and imprecision. To illustrate the practical utility of the proposed method, we apply it to a numerical example involving the selection of a logistics specialist, a critical decision in emergency logistics optimization. The research also includes a case study on a logistics specialist, highlighting the practical application of the methods discussed. Furthermore, this study provides a comprehensive sensitivity analysis of the parameters' weights to evaluate the robustness and reliability of the proposed method. The results highlight the effectiveness of the LDF CODAS method in making informed and reliable decisions under conditions of uncertainty, paving the way for future applications in other decision-making scenarios.

Research on food security issues considering changes in rainfall

Ensuring food security is not only vital to the adequate supply of food in the world, but also the key to the economic development and social stability of various countries. Based on the panel data of 29 provinces in China from 2016 to 2020, this paper selects the number of foodborne diseases patients and iodine deficiency disease patients as reference objects, uses stunting rate of children under 5 years old, malnutrition rate of children under 5 years old, obesity rate of children under 5 years old, and newborn visit rate to measure improving nutrition, proposes Meta Entropy Two-Stage Dynamic Direction Distance Function (DDF) Under an exogenous Data Envelopment Analysis (DEA) model to measure the efficiency of hunger eradication, food security, and improving nutrition under the influence of exogenous variable rainfall. The research results indicate that the sustainability of China’s agricultural economy is insufficient, and the focus of attention should be different in different stages. In addition, the average efficiency of the three regions generally shows a decreasing level in the eastern, western, and central regions. In order to improve China's ability to guarantee food security, we must continue to strengthen the construction of agricultural infrastructure, increase policy support for green agricultural production, promote the diversification of agricultural production, and enrich people’s agricultural product consumption varieties.