Local Rank Research Articles

Physiological and perceptual demands of singles and doubles beach tennis in women of different competition levels.

To analyze and compare the physiological responses of women during singles and doubles beach tennis sessions. In this crossover trial, twenty-two women with previous participation in amateur beach tennis tournaments randomly performed two experimental sessions: singles and doubles beach tennis. The routine for both sessions consisted of 10-min of seated rest, followed by 45-min of beach tennis and 30-min of post-exercise recovery. Participants were matched against opponents of the same competition level, defined according to their local beach tennis ranking (advanced or intermediate level). They warmed up with basic techniques for 5-min and played 3 matches lasting 12-min, interspersed with 2-min recovery intervals. Heart rate (HR), energy expenditure (EE), number of steps (STEPS), handgrip strength (HS), rating of perceived exertion (RPE), and enjoyment were assessed throughout the sessions. Generalized estimating equations were employed to examine the main effects between experimental sessions over the time and in relation to competition level. HRmean and HRmax (Δ: HRmean = 13 ± 3 bpm; HRmax = 11 ± 3 bpm) as well as EE and Steps (Δ: EE = 66 ± 22 kcal; RPE = 2 ± 0 A.U.; Steps = 250 ± 52 A.U.) were higher in singles than doubles (p < 0.05). The percentage of total time spent in the highest HR zone (91-100%HRmax) was significantly greater in singles than in doubles (39% ± 22% vs. 15% ± 18%; p < 0.05). Differences were found in the percentage of total time spent in each HR zone, recovery HR, and HS between competition levels (p < 0.05). Singles beach tennis resulted in higher physiological demands than doubles in women, and players' competition level partly affects the training responses.

GRAMP: A gene ranking and model prioritisation framework for building consensus genetic networks

Despite significant recent advancements in computational and statistical methods, different methods have specific strengths and weaknesses in the accurate reconstruction of gene regulatory networks (GRNs), making it difficult to determine the best method for each specific problem. To overcome these challenges, ensemble approaches, which combine the strengths of individual inference methods, are valuable. However, existing ensemble methods for GRN inference lack a sophisticated network aggregation method and generally rely solely on ranking approaches. These ensemble methods have no reliable mechanisms to identify highly performing inference methods specific to a given problem. They therefore tend to aggregate weak methods, diminishing the overall accuracy of the approach. Thus, developing a reliable mechanism to identify the most effective methods for specific problems and prioritize them in consensus network building is important. This paper presents a novel ensemble approach for reconstructing GRNs by integrating previously developed diverse GRN inference approaches. A novel network aggregation method called GRAMP, Gene Ranking And Model Prioritisation framework was developed, taking into consideration both local and global gene ranking and the performance of different inference approaches on a specific network. The proposed ensemble approach demonstrated performance superior to those of other state-of-the-art methods, as evidenced by results from simulated datasets and a real-world gene expression dataset.

Crop Water Status Analysis from Complex Agricultural Data Using UMAP-Based Local Biplot

To optimize growth and management, precision agriculture relies on a deep understanding of agricultural dynamics, particularly crop water status analysis. Leveraging unmanned aerial vehicles, we can efficiently acquire high-resolution spatiotemporal samples by utilizing remote sensors. However, non-linear relationships among data features, localized within specific subgroups, frequently emerge in agricultural data. Interpreting these complex patterns requires sophisticated analysis due to the presence of noise, high variability, and non-stationarity behavior in the collected samples. Here, we introduce Local Biplot, a methodological framework tailored for discerning meaningful data patterns in non-stationary contexts for precision agriculture. Local Biplot relies on the well-known uniform manifold approximation and projection method, such as UMAP, and local affine transformations to codify non-stationary and non-linear data patterns while maintaining interpretability. This lets us find important clusters for transformation and projection within a single global axis pair. Hence, our framework encompasses variable and observational contributions within individual clusters. At the same time, we provide a relevance analysis strategy to help explain why those clusters exist, facilitating the understanding of data dynamics while favoring interpretability. We demonstrated our method’s capabilities through experiments on both synthetic and real-world datasets, covering scenarios involving grass and rice crops. Moreover, we use random forest and linear regression models to predict water status variables from our Local Biplot-based feature ranking and clusters. Our findings revealed enhanced clustering and prediction capability while emphasizing the importance of input features in precision agriculture. As a result, Local Biplot is a useful tool to visualize, analyze, and compare the intricate underlying patterns and internal structures of complex agricultural datasets.

Explaining Genetic Programming-Evolved Routing Policies for Uncertain Capacitated Arc Routing Problems

Genetic programming has been successfully used to evolve routing policies that can make real-time routing decisions for uncertain arc routing problems. Although the evolved routing policies are highly effective, they are typically very large and complex, and hard to be understood and trusted by real users. Existing studies have attempted to improve the interpretability by developing new genetic programming approaches to evolve both effective and interpretable (e.g., with smaller program size) routing policies. However, they still have limitations due to the trade-off between effectiveness and interpretability. To address this issue, we propose a new post-hoc explanation approach to explaining the effective but complex routing policies evolved by genetic programming. The new approach includes a local ranking explanation and a global explanation module. The local ranking explanation uses particle swarm optimisation to learn an interpretable linear model that accurately explains the local behaviour of the routing policy for each decision situation. Then, the global explanation module uses a clustering technique to summarise the local explanations into a global explanation. The experimental results and case studies on the benchmark datasets show that the proposed method can obtain accurate and understandable explanations of the routing policies evolved for uncertain arc routing problems. Our explanation approach is not restricted to uncertain arc routing, but has a great potential to be generalised to other optimisation and machine learning problems such as learning classifier systems and reinforcement learning.

Breeding practice of indigenous village chickens, and traits and breed preferences of smallholder farmers.

Indigenous village chickens, or (IVCs), significantly contribute to rural livelihoods. Although natural selection has a disproportionate impact on the genetic structure of IVCs, farmers have developed locally tailored breeding practices to get the most out of their flocks. Small-scale farmers' insights on trait breed preferences and family flock breeding practices are presented in this cross-sectional study. A cross-sectional study was conducted in two agroecological zones using face-to-face individual interviews with 119 general informants. Farmers prefer IVCs because they are multipurpose birds. Unlike policymakers, who usually underestimate the importance of IVCs, small-scale farmers acknowledge the coexistence of local and commercial chickens. Only 15.7% of farmers recruited homegrown cocks, whereas 47.9% outsourced breeding cocks from local markets and 36.4% from neighbours (χ-squared=15.976, df=2, p=0.0003395). About 49.2% of small-scale farmers believed that consanguineous mating-induced inbreeding has only trivial effects. High flock turnover significantly reduces inbreeding. Regardless of the low production capacity, small-scale farmers prefer local (rank=1.47) chickens to commercial (rank=1.61). For cocks, fertility and growth traits were highly sought after, whereas for hens, maternal instincts and laying performance were prioritized. Compared to the highlands, the lowlands had a longer egg storage period (t=2.677, df=117, p=0.009, 95% CI: -3.7607, -0.5622). This study documented the wisdom of small-scale farmers and encouraged the incorporation of their insights into a sustainable genetic improvement program.

Containerization on a self-supervised active foveated approach to computer vision

Scaling complexity and appropriate data sets availability for training current Computer Vision (CV) applications poses major challenges. We tackle these challenges finding inspiration in biology and introducing a Self-supervised (SS) active foveated approach for CV. In this paper we present our solution to achieve portability and reproducibility by means of containerization utilizing Singularity. We also show the parallelization scheme used to run our models on ThetaGPU–an Argonne Leadership Computing Facility (ALCF) machine of 24 NVIDIA DGX A100 nodes. We describe how to use mpi4py to provide DistributedDataParallel (DDP) with all the needed information about world size as well as global and local ranks. We also show our dual pipe implementation of a foveator using NVIDIA Data Loading Library (DALI). Finally we conduct a series of strong scaling tests on up to 16 ThetaGPU nodes (128 GPUs), and show some variability trends in parallel scaling efficiency.

286 Partnering and engaging in Indiana Communities through listening sessions and data sharing: successes of Connection IN Health

OBJECTIVES/GOALS: Participants will be able to identify how partnering with state health departments for a CTSA initiative assists in meeting shared goals by building infrastructure and sharing resources and list key components of a successful county engagement process that can be replicated. METHODS/STUDY POPULATION: Connections IN Health is a collaborative project with the Indiana Clinical and Translational Sciences Institute, Indiana Department of Health, Indiana University Simon Comprehensive Cancer Center, and community partners. We address chronic disease in Indiana with coalition-based engagement at the grassroots level, and partnering to provide technical assistance, resources, connections and evidence-based strategies to address the health challenges. Our methods of county engagement include surveying the broad community, conducting listening sessions with key community stakeholders, compiling, analyzing and sharing data, collaborating with existing local coalitions, assessing community readiness and suggesting evidence-based practices to implement. RESULTS/ANTICIPATED RESULTS: As a result of county engagement, local coalitions have current, local data to drive their efforts in improving local health rankings and outcomes. Community partners in eight counties have selected and implemented evidence-based strategies to manage and/or prevent diabetes, cardiovascular disease and/or stroke. Some examples include: starting a community garden with cooking classes in a food desert to provide fresh produce and nutrition/cooking knowledge, creating a mobile kitchen on hand for organizations to use to provide education and cooking skills, providing a passport for wellness at existing community events with food samples and health screenings and offering evidence-based educational programming such as Dining with Diabetes and Be Heart Smart. DISCUSSION/SIGNIFICANCE: Moving county health coalitions to evidence-based programming that has the greatest likelihood for success is a critical translational sciences challenge. Our rigorous and well defined approach yields significant improvement in local health coalition activities, sustaining their activities through long-term trusted relationships.

Three-phase multi-criteria ranking considering three-way decision framework and criterion fuzzy concept

The criterion fuzzy concept refers to a fuzzy set that represents the decision-maker's subjective preference for each criterion within the universe of criteria. Addressing the challenge of ranking all alternatives based on a given criterion fuzzy concept is a novel research direction in the field of fuzzy multi-criteria ranking issues. This paper proposes a three-phase approach for multi-criteria ranking in fuzzy environments, which combines the criterion fuzzy concept and three-way decision thinking. The proposed approach not only analyzes the decision-making characteristics of all alternatives but also facilitates their ranking. During the first phase, a qualitative classification method based on the criterion fuzzy concept and ideal solutions is defined, which divides all alternatives into three independent decision sub-regions. During the second phase, by analyzing the priority relationships among the alternatives within every sub-region, three local ranking rules for alternatives are proposed to determine the ranking of alternatives in each classification region. During the third phase, the semantic relations among three classification regions are considered to give an overall ranking of all alternatives. Finally, combined with two existing quantitative ranking indicators, multiple data sets are employed to verify the feasibility and superiority of the proposed three-phase multi-criteria ranking approach.

Innovation’s Performance: A Transnational Analysis Based on the Global Innovation Index

The pandemic marked the beginning of a succession of events on a global scale (not the least of which is a greater concern for the environment and for quality of life/distance work) with a major impact on the economy. Innovation plays a key role in meeting the challenges of the future, but despite investment in innovation, global economic growth has fallen short of the expected performance. The aim of this study is to identify the factors with the greatest impact on the performance of innovation ecosystems based on the performance of the innovation ecosystems of 64 countries assessed by the Global Innovation Index 2022. The methodology consists of multiple hierarchical linear regressions, in which the impact factors on innovation ecosystems, measured through indicators, are the independent variables and innovation performance, in knowledge and technology and in creativity, are the dependent variables in an iterative process, using STATA/MP 18.0 data analysis software. The results indicate that human capital and research (the basis of business and innovative products aimed at filling gaps in the market are people with a good higher education, which is also linked to local university rankings) and business sophistication (highly qualified work, leveraging strategic partnerships, and with knowledge absorption capacity) are the main pillars determining innovation performance at a global level. Education (an educated workforce is of growing importance in the knowledge era), R&amp;D investment (including support from the state in the form of tax incentives for whoever invests in R&amp;D), innovation partnerships (for a faster, more open innovation effort), ecological sustainability (a new reinforced priority after COVID-19) and knowledge absorption (to absorb one must first detain valuable knowledge in the area) are the variables with the greatest impact on innovation performance. The work provides guidance on which areas should be prioritized in the development of policies and strategies to accelerate innovation in countries. The study is limited by the time frame and reveals, by comparison with pre-pandemic studies, that the determinants of innovation can be dynamic, varying according to the countries and, consequently, the global context of the analysis.

Custom injury prevention priority scoring: Local ranking procedures to assess unique community needs: Local Pediatric Injury Prevention Priority Scoring

BackgroundTrauma is the leading cause of morbidity and mortality in children. Many traumatic injuries are preventable and trauma centers play a major role in directing population-level injury prevention strategies. Given the constraint of finite resources, calculating priorities for injury prevention at an institutional level is essential. The Injury Prevention and Priority Score (IPPS) is a widely applicable tool that is more robust than simple prevalence rankings and considers injury severity – an important factor when developing prevention strategies. We developed an adapted-IPPS methodology to define our local injury prevention priorities using our institution's patient population. MethodsThe institution-specific trauma registry was used, which includes patients presenting to a level 1 pediatric trauma center July 2018 - June 2022. Causes of injury were categorized into injury mechanisms based on external cause codes. Mechanisms of injury were ranked by frequency and severity (based on mean Injury Severity Score, ISS). An IPPS was calculated for each of the injury mechanisms, which were then ranked from highest to lowest priority injury mechanism. ResultsIn ranking injury mechanisms by IPPS, “falls” remain the top priority mechanism despite their relatively low severity, given their overwhelming frequency (n = 1993, mean ISS = 5.9). The injury mechanisms “motor vehicle” (n = 434, mean ISS = 10.9) and “pedestrian” (n = 13, mean ISS = 15), become higher priority given their injury severity, despite lower frequency. “Pedestrian” includes non-traffic incidents such as patients run over by cars in driveways or rural settings. ConclusionsComputing the IPPS for each injury mechanism, using data collected routinely for trauma registries, enables trauma centers to use local data to inform injury prevention efforts in their communities. Calculating rankings based on an injury mechanism's relative frequency and severity allows a more robust understanding of their impact. Level of EvidenceIV

ON RANK NOT ONLY IN NSOP THEORIES

Abstract We introduce a family of local ranks $D_Q$ depending on a finite set Q of pairs of the form $(\varphi (x,y),q(y)),$ where $\varphi (x,y)$ is a formula and $q(y)$ is a global type. We prove that in any NSOP $_1$ theory these ranks satisfy some desirable properties; in particular, $D_Q(x=x)&lt;\omega $ for any finite tuple of variables x and any Q, if $q\supseteq p$ is a Kim-forking extension of types, then $D_Q(q)&lt;D_Q(p)$ for some Q, and if $q\supseteq p$ is a Kim-non-forking extension, then $D_Q(q)=D_Q(p)$ for every Q that involves only invariant types whose Morley powers are -stationary. We give natural examples of families of invariant types satisfying this property in some NSOP $_1$ theories. We also answer a question of Granger about equivalence of dividing and dividing finitely in the theory $T_\infty $ of vector spaces with a generic bilinear form. We conclude that forking equals dividing in $T_\infty $ , strengthening an earlier observation that $T_\infty $ satisfies the existence axiom for forking independence. Finally, we slightly modify our definitions and go beyond NSOP $_1$ to find out that our local ranks are bounded by the well-known ranks: the inp-rank (burden), and hence, in particular, by the dp-rank. Therefore, our local ranks are finite provided that the dp-rank is finite, for example, if T is dp-minimal. Hence, our notion of rank identifies a non-trivial class of theories containing all NSOP $_1$ and NTP $_2$ theories.

Accessibility and Visibility Analysis for Academic Portals of the Universities of Cartagena

Introduction: With the growing demand for applications in the market, companies have increasingly focused on meeting the technological needs of the average user, often overlooking those with functional diversity. Consequently, accessibility has emerged as a critical challenge across various contexts, particularly within the educational sphere, where the diverse range of individuals accessing web content is particularly pronounced. Objective: This paper presents a study centered on the accessibility inspection of six university websites located in the city of Cartagena. The primary aim is to ascertain the relationship between the integration of accessibility guidelines and web positioning factors as determined by Webometrics. Methodology: The methodology comprises five distinct phases: website selection, tool selection for inspection, execution of accessibility inspection, analysis of obtained results, and formulation of conclusions and recommendations. Results: The study revealed a correlation exceeding 0.8 between the local ranking of universities according to Webometrics and the ranking of accessibility issues identified through automated inspection tools. Conclusions: It is recommended that educational institutions adopt automatic web evaluation tools to enhance the accessibility of their institutional websites. This regular review and rectification of issues represent best practices for improving both local and international visibility and usability.

Limited Access to Aortic Valve Procedures in Socioeconomically Disadvantaged Areas.

To explore how differences in local socioeconomic deprivation impact access to aortic valve procedures and the treatment of aortic valve disease, in comparison to other open and minimally invasive surgical procedures. Procedure volume data were obtained from the Healthcare Cost and Utilization Project from 18 states from 2016 to 2019 and merged with area deprivation index data, an index of zip code-level socioeconomic distress. We estimate the relationship between local deprivation ranking and differences in volumes of aortic valve replacement, which include transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR), versus coronary artery bypass graft surgery and laparoscopic colectomy (LC). All regressions control for state and year fixed effects and an array of zip code-level characteristics. TAVR procedures have increased over time across all zip codes. The rate of increase is negatively correlated with deprivation ranking, regardless of the higher share of hospitalizations per population in high deprivation areas. Distributional analysis further supports these findings, showing that lower area deprivation index areas account for a disproportionately large share of SAVR, TAVR, and LC procedures in our sample relative to their share of all hospitalizations in our sample. By comparison, the cumulative distribution of coronary artery bypass graft procedures was nearly identical to that of total hospitalizations, suggesting that this procedure is equitably distributed. Regressions show high area deprivation index areas have lower prevalence of SAVR (β=-15.1%, [95% CI, -26.8 to -3.5]), TAVR (β=-9.1%, [95% CI, -18.0 to -0.2]), and LC (β=-19.9%, [95% CI, -35.4 to -4.4]), with no statistical difference in the prevalence of coronary artery bypass graft (β=-2.5%, [95% CI, -12.7 to 7.6]), a widespread and commonly performed procedure. In the population aged ≥80 years, results show high area deprivation index areas have a lower prevalence of TAVR (β=-11.9%, [95% CI, -18.7 to -5.2]) but not SAVR (β=-0.8%, [95% CI, 8.1 to 6.3]), LC (β=-3.5%, [95% CI, -13.4 to -6.4]), or coronary artery bypass graft (β=5.2%, [95% CI, -1.1 to 1.1]). People living in high deprivation areas have less access to life-saving technologies, such as SAVR, and even moreso to device-intensive minimally invasive procedures such as TAVR and LC.

Pure tone audiometry is a new method for evaluating congenital malformation of the middle and outer ear (CMMOE)

Background: The preoperative evaluation of Congenital Malformation of the Middle and Outer Ear (CMMOE) is very important. Jahrsdoerfer score commonly used at present, based on CT scanning images of the temporal bone, is often unable to accurately evaluate deformity and hearing level. Aims/Objectives: To investigate and promote a straightforward and easily accessible assessment method, pure tone audiometry, for the evaluation of CMMOE. Material and Methods: A total of 223 cases (244 ears) CMMOE with hearing data were retrospectively analyzed. Among them, 180 cases (197 ears) underwent exploratory tympanoplasty with clear conditions: ossicle numbers in 136 cases (147 ears) and morphology in 128 cases (138 ears) and vestibular window development in 137 cases (146 ears), and CT scans of temporal bone in 113 cases (120 ears). 1). The correlation was analyzed between ossicle numbers, ossicle morphology, Jahrsdoerfer score groups and their corresponding Average Air-Conduction Threshold of pure tone (AACT) at 0.5–4 KHz. 2) The AACT difference is compared among the above groups respectively and between the developed and undeveloped groups of vestibular window at 0.5–4 KHz and each frequency of 0.125–8 KHz. Spearman method was used for correlation analysis (calculating coefficient r and p values). For the data followed a normal distribution, a one-way analysis of variance (ANOVA) and t-test were employed, otherwise, Kruskal Wallis multiple local rank coincidence test and Wilcoxon rank sum test were used. p <0 .05 was considered statistically significant. Results: 1) The correlation coefficients between the groups of ossicle number scores, ossicle morphology scores, Jahrsdoerfer scores and their corresponding AACT are r = −0.187 (p <0 .05), r = −0.073 (p >0 .05) and r = −0.079 (p > 0.05), respectively. 2) Comparison of AACT difference based on ossicle number or morphological scores and Jahrsdoerfer scores with p > 0.05 among all groups, respectively. The AACT difference between the developed and undeveloped vestibular window groups is 5.5 (63.5/69.0) dB HL(p < .05) at 0.5–4KHz, out of 0.125–8 KHz frequency 1, 2, 4 KHz were 5.7 (65.0/70.7) dB HL, 8.4 (60.7/69.1) dB HL and 2 (61.5/63.5) dB HL, respectively, all p < 0.05, the other frequencies with all p > 0.05. Conclusions and Significance: 1) Ossicle number was correlated with AACT, but not for ossicle morphology and Jahrsdoerfer scores. 2) There was no significant difference in AACT corresponding to ossicle number or morphology scores and Jahrsdoerfer scores groups, but the patients with undeveloped vestibular window had poorer hearing than those with developed ones. Therefore, the AACT can evaluate the development of ossicle and vestibular window, and more directly reflect the hearing level than Jahrsdoerfer score. Pure tone audiometry is simple, widely used, and easily accessible, which making it a new assessment method of CMMOE.

Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation.

Matrix low rank approximation is an effective method to reduce or eliminate the statistical redundancy of its components. Compared with the traditional global low rank methods such as singular value decomposition (SVD), local low rank approximation methods are more advantageous to uncover interpretable data structures when clear duality exists between the rows and columns of the matrix. Local low rank approximation is equivalent to low rank submatrix detection. Unfortunately, existing local low rank approximation methods can detect only submatrices of specific mean structure, which may miss a substantial amount of true and interesting patterns. In this work, we develop a novel matrix computational framework called RPSP (Random Probing based submatrix Propagation) that provides an effective solution for the general matrix local low rank representation problem. RPSP detects local low rank patterns that grow from small submatrices of low rank property, which are determined by a random projection approach. RPSP is supported by theories of random projection. Experiments on synthetic data demonstrate that RPSP outperforms all state-of-the-art methods, with the capacity to robustly and correctly identify the low rank matrices when the pattern has a similar mean as the background, background noise is heteroscedastic and multiple patterns present in the data. On real-world datasets, RPSP also demonstrates its effectiveness in identifying interpretable local low rank matrices.

IDENTIFICATION AND INFERENCE IN A QUANTILE REGRESSION DISCONTINUITY DESIGN UNDER RANK SIMILARITY WITH COVARIATES

This study investigates the identification and inference of quantile treatment effects (QTEs) in a fuzzy regression discontinuity (RD) design under rank similarity. Unlike Frandsen et al. (2012, Journal of Econometrics 168, 382–395), who focus on QTEs only for the compliant subpopulation, our approach can identify QTEs and average treatment effect for the whole population at the threshold. We derived a new set of moment restrictions for the RD model by imposing a local rank similarity condition, which restricts the evolution of individual ranks across treatment status in a neighborhood around the threshold. Based on the moment restrictions, we derive closed-form solutions for the estimands of the potential outcome cumulative distribution functions for the whole population. We demonstrate the functional central limit theorems and bootstrap validity results for the QTE estimators by explicitly accounting for observed covariates. In particular, we develop a multiplier bootstrap-based inference method with robustness against large bandwidths that applies to uniform inference by extending the recent work of Chiang et al. (2019, Journal of Econometrics 211, 589–618). We also propose a test for the local rank similarity assumption. To illustrate the estimation approach and its properties, we provide a simulation study and estimate the impacts of India’s 40-billion-dollar national rural road construction program on the reallocation of labor out of agriculture.

PROSPECTIVE MODELS OF THE CONSERVATION AND ECOLOGICAL NETWORK OF TERRITORIAL COMMUNITIES OF CHORTKIV DISTRICT

In the publication, the main attention is drawn to the improvement of the functional and spatial structure of the protected and ecological networks of the administrative district (AR). The problem of the degree of conservation of territories became especially relevant after the implementation of the decentralization reform, because in some administrative districts and territorial communities the level of conservation is 0.5-5%, while the average district indicator is 13.98%. It was established that protected areas in the Chortkiv administrative district are represented by 10 of the 11 protected categories available in Ukraine. The situation with local fragments of eco-networks and basic protected objects is the most problematic. The degree of protection at the level of territorial communities in 72.7% does not meet the established nature protection norms (more than 10%).&#x0D; The eco-network concept was implemented in Ukraine at the national and regional levels in the period from 2000 to 2015. Despite the expiration of the Law of Ukraine "On the Statewide Program for the Formation and Development of the National Ecological Network for the Period 2000-2015", a number of tasks at the level of new administrative districts and territorial communities remained unresolved within the framework of the program. Precisely those levels at which the basic elements of eco-networks receive their metric reflection and the eco-network system is filled with concrete content. With these elements, it is possible to carry out renaturalization measures, set aside the width of nature protection zones within river Eco corridors, restore the connection between the constituent parts of key territories, establish configurations and fix the boundaries of protective territories on the terrain, etc. Therefore, it can be assumed that instead of office modeling of national and regional eco-network schemes, the stage of substantiation and selection on the ground (visual modeling) begins. At the same time, it is necessary to include not only areas of natural vegetation in the composition of elements of eco-network models, but also the configuration of numerous promising territories and objects proposed for creation by local specialists in nature protection, environmental activists of territorial communities.&#x0D; The proposed small-scale promising nature reserves and natural monuments (98 positions) will allow to increase the protection of territorial communities, and from the positions of their role in the eco-network of AR will form a new configuration of connecting and protective territories (submeridional direction) such as: Zolotolipsk regional, Baryeka local, Koropetsk local, Strip regional, Dzhuryn local, Seret regional, Nichlav local, Zbrut regional, Dniester national sub-latitudinal connecting territory, Tovtrova regional (sub-latitudinal), New key and connecting territories within landscape areas have been identified, promising protected objects, elements of eco-networks of local importance have been identified. At the same time, the prospect of creating protected areas with an area of more than 100 hectares (Table 2) within six territorial communities will provide an opportunity to design key territories at the regional and local levels. The indicators of existing and prospective protected areas of territorial communities, administrative districts were calculated, taking into account the creation of prospective protected areas and objects (98 units). The most significant changes in the basic elements of regional networks will take place within the connecting territories of the regional and local levels, territorial communities. An integrated map scheme-model of protected and ecological networks with promising protected objects, new local key and connecting territories has been created, which will contribute to the introduction of a territorially differentiated approach to the optimal landscape and ecological organization of the territory.&#x0D; The eco-network of the Chortkiv administrative district represents the rank of a subsystem of the regional eco-network of the Ternopil region. Its basic structural elements are: 2 key territories of national rank (Medoborska and Zalishchytska), 5 key territories of regional rank (Yablunivska, "Dacha Galileya", Shuparska, promising Baryska, Skala-Podilska, Borschivska, Koropetska, Serednyoseretska) and local rank (Nad Dzhurynom, Chahor, Moklekiv, "Forest Mordova").&#x0D; The connecting national territory is Dnistrovsk, regional ones (Tovtrova, Zbrutska, Seretska, Stripska, Zolotolypska). Local connecting territories will be (Bpriska, Dzhurynska, Nichlavska, Seretsko-Zbruska). In connection with the creation and prospect of creation of new protected territories and objects, there will be a change in the configuration of mainly capital and protective territories, as well as the filling of protected objects in territorial communities (Koropetska, Zolotopoticska, Zalishchytska, Chortkivska, Husyatynska). The formation of updated models of protected and ecological networks of the administrative district will contribute to the optimization of the landscape and ecological organization of the territory.&#x0D; Key words: protected network, econetwork, administrative district, territorial community.

Funkcjonalno-przestrzenna optymalizacja sieci stref chronionych i regionów ekologicznych Tarnopola na Ukrainie

The article examines the essence of the European Strategy for the Conservation of Landscape and Biotic Diversity, the principles of formation, conservation and use of eco-networks in Ukraine, the existing problems of national and regional networks, taking into account the new administrative territorial structure at the administrative-district level and the level of territorial communities. The purpose of the article is to assess the functional and territorial structure of the protected and ecological networks of Ternopil region and to substantiate the ways of their optimization in modern conditions. The paper is based on the information obtained in the course of field expeditionary research in 2019–2022, as well as on statistical data, cartographic materials, and materials from the open network of aerospace satellite images Google Earth. The collected materials were processed using a system of methods (analysis, synthesis, comparison, decoding, cartographic, computer modeling, etc.). The data obtained showed that in 36.5% of the territorial communities, protected areas cover less than 1%. In order to improve the situation, the authors propose the creation of 53 new protected areas in 25 communities of Ternopil region with a total area of 39,358 hectares and substantiate the new core and connecting territories of the local rank of the regional eco-network.

Pricing policies for international airports: Per-flight versus per-passenger charges

This study investigates the pricing regime choices between per-flight and/or per-passenger charges for international airports. Each country may choose (i) mix charges for per-flight and per-passenger charges, (ii) per-flight charges only, (iii) per-passenger charges only, and (iv) marginal-operating-cost pricing for each type of charge (Duo-MOC pricing). Each country’s airline competes on flight frequency and passenger volume in the next stage. The global welfare maximization shows that the global welfare levels rank as follows: mix charges (which leads to the first-best outcome), per-passenger charges only, and per-flight charges only (equivalent to Duo-MOC pricing). Regarding local welfare maximization, if both countries choose the same pricing regime in the first stage, then each country’s maximum local welfare achieved in the second airport stage is ranked as follows: Duo-MOC pricing, per-flight charges only, mix charges, and per-passenger charges only. If each country is allowed to choose different regimes, each chooses mix charges to achieve a unique equilibrium. A typical prisoner’s dilemma occurs. The local (and global) welfare rankings under local welfare maximization, combined with the unique equilibrium in the pricing regime choice game, provides clear and sharp policy implications for international airports.

A Comparative Study of Criteria and Indicators of Local, Regional, and National University Ranking Systems

A Comparative Study of Criteria and Indicators of Local, Regional, and National University Ranking Systems