Interobserver Reliability and Sensitivity to Change of a Composite Ocular Inflammatory Activity Index: UVEDAI©.

INTRODUCTION: This was a multicenter, prospective, longitudinal, observational study involving eight Spanish tertiary hospitals to determine the interobserver reliability of an uveitis disease activity index, (UVEDAI) and assess its sensitivity to change in patients with receiving pharmacologic treatment. METHODS: Patients aged ≥ 18 years diagnosed with active noninfectious uveitis were included. A complete baseline assessment was performed by two ophthalmologists who determined ocular inflammatory activity using the UVEDAI index independently of each other. The principal ophthalmologist made a new visit at 4 weeks to determine the change in inflammatory activity. The interobserver reliability analysis was performed by calculating the intraclass correlation coefficient (ICC), with the values of the variables and the UVEDAI obtained by both ophthalmologists in the more active eye at the baseline visit. Sensitivity to change in the UVEDAI index was assessed at 4 weeks from the start of pharmacologic treatment by determining the clinically relevant change, defined as a change in UVEDAI of ≥ 0.8 points over baseline. The mean change between both measures was compared using the repeated-measures t-test. RESULTS: A total of 111 patients were included. In the interobserver reliability analysis, the ICC for the UVEDAI value was 0.9, and, when compared with the mean UVEDAI values obtained by the ophthalmologists, no statistically significant differences were found (p value > 0.05). As for the sensitivity to change in UVEDAI, statistically significant differences (p value = 0.00) were found for the mean values of the index compared with baseline. In all cases, the index value decreased by > 1 point at the 4-week visit. CONCLUSIONS: The interobserver reliability of the UVEDAI was high in the total sample. Furthermore, the index was sensitive in determining the change in inflammatory activity after treatment. We believe that UVEDAI is a disease activity index that enables objective comparison of results in clinical practice and trials.

Construction of yield loss indicators for cold vortex, light-temperature-water combined stress during the flowering period of rice in Northeast China.

The construction of a yield loss evaluation index for the cold vortex type light-temperature-water composite adversity during rice flowering period in Northeast China is important for elucidating the impacts of cold vortex type composite disasters on rice yield loss in middle and high latitude areas. Moreover, it can provide meteorological support to ensure safe production of high-quality japonica rice in China and contribute to regional disaster reduction and efficiency improvement. By combining growth period data, meteorological data, and yield data, we delineated and constructed the composite stress occurrence index of cold vortex type light-temperature-water at the flowering stage of japonica. We analyzed the relationship between factors causing disasters and yield structure, as well as the relationship between different yield structures and yield by employing BP neural network method. We further dissected the processes involved in the causation of combined disasters. Based on the K-means clustering method and historical typical disaster years, we quantified the critical thresholds and disaster grades, and established an evaluation index and model for assessing yield loss caused by combined stress from cold vortex type light-temperature-water. Finally, we examined the spatial and temporal variations of low temperature, abundant rainfall, and reduced sunlight during the flowering period in the three provinces of Northeast China. Results showed that the critical thresholds for light, temperature, and water stress index during the flowering stage of mild, moderate, and severe cold vortex types were [0, 0.21), [0.21, 0.32), and [0.32, 0.64], respectively. The rates of yield loss were [0, 0.03), [0.03, 0.08), and [0.08, 0.096], respectively. Based on the verification results of a total of 751 samples in 11 random years from 1961 to 2020, the percentage of stations for which the production reduction grade, as calculated by the composite index developed in this study, aligning with the actual production reduction grade was 63.7%, consistently exceeding 58.0% annually. Moreover, the proportion of sites with a similarity or difference level of 1 stood at 88.3%, surpassing 85.0% in each year. The index could effectively assess the extent of rice yield loss caused by cold vortex disasters in Northeast China.

Anthropometric failures and its predictors among under five children in Ethiopia: multilevel logistic regression model using 2019 Ethiopian demographic and health survey data.

BACKGROUND: Composite Index of Anthropometric Failure (CIAF) combines all three forms of anthropometric failures to assess undernutrition status of children. There is no study on CIAF to identify the real and severe form of under nutrition among Ethiopian children that addressed community level factors. So, this study determined CIAF and identified important factors which helps to design appropriate intervention strategies by using multi-level advanced statistical model. METHODS: The study included 5,530 under five children and utilized a secondary data (EMDHS 2019) which was collected through community-based and cross-sectionally from March 21 to June 28, 2019. Composite index of anthropometric failure among under five children was assessed and a two-stage sampling technique was used to select the study participants. Descriptive summary statistics was computed. A multi-level binary logistic regression model was employed to identify important predictors of CIAF in under five children. Adjusted odds ratio with its 95% CI was estimated and level of significance 0.05 was used to determine significant predictors of CIAF. RESULTS: The prevalence of composite index of anthropometric failure (CIAF) was 40.69% (95% CI: 39.41, 42.00) in Ethiopia. Both individual and community level predictors were identified for CIAF in under five children. Among individual level predictors being male sex, older age, short birth interval, from mothers who have not formal education, and from poor household wealth quintile were associated with higher odds of CIAF among under five children. Low community women literacy and being from agriculturally based regions were the community level predictors that were associated with higher odds of CIAF in under five children in Ethiopia. CONCLUSIONS: The burden of composite index of anthropometric failure in under five children was high in Ethiopia. Age of child, sex of child, preceding birth interval, mother's education, household wealth index, community women literacy and administrative regions of Ethiopia were identified as significant predictors of CIAF. Therefore, emphasis should be given for those factors to decrease the prevalence of CIAF in under five children in Ethiopia.

Generalized Structured Component Analysis Accommodating Convex Components: A Knowledge-Based Multivariate Method with Interpretable Composite Indexes.

Generalized structured component analysis (GSCA) is a multivariate method for examining theory-driven relationships between variables including components. GSCA can provide the deterministic component score for each individual once model parameters are estimated. As the traditional GSCA always standardizes all indicators and components, however, it could not utilize information on the indicators' scale in parameter estimation. Consequently, its component scores could just show the relative standing of each individual for a component, rather than the individual's absolute standing in terms of the original indicators' measurement scales. In the paper, we propose a new version of GSCA, named convex GSCA, which can produce a new type of unstandardized components, termed convex components, which can be intuitively interpreted in terms of the original indicators' scales. We investigate the empirical performance of the proposed method through the analyses of simulated and real data.

Developing a composite index for urban ecosystem services (Hyrcanian forests-Gorgan).

The current era has been termed the "Anthropocene," because of the irreversible impact of human activities. Land use change and urban growth are examples of these disturbances leading to the reduction in many ecosystem services (ESs). The subject of this study, Gorgan, has undergone significant changes that significantly affected the area. Studying these changes and understanding their effects on the ecosystem is essential. An integrated method was used to investigate the process of changing the urban ESs over 35 years, considering the physical and ecological characteristics of the area. This marks the first time such a study has been conducted using the hexagonal unit. Then, the composite total ecosystem services (TESs) index was calculated from the modeled and quantified combination of six ESs, including water yield, flood volume, net primary production, soil retention, carbon sequestration, and air pollution removal. Thereafter, the ESs were mapped and evaluated across time and space. The TES is proposed as an appropriate measure for quantifying ES supply and can indicate the overall function of ESs. According to the findings, the TES value declined from 0.427 in 1985 to 0.247 in 2005 and declined to 0.192 in 2020. Moreover, the Hyrcanian forests were the main source of the highest TES in Gorgan city, whereas urban areas had the lowest levels. The shortage of ESs in the study area has resulted in various crises. These include reduced air quality, heightened flood risk, soil erosion, and ecological imbalances in urban regions. Integr Environ Assess Manag 2024;20:465-480. © 2023 Society of Environmental Toxicology & Chemistry (SETAC).

DAS28-γGT for the prediction of major cardiovascular events in rheumatoid arthritis: results from the ESPOIR cohort.

OBJECTIVE: To validate the predictive value of the DAS28 γ-glutamyl transferase (DAS28-γGT) for the occurrence of major cardiovascular (CV) events (MACE) in the 'Etude et Suivi des Polyarthrites Indifférenciées Récentes' ESPOIR cohort. METHODS: Analysis of 13-year outcome from the ESPOIR cohort. RA patients with missing data for baseline γGT activity and those not followed-up to 1 year were excluded. Baseline DAS28-γGT was calculated using the following formula: 0.56*√TJ-28 + 0.28 * √SJ-28 + 2*ln(γGT) + 0.014 * GH. Our primary outcome was the merit of the DAS28-γGT in predicting the occurrence of MACE. RESULTS: Among the 696 patients [536 women, mean (s.d.) age of 49 (12) years], 34 MACE were recorded, with a mean time to event of 71 (44) months. Receiver operating characteristic curve analysis indicated that a DAS28-γGT >9.4 had the best sensitivity and specificity for the diagnosis of MACE during the observation period. DAS28-γGT >9.4 was predictive of the occurrence of MACE, with a hazard ratio (HR) of 3.11 (95% CI 1.41, 5.43). Multivariate Cox analyses confirmed higher DAS28-γGT (HR 2.44, 95% CI 1.05, 5.64) together with age (HR 1.04, 95% CI 1.01, 1.07) and diabetes mellitus (HR 4.12, 95% CI 1.55, 10.95) as independent predictors of MACE. There was a dose effect of the DAS28-γGT for MACE-risk prediction, which was in line with the application of the Framingham risk score. CONCLUSION: The DAS28-γGT was identified in this large prospective cohort as an independent predictor of MACE in patients with RA. The DAS28-γGT is a simple and useful tool to evaluate CV risk in routine and warn the clinician about the CV risk burden in patients with RA.

A new comprehensive quantitative index for the assessment of essential amino acid quality in beef using Vis-NIR hyperspectral imaging combined with LSTM.

The quality of beef is usually predicted by measuring a single index rather than a comprehensive index. To precisely determine the essential amino acid (EAA) contents in 360 beef samples, the feasibility of optimized spectral detection techniques based on the comprehensive EAA index (CEI) and comprehensive weight index (CWI) constructed by factor analysis was explored. Two-dimensional correlation spectroscopy (2D-COS) was used to analyse the mechanisms of spectral peak shifts in complex disturbance systems with CEI and CWI contents, and 15 sensitive feature variables were extracted to establish a quantitative analysis model of a long short-term memory network (LSTM). The results indicated that 2D-COS had good predictive performance in both CEI-LSTM (R2P of 0.9095 and RPD of 2.76) and CWI-LSTM (R2P of 0.8449 and RPD of 2.45), which reduced data information by 88%. This indicates that utilizing 2D-COS can eliminate collinearity and redundant information among variables while achieving data dimensionality reduction and simplification of calibration models. Furthermore, a spatial distribution map of the comprehensive EAA content was generated by combining the optimal prediction model. This study demonstrated that the comprehensive index method furnishes a new approach to rapidly evaluate EAA content.

Proposal to measure tourism development within a destination and segment its different territories.

Tourism offers a means of promoting a local development strategy capable of harnessing the resources available within a territory. In order to do this, we must know the potential for tourism development in each territory, as well as the factors that would condition it. In this article, a methodology (based on the design of a system of indicators, the construction of composite indexes, and segmentation by means of cluster analysis) is proposed to measure tourism development within an emerging country and segment its different territories. The case study chosen to validate this methodology is Ecuador, a country with interesting tourist potential, where individual cities have very different levels of tourism development. The results highlight the factors that drive or constrain the degree of tourism development presented by the cities analysed, thereby facilitating decision-making for major stakeholders in each of them.

Does energy-consuming right trading have double dividend effect on firm's economic performance and carbon emission?

Whether the market-based environmental regulation policy can achieve a win-win situation of economic growth and carbon emission reduction has always been an academic controversial topic. Taking the pilot policy of energy-consuming right trading (ECRT) of China in 2016 as a quasi-natural experiment, this paper uses the difference-in-differences (DID) method to investigate the policy impact of ECRT on the economic performance and carbon emissions of firms. An economy-environment composite index has been conducted for testing double dividend effect of ECRT. The empirical results show that ECRT can improve the economic performance and reduce carbon emissions of firms significantly. The double dividend effect is more significant in high-carbon emission firms, non-state-owned firms and prior to COVID-19 pandemic. ECRT policy has Porter innovation mechanism, in which innovation input is the main contribution of economic dividend effect and green technology innovation is the main contribution of environmental dividend effect. The conclusions of this paper provide empirical evidence and policy implications for realizing the common development of economy and environment, accelerating the process of emission reduction and building a national energy trading market.

Built and social indices for hazards in Children's environments.

Leveraging the capabilities of the Historical Spatial Data Infrastructure (HSDI) and composite indices we explore the importance of children's built and social environments on health. We apply contemporary GIS methods to a set of 2000 historical school records contextualized within an existing HSDI to establish seven variables measuring the relative quality of each child's built and social environments. We then combined these variables to create a composite index that assesses acute (short-term) health risks generated by their environments. Our results show that higher acute index values significantly correlated with higher presence of disease in the home. Further, higher income significantly correlated with lower acute index values, indicating that the relative quality of children's environments in our study area were constrained by familial wealth. This work demonstrates the importance of analyzing multiple activity spaces when assessing built and social environments, as well as the importance of spatial microdata.

Kernel-Free Quadratic Surface Support Vector Regression with Non-Negative Constraints.

In this paper, a kernel-free quadratic surface support vector regression with non-negative constraints (NQSSVR) is proposed for the regression problem. The task of the NQSSVR is to find a quadratic function as a regression function. By utilizing the quadratic surface kernel-free technique, the model avoids the difficulty of choosing the kernel function and corresponding parameters, and has interpretability to a certain extent. In fact, data may have a priori information that the value of the response variable will increase as the explanatory variable grows in a non-negative interval. Moreover, in order to ensure that the regression function is monotonically increasing on the non-negative interval, the non-negative constraints with respect to the regression coefficients are introduced to construct the optimization problem of NQSSVR. And the regression function obtained by NQSSVR matches this a priori information, which has been proven in the theoretical analysis. In addition, the existence and uniqueness of the solution to the primal problem and dual problem of NQSSVR, and the relationship between them are addressed. Experimental results on two artificial datasets and seven benchmark datasets validate the feasibility and effectiveness of our approach. Finally, the effectiveness of our method is verified by real examples in air quality.

Predicting the Potential Impact of Emergency on Global Grain Security: A Case of the Russia-Ukraine Conflict.

Global emergencies have a profound impact on exacerbating food insecurity, and the protracted Russia-Ukraine conflict has emerged as a significant driver of a global food crisis. Accurately quantifying the impact of this conflict is crucial for achieving sustainable development goals. The multi-indicator comprehensive evaluation approach was used to construct a grain security composite index (GSCI). Moreover, econometric model was used to predict the potential impacts of the conflict on global grain security in 2030 under two scenarios: with and without the "Russia-Ukraine conflict". The results conclude that global food prices reached unprecedented levels as a consequence of the conflict, leading to notable fluctuations in food prices, especially with a significant surge in wheat prices. The conflict had a negative impact on global grain security, resulting in a decline in grain security from 0.538 to 0.419. Predictions indicate that the influence of the conflict on global grain security will be substantially greater compared to the scenario without the conflict in 2023-2030, ranging from 0.033 to 0.13. Furthermore, grain security will first decrease and then increase under the sustained consequences of the conflict. The achievement of the 2030 sustainable development goals will encounter significant challenges in light of these circumstances.

Measuring digital capital in Italy.

Introduction: This paper aims to theoretically and empirically investigate the concept of digital capital in the Italian context. Digital Capital can be conceived as independent individual capital whose lack within a population can be a cause of digital inequality. Our paper draws from recent works that have measured the Digital Capital as a combination of digital access and digital competences, and have tested this operational definition through an online survey on a UK sample. The results of such research proved the construct validity of the operational definition, thus showing that Digital Capital could be empirically measured. However, a measurement model needs to be tested and validated over time and in different socio-cultural contexts in order to be refined and strengthened, and eventually disseminated on a large scale. Method: This is the reason why this paper will show the results of a funded research project (named DigiCapItaly) carried out to test the validity of the Digital Capital measure in a different country, i.e., Italy. The data were collected with an online survey using a representative sample (by age, gender and geographical area) of individuals living in Italy aged 18 years or more. The creation of a composite index to measure Digital Capital followed a two-stage Principal Component Analysis approach. Results: First, the paper provides a methodological framework for facing challenges and pitfalls in operationalizing and assessing a complex concept in social research. Secondly, results show that Digital Capital operational definition works in Italy as well as in the UK, thus legitimizing its recognition as an independent capital.

A community-based cross-sectional study to assess the burden of prevalence of undernutrition in 0-6 Years Anganwadi Children of Panvel Block, Raigad District, Maharashtra.

An impaired nutritional status in preschool children leaves significant impact on their overall childhood development. A community-based, cross-sectional study was conducted in Panvel, Maharashtra, over 15 months to assess the overall prevalence and patterns of undernutrition in preschool children using the composite index of anthropometric failure (CIAF). The sample size of 8542 was obtained from randomly selected 132 Anganwadis. Conventional indices (underweight, stunting, and wasting) and CIAF classification were used to assess the prevalence of undernutrition. Statistical analysis was performed using the SPSS version 27. About 50.6% of children were detected as "anthropometric failure" by CIAF method which is higher than conventional indices for underweight (32.9%), stunting (35.7%), and wasting (16.4%). The 13-25 months' age group was most significantly affected (57%) as per the CIAF. Undernutrition prevalence was similar for both genders across all age groups. A comprehensive policy is needed to identify and treat all anthropometrical failure children with special emphasis on 13-25 months' age group.

Overall lifestyle changes in adulthood are associated with cancer incidence in the Norwegian Women and Cancer Study (NOWAC) - a prospective cohort study.

BACKGROUND: Cancer is a leading cause of premature death worldwide and incidence is expected to rise in the coming decades. Many cohort studies, measuring lifestyle factors at one time-point, have observed that overall healthy lifestyles were inversely related to cancer incidence. However, there is little knowledge on the impact of lifestyle modification within adulthood. METHODS: Using the Norwegian Women and Cancer study, two repeated self-reported assessments of lifestyle behaviours were used to calculate healthy lifestyle index scores at each time-point (N = 66 233). The associations between change in healthy lifestyle index score and lifestyle-related cancer incidence, including alcohol-, tobacco-, obesity-, and reproductive-related, and site-specific breast and colorectal cancer incidence were estimated using Cox proportional hazard regression models. To assess nonlinearity in the dose-response relationships, restricted cubic spline models were used. RESULTS: Independent of baseline lifestyle, positive lifestyle changes were inversely related to the incidence of overall lifestyle-related cancers, as well as alcohol-related, tobacco-related, obesity-related, and reproductive-related cancers, but not breast and colorectal site-specific cancers. An association between lifestyle worsening and cancer incidence compared to stable lifestyle was observed. CONCLUSIONS: This study provides evidence that overall lifestyle changes among cancer-free women between the ages of 41 and 76 impact the incidence of many cancer types. Regardless of baseline lifestyle, there was a negative dose-response relationship between magnitude of positive lifestyle change and the incidence of overall lifestyle-related cancers. We observed that underlying this trend was an especially clear association between lifestyle worsening and increased risk compared to stable lifestyle. For adult women, maintaining a stable healthy lifestyle and lifestyle improvement are important for preventing the occurrence of many cancer types.

Substantial mismatch of skeletal maturity assessment between Risser sign and Simplified Skeletal Maturity Scale/Thumb Ossification Composite Index in patients with adolescent idiopathic scoliosis.

BACKGROUND: Recently, hand skeletal maturity systems such as the Simplified Skeletal Maturity Scale (SSMS) or Thumb Ossification Composite Index (TOCI) have been introduced to attempt to prospectively predict the occurrence of peak height velocity (PHV) in adolescents. This study aims to compare the frequency of the mismatch in estimation of HV between Risser sign (RS) and SSMS/TOCI stages in adolescent idiopathic scoliosis (AIS) patients. METHODS: One hundred thirty-three female patients with AIS were included. The mean age of the patients was 13.1 years. A whole spine and hand X-rays were obtained to establish skeletal maturity stage according to RS, SSMS, and TOCI systems. A mismatch resulting in overestimation (MOE) with RS compared to SSMS/TOCI was defined as the combination of RS 3-4/SSMS 3-5 or RS 3-4/TOCI 4-6, whereas a mismatch resulting in underestimation (MUE) with RS and SSMS/TOCI was defined as RS 0-1/SSMS 6-8 or RS 0-1/TOCI 7-8. Height velocity (HV) was compared between MOE/non-MOE and MUE/non-MUE groups. RESULTS: Between RS and SSMS, the rates of the MOE and MUE groups were 4.3% and 1.7%, respectively. Between RS and TOCI, rates were 2.8% and 1.7%, respectively. With the combination of RS and SSMS stages, an estimate of HV of 5.6 cm/year in the MOE group was significantly larger than that of 2.7 cm/year in the non-MOE group, and 3.7 cm/year in the MUE group was significantly smaller than 6.9 cm/year in the non-MUE group. Likewise, with the combination of RS and TOCI stages, an estimate of HV of 5.8 cm/year in the MOE group was significantly greater that of 2.7 cm/year in the non-MOE group, and 3.7 cm/year in the MUE group was significantly smaller than 6.9 cm/year in the non-MUE group. CONCLUSIONS: These findings support the use of SSMS/TOCI as the standard for assessing HV and skeletal maturity in patients with AIS.

Research on Spatial Delineation Method of Urban-Rural Fringe Combining POI and Nighttime Light Data-Taking Wuhan City as an Example.

The boundary delineation of the urban-rural fringe (URF) is the basic work of fine planning and governance of cities, which plays a positive role in promoting the process of global sustainable development and urban and rural integration. In the past, the delineation of URF had shortcomings such as a single selected data source, difficulty in obtaining data, and low spatial and temporal resolution. This study combines Point of Interest (POI) and Nighttime Light (NTL) data, proposes a new spatial recognition method of URF according to the characteristics of urban and rural spatial structure, and conducts empirical analysis with Wuhan as the research object, combining the information entropy of land use structure, NDVI, and population density data to verify and compare the delineation results and field verification was conducted for typical areas. The results show that (1) the fusion of POI and NTL can maximize the use of the characteristics of the differences in facility types, light intensity, and resolution between POI and NTL, compared with the urban-rural fringe boundary identified by POI, NTL or population density data alone, and it is more accurate and time-sensitive; (2) NPP and POI (fusion data of Suomi NPP-VIIRS and POI) can quantitatively identify potential central area and multi-layer structure of the city. It fluctuates between 0.2 and 0.6 in the urban core area of Wuhan and between 0.1 and 0.3 in the new town clusters, while in the URF and rural areas drops sharply to below 0.1; (3) the urban-rural fringe area of Wuhan covers a total area of 1482.35 km2, accounting for 17.30% of the total area of the city. Its land use types are mainly construction land, water area, and cultivated land, accounting for 40.75%, 30.03%, and 14.60% of the URF, respectively. Its NDVI and population density are at a medium level, with values of 1.630 and 2556.28 persons/km2, respectively; (4) the double mutation law of NPP and POI in urban and rural space confirms that the URF exists objectively as a regional entity generated in the process of urban expansion, provides empirical support for the theory of urban and rural ternary structure, and has a positive reference value for the allocation of global infrastructure, industrial division, ecological function division, and other researches.

Water-Energy-Food nexus index proposal as a sustainability criterion on dairy farms.

Cow milk is a fundamental nutrients source for the human diet at all stages of life. However, the decline in cow milk consumption over the years has been driven by increased consumer awareness of animal welfare and the environmental burdens associated. In this regard, different initiatives have emerged to mitigate the impacts of livestock farming, but many of them without addressing the multi-perspective view of environmental sustainability. Thus, the Water-Energy-Food (WEF) nexus emerges as a framework to consider the complex synergies among carbon emissions, water demand, energy requirements and food production. In this study, a novel and harmonised WEF nexus approach has been proposed and applied to evaluate a set of 100 dairy farms. For that, the assessment, normalisation, and weighting of three lifecycle indicators such as carbon, water and energy footprints, as well as the milk yield were carried out to obtain a single value, the WEF nexus index (WEFni), which varies from 0 to 100. Results show that the WEF nexus scores obtained vary from 31 to 90, demonstrating large differences among the farms assessed. A cluster ranking was performed to identify those farms with the worst WEF nexus indexes. For this group, consisting of 8 farms with an average WEFni of 39, three improvement actions focused on the feeding, digestive process and wellbeing of the cows were applied to determine the potential reduction in the two main hotspots identified: cow feeding and milk production level. The proposed methodology can establish a roadmap for promoting a more environmentally sustainable food industry, although further studies are still required in the pathway of a standardised WEFni.

Dataset for the climate-related financial policy index (CRFPI).

Data on the climate-related financial policy index (CRFPI) - comprising the global climate-related financial policies adopted globally and the bindingness of the policy - are provided in this paper for 74 countries from 2000 to 2020. The data include the index values from four statistical models used to calculate the composite index as described in [3]. The four alternative statistical approaches were designed to experiment with alternative weighting assumptions and illustrate how sensitive the proposed index is to changes in the steps followed to construct it. The index data shed light on countries' engagement in climate-related financial planning and highlight policy gaps in relevant policy sectors. Researchers could use the data provided in this paper to study green financial policies further and compare countries, highlighting engagement in specific policy areas or the entire spectrum of climate-related finance policy. Moreover, the data might be used to investigate the relationship between green finance policy adoption and credit market changes and assess their effectiveness in managing credit and financial cycles in the face of climate risks.

Leveraging Multivariable Linear Regression Analysis to Identify Patients with Anterior Cruciate Ligament Deficiency Using a Composite Index of the Knee Flexion and Muscle Force.

Patients with anterior cruciate ligament (ACL) deficiency (ACLD) tend to have altered lower extremity kinematics and dynamics. Clinical diagnosis of ACLD requires more objective and convenient evaluation criteria. Twenty-five patients with ACLD before ACL reconstruction and nine healthy volunteers were recruited. Five experimental jogging data sets of each participant were collected and calculated using a musculoskeletal model. The resulting knee flexion and muscle force data were analyzed using a t-test for characteristic points, which were the time points in the gait cycle when the most significant difference between the two groups was observed. The data of the characteristic points were processed with principal component analysis to generate a composite index for multivariable linear regression. The accuracy rate of the regression model in diagnosing patients with ACLD was 81.4%. This study demonstrates that the multivariable linear regression model and composite index can be used to diagnose patients with ACLD. The composite index and characteristic points can be clinically objective and can be used to extract effective information quickly and conveniently.