Changes In Ranking Research Articles

A framework for estimating actual evapotranspiration at weather stations without flux observations by combining data from MODIS and flux towers through a machine learning approach

The scarcity of site-scale actual evapotranspiration (ET) measurements poses a challenge for modelling and verifying regional ET. Taking the grassland ecosystem in arid and semi-arid regions of Northern China (ASNC) as an example, we proposed a framework for estimating ET at weather stations without flux observations through a machine learning approach by combining data from MODIS and fifteen flux towers distributed in alpine grassland (AG) and temperate grassland (TG) across ASNC. First, we analyzed the temporal characteristics of grassland ET at site scale. Second, we applied the machine learning approach Random Forest (RF) to develop a robust model for simulating site-scale grassland ET, and used random and spatial cross-validations (CVs) and three metrics to evaluate the RF models performance. Two strategies (using pooled data from all flux towers for a general model, and dividing data by grassland type to develop models specific to AG and TG) and four temporal resolutions (daily, 8-day, monthly and seasonal) were used to develop the RF models. Third, we investigated how the importance of predictor variables for estimating grassland ET changed in different CVs, strategies and temporal resolutions. The ET of AG and TG showed similar dynamic patterns but differed in magnitude. The RF models showed good performance in both strategies and all four temporal resolutions (R2 > 0.64, MAE < 0.53 mm d−1, RMSE < 0.72 mm d−1). However, seasonal ET simulations performed better than that of daily, 8-day and monthly using pooled data from all flux towers, especially in spatial CV. Meteorological variables (temperature, precipitation and radiation), vegetation (NDVI, LAI and FPAR) and soil (soil water content and soil temperature) were strong predictors of variation in grassland ET. Changes in the importance ranking and value of predictor variables partly explained the variations of model performance. The robust model performance in spatial CV proved that the framework developed in this study was reliable when applied to weather stations without flux observations, thereby overcoming the scarcity of site-scale actual ET measurements.

Impact of artificial intelligence on US medical students' choice of radiology

PurposeInternational student surveys have shown significant anxiety about pursuing radiology as a career due to artificial intelligence (AI). For a counterpart study in the US, we examined the impact of AI on US medical students' choice of radiology as a career, and how such impact is influenced by students' opinions on and exposures to AI and radiology. MethodsStudents across 32 US medical schools participated in an anonymous online survey. The respondents' radiology ranking with and without AI were compared. Among those considering radiology within their top 3 choices, change in radiology ranking due to AI was statistically examined for association with baseline characteristics, subjective opinions, and prior exposures. ResultsAI significantly lowered students' preference for ranking radiology (P < .001). One-sixth of students who would have chosen radiology as the first choice did not do so because of AI, and approximately half of those considering radiology within their top 3 choices remained concerned about AI. Ranking radiology lower due to AI was associated with greater concerns about AI (P < .001), less perceived understanding of radiology (P = .02), predicting a decrease in job opportunities (P < .001), and exposure to AI through medical students/family (P = .03) as well as through radiology attendings and residents (P = .03). Education on AI during radiology rotations, followed by pre-clinical lectures, was the most preferred way to learn about AI. ConclusionAI has a significantly negative impact on US medical students' choice of radiology as a career, a phenomenon influenced by both individual concerns and exposure to AI from the medical community.

Influence of social determinants of health on oncology care quality rankings.

139 Background: Adjustment for social determinants of health (SDOH) when assessing provider care quality remains limited. The Oncology Care Model (OCM), for example, includes low-income status/dual eligibility (LIS/DE) as a part of the risk adjustment model for some quality measures, but does not account for any social risk variables in the hospice measure. No measures within the OCM account for additional social risk factors beyond LIS/DE such as patients’ race, rurality, and social deprivation. Additional SDOH adjustment could increase the accuracy of provider quality rankings and better align performance-based payments with true provider quality. Methods: North Carolina Medicare claims from 2015-2017 comprised the data for this study. The year 2015 was used to establish baseline covariates. Episodes were attributed to physician practices’ Tax Identification Number (TIN), lasted 6 months, and were divided into performance years beginning 1/1/2016 and 7/1/2016. Three measures were used: 1) all-cause hospital admissions; 2) all-cause emergency department visits or observation stays; and 3) admission to hospice for 3 days or more among patients who died. SDOH included patient-level race as well as county-level rurality and social deprivation, measured using the social deprivation index (SDI). TIN-level scores with and without expanded SDOH variables were divided into quintiles and compared descriptively as well as using weighted kappa statistics. Results: No SDOH were significantly associated with the hospitalization outcome (P = 0.118-0.944). For the ED measure, Black patients and rural patients were significantly more likely to have an ED visit or observation stay during an episode than white patients and urban patients (P &lt; 0.0001). For the hospice measure, greater SDI values were associated with less hospice use (P &lt; 0.05). Accordingly, including SDOH variables for ED visit/observation stay and hospice measures had a greater impact on TIN rankings than for the hospitalization measure (Table). Conclusions: Because quintile rankings in determine potential shared savings under models like the OCM, differences in rankings due to additional SDOH variables could have a meaningful impact on TIN-level revenue. Additional work is needed to expand the scope of patient-level SDOH variables used for risk adjustment and to explore differences across TINs which contribute to SDOH-sensitive changes in rankings.[Table: see text]

Grading of Raw Jute Fibres Using Criteria Importance through Intercriteria Correlation (CRITIC) and Range of Value (ROV) Approach of Multi-criteria Decision Making

ABSTRACT In modern BIS system, a scientific approach is adopted for grading the raw jute fibers based on six apposite physical properties, namely fiber strength, defect, root content, fineness, color, and bulk density, of which the latter two parameters are still evaluated subjectively. Several researchers have attempted, over the years, many exponents of multi-criteria decision making (MCDM) approaches and got encouraging results. However, in all these approaches, subjective weighting methods have been used in the form of analytic hierarchy process (AHP). In this paper, a maiden integrated approach using criteria importance through intercriteria correlation (CRITIC) and range of value (ROV) is presented for grading jute fibers on the basis of abovementioned six attributes. Ranking performance of the present approach closely resembles with other approaches hitherto attempted by several researchers. The efficacy and robustness of the new approach are validated using sensitivity analysis through altering the weightage levels of the criteria. The rank correlation coefficients between the ranking patterns obtained in each of the weightage levels are, in most of the cases, 1 or very close to 1, which signifies no occurrence of rank reversal or change in ranking. During sensitivity analysis in dynamic decision conditions, the approach is stable up to certain level and then rank reversal takes place for some of the alternatives including the top ranked one. The uniqueness of the present study lies in the fact that here criteria weights are determined objectively using CRITIC and hence more reliable and devoid of influence/preferences of decision-makers (DMs). Moreover, the new approach is very simple with a few simple mathematical equations, albeit a potent tool of decision making with strong background logic.

The Efficiency and Productivity Evaluation of National Innovation Systems in Europe

Purpose: An efficient innovation system currently plays a crucial role in creating competitive prevalence, contributing to the economic growth of individual states. The innovation system is influenced by many socioeconomic factors, including in international rankings of innovativeness of economies. These classifications have some limitations. Primarily, they do not examine the efficiency, which means they do not analyze the relationship between the involved inputs and the relevant outputs generated in the innovation system. The study aims to measure the efficiency and productivity of the European state's innovation system based on the data from the international ranking of economies' innovation. Design/Methodology/Approach: In this study, the changes in the efficiency and productivity of the innovation system coming from European states were measured using the DEA and Malmquist index methods, based on data from the European Innovation Scoreboard international ranking innovation in economies. The maximizing of economic benefits was assumed in its impact on employment and sales in a given state. The non-radial SBM model, Super SBM, and Malmquist index based on SBM were used for the research. 27 European states were subjected to the analysis in the period from 2012 to 2019. Findings: The research results indicate that the average level of efficiency in the surveyed period fluctuated around 70%. Higher results of efficiency were achieved more frequently by states that joined the EU after 2004. The increase in the productivity of individual states was caused most frequently by an increase in their efficiency (catch-up effect) and less frequently by shifting the efficiency frontier (frontier effect). Practical Implications: The following research hypothesis was decided to be laid down: developing states and those newly admitted to the European Union after 2004 have been gaining relatively more economic benefits from smaller national innovation systems (NIS) resources than developed states and the so-called states of the old Union. Originality/Value: The added value of the article is, first of all, a comprehensive measurement of the efficiency and productivity of European states NIS in three aspects - efficiency status, efficiency ranking, and productivity changes assessment.

Wealth-adjusted Human Development Index

It has been shown that the development of a country's people stems from its wealth, which is characterized by human, social, and natural capital, but an assessment of the Human Development Index adjusted for wealth is still missing in the literature. There are large differentiations in the productive bases of countries, and the Human Development Index alone does not allow for encompassing the systems' ability for fostering human development from the endowment of resources available. The input-to-output link between the resources and human development reflects the systems' ability to optimise assets. This paper introduces an evaluation of the Human Development Index adjusted for the comprehensive wealth of countries using an ordinal non-compensatory technique that is robust to outliers, and which allows for the consideration of environmental factors and non-discretional inputs. Results show relevant changes in ranking when Human Development Indexes is adjusted for wealth. Decreases in the Human Development Index when wealth is considered, are observed in North America, the Middle East & North Africa, while increases in the Human Development Index when wealth is considered, are observed in most Sub-Saharan African and South Asian countries. The unexplored link between wealth and human development reveals an unprecedented heterogeneity among countries that is affected by economic, social, and institutional factors. The gaps in these factors must be further investigated if the increase of human development is to be implemented because efficient long-term management of natural resources is necessary for sustainability.

Application of Multi-Criteria Decision analysis including sustainable indicators for prioritization of public transport system.

Paratransit modes dominate the public transportation industry in the majority of developing countries, especially those in Sub-Saharan Africa. The number of these modes has increased rapidly over the years. Authorities have not yet been able to provide a better alternative for passengers, whose demand is ever-growing. In this research, the main modes of public transport in a Sub-Saharan African city, Kampala, have been studied. Here we used multi-criteria decision-making methods to find out which among the four major public transport modes in Kampala, Uganda, are best from a transportation operator's perspective. The evaluation of alternatives was conducted using Analytic Network Process (ANP) and Elimination Et Choice Translating Reality (ELECTRE III) methods. Both the ANP and the ELECTRE III analysis results demonstrate that alternative "Coaster" is the most appropriate alternative from a public transport operator's point of view. A sensitivity analysis consisting of four different scenarios was considered in the changing of weighting percentages (for benefit, cost, and risk clusters) in the ANP and the ELECTRE III analyses, to show the robustness of the ranking results. According to the sensitivity analysis results, there was no change in the final ranking. The findings of this paper are crucial to policymakers within the transportation sectors of developing countries. Integr Environ Assess Manag 2022;18:25-38. © 2021 SETAC.

Masculinity Contest Cultures and Inclusive Cultures: Insights From an Agent-Based Model

Recent scholarship by Berdahl et al. (2018) finds that “work” becomes a masculinity contest when organizations valorize acts of dominance, acts which likely perpetuate barriers to the advancement of marginalized groups in organizations (as with the “glass ceiling”). But how such Masculinity Contest Cultures (MCCs) develop and sustain themselves remain open questions. This study juxtaposes MCCs with Inclusive Cultures to examine how each culture spreads in organizations. Drawing upon systems theory, we simulated the processes of socialization and promotion in organizations via an agent-based computational model. Varying the hiring pools for different organizations from inclusive to contest-oriented revealed that inclusiveness emerged as self-reinforcing in all but organizations with the most contest-oriented hiring pools. In contrast, hiring pools socialized into hegemonic masculinity made organizations more likely to resist Inclusive Cultures and showed potential to evolve into MCCs in productivity-oriented, hierarchical organizations. Furthermore, organizations tended to see greater cultural change in higher ranks of the organizational hierarchy than in lower ranks, regardless of the more-prevalent culture. Such cultural stratification demonstrates the challenge in transforming the culture of every organizational level toward inclusiveness without further study of socialization processes.

Quantifying the effects of watershed subdivision scale and spatial density of weather inputs on hydrological simulations in a Norwegian Arctic watershed

Abstract The effects of watershed subdivisions on hydrological simulations have not been evaluated in Arctic conditions yet. This study applied the Soil and Water Assessment Tool and the threshold drainage area (TDA) technique to evaluate the impacts of watershed subdivision on hydrological simulations at a 5,913-km2 Arctic watershed, Målselv. The watershed was discretized according to four TDA scheme scales including 200, 2,000, 5,000, and 10,000 ha. The impacts of different TDA schemes on hydrological simulations in water balance components, snowmelt runoff, and streamflow were investigated. The study revealed that the complexity of terrain and topographic attributes altered significantly in the coarse discretizations: (1) total stream length (−47.2 to −74.6%); (2) average stream slope (−68 to −83%); and (3) drainage density (−24.2 to −51.5%). The spatial density of weather grid integration reduced from −5 to −33.33% in the coarse schemes. The annual mean potential evapotranspiration, evapotranspiration, and lateral flow slightly decreased, while areal rainfall, surface runoff, and water yield slightly increased with the increases of TDAs. It was concluded that the fine TDAs produced finer and higher ranges of snowmelt runoff volume across the watershed. All TDAs had similar capacities to replicate the observed tendency of monthly mean streamflow hydrograph, except overestimated/underestimated peak flows. Spatial variation of streamflow was well analyzed in the fine schemes with high density of stream networks, while the coarse schemes simplified this. Watershed subdivisions affected model performances, in the way of decreasing the accuracy of monthly streamflow simulation, at 60% of investigated hydro-gauging stations (3/5 stations) and in the upstream. Furthermore, watershed subdivisions strongly affected the calibration process regarding the changes in sensitivity ranking of 18 calibrated model parameters and time it took to calibrate.

Long-term orientation and the passage of time: Is it time to revisit Hofstede’s cultural dimensions?

Hofstede’s cultural dimensions are one of the most commonly referenced cultural models in the literature, but it has also been criticized for its inflexibility in terms of allowing for cultural changes over time. In this study, we focus on one salient dimension of national culture, long-term orientation (LTO), to investigate cultural change over time. Using the LTO scale developed by Bearden et al. ((2006) A measure of long-term orientation: development and validation. Journal of the Academy of Marketing Science 34(3): 456–67), we conducted a survey in Brazil, China, Colombia, India, Portugal, Romania, Spain, and Turkey, and collected 1,452 valid responses. Our study provided new evidence on LTO national ranking and cultural change. We found the countries surveyed no longer appear to be in the same relative positions as when Hofstede first published his results in the 1980s, or his more recent results based on data from the World Value Survey (WVS). Implications for practitioners, academics, and students in the cross-cultural management field are discussed.

Exploring the link between project delays and cancelation rates in the U.S. rooftop solar industry

About 1 in 10 rooftop solar photovoltaic (PV) customers who sign a contract to install a PV system cancel their contract before the system is installed. Although some cancelation risk is inherent in the solar industry, there may be ways to reduce cancelation volume, such as reducing project delays. Delays can occur at each stage of PV adoption processes, which take several weeks to months from contract signature to system operation. Using data from a recent survey of PV installers, we explore the factors that explain PV project delays and cancelations. The survey data suggest that PV adoptions take about 16 weeks, on average, from contract signature until system operation. Survey respondents consistently identified permitting, inspection, and interconnection (PII) processes as key drivers of project delays. Most respondents then suggested these PII-related delays increase contract cancelations. However, larger-scale installers report higher cancelation rates, and these installers rank changes in customer financial situations higher than PII-related delays as the main cause for cancelations. Most respondents also reported avoiding jurisdictions with particularly onerous PII requirements or charging more in these jurisdictions. On balance, the results provide a rationale for measures to streamline PII processes to reduce delays and potentially mitigate cancelation risk.

Multi-criteria decision analysis methods for energy sector's sustainability assessment: Robustness analysis through criteria weight change

Well-optimized decision-making is a prerequisite for effective energy planning, and this requires several criteria to be considered. The multi-criteria decision analysis (MCDA) methods underpin this decision-making process through different techniques. A MCDA method can provide a reliable methodology that helps to organize the most optimized result in the presence of many different opportunities, parameters, and constraints. The selection of an effective MCDA method in the energy sector is challenging. Particularly, sustainability assessment of the electricity generation sector using a MCDA method is difficult as it is necessary to consider at least three different criteria (economic, environmental, and social) with many indicators. This work compares the robustness, with respect to criteria weight change, of seven MCDA methods that are employed to assess the sustainability of electricity generation technologies through a case study. This case study underpins conducting an effective comparison between the employed methods and conclusions drawn. Robustness is defined cumulatively, counting the number of ranking changes while varying the criteria weights by 5%, 15% and 50%. The methods considered are Weighted Sum Method (WSM), Weighted Product Method (WPM), VIKOR, Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS), Performance Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), Analytical Hierarchy Process (AHP), and COmplex PRoportional ASsessment (COPRAS). The analysis revealed that COPRAS is the most robust MCDA method, followed by WPM. The least robust one is found to be TOPSIS. Both AHP and WSM ranked third in the robustness measure.

Dance Exposure, Individual Characteristics, and Injury Risk over Five Seasons in a Professional Ballet Company.

This study aimed to describe the relationships between dance exposure, dancer characteristics, and injury risk across five seasons in a professional ballet company. Dance exposure time and clinician-reported time-loss and medical attention injury data were prospectively collected from 118 professional dancers of The Royal Ballet between 2015/2016 and 2019/2020. Cox proportional hazards and shared frailty models were fitted to overuse and traumatic injuries; individualized robust Z-scores for 7- and 28-d accumulated exposure, and week-to-week change in exposure, age, sex, company rank, and injury history were included as time-varying covariates. Across 381,710 h of exposure, 1332 medical attention and 427 time-loss injuries were observed. Positive relationships were observed between week-to-week change in exposure and overuse time-loss (+1 Z-score hazard ratio (HR), 1.27; 95% confidence interval (CI), 1.06-1.53) and medical attention injury risk (+1 Z-score HR, 1.17; 95% CI, 1.06-1.28). A negative relationship was observed between 7-d accumulated exposure and overuse medical attention injury risk (+1 Z-score HR, 0.74; 95% CI, 0.66-0.84). Overuse time-loss injury risk was greater in soloists compared with the corps de ballet (HR, 1.47; 95% CI, 1.01-2.15) and in dancers with a higher previous injury rate (+1 injury per 1000 h HR, 1.06; 95% CI, 1.02-1.10). Only age was associated with traumatic time-loss (+1-yr HR, 1.05; 95% CI, 1.01-1.09) or medical attention injury risk (+1-yr HR, 1.04; 95% CI, 1.01-1.07). Professional ballet companies should implement training principles such as periodization and progression, particularly in the case of senior-ranking dancers, older dancers, and dancers with high rates of previous injury. These findings provide a basis for future prospective investigations into specific causal injury pathways.

Shared Decision-Making With a Virtual Patient in Medical Education: Mixed Methods Evaluation Study.

BackgroundShared decision-making (SDM) is a process in which clinicians and patients work together to select tests, treatments, management, or support packages based on clinical evidence and the patient’s informed preferences. Similar to any skill, SDM requires practice to improve. Virtual patients (VPs) are simulations that allow one to practice a variety of clinical skills, including communication. VPs can be used to help professionals and students practice communication skills required to engage in SDM; however, this specific focus has not received much attention within the literature. A multiple-choice VP was developed to allow students the opportunity to practice SDM. To interact with the VP, users chose what they wanted to say to the VP by choosing from multiple predefined options, rather than typing in what they wanted to say.ObjectiveThis study aims to evaluate a VP workshop for medical students aimed at developing the communication skills required for SDM.MethodsPreintervention and postintervention questionnaires were administered, followed by semistructured interviews. The questionnaires provided cohort-level data on the participants’ views of the VP and helped to inform the interview guide; the interviews were used to explore some of the data from the questionnaire in more depth, including the participants’ experience of using the VP.ResultsThe interviews and questionnaires suggested that the VP was enjoyable and easy to use. When the participants were asked to rank their priorities in both pre- and post-VP consultations, there was a change in the rank position of respecting patient choices, with the median rank changing from second to first. Owing to the small sample size, this was not analyzed for statistical significance. The VP allowed the participants to explore a consultation in a way that they could not with simulated or real patients, which may be part of the reason that the VP was suggested as a useful intervention for bridging from the early, theory-focused years of the curriculum to the more patient-focused ones later.ConclusionsThe VP was well accepted by the participants. The multiple-choice system of interaction was reported to be both useful and restrictive. Future work should look at further developing the mode of interaction and explore whether the VP results in any changes in observed behavior or practice.

Guide for the establishment of the decomposition model of the probability density function based on the hyphal extension rate of fungi

The main purpose of this paper is to provide readers with a guide to mathematical modeling. The idea of establishing a model is roughly as follows: extract the probability factors of the research object, analyze the research object itself, observe the changes of the research object, and observe the effects of environmental changes on the research object. In this article, taking the 2021 American Mathematical Competition in Modeling (MCM) as an example, using the proposed modeling guidelines, a mathematical model was established to describe the decomposition of woody fiber by fungi, and the independent variable was set to hyphal extension rate, temperature conditions, climate conditions, etc. Set the dependent variable to decomposition rate, and fit a series of logarithmic expression and exponential expression according to the data provided by references[1][2]. Establish a community evolution model to realize the dynamic evolution of the interaction between different types of fungi, fungi with a higher competitive ranking will have a higher hyphal extension rate than the original without the interaction. As a result, fungi with a higher competitive ranking is in a dominant position in the colony, and fungi with a lower competitive ranking is in a subordinate or inferior position in the colony. In order to use the relative advantages and disadvantages of various fungi in different environments to predict the exact composition of fungi in the colony, considering the influence of initial climatic conditions on the evolution of the community, and bring about relative changes in the competitive ranking of different types of fungi. The model example in this article reflects the correctness of the modeling guidelines.

Metric Routing Protocol for Detecting Untrustworthy Nodes for Packet Transmission

IoT objects that have a resource constrained nature resulting in a number of attacks in the routing protocol for lossy networks and low-power networks. RPL is very vulnerable to selfish behaviours and internal attacks though they are built with encryption protection to secure messages. To address this vulnerability, in this paper, we propose a novel trustworthiness methodology based on metric for incorporating trust evaluation, enhancing the robustness of security mechanism. Simulation results indicate that the proposed work is efficient in terms of throughput, nodes’ rank changes, energy consumption and packet delivery ratio. Moreover, using mathematical modelling, it has been observed that this methodology meets the demands of loop-freeness, optimality and consistency. This shows that this metic has both monotonicity and isotonicity requirements to enable the routing protocol. Incorporating the concepts of game theory, we can use this technique as a strategy to iterate Prisoner’s Dilemma. Both evolutionary simulation and mathematical analysis indicate that the proposed metric-based routing protocol is an efficient technique in promoting evolution and stability of the IoT network.

ANALISIS KESEHATAN KEUANGAN DAERAH KABUPATEN/ KOTA SE PROVINSI BANTEN TAHUN ANGGARAN 2016-2019

The regional financial condition is an important instrument to assess the extent of the condition of regional financial capacity and performance. In this research, he wants to know the condition of the regional financial health in the regencies / cities in Banten Province, in the period 2016-2019. The research method used is quantitative with the results of calculations described descriptively, the data used is a summary of the realization of the TA budget. 2016-2019, and regional statistical data in numbers, such as total population and gross regional income (PDRB) of each Regency / City in Banten Province. The results of the analysis and findings show that the highest index score in the 2016-2019 period ranged from 0.724 to 0.791, while the lowest index score was between 0.124-0.159. There are 5 regions that show an increase in the index, while 3 other regions have a decrease. In terms of index scores, the regions that experienced an increase in the regional financial health index were Serang Regency (0.162), Lebak Regency (0.138), Serang City (0.084), South Tangerang City (0.023) and Cilegon City (0.003). Meanwhile, the regions whose scores decreased were Tangerang City (-0.009), Pandeglang Regency (-0.035) and Tangerang Regency (- 0.061). In terms of ranking, the highest score index is South Tangerang City and Tangerang Regency. In 2016 the highest score was South Tangerang City (0.724), in 2017-2018 there was a change in ranking, the highest was Tangerang Regency (2017: 0.791) and (2018: 0.742), in 2019 the highest ranking was South Tangerang City (0.747). The districts / cities that did not experience a change in the regional financial health index score rankings were Tangerang City (rank 3), Cilegon City (rank 4) and Serang Regency (rank 5). Meanwhile, the districts with the lowest average index were Lebak (0.244) and Pandeglang (0.147). Meanwhile, based on the type of city government, only Serang City whose score is still below the average index. Meanwhile, in the district government type, Tangerang Regency is the representative of the Regency which has a high index score. Even though Serang City is below average, but in terms of consistent scores, Serang city continues to increase and experience improvement. The regional financial health ranking index score is only compared between districts / cities in Banten Province for the 2016-2019 fiscal year. The development gap and regional fiscal ratio in Banten Province are very visible. The next research, especially to examine the financial performance of the City, can compare with other cities that are considered more equal.

Adjusting Client-Level Risks Impacts on Home Care Organization Ranking.

Quality indicators (QIs) based on the Resident Assessment Instrument-Home Care (RAI-HC) offer the opportunity to assess home care quality and compare home care organizations’ (HCOs) performance. For fair comparisons, providers’ QI rates must be risk-adjusted to control for different case-mix. The study’s objectives were to develop a risk adjustment model for worsening or onset of urinary incontinence (UI), measured with the RAI-HC QI bladder incontinence, using the database HomeCareData and to assess the impact of risk adjustment on quality rankings of HCOs. Risk factors of UI were identified in the scientific literature, and multivariable logistic regression was used to develop the risk adjustment model. The observed and risk-adjusted QI rates were calculated on organization level, uncertainty addressed by nonparametric bootstrapping. The differences between observed and risk-adjusted QI rates were graphically assessed with a Bland-Altman plot and the impact of risk adjustment examined by HCOs tertile ranking changes. 12,652 clients from 76 Swiss HCOs aged 18 years and older receiving home care between 1 January 2017, and 31 December 2018, were included. Eight risk factors were significantly associated with worsening or onset of UI: older age, female sex, obesity, impairment in cognition, impairment in hygiene, impairment in bathing, unsteady gait, and hospitalization. The adjustment model showed fair discrimination power and had a considerable effect on tertile ranking: 14 (20%) of 70 HCOs shifted to another tertile after risk adjustment. The study showed the importance of risk adjustment for fair comparisons of the quality of UI care between HCOs in Switzerland.

How Robust are Model Rankings : A Leaderboard Customization Approach for Equitable Evaluation

Models that top leaderboards often perform unsatisfactorily when deployed in real world applications; this has necessitated rigorous and expensive pre-deployment model testing. A hitherto unexplored facet of model performance is: Are our leaderboards doing equitable evaluation? In this paper, we introduce a task-agnostic method to probe leaderboards by weighting samples based on their 'difficulty' level. We find that leaderboards can be adversarially attacked and top performing models may not always be the best models. We subsequently propose alternate evaluation metrics. Our experiments on 10 models show changes in model ranking and an overall reduction in previously reported performance- thus rectifying the overestimation of AI systems' capabilities. Inspired by behavioral testing principles, we further develop a prototype of a visual analytics tool that enables leaderboard revamping through customization, based on an end user's focus area. This helps users analyze models' strengths and weaknesses, and guides them in the selection of a model best suited for their application scenario. In a user study, members of various commercial product development teams, covering 5 focus areas, find that our prototype reduces pre-deployment development and testing effort by 41% on average.

Student perceptions of older adults after a music intervention: A mixed approach

AimsThe aims of this project were to investigate changes in nursing students’ attitudes and perceptions of older adults after implementing individualized Music and Memory© playlists. In addition, the inquiry sought to compare pre and post survey responses for changes in rankings of caring for the older adult as a career choice. The qualitative inquiry sought to explore students’ perceptions of their experience through narrative journaling for a better understanding of the experience. DesignThis study used an explanatory sequential mixed design. MethodsA pre post-intervention approach was used for quantitative data collection along with a ranking item for career choices. Journal narratives completed within one week following the experience were explored for qualitative themes to better understand students’ experiences. Attitudes and perceptions of students (N = 44) were measured by two tools before and after implementation of Music and Memory© Interventions during a 7-week clinical experience. Student journals were analyzed for themes. ResultsIn the two-tailed paired t-test, nursing students’ attitudes and perceptions of caring for older adults were analyzed for differences. Significance improvement was found in students’ reported interaction scores and other constructs (p ≤ .01). Mean ranking of caring for the older adult improved from 7.6 to 7.0 in the post intervention analysis. Student journals reported the activity as worthwhile and time consuming. ConclusionsAs the baby boomer generation ages the need for residential long-term care is projected to increase significantly. Recruiting and retaining nurses to care for this vulnerable population is challenging. Music and Memory© Interventions have the potential to change student attitudes and perceptions of the older adult that could improve caring for the older adult as a career choice.