Ranking Index Research Articles

Addressing the Global Logistics Performance Index Rankings with Methodological Insights and an Innovative Decision Support Framework

This study examines the Logistics Performance Index (LPI) rankings developed by the World Bank from a methodological perspective and proposes an alternative decision support framework. LPI serves as an interactive tool that helps countries identify challenges, innovative solutions, and opportunities in their trade and logistics sectors. In this study, the efficiency of logistics operations in 118 countries was evaluated using an integrated multi-criteria decision-making (MCDM) model objectively weighted by the Entropy method. Countries were ranked using the MCRAT, SAW, TOPSIS, and FUCA methods. According to the findings, large datasets provide more robust insights for sensitivity analyses, and wider weighting coefficient combinations make the data more meaningful. In addition, it is suggested to use low-compensation methods instead of classical additive methods for LPI. Unlike other studies in literature, this research applied an innovative sensitivity analysis to test the robustness of the model and comprehensively examined the effects of weighting techniques based on over 2500 different MCDM results. The findings suggest that the FUCA method should be recommended to decision-makers for calculating LPI rankings due to its simplicity, practicality, low compensatory power, and low sensitivity. This study offers methodological improvements when evaluating logistics performance and provides significant contributions to decision-making processes. The findings are expected to provide a valuable resource for policymakers and businesses in understanding a country’s position in global competition, as well as serving as a reference for researchers evaluating the logistics performance of countries.

Parametrized fragility, failure analysis and cost-effectively strengthening of electrical power distribution system under ice and concurrent wind hazards

In the past decades, the increasing frequency and severity of winter storms due to climate change have revealed the vulnerability of power systems against such events. This study aims to investigate the impact of ice and concurrent wind hazards on power systems by proposing a set of parametrized fragility functions for utility poles and conductors, and then applying them to system failure analysis and cost-effectively strengthening. The fragility model is generated by logistic regression to estimate the failure probability of poles and conductors as a function of hazard and structural characteristics. Applying proposed functions, system failure analysis is performed using IEEE123 testbed in four cities with various hazard characteristics. The results show that wind speed significantly affects pole rupture, while extreme ice and wind combination influences conductor breakage. Meanwhile, even minor structural failure leads to severe outages. Moreover, the risk-based Expected Outage Reduction (EOR) is calculated with developed fragility models as pole replacement ranking index. By comparing different replacement strategies, the 70-year system performance can be cost-effectively optimized by risk-based pole ranking and replacement pace and timing. Overall, the models and applications presented in this paper serve as a critical part of power system resilience analysis against winter-related hazards.

Web-Based Expert System Chatbot Determines The Best Cheap Camera For New Users Using The Vikor Method

In this technological era, a variety of new products have emerged, including in transportation, industry, health, entertainment and business. Cameras are an example of an increasingly diverse range of products, especially in mobile devices. However, the wide variety of cameras can be confusing. The VIKOR method is an approach to ranking the closest solution to the ideal solution in ranking. This is useful in situations where criteria conflict with each other, helping to find the optimal solution through a multicriteria ranking index. Especially in discrete decision making, VIKOR helps determine the ideal solution from conflicting alternatives. Testing this method is used in assessing cameras to help beginners choose the best type of camera based on user answers. By processing camera data through the VIKOR method and filter questions,

Assessment on major browse feed resources and determine their chemical composition in Korhaye zone, Somali Region, Ethiopia

Assessment of major browse feed resources and determine the chemical composition of selected browse feed resource in Korahay Zone, Somali Regional State, was the aim of this study. Kebeles and the household heads were selected purposively in study area. The samples of fresh leaves (800 g) of selected browse species were collected to determine chemical compositions. SPSS version 20 was used for data analysis. The feed related constraints were ranked and analyzed by the ranking index. The current result indicated that, total of 22 trees, 6 shrub, 4 bush and 6 herbaceous species used as feed for livestock in dry and/or wet season were identified in the study area. DM, OM, CP, NDF, ADF, ADL and Ash of Dobera glabra, Grewia bicolor, Boscia minimfolia, Prosopis juliflora, Acacia Senegal, Unidentified (Alankhayir), Unidentified (Geed chic) were determined in current laboratory analysis. DM, OM, CP, NDF, ADF, ADL and Ash of Dobera glabra was 92.8 %, 94.28 %, 14.4 %, 42.5 %, 26.9 %, 5.22 % and 5.73 % respectively. Finally, feed quality and quantity, drought, invasive species and ecological deterioration were identified as major constraints of feed resources in study area. Due to this, intervention and further study should be conducted to tackle existing feed and feed related issues.

Evaluation of OECD Countries in Terms of Better Life Index According to Bulut Index

Background: The "Better Life Index", first developed by the Organization for Economic Co-operation and Development (OECD) in 2011, includes many criteria from the functioning of public services to environmental wealth, from security services to individual and social well-being. Method: The performances of OECD countries according to the decision criteria that constitute the Better Life Index has been evaluated with Bulut Index (BI) method, which is a multi-criteria decision-making method. Normalized Maximum Values (NMV) method, one of the objective weighting methods, was used to determine weights of decision criteria. Findings: Among the indicators of the Better Life Index, the murder rate per 100 thousand population ranks first in terms of criterion weight. In the study, due to the analysis and evaluation made with Bulut Index, Switzerland ranked first among OECD countries with 82.28 points in the welfare and well-being index ranking. On the other hand, Türkiye ranked fourth from the bottom among OECD countries. Conclusion: Based on the findings of the study, it is recommended that urgent and necessary measures be taken on homicide rates, long-term unemployment rates and air pollution criteria. The lack of criteria regarding civic participation, work-life balance and income status constitute limitations of the study. In future studies, it is especially recommended that other researchers include these variables.

How do palliative care clinicians use their emotions during end-of-life encounters?

Abstract Background Palliative care clinicians are regularly exposed to emotionally laden end-of-life care situations. Until now, the use of their emotions during palliative care consultations has remained understudied. We aimed to develop a theory to understand how palliative care clinicians use their emotions. Methods Qualitative data were collected via individual interviews held with different types of palliative care clinicians across the world (countries were selected based on their Quality of Death Index ranking). We used a social constructivist grounded theory approach to analyze the data using a constant comparative method. Results We held interviews with 21 palliative care clinicians (5 nurses, 11 physicians, 2 psychologists, and 3 social workers) from 10 different countries. Fourteen were female. Participants’ average age was 46 and they had 14 or more years of palliative care experience. The mean length of the interviews was 52 minutes. The process of using emotions could be characterized as follows: first, a difficult end-of-life encounter (e.g. ethical dilemmas or conflicts) would trigger a strong emotion in clinicians. Second, clinicians become aware of the specific emotion via its physical or psychological cues. Third, an assessment of the appropriateness of the use of the emotion follows, in which facilitators and barriers (e.g. the level of emotion skills, the view on emotions, or the feeling of safety in the team) interplay, influencing the clinician to act upon a specific emotion or not. Finally, with a specific intent (e.g. to build connection, stimulate patients and relatives to express their feelings, or clarify a point of view) the clinician shares, shows, or expresses the emotion. Conclusions We found that the strong emotions clinicians experience can be used as a valuable resource to provide palliative care. We also identified key steps to aid clinicians reflect on the appropriateness of using certain emotions in patient care. Key messages • Palliative care clinicians’ emotions can be considered as tools to support palliative care provision. • The developed theory shows potential to explore its applicability in other professions that are also regularly confronted with emotionally charged situations.

E-Government Progress in Emerging Nations Insights from Developing Countries

E-government, which stands to benefit from ICT, offers the chance to improve public services. ICT has been successfully incorporated into several nations' governing structures, like China, South Korea. Many other nations, particularly those in the developing world, are still struggling to create stronger governance systems because they have not yet successfully incorporated ICT into their governance frameworks. This study contributes by conducting a comparative study on the Bangladesh-Indonesia’s current e-government progress. Both countries transferring to digital systems and attempting to establish an electronic government. The E-Government Development Index (EGDI) reports and rankings from the United Nations are the focus of this research. Our study's results demonstrate that, Bangladesh and Indonesia have significantly improved its ranking from 2008 to 2022. In order to facilitate e-governance and support improved online services, progress in human development, and telecommunication infrastructure, Bangladesh and Indonesia require an improve and more advance e-government model in terms of administration, facilitation, and participation.

Exploring changes in epibenthic food web structure after implementation of a water-sediment regulation scheme

The water-sediment regulation scheme (WSRS) in the Yellow River is a large-scale initiative to artificially regulate the flow of sediment to the sea, thereby increasing the flood-carrying capacity of the riverbed and reservoirs. Currently, systematic studies on ecological impacts of WSRS at ecosystem-level are still insufficient. This limitation hampers the pursuit of a ‘green’, healthy, ecosystem and sustainable fisheries. This study constructed the topological structure of food webs in the Yellow River Estuary (YRE) before, during, and after implementation of the WSRS, analyzing changes in food web complexity and key species based on fishery independent data collected in June, July, and August 2023. The results showed decreases from 59 to 52 in the number of trophic species, and from 539 to 395 in the number of feeding relationships after WSRS implementation. Increased node density, decreased link density, and decreased structural complexity index also indicated a simplification of the YRE food web structure after WSRS implementation. The relatively low value of the characteristic path length indicated that the YRE food web has high connectivity with short path lengths of trophic interaction. Based on the ranking of various topological indices, Japanese seabass (Lateolabrax japonicas) and mantis shrimp (Oratosquilla oratoria) persisted as the key species. Our research revealed limited potential ecological effects that WSRS may have on the YRE food web over a short period. The effects did not persist, and omnivorous key species were identified as being critical in contributing to overall system resilience. These omnivores with high complexity, connectivity and low path lengths allowed the food web to quickly dissipate the exogenous disruption from the WSRS. This provides a theoretical basis for assessing the future ecological health and scientific management of YRE fisheries and similar large estuaries for which sediment transport mitigation is under consideration.

Scientometric vector of development

Bibliometric methods of evaluating the effectiveness of scientific activity are quite widespread in the world. When used correctly, these methods can reflect objective trends in the development of domestic and world science. To clarify the vector of editorial policy for the purpose of sustainable development of the journal among the periodicals of the Higher Attestation Commission of the Russian Federation (subject “Agriculture and Forestry”), an analysis of the publication activity of the journal “Agrarian Science” for a five-year period (2019–2023) was performed.The material for the study was statistical data obtained after collecting the necessary information on the RSCI website. The data obtained were analyzed using problem-thematic and system analysis.The scientometric indicators of the journal “Agrarian Science” for the analyzed period (from 2019 to 2023) showed an overall positive trend.In September 2024, the RSCI published magazine ratings for 2023, the scientific-theoretical and industrial journal “Agrarian Science” has the following indicators: place in the overall SCIENCE INDEX ranking — 830th (among 3970 journals), percentile in the SCIENCE INDEX ranking — 21, place in the SCIENCE INDEX ranking on the topic “Agriculture and forestry” — 58th (among 220 magazines).

Media politics in Japan: News journalism between interdependence, integrity, and influence

AbstractAlthough Japan is generally considered a liberal democracy with a free press, concerns about media independence have repeatedly been raised. The World Press Freedom Index ranks Japan last among G7 nations. One of the major reasons for its performance lies in a deep-rooted entanglement of the mainstream media with the political establishment, which is said to promote a climate of self-censorship and impede courageous, critical journalism. While the government-approved reporters’ clubs (“kisha clubs”) are often cited as lying at the heart of the problem, there are other relevant structural and historically grown factors hindering the improvement of press freedom: Despite theoretical constitutional protection, media governance in Japan does not provide an adequate framework for journalistic independence; furthermore, revolving door politics, editorial interventions and informal arrangements are well-established practices inside the sphere of media and politics. Nevertheless, there have been those critical moments when the mainstream media, in fact, influenced the course of politics. Setting out from the present condition of media democracy in Japan, this article traces back the historical roots of the seemingly firmly ingrained relationship between journalism and the state. Thereby, it portrays the ambivalent interdependence between the media and politics, and the dilemmatic tension between journalistic integrity, economic interests, and political influence. Finally, it explains why the current hegemony of the legacy media in the public sphere may eventually face a silent, but profound transformation in light of digitization and advancements in artificial intelligence.

COVID-19 Deaths and Minority Health Social Vulnerability, in the U.S., January 1, 2020 through June 24, 2023.

Health disparities, leading to worse health outcomes such as elevated COVID-19 mortality rates, are rooted in social and structural factors. These disparities notably impact individuals from lower socioeconomic backgrounds and more socially vulnerable areas. We analyzed the relationship between COVID-19 deaths and social vulnerability using the Minority Health Social Vulnerability Index (MHSVI). COVID-19 death data in the U.S. was obtained from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics, where COVID-19 deaths were defined using the ICD-10 code U07.1. MHSVI composite scores were calculated for 3089 U.S. counties and categorized into social vulnerability quartiles, where values ranged from 0 (lowest vulnerability) to 1 (highest vulnerability). Negative binomial regression was employed to determine death rate ratios for each quartile within each theme. Finally, a multivariate negative binomial regression including all MHSVI sub-themes, excluding the overall index ranking, was used to assess the association between each theme and COVID-19 death rates independently. There were 1,134,272 COVID-19 deaths from January 1, 2020 through June 24, 2023. Adjusted rate ratios for COVID-19 deaths in the overall index ranking were 1.06 (95% CI 0.99-1.13), 1.14 (95% CI 1.06-1.22), and 1.41 (95% CI 1.31-1.52) for the second, third and fourth quartiles, respectively. Sub-themes of socioeconomic status (SES), household characteristics (HC), racial and ethnic minority status (REMS), housing type and transportation (HTT), and medical vulnerability (MV) revealed increasing death rates in higher vulnerability quartiles. The healthcare infrastructure and access (HIA) theme had decreasing death rate ratios of 0.74 (95% CI 0.71-0.78), 0.59 (95% CI 0.56-0.62), and 0.42 (95% CI 0.39-0.44) for the second, third, and fourth quartiles, respectively. Finally, the multivariate analysis showed that the HC, HTT, HIA, and MV themes were associated with COVID-19 deaths (P < 0.05). Counties that were identified as more socially vulnerable experienced higher death rates from COVID-19. These areas may need additional public health and social support during future pandemics.

Research on the evaluation of the manual manipulation level of a student pilot in a typical scene

The traditional evaluation method of student pilots ' manual manipulation level relies too much on teachers' subjective judgment. A quantitative evaluation method based on flight data is proposed to compensate for the shortcoming of the traditional method. According to the theory of the core competence of a pilot, the evaluation index system of manual manipulation level of student pilots in a typical scene is constructed. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) categorizes pilot manipulation levels into four grades. The improved support vector machine (SVM) model with particle swarm optimization (PSO) is trained using index data and rank labels as inputs. The data is split into training and verification sets with the cross-validation method. The training data for Guanghan Airport are taken as an example to verify the model's reliability. The model's prediction accuracy is compared with that of K-nearest neighbor and random forest models. The results show that the PSO-SVM model has higher prediction accuracy. The research can provide a theoretical reference for quantitatively evaluating manual manipulation levels and improving flight training quality.

The relationship between radiation oncology department NIH funding and institutional community inclusion/investment.

153 Background: Disparities in healthcare access and funding allocation persist among racial minorities and low-income populations. Radiation Oncology departments play a crucial role in cancer treatment, yet the extent to which these departments serve historically underrepresented communities following receipt of National Institutes of Health (NIH) funding remains unclear. This study accessed the relationship between radiation oncology departments that are awarded National Institute of Health (NIH) funding and Lown Institute Hospitals Index rankings for community benefit and inclusivity. Methods: Radiation oncology departments awarded funding from the NIH from 2019-2021 were retrospectively studied. The 2023 Lown Institute Hospital Index rankings for community benefit and inclusivity were examined. The community benefit metric measures financial assistance spending, community investment spending, and Medicaid as a portion of patient revenue. The inclusivity metric measures the similarities of income, race, and education level between the hospital patient population and the surrounding community. Kendall’s correlation coefficient (tau value) and linear regression were used to evaluate the relationship between measures of community benefit and inclusivity and NIH radiation oncology department research funding. Results: Twenty-two radiation oncology departments that received NIH funding (median = $ 419,555.00) were included. A statistically significant positive correlation was observed between the amount of radiation oncology NIH research funding received and institutional rankings for overall community benefit (tau = 0.378; P &lt; 0.034), with a trend towards significance for institutional rankings for community investment spending (tau = 0.497; P &lt; 0.053). No significant correlation was observed between the amount of radiation oncology department funding and institutional rankings for charity care spending (P = 0.430), Medicaid as a portion of patient revenue (P = 0.837), and service of patients from racial and or ethnic minorities (P = 0.505), with low income (P = 0.612), or with lower levels of education (P = 0.700). Conclusions: Our study highlights the relationship between recent NIH funding received by Radiation Oncology departments and their commitment to community health and inclusivity. Our findings indicate a significantly positive correlation between NIH funding received by radiation oncology departments and overall community benefit. This suggests that departments receiving NIH funding may be incentivized to allocate resources towards initiatives to improve community health outcomes beyond direct patient care. This study prompts further exploration into the mechanisms through which NIH-funded radiation oncology departments allocate resources and engage with their surrounding communities.

What drives the development of digital rural life in China?

Background and objectiveEmpowering rural life through digital technology reflects the collective aspirations of millions of farmers striving for a better quality of life. Ensuring that the benefits of digital advancements reach every corner of the population is a crucial and inevitable choice. To expedite the establishment of an inclusive digital life for all citizens, the Chinese government has exerted substantial efforts by positioning the development of digital villages as a national strategy. Through comprehensive initiatives in digital village construction, facilitating the extension of "Internet+" services such as education, healthcare, transportation, and entertainment to rural areas. 24-hour digital village libraries, smart health stations, intelligent homes, facial recognition payments, unmanned supermarkets, and a variety of digitized, networked, and intelligent lifestyle applications are increasingly prevalent in Chinese rural regions. The digital gap between urban and rural areas in China is gradually diminishing, and the ongoing evolution of rural digital lifestyles paints a picturesque picture of an enhanced rural life. This study endeavors to provide a meticulous analysis of the digital landscape in Chinese villages, seeking to unravel the intricacies behind the swift development of rural digital life. MethodsUsing the top 100 counties in China's 2020 Rural Life Digitization Index ranking as case studies, this research collected the necessary data through industry research reports and official statistical sources. To begin with, based on the Technology-Organization-Environment (TOE) analysis framework, variables such as digital infrastructure, government policy support, funds are put into utilization, digital economy level, and farmer digital literacy were identified. The fuzzy set qualitative comparative analysis (fsQCA) method was then employed to recognize the influencing factors of rural digital life and combinations of condition variables. Subsequently, utilizing the system dynamics methodology, the relationships between factors were analyzed, simulating changes in rural digital life development to gain a deeper understanding of the key elements affecting rural digital life. Sensitivity analysis was conducted to further reveal the extent of influence of these key elements on rural digital life. ResultsThe fuzzy set qualitative comparative analysis reveals that the evolution of rural digital life in China is a complex outcome influenced by the simultaneous interplay of multiple factors. It demonstrates a pattern of diverse combinations and parallel pathways encompassing various variables. Among these configurations, six paths stand out with the highest coverage. These six paths can be further classified into three modes of rural digital life development in China: environment-empowered type, organization-pushed type, and compound-driven type. Further dissection of causal combinations through a system dynamics model unveils that the progression of rural digital life is intricately linked to key factors such as information infrastructure, policy intensity, and digital learning and development. Over time, there is a discernible upward trajectory in the level of rural digital life, characterized by an accelerating pace of improvement. The influence of policy intensity on rural digital life surpasses that of information infrastructure and digital learning and development, indicating that policy intensity exerts the most significant impact overall. ConclusionThe evolution of rural digital life in China is a complex, long-term process propelled by a combination of multiple factors. China's experience demonstrates that achieving high-level development in rural digital life demands attention not only to the synergistic interplay of various factors but also a strategic focus on leveraging specific key elements. This entails skillfully integrating diverse factors and identifying pivotal areas to maximize the impact of relevant conditions to the greatest extent possible.

Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data.

Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients endured worse outcomes disproportionately compared with non-Hispanic White patients, but the epidemiological basis for these observations was complex and multifaceted. This study aimed to elucidate the potential reasons behind the worse outcomes of COVID-19 experienced by non-Hispanic Black patients compared with non-Hispanic White patients and how these variables interact using an explainable machine learning approach. In this retrospective cohort study, we examined 28,943 laboratory-confirmed COVID-19 cases from the OneFlorida Research Consortium's data trust of health care recipients in Florida through April 28, 2021. We assessed the prevalence of pre-existing comorbid conditions, geo-socioeconomic factors, and health outcomes in the structured electronic health records of COVID-19 cases. The primary outcome was a composite of hospitalization, intensive care unit admission, and mortality at index admission. We developed and validated a machine learning model using Extreme Gradient Boosting to evaluate predictors of worse outcomes of COVID-19 and rank them by importance. Compared to non-Hispanic White patients, non-Hispanic Blacks patients were younger, more likely to be uninsured, had a higher prevalence of emergency department and inpatient visits, and were in regions with higher area deprivation index rankings and pollutant concentrations. Non-Hispanic Black patients had the highest burden of comorbidities and rates of the primary outcome. Age was a key predictor in all models, ranking highest in non-Hispanic White patients. However, for non-Hispanic Black patients, congestive heart failure was a primary predictor. Other variables, such as food environment measures and air pollution indicators, also ranked high. By consolidating comorbidities into the Elixhauser Comorbidity Index, this became the top predictor, providing a comprehensive risk measure. The study reveals that individual and geo-socioeconomic factors significantly influence the outcomes of COVID-19. It also highlights varying risk profiles among different racial groups. While these findings suggest potential disparities, further causal inference and statistical testing are needed to fully substantiate these observations. Recognizing these relationships is vital for creating effective, tailored interventions that reduce disparities and enhance health outcomes across all racial and socioeconomic groups.

Prepackaged foods healthiness ranking index: developing front-of-pack labeling to facilitate the assessment and validation of healthiness rankings of prepackaged foods in China

BackgroundThe Medium and Long-Term Plan for the Prevention and Treatment of Chronic Diseases (2017–2025) in China has highlighted the importance of reducing fat, sodium, and sugar in foods. However, front-of-pack labeling, which enables consumers to assess the health levels of prepackaged foods, is lacking in China. In response to the Zhejiang Provincial Health Commission’s request, we sought to develop a method for efficiently evaluating the health level of prepackaged foods.MethodsThrough a comprehensive literature review, we established a systematic framework: the Prepackaged Foods Healthiness Ranking Index (PHRI). We determined specific threshold values and grading criteria and conducted two rounds of Delphi survey to refine the index. Using a measurement dataset, we aimed to determine the optimal limit values for assessing the health level of prepackaged foods in real-world settings.ResultsAfter two rounds of Delphi surveys, the PHRI underwent multiple revisions until consensus among experts was reached. The final decision regarding the upper limit values set 30% Nutrient Reference Values as the limit for solid foods and 15% Nutrient Reference Values for liquid foods. The calculation of PHRI values was successfully implemented with the dataset, in accord with current nutrition awareness and real-world conditions.ConclusionsThe PHRI provides a valuable tool for assessing the healthiness of prepackaged foods. This front-of-pack labeling system provides a convenient method for evaluating the nutritional quality of prepackaged foods. Ultimately, the PHRI has the potential to contribute to advancements in health policy, practice, and education in China.

Genotype x environment interaction and yield stability of soybean (Glycine max l.) genotypes in multi-environment trials (METs) in Nigeria

Genotype × environment interaction (GEI) poses a critical challenge to plant breeders by complicating the identification of stable variety (ies) for performance across diverse environments. GGE biplot and AMMI analyses have been identified as the most effective and appropriate statistical techniques for identifying stable and high-performing genotypes across diverse environments. The objective of this study was to identify widely adapted and high-yielding soybean genotypes from Multi-Locational Trials (MLTs) using GGE and AMMI biplot analyses. Fifteen IITA-bred elite soybean lines and three standard checks were evaluated for stability of performance in a 3 × 6 alpha lattice design with three replications across seven locations in Nigeria. Significant (p < 0.001) differences were detected among genotypes, environments, and GEI for grain yield, which ranged between 979.8 kg ha−1 and 3645 kg ha−1 with a mean of 2324 kg ha−1. To assess the stability of genotypes, analyses were conducted using the general linear method, GGE, and the Additive Main Effect and Multiplicative Interaction (AMMI) approach, as well as WAAS and ASV rank indices. In the GGE biplot model, the first two principal components accounted for 67.4 % of the total variation, while in the AMMI model, the first two Interaction Principal Component Axes (IPCA1 and IPCA2) explained 73.20 % and 11.40 % of the variation attributed to genotype by environment interaction, respectively. GGE biplot identified G10 and G16 as the most stable and productive genotypes, while WAASB index revealed G16, G10, G9, G4 and G2 as the most adaptive, stable and productive genotypes across locations, and ASV identified G9, G13, G4, G14 and G10 as the most stable and productive.Consequently, genotypes G2, G4, G9, G10 and G16 displayed outstanding and stable grain yield performance across the test locations and are, therefore, recommended for release as new soybean varieties suitable for cultivation in the respective mega environment where they performed best. More importantly, the two genotypes are recommended for recycling as sources of high-yield and yield stability genes, and as parental lines for high-yield and stable performance for future breeding and genomic selection.

Opportunities and Constraints of Promoting Coffee Plantation in Southern Tigray, Ethiopia

In Ethiopia, coffee is a significant crop, but in the Tigray region, particularly southern Tigray, it receives less emphasis despite its national importance. This study investigates the status of coffee production in southern Tigray, Ethiopia, using a multistage sampling technique to gather data from 113 respondents during 2015. The goal is to identify opportunities and constraints in coffee production in the region. Data were collected using individual interviews and Focus Group Discussions, and analyzed using SPSS software and a ranking index. The study found that favorable agro ecology, fertile soils, accessibility to water, and existence of tolerant coffee varieties are the opportunities in southern Tigray, Ethiopia. However, constraints include irrigation competition, lack of training, limited input use, and shifting to khat (Catha edulis) cultivation. Additionally, most farmers do not practice pruning and rejuvenation due to lack of technical knowledge. This result in the coffee plants stand; more erect, less branched and unmanageably tall which rendering difficult to harvest berries. Hence, the study suggested that an integrated coffee production intervention is important to boost coffee production and local policy instrument is prerequisite that restrict the shifting of coffee to khat production in the study districts.

Towards maximization of parameters identifiability: Development of the CalOpt tool and its application to the anaerobic digestion model

This work addresses the need for robust approaches to estimate kinetic parameters in continuous anaerobic co-digestion plants. Specifically, it outlines a procedure for including data from batch activity tests on digestate samples, in addition to the poorly informative dataset from conventional monitoring of biogas facilities. To profitably make use of activity tests, the estimation of the biomass composition in digestate samples is required to improve parameter identifiability. To this purpose, an open-source tool (CalOpt) was developed and tested on a pilot-scale co-digester, simultaneously using data from both conventional monitoring and lab-scale activity tests. Targeting the prediction of volatile fatty acids (VFAs) concentrations in the digestate of the continuous co-digester, the kinetic parameters of different microbial groups were selected for calibration based on parameters importance ranking and collinearity index. The results demonstrate that the CalOpt tool significantly improved the fitting of acetic, propionic, and butyric acid concentrations in digestate as well as the methane flowrate from the digester. Furthermore, the study assessed the necessity of modifying the Monod kinetics to account for substrate inhibition by incorporating the Haldane term in the VFAs uptake kinetic model, which proved to be essential for better interpreting batch activity tests.

Relationship Between Radiation Oncology Department National Institutes of Health Funding and Institutional Community Inclusion/Investment

PURPOSE Disparities in health care access and funding allocation persist among racial minorities and low-income populations. Radiation oncology departments play a crucial role in cancer treatment, yet the extent to which these departments serve historically underrepresented communities following receipt of National Institutes of Health (NIH) funding remains unclear. METHODS Radiation oncology departments awarded NIH funding from 2019 to 2021 were studied using the 2023 Lown Institute Hospital Index rankings for community benefit and inclusivity to assess the relationship between measures of community benefit and inclusivity and NIH radiation oncology department research funding. RESULTS Twenty-two radiation oncology departments were analyzed in this study. A significant positive correlation was identified between the NIH research funding these departments received and their institutional rankings for overall community benefit (tau = 0.38; P &lt; .034). Additionally, there was a trend toward significance for the relationship between NIH funding and institutional rankings for community investment spending (tau = 0.497; P &lt; .053). No significant correlation was observed for other variables, including institutional rankings for charity care spending, Medicaid as a portion of patient revenue or services provided to patients from minoritized groups, low-income backgrounds, or those with lower levels of education. CONCLUSION Our findings indicate a significantly positive correlation between NIH funding received by radiation oncology departments and overall community benefit (measured by spending on financial assistance, community investment, and Medicaid). This suggests that departments receiving NIH funding may be incentivized to allocate resources toward initiatives aimed at improving community health outcomes extending beyond direct patient care.