Background: The modified Duke index derived from coronary computed tomography angiography (CCTA) was designed to predict cardiovascular outcomes based on the severity of coronary ste-nosis. However, it does not take into consideration the presence or severity of peri-coronary in-flammation. The peri-coronary fat attenuation index (FAI) is a novel imaging marker determined by CCTA which reflects the degree of inflammation in the coronary tree in patients with coronary artery disease. Purpose: To assess the association between the modified Duke index assessed by CCTA, cardiovascular risk factors and peri-coronary inflammation in the coronary arteries of pa-tients with coronary artery disease. Methods: One hundred seventy-two patients who underwent CCTA for typical angina were assigned into two groups based on the modified Duke index: group 1 – patients with low index ≤ 3 (n=107) and group 2 – patients with high index > 3 (n=65). Demo-graphic, clinical and CCTA data were collected for all patients, and FAI analysis of coronary in-flammation was performed. Results: Patients with increased values of the modified Duke index were significantly older compared to those with a low index (61.83 ± 9.89 vs. 64.78 ± 8.9; p = 0.002). No differences were found between the two groups in terms of gender distribution, hypertension, hypercholesterolemia or smoking history (all p > 0.5). The FAI score was significantly higher in patients from group 2, who presented a significantly higher score of inflammation compared to the patients in group 1, especially at the level of the right coronary artery (FAI score 20.85 ± 15.80 vs. 14.61 ± 16.66; p = 0.01 for the right coronary artery, 13.85 ± 8.04 vs. 10.91 ± 6.5; p = 0.01 for the circumflex artery, and 13.26 ±10.18 vs. 11.37 ± 8.84; p = 0.2 for the left anterior descending artery). CaRi-Heart® analysis identified a significantly higher risk of future events among patients with a high modified Duke index (34.84 % ± 25.86 % versus 16.87 % ± 15.80 %; p

Aims: Chronic coronary syndrome is associated with several risk factors, such as dyslipidemia and hypertension. AIP has been demonstrated to be a biochemical risk factor for coronary artery disease (CAD). This study aimed to determine whether AIP is an effective parameter for estimating obstructive CAD. Methods and Results: A total of 345 patients (mean age 62,2±10,3; 63% male) who underwent coronary angiography were included in this study. Obstructive CAD is defined as having one or more vessels with a stenosis of≥50%. Depending on the presence of obstructive CAD, all patients were divided into two groups. The AIP was significantly higher in the obstructive coronary artery group (AIP; 0,49±0,26 vs. 0,58±0,27, p=0,002). In univariate analysis, AIP was significantly associated with obstructive coronary artery disease [OD:3,74 (CI95% 1,62-8,64), P=0,020]. The AIP was further adjusted for confounding risk factors in three multivariate analysis models. Therefore, all three models showed a significant association. According to ROC analysis, 0.49 is the cut-off value for AIP, and a value above 0.49 indicates 50% coronary artery stenosis Conclusions: AIP may be used in the assessment of cardiovascular risk in patients with stable angina pectoris, and it may also be used to estimate obstructive CAD.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak and accumulated rainfall-based damage are likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index (SWRI24−hr−S), derived from normalising the existing 24-hourly water resources index (WRI24−hr−S) in literature, to monitor flash flood risks on an hourly scale. The proposed SWRI24−hr−S is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V) and peak (Q). The comprehensive result analysis establishes the practical utility of SWRI24−hr−S in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji’s study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data is available, offering crucial information for flood risk monitoring, assessment, and the development of effective mitigation strategies.

Risk management for technological hazards mainly focuses on the consequences on human lives. Although technological risk analysis evaluates environmental vulnerability, it does not reflect the consequences on environmentally exposed elements, such as rivers, water springs, flora, and fauna. This paper's objective was to propose a conceptual framework and create a multidisciplinary evaluation model for environmental risk analysis in the oil and gas industry. Initially, the problem was approached from a global perspective to justify the necessity of a holistic environmental risk analysis methodology in the oil industry, using environmental risk factors as well as underlying factors, such as environmental fragility and lack of resilience. The holistic assessment was carried out based on probabilistic risk analysis methodologies to obtain a holistic environmental risk index, HERI. This methodology was applied to an oil and gas industry company in Colombia. This allowed greater disaggregation of the results to establish priorities for risk reduction actions and identify the company's weaknesses.

Annually, the oak forests of the Zagros Mountain chains, in western Iran and northeastern Iraq, face recurring challenges posed by forest fires, particularly in the Kurdo-Zagrosian forests situated in western Iran and northeastern Iraq. Assessing fire susceptibility relies significantly on vegetation condition. Integrating in situ data, Remote Sensing (RS) data, alongside the integration of Geographical Information Systems (GIS), presents a cost-effective and precise approach to capturing environmental conditions before, during, and after fire events, minimizing the need for extensive fieldwork. This study refines and applies the Zagros Grass Index (ZGI), a local vegetation index tailored to discern between grass-covered surfaces from tree canopies in Zagros forests, identifying the grass masses as the most flammable fuel type. Utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) product as input, from 2013 to 2022, the ZGI aims to mitigate the influence of tree canopies, isolating NDVI values solely attributable to grass cover. By incorporating phenological characteristics of forest trees and grass species, the ZGI outperforms NDVI in mapping grass-covered areas that are crucial for fire susceptibility assessment in the study region. Results demonstrate a strong overlap between ZGI-based maps and recorded fire occurrences, validating the efficacy of the index in fire susceptibility estimation.

Introduction: The coronary flow reserve (CFR) is a sign of early-stage coronary artery disease (CAD). Plasma atherogenic index (PAI) is related to atherosclerosis and cardiovascular mortality. Therefore, our aim was to determine CFR and PAI in patients with primary hyperparathyroidism (PHPT) and investigate whether PAI can be used in the detection of early-stage CAD. Material and Methods: The sample was comprised of 44 patients with PTHT and 33 healthy volunteers. We defined CFR as the ratio of the hyperemic diastolic peak velocity to the baseline diastolic peak velocity. PAI values were calculated with the formula of log 10 triglyceride (TRG) / high-density lipoprotein (HDL). Result: The comparison of the groups for PAI and CFR demonstrated that PAI levels were significantly higher while CFR levels were significantly lower in the PTHT patients (p<0.01, p=0.01, respectively). The correlation analysis revealed that CFR was negatively correlated with PAI and TRG (PAI- p<0.0001 r=-0.537).The multivariate logistic regression analysis showed that only a high PAI level (OR: 151.6, 95% confidence interval (CI): 4.1-5480, p=0.006) was an independent predictor of reduction in CFR in PHPT patients. Conclusion: Overall, we found an independent correlation between PAI and CFR values. Hence, PAI may be useful in identifying PHPT patients facing a high risk of adverse cardiovascular events and may also allow early diagnosis of subclinical atherosclerosis.

This purpose was to compare the ability of body shape index (ABSI) and body roundness index (BRI) with waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and body adiposity index (BAI) to predict metabolic risk. The cross-sectional study was conducted in 17,360 Chinese subjects (were aged 18-95 years old) who escaped cardiovascular disease (CVD) or diabetes. Biochemical and anthropometric variables were measured by trained staff. Receiver operating characteristic curve (ROC) and optimal cutoff values of obesity indices were recruited to compare the predictive ability for metabolic risk factors. The mean age of subjects was 53.7(13.1) years, 41.6 % were males. Within young group (<60 years), the areas under the curve (AUC) demonstrated that WC, BMI, WHR, WHtR and BRI were able to similarly predict high metabolic risk in males (0.74 vs. 0.74 vs. 0.73 vs. 0.73 vs. 0.73) and in females (0.73 vs. 0.73 vs. 0.71 vs. 0.73 vs. 0.73), while the approximate predictive ability were only acquired in males (0.73 vs. 0.73 vs. 0.70 vs. 0.73 vs. 0.73) within elder group (≥60 years). The optimal cut-off values of BRI for high metabolic risk were calculated in males (<60 y: 3.49 vs. ≥60 y: 3.46) and females (<60 y: 3.47 vs. ≥60 y: 3.60). Meanwhile, BRI displayed a strong prediction to elevated BP and elevated TG in males (AUC = 0.64; AUC = 0.70) and to elevated BP, elevated TG and elevated SUA in females (AUC = 0.67; AUC = 0.69; AUC =0.70). BRI was able to similarly predict high metabolic risk compared to WC, BMI, WHR, WHtR and BAI, while ABSI was not. Moreover, BRI revealed specific predictive ability for elevated BP, elevated TG and elevated SUA.

Abstract: The VSI represents a significant advancement in the assessment of gastrointestinal-specific anxiety among patients with Irritable Bowel Syndrome (IBS) and other Chronic Inflammatory Bowel Diseases (IBD). However, an Italian version of the instrument is not yet available for the reference population. This study utilized a national sample of 500 individuals, including healthy controls and patients with Ulcerative Colitis and Crohn's Disease, to test the validity and reliability of the Italian VSI. Using back-translation methodology to ensure translation fidelity, the research applied a questionnaire and the VSI through an online format to 500 participants. Data analysis revealed that the Italian VSI had excellent psychometric properties, demonstrating high internal consistency (Cronbach’s α = 0.95) and construct validity. The scale proved sensitive in detecting significant differences in visceral sensitivity among groups, highlighting its utility as a clinical and research assessment tool. Specifically, the Italian VSI exhibited a unidimensional factorial structure and maintained a strong correlation with other measures of anxiety and the severity of gastrointestinal symptoms, confirming its role in enhancing the understanding and management of IBS and IBD in Italy.

COPD is currently the fourth leading cause of death in the world. Globally, due to continued exposure to COPD risk factors and an aging population, the burden of COPD is expected to increase in the coming decades. The BODE (body mass index, airflow obstruction, dyspnea, and exercise capacity) index is a practical and multidimensional predictor for prognosis of COPD, and better than FEV1.We used the database of Kaohsiung Chang Gung Memorial Hospital medical center, Taiwan to analyze the correlation between BODE index, healthcare resource utilization, and Charlson comorbidity index (CCI). This retrospective study to collect COPD patients with complete BODE index data who had undergone a 6-minute walk examination in our hospital from January 2015 to December 2016. The medical cost and comorbidities database were analyzed from January 1, 2015, to August 31, 2017. Of 396 patients, 382 (96.5%) were male, with an average age of 71.3 ± 8.4 years. There was a significant association between the BODE index and the CCI of COPD patients (p < 0.001). Healthcare resource utilization was positively correlated with the BODE index during the 32 months of retrospective clinical outcomes: positively correlated with the number of hospitalizations (p<0.001), hospitalization days (p<0.001), hospitalization expenses (p=0.005), and total medical expenses (p=0.024), respectively. Our findings provide the crucial information for clinician to predict medical burden and comorbidities in patients with COPD by using BODE index.

Lifestyle has been associated with breast cancer risk through different pathways, including oxidative stress. Antioxidant enzymes are endogenous defense mechanisms against oxidative stress damage, and this response might be modulated by the genetic variation in these enzyme-codifying genes. This study aimed to analyze the synergistic effect of an antioxidant Healthy Lifestyle Index (HeLiX) composed of principal components of Western dietary pattern, alcohol consumption, smoking and physical activity, and genetic polymorphisms in the first-line antioxidant response family genes SOD, GPX, and CAT on breast cancer risk. We included 176 SNPs, and only CAT rs554576 remained significant after correction for multiple comparisons. Breast cancer odds were reduced at the highest (T3) and medium (T2) tertiles of the HeLiX. When stratified by HeLiX, we observed a reduced risk of breast cancer with at least one T-allele, and the effect increased in a dose-dependent manner. Compared to the reference category (HeLiX T1 and AA genotype), women at the HeLiX T3 with AT and TT genotypes in postmenopausal women showed an OR = 0.15 (95% CI 0.07–0.32). For HeLiX T2 and AT genotype OR = 0.26 (95% CI 0.13–0.54); for TT genotype OR = 0.24 (95% CI 0.12–0.45). For premenopausal women, at the HeLiX T3 and AT genotype OR = 0.29 (95% CI 0.13–0.62); for the TT genotype OR = 0.21 (95% CI 0.08–0.51). We also observed an inverse association for HeLiX T2 and TT genotype (OR 0.39 95% CI 0.17–0.87). Our study shows a significant synergistic gene-environment interaction on an additive scale, contributing to understanding pathways involved in breast cancer etiology and prevention.

One of the major challenges in the post-genomic era is elucidating the genetic basis of human diseases. In recent years, studies have shown that polygenic risk scores (PRS), based on aggregated information from millions of variants across the human genome, can estimate individual risk for common diseases. In practice, the current medical practice still predominantly relies on physiological and clinical indicators to assess personal disease risk. For example, caregivers mark individuals with high body mass index (BMI) as having an increased risk to develop type 2 diabetes (T2D). An important question is whether combining PRS with clinical metrics can increase the power of disease prediction in particular from early life. In this work we examined this question, focusing on T2D. We show that an integrated approach combining adult BMI and PRS achieves considerably better prediction than each of the measures on unrelated Caucasians in the UK Biobank (UKB, n=290,584). Likewise, integrating PRS with self-reports on birth weight (n=172,239) and comparative body size at age ten (n=287,203) also substantially enhance prediction as compared to each of its components. While the integration of PRS with BMI achieved better results as compared to the other measurements, the latter are early-life measurements that can be integrated already at childhood, to allow preemptive intervention for those at high risk to develop T2D. Our integrated approach can be easily generalized to other diseases, with the relevant early-life measurements.

The association between normal-range triglycerides and diabetes mortality remains unclear. This cohort study aimed to elucidate this relationship by examining 19,010 US adult participants with fasting serum triglycerides below 150 mg/dL. Cox proportional hazards models were employed to estimate mortality hazard ratios (HRs) and 95% confidence intervals (CIs). Participants were followed up for a mean of 15.3 years, during which 342 diabetes deaths were recorded. A 1-natural-log-unit increase in triglycerides was associated with a 57% higher risk of diabetes mortality (adjusted HR, 1.57; 95% CI, 1.04–2.38). Comparable results were obtained when triglycerides were analyzed in quartiles. Receiver operating characteristic curve analysis identified an optimal triglyceride cutoff of 94.5 mg/dL for diabetes mortality; individuals with triglyceride levels above this threshold faced a greater risk of diabetes mortality (adjusted HR, 1.43; 95% CI, 1.12–1.83). Further investigation revealed a positive association between normal triglyceride levels and all-cause mortality, though no association was observed between normal triglycerides and mortality from hypertension or cardiovascular disease. In conclusion, elevated triglycerides within the normal range were associated with an increased risk of diabetes mortality. Individuals with triglyceride levels of 95 mg/dL or higher may require vigilant monitoring for diabetes and its associated complications.

Objective: To analyse the association between maternal risk factors such as age, body mass index (BMI) and cigarette smoking, with perinatal outcomes. Materials and Methods: This a retrospective analysis from prospectively collected data performed at Hospital Universitario de Torrejón (Madrid, Spain), between September 2017 and December 2019. All pregnant women with singleton pregnancies and non-malformed live fetuses attending their routine ultrasound examination at 11+0 to 13+6 weeks' gestation were invited to participate. Association between preeclampsia, preterm birth, gestational diabetes mellitus (GDM), small for gestational age (SGA) or fetal growth restricted (FGR) neonates and type of delivery according to maternal age, BMI, and cigarrete smoking was studied. Logistic mixed models were used to analyze the data. Results: 1921 patients were included in the analysis. Women of 40 years old had a significantly higher risk of having GDM (Odds Ratio (OR) 1.61, 95% Confidence Interval (CI) 1.08 to 2.36), and SGA neonates (OR 1.54, 95% CI 1.00 to 2.37). Women with a BMI &lt;18 had an increased rate of birth SGA and FGR neonates (OR 3.28, 95% CI 1.51 to 7.05, and OR 3.73, 95% CI 1.54 to 8.37, respectively), whereas women with a BMI ≥35 had a higher risk of GDM (OR 3.10, 95% CI 1.95 to 4.89). Smoking increased the risk of having SGA and FGR neonates (OR 1.83, 95% CI 1.36 to 2.46, and OR 1.91, 95% CI 1.29 to 2.78). Conclusions: Advanced maternal age, low or high BMI, and smoking status are significant risk factors for pregnancy complications. Both clinicians and society should concentrate their efforts on addressing these factors to enhance reproductive health.

In the paper the verification of forecasts of precipitation conditions measured by the standardized precipitation index SPI is presented. For the verification of categorical forecasts a contingency table was used. Standard verification measures were used for the SPI value forecast. The 30 day SPI moved every 10 days by 10 days was calculated in 2013-2015 from April to September on the basis of precipitation data from 35 meteorological stations in Poland. Predictions of the 30 day SPI were created in which precipitation was forecasted in the next 10 days (the SPI 10-day forecast) and 20 days (the SPI 20-day forecast). Both for the 10 and 20 days, the forecasts were skewed towards drier categories at the expense of wet categories. There was a good agreement between observed and 10-day forecast categories of precipitation. Less agreement is obtained for 20-day forecasts – these forecasts evidently “over-dry” the assessment of precipitation anomalies. The 10-day SPI value forecast accuracy is acceptable, whereas for the 20-day forecast is unsatisfactory. Both for the SPI categorical and the SPI value forecast, the 10-day SPI forecast is reliable and the 20-day forecast should be accepted with reservation and used with caution.

Recent analyses of cosmic microwave background surveys have revealed hints that there may be a non-trivial running of the running of the spectral index. If future experiments were to confirm these hints, it would prove a powerful discriminator of inflationary models, ruling out simple single field models. We discuss how isocurvature perturbations in multi-field models can be invoked to generate large runnings in a non-standard hierarchy, and find that a minimal model capable of practically realising this would be a two-field model with a non-canonical kinetic structure. We also consider alternative scenarios such as variable speed of light models and canonical quantum gravity effects and their implications for runnings of the spectral index.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

Droughts are a common occurrence in various climates and are primarily caused by a prolonged decrease in rainfall. Several factors contribute to droughts, including temperature, wind speed, relative humidity, rainfall timing, amount, and intensity during the growing season. The objective of this study is to establish a new index, named soil moisture and evapotranspiration revealed drought index (SERDI), for displaying dry and wet conditions based on combining both soil moisture and evapotranspiration (Penman-Monteith) to improve drought early warning and its severity globally. For validation of the SERDI with other indices such as LST, VHI, NDVI, and NDWI, different ways used such as R-square, RMSE, MAPE, and P-value to estimate the accuracy, variability of data, the forecast conditions, and how the significance of data. The results showed that the low RMSE and high r² were found between SERDI with LST and VHI. In contrast, the low R- square and high RMSE were between SERDI with NDVI and NDWI in most of the semi-arid areas. Furthermore, most of the semi-arid areas from Iran, Iraq, Syria, Jordan, and Israel experienced moderate and severe dry conditions, except some parts of these regions had normal conditions in Iran and Syria. The SERDI analysis revealed a strong correlation between (LST) and a moderate correlation with (VHI) across all study areas. However, the relationship between other indices, like (NDWI) and (NDVI), varied depending on the regions. To conclude, SERDI can be used globally for detecting drought based on soil moisture and evapotranspiration.

This paper initiates the study of the mathematical aspects of the ad-hoc Lanzhou index. If G is a graph with the vertex set {x1,⋯,xn}, then the ad-hoc Lanzhou index of G is defined by Lz¯(G)=∑i=1ndi(n−1−di)2, where di represents the degree of the vertex xi. Several identities for the ad-hoc Lanzhou index, involving some existing topological indices are established. The problems of finding graphs with the extremum values of the ad-hoc Lanzhou index from the following sets of graphs are also attacked: (i) set of all connected ξ-cyclic graphs of a fixed order, (ii) set of all connected molecular ξ-cyclic graphs of a fixed order, (iii) set of all graphs of a fixed order, (iv) set of all connected molecular graphs of a fixed order.

Aim: To investigate inflammation indices and erythropoietin (EPO) levels for their potential role in distinguishing polycythemia vera (PV) from secondary polycythemia (SP), and to compare different parameter combinations in terms of diagnostic accuracy. Methods: This retrospective cohort was created from patients assessed for polycythemia from January 2020 to December 2023. PV diagnosis was made according to the 2016 WHO criteria (n=145). Those who did not fulfill the criteria were defined as having SP (n=84). Results: NLR, PLR and SII were significantly higher in the PV group (p

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Abstract: Doppler renal resistive index (RRI) has been used for several decades as a potential indi-cator for renal disease and progression. In recent years, RRI has emerged as a useful prognostic indicator for a range of co-morbidities in patients who are acutely unwell and as a potential marker for sub-clinical acute kidney injury (AKI) and post procedural AKI risk. Despite this, the clinical and theoretical determinants of RRI are poorly understood and remain contentious. Method: A narrative review of studies exploring the theoretical, experimental, and clinical evidence for factors affecting RRI. No date restrictions were set. Findings: Both experimental and clinical data confirm that RRI is markedly affected by a range of systemic and renal determinants and is influenced closely by the underlying risk factors and sys-temic vascular changes that lead to progressive renal damage. Discussion: This paper provides an overview of the key haemodynamic determinants of renal re-sistive index and aims to clarify their relative importance. With reference to a simplified theoretical model, evidence from experimental and clinical studies is reviewed. Pathophysiological factors and patient characteristics that influence RRI are explored to provide a better understanding of why RRI values change in the presence of common or complex pathologies. Conclusion: By gaining a better understanding of the complex systemic and renal factors that influ-ence RRI, ultrasound users will be better prepared to understand and interpret changes in RRI across a range of patient presentations.

This research aimed to investigate the relationship between climate policy uncertainty (CPU), clean energy (ENERGY), carbon emission allowance prices (CARBON), and Bitcoin returns (BTC) for the period from August 2012 to August 2022. The empirical analysis strategies utilized in this study included the Fourier Bootstrap ARDL long-term coefficient estimator, Fourier Granger Causality, and Fourier Toda Yamamoto Causality methods. Following the confirmation of cointegration among the variables, we observed a positive relationship between BTC and CARBON, a positive relationship between BTC and CPU, and a negative relationship between BTC and ENERGY. In terms of causal associations, we identified one-way causality running from CARBON to BTC, BTC to CPU, and BTC to the ENERGY variable. The study underscores the potential benefits and revenue opportunities for investors seeking diversified investment strategies in light of climate change concerns. Furthermore, it suggests actionable strategies for policymakers, such as implementing carbon taxes and educational campaigns, to foster a transition towards clean energy sources within the cryptocurrency mining sector and thereby mitigate environmental impacts.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

The following article analyzes the determinants of the innovation index in Europe. The data refer to the European Innovation Scoreboard-EIS of the European Commission for the period between 2010 and 2019 for 36 countries. The data are analyzed using the following econometric techniques: Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel Data, Pooled OLS, WLS. The results show that the Innovation Index is negatively connected to some variables, among which the most significant are "GDP per capita", "R&D expenditure public sector", "Venture capital", "Tertiary education", and positively connected to some variables among which the most relevant are: "Government procurement of advanced technology products", "Average annual population growth", "Finance and support", "Human resources", "Marketing or organisational innovators", "Linkages". A clustering was then carried out using the unsupervised k-Means algorithm optimized with the Silhouette coefficient which shows the presence of 2 clusters per value of the Innovation Index. Eight machine learning algorithms has been used for prediction with real data. The Tree Ensemble Regression algorithm has been chosen as best performer. A further prediction has been made with the augmented data. The result shows that the best performing algorithm is Linear Regression with an innovation index value predicted to grow by approximately 3.38%.

This article analyzes the determinants of the "Broadband Price Index" in Europe. The data used refer to 28 European countries between 2016 and 2021. The database used is the Digital, Economy and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index, and "Connectivity" while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills ", "Above Basic Digital Skills "," At Least Basic Software Skills ". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN with an estimated value equal to an amount of 9.21%.

A new model for risk assessment of urban rainstorm disasters, based on information diffusion method and variable fuzzy sets (IDM-VFS) was proposed. In addition, an integrated index system of urban rainstorm risk was established. In the proposed model, IDM was employed to calculate the classification standards of urban rainstorm risk levels, then the VFS was adopted to assess the dangerousness, sensitivity, vulnerability and comprehensive risk of urban rainstorm disasters. In the present study, the urban rainstorm risk of Jiangsu province was evaluated with the proposed model. The results show that Wuxi, Changzhou, Nanjing and Suzhou have higher dangerousness, due to sustained rainfall and strong rainfall intensity in short duration; Wuxi, Changzhou and Nanjing have higher sensitivity because of lower disaster resistance ability; and Wuxi and Suzhou have higher vulnerability because these cities have higher potential losses in face of urban rainstorm disasters. The comprehensive risk zoning map of urban rainstorm shows apparent regional characteristics: the northwestern cities have lower risk than the southern cities. Moreover, most cities of the Jiangsu province are of the moderate urban rainstorm risk level. The results are consistent with the actual situation of Jiangsu province, and the study can provide some decision-making references for the urban rainstorm management.

Floods are among the most serious natural disasters worldwide; they cause enormous crop losses every year and threaten world food security. There are many studies focused on flood impact assessments for administrative districts but fewer on postdisaster impact assessments for specific crops. Therefore, this study used remote sensing data, including the normalized difference vegetation index (NDVI), elevation data, slope data, and rainfall data, combined with crop growing season data to construct a crop flood damage assessment index (CFAI). First, an analytic hierarchy process (AHP) was used to assign weights to the impact factors; then, the weighted composite score method was used to calculate the CFAI; and finally, the impact was classified as slight, moderate, or severe based on the magnitude of the CFAI . This method was used for the Missouri River floods of 2019 in the U.S. Due to the lack of measured data, the disaster vegetation damage index (DVDI) was used to validate the results. The combined approach achieved a high degree of consistency in spatial distribution. The CFAI can respond well to the degree of crop impact after flooding, providing new ideas and reference standards for agriculture-related departments.

In geotechnical engineering applications, it is very important to obtain the undrained shear strength of remolded soils accurately and reliably. This study aims to obtain a trustworthy solution to determine the undrained shear strength of remolded clay mixtures using Atterberg limit test results in various states of consistency. An experimental study was carried out involving a wide range of clay mixtures of varying plasticity and geological origin. In the analyses, the variation of the remolded undrained shear strength depending on the cone penetration depth, water content, flow index, liquidity index and log liquidity index were investigated. In the study, the highest undrained shear strength of 100% Na-montmorillonite (NaM) was obtained at 171.89 kPa at 56.60% water content, while the lowest undrained shear strength was obtained for 100% Sepiolite (S), 9.28 kPa at 31.65% water content. The results of this study revealed that the shear strength is significantly affected by soil conditions, rather than dominant clay mineral. Besides, it was observed that the undrained shear strength at the plastic limit was approximately 30-35 times greater than that at liquid limit. The equations of liquid limit-flow index and plasticity index- flow index were proposed. It was concluded that the interdependence between undrained shear strength, liquidity index, log liquidity index, and flow index is not unique due to the different physical and chemical properties of clays.

Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

Introduction: The viral respiratory disorder known as severe acute respiratory syndrome (SARS) is caused by the SARS-associated coronavirus. End of May 2021, there have been over 170 million reported cases and more than 3.53 million deaths worldwide. In the field of cardiovascular performance, the shock index (SI) is a simple and widely used formula that measures the physiological response prior to systemic hypotension. It is obtained by dividing the heart rate by the systolic blood pressure. Another parameter, the modified shock index (MSI), is defined as the ratio of heart rate to mean arterial pressure (MAP). Methods: In this retrospective study, we examined the data of COVID-19 patients who were admitted to the ICU between June 1st, 2020, and January 31st, 2021. The patient details were collected from the Medical Records Department (MRD) in a tertiary care center. A case-recorded proforma was used to record the patient information, which was then analyzed using SPSS software. Results: The mean age of the patients was 67 years, consisting of 64 males (68.9%) and 29 females (31.1%). The standard deviation was calculated as 13.557. Among the patients, the minimum age recorded was 28, while the maximum age was 97. Patients with known CAD (Coronary Artery Disease) had a higher mortality rate among comorbidities. The p-value for Shock Index and Mortality Status was 0.205 (with an alpha value greater than 0.05), indicating no significant association. However, the modified shock index (MSI) showed a significant association with mortality status. The Pearson chi-square value for MSI and Mortality Status was 4.19, with a p-value of 0.041 (with an alpha value less than 0.05). These results suggest that there is a higher risk of mortality for patients with a Modified Shock Index of less than 0.7 or greater than 1.3. The MSI Odds ratio was found to be 4.500, indicating that such patients have a 4.5 times higher risk of mortality compared to others. Conclusion: In conclusion, our study found that there is no significant association between the Shock Index (SI) and mortality, as the p-value was greater than 0.05. However, the Modified Shock Index (MSI) showed a significant association with mortality status, with a p-value less than 0.05. This suggests that patients with a Modified Shock Index less than 0.7 or greater than 1.3 are at a higher risk of mortality. It is important to consider these findings when assessing the prognosis and potential interventions for COVID-19 patients.

Insurance serves as a mechanism to effectively manage and transfer revenue-related risks. We conducted a study to explore the potential financial advantages of index insurance, which protects agricultural producers, specifically sugarcane, against excessive rainfall. Creation of the index involved utilizing generalized additive regression models, allowing for consideration of non-linear effects and quantile generalized additive regression to evaluate relationships with lower quantiles, such as low yield events. To quantify the financial benefits for farmers, should they opt for excessive rainfall index insurance, we employed efficiency analysis based on metrics such as Conditional Tail Expectation, Certainty Equivalence of Revenue, and Mean Root Square Loss. The results of the regression model demonstrate its accuracy in predicting sugar cane yields, with a split testing R2 of 0.691. Additionally, our study suggests that this type of insurance could also apply to sugarcane farmers and other crop producers in regions where extreme rainfall threatens the financial sustainability of agricultural production.

The rapid development of the regional economy in China has led to the rise of local ecological risks. It is very important to provide enjoyable ecosystem services to residents while reducing ecological risks. In order to understand spatial relationships between ecosystem services and ecological risks, we took Chongqing as an example in this study to assess the spatial relationship between ecosystem services and ecological risks at the county scale based on the ES-DPSIR system. The main findings include: (1) significant variation in the spatial distribution of the comprehensive ecosystem service index, where the lowest ecosystem service index (0.013) was found in the main urban area of Chongqing and the scores gradually increased outward from this center, reaching 0.689 in the outermost areas, (2) the increase of the comprehensive ecological risk index from east to west, ranging from -0.134 to 0.333, (3) the spatial relationship between ecosystem services and ecological risks was prominent, with 52.63% of the districts and counties being imbalanced or mild imbalanced, and (4) the significant differences between development trends of ecosystem services-ecological risks, including 60.53% being imbalanced districts and 30.47% mildly balanced. Overall, it was necessary to improve the relationship between ecosystem services and ecological risks in Chongqing by reducing ecological risks., and these research results could provide effective approaches and technical support for improving regional ecological security and enhancing ecosystem service capabilities.

Surface water distribution extracted from remote sensing data has been used in water resource assessment, coastal management, and environmental change studies. Traditional manual methods for extracting water bodies cannot satisfy the requirements for mass processing of remote sensing data; therefore, accurate automated extraction of such water bodies has remained a challenge. The histogram bimodal method (HBM) is a frequently used objective tool for threshold selection in image segmentation. The threshold is determined by seeking twin peaks, and the valley values between them; however, automatically calculating the threshold is difficult because complex surfaces and image noise which lead to not perfect twin peaks (single or multiple peaks). We developed an operational automated water extraction method, the modified histogram bimodal method (MHBM). The MHBM defines the threshold range of water extraction through mass static data; therefore, it does not require the identification of twin histogram peaks. It then seeks the minimum values in the threshold range to achieve automated threshold. We calibrated the MHBM for many lakes in China using Landsat 8 Operational Land Imager (OLI) images, for which the relative error (RE) and squared correlation coefficient (R2) for threshold accuracy were found to be 2.1% and 0.96, respectively. The RE and root-mean-square error (RMSE) for the area accuracy of MHBM were 0.59% and 7.4 km2. The results show that the MHBM could easily be applied to mass time-series remote sensing data to calculate water thresholds within water index images and successfully extract the spatial distribution of large water bodies automatically.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

The Randić index of a graph G is the sum of (dG(u)dG(v))−1/2 over all edges uv of G, where dG(u) denotes the degree of vertex u in G. In this paper, we investigate a few graph transformations that decrease Randić index of graph. By applying those transformations, we determine the minimum Randić index on tricyclic graphs, and characterize the corresponding extremal graphs.

The aim of this report is to evaluate the segmental rib index (RI) from T1-T12 spinal level in mild and moderate idiopathic scoliosis (IS) curves of thoracic, thoracolumbar and lumbar type by gender. The relationship of segmental RI to the frontal plane radiological deformity presented as the Cobb angle and to the posterior truncal surface deformity presented as the scoliometric readings of Angle of Trunk Rotation (ATR) in these patients is also assessed. Any statistical significant rela-tionship of these parameters would be very important for biomechanical relations of the rib cage (RC) deformity presented as the rib hump deformity (RHD) and the deformity in the spine and it would thus provide valuable information about scoliogeny. The segmental rib index (RI) is presented in 83 boys and girls with mild and moderate IS. The measurements include the scoliometric readings for truncal asymmetry (TA), the Cobb angle assessment and the segmental RI from T1-T12. The statistical package SPSS 23 was used for statistical analysis. The TA is documented and the Cobb angle is presented by gender and curve type. The segmental RI of thoracic, thoracolumbar and lumbar curves are presented for the first time. The correlations of the segmental RI to surface deformity presented as the rib hump deformity (RHD) in all IS patients and particularly in thoracic curves, to Cobb angle by gender and age and the comparison of the segmental RI index of asymmetric but not scoliotic children to the scoliotic peers by curve (in thoracic, thoracolumbar, lumbar curves) in boys and girls are presented. The findings emphasize the significant protagonistic role of the thoracic asymmetry in relation to the spinal deformity mainly in girls for the thoracic and in boys for the thoracolumbar curves. The cut-off point of age of the examined scoliotics is 14 years, that is when the RI shows stronger correlation with the spinal deformity, namely when the thoracic deformity is decisively effective to the developing thoracic spinal deformity, in terms of Cobb angle. In summary, the results of this study provide aetiological implications for IS, as far as the role of thorax is con-cerned.

The Metropolitan Economic Freedom Index (MEFI) ranks cities based on their support of free market enterprise. In its current state, MEFI purports to measure three constructs (government spending, taxation, and labor market freedom) with three equally weighted variables for each one, assuming perfect substitutability of variables. This study investigates the statistical consistency of MEFI through Confirmatory Factor Analysis. Multiple models investigate current variable selection by providing a potentially better indicator of labor market freedom, aggregation assumptions by removing the requirements for fixed and equal weights, and statistical consistency by evaluating the fit between the data and models. Results indicate that the current MEFI model is not statistically consistent with the data, that weighting of variables should not be equal, that variable selection should be investigated, and that constructs should be re-imagined. The models investigated provide an initial starting point for redefining MEFI.

The fetal splenic artery pulsatility index (PI) is a parameter that reflects fetal well-being and has been used as a predictor of adverse pregnancy outcomes. The aim of this study was to investigate the predictive value of splenic artery PI in GDM class A1 cases for NICU admission. In this prospective case controlled study, only sixty single pregnancy cases diagnosed with gestational diabetes mellitus class A1 were evaluated. Fetal splenic artery Doppler parameters Peak systolic velocity (PSV), Pulsatility index (PI), Resistivity index (RI) and End diastolic velocity (EDV) were measured in all cases. The rate of re-quirement of need of neanoatal intensive care unit was noted. In cases with need fetal intensive care, fetal splenic PI index was found to be statistically significantly lower than in healthy cases without it (0.94 ± 0.29 vs. 1.70 ± 0.53, respectively, p

Background: Modulator therapies improve weight and body mass index (BMI) in cystic fibrosis (CF) patients. We aimed to compare the nutritional risk index (NRI) in adult CF patients receiving modulator (MT) or only non-modulator (conventional) therapies (non-MT). Methods: A single-center prospective cohort study was conducted between June-December 2023. The NRI based on weight gain and albumin was calculated at beginning and end of a 12 weeks period in both groups. This design was pragmatic, since based on individual patient access to MT for 12 weeks. Results: 107 patients were included [mean (SD) age: 23.85 (4.98) years, 54.7% male, 46.7% MT]. In the MT group, mean (SD) weight (kg) and albumin (g/dL) increased significantly [changes: +3.09 (2.74) and +0.17 (0.37); p

The COVID-19 pandemic over the past years has shown a great need for rapid, low-cost and on-site detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, an aptamer-based colloidal gold nanoparticle lateral flow test strip was well developed to realize the visual detection of wild type SARS-CoV-2 spike protein (SP) and multiple variants. Under the optimal reaction conditions, a low detection limit of SARS-CoV-2 S protein of 0.68 nM was acquired, and the actual detection recovery was 83.3% to 108.8% for real world samples. This suggests a potential tool for the prompt detection of SARS-CoV-2 with good sensitivity and accuracy, and a new method for the development of alternative antibody test strips for the detection of other viral targets.

Many metrics exist for the evaluation of binary classifiers, all with their particular advantages and shortcomings. Recently an “Efficiency Index” for the evaluation of classifiers has been proposed, based on the consistency, or matching, and contradiction, or mismatching, of outcomes. This metric and its confidence intervals are easy to calculate from base data in a 2x2 contingency table, and values can be qualitatively and semi-quantitatively categorised. For medical tests, in which context the Efficiency Index was originally proposed, it facilitates communication of risk (of correct diagnosis versus misdiagnosis) to both clinicians and patients. Variants of the efficiency index (balanced, unbiased) which take into account disease prevalence and test cut-offs have also been described. The objectives of the current paper were firstly to extend the EI construct to other formulations (balanced level, quality) and secondly to explore the utility of EI and all four of its variants when applied to the dataset of a large prospective test accuracy study of a cognitive screening instrument. This showed that the balanced level, quality, and unbiased formulations of EI are more stringent measures.

Let G[F,Vk, Huv] be the graph with k pockets, where F is a simple graph of order n ≥ 1,Vk= {v1,v2,··· ,vk} is a subset of the vertex set of F and Hvis a simple graph of order m ≥ 2,v is a specified vertex of Hv. Also let G[F,Ek, Huv] be the graph with k edge pockets, where F is a simple graph of order n ≥ 2, Ek= {e1,e2,···ek} is a subset of the edge set of F and Huvis a simple graph of order m ≥ 3, uv is a specified edge of Huvsuch that Huv− u is isomorphic to Huv− v. In this paper, we derive closed-form formulas for resistance distance and Kirchhoff index of G[F,Vk, Hv] and G[F,Ek, Huv] in terms of the resistance distance and Kirchhoff index F, Hv and F, Huv, respectively.

We investigate the effect of geopolitical risk on the returns of the Information Technology, Communication Services, and Consumer Staples sector firms within the S&P 500 index. We use the event study methodology and perform more than 17,000 regressions to provide empirical evidence at the sector level that geopolitical risk leads to different responses across these 3 sectors. The response of the Information Technology sector is negative for all event windows under study, except the one spanning 10 days prior to the geopolitical event and 10 days after. The Communication Services sector has positive returns as a result of geopolitical events for all event windows, except the one from the geopolitical event date and 5 days after. The Consumer Staples sector shows a negative impact on geopolitical risk for all event windows except the one from the geopolitical event date and 5 days after, demonstrating a negative correlation to the Communication Services sector.

Fire risk can be defined as the probability that a fire will spread. Reliable monitoring of fire risk is essential for effective landscape management. Compilation of fire risk records enable identification of seasonal and inter-annual patterns and provide a baseline to evaluate the trajectories in response to climate change. Typically, fire risk is estimated from meteorological data. In regions with sparse meteorological station coverage environmental proxies provide important additional data stream for estimating past and current fire risk. Here we use a 60-year record of daily flows from two rivers (Franklin and Davey) in the remote Tasmanian Wilderness World Heritage Area (TWWHA) to characterize seasonal patterns in fire risk in temperate Eucalyptus and rainforests. We show that river flows are strongly related to landscape soil moisture estimates derived from down-scaled re-analysis of meteorological data available since 1990. To identify river flow thresholds where forests are likely to burn, we relate river flows to known forest fires that have occurred in the previously defined ecohydrological domains that surround the Franklin and Davey catchments. Our analysis shows that the fire season in the TWWHA is centered on February (70% of all years below the median threshold), with shoulders on December-January and March. Since 1954 forest fire can occur in at least one month for all but four summers in the ecohydrological domain that includes the Franklin catchment, and since 1964 fire fires could occur in at least one month in every summer in the ecohydrological domain that includes the Davey catchment. Our analysis shows that mangers can use river flows as a simple index that provide a landscape-scale forest fire risk in the TWWHA.

Objective Image Quality Assessment (IQA) measures are playing an increasingly important role in the evaluation of digital image quality. New IQA indices are expected to be strongly correlated with subjective observer evaluations expressed by MOS/DMOS scores. One such recently proposed index is the SuperPixel-based SIMilarity (SPSIM) index, which uses superpixel patches instead of the rectangular pixel grid.The authors in this paper have been proposed three modifications of SPSIM index. For this purpose, the color space used by SPSIM was changed and the way SPSIM determines similarity maps was modified using methods derived from the algorithm for computing the MDSI index. The third modification was a combination of the first two. These three new quality indices were used in the assessment process. The experimental results obtained on many color images from five image databases demonstrated the advantages of the proposed SPSIM modifications.

The Body Mass Index (BMI) formula has been developed by Belgian mathematician Adolphe Quetelet and published in 1840 [1] as a law of nature and society, based on statistics about the weight and height of the population of that time, the first part of the 19^th century. He called it “social physics”. From then, for nearly two centuries, the BMI had been the most important formula describing the normal relations and ratio of weight to the square of the height for humans. The problem arises if the BMI formula, developed in the first part of the 19^th century is still good today when the type of work people perform is very different? In modern times, most people are less muscular than at the time when the BMI was developed because they do not work physically as heavy as at that time. In many cases, the Body Mass index can predict mortality, morbidity and illness but not always, for example cases such as (a) the obesity paradox for some cardiovascular problems and (b) the U shape mortality paradox as well as (c) false positive obesity diagnostic in regard to people who are strong and muscular, have low body fat percentage but are classified as obese by the BMI and (d) cases where BMI is normal but people have an “obese metabolism” (e) BMI normal but high fat percentage. The objective is to develop a formula good for all body types, a formula that makes the difference between fat and non-fat body weight such as muscle and body frame and quantifies the effect of strength and fitness, which BMI does not. Another objective is to develop a formula to predict the health risks and fitness status of people, better than BMI. The first generalizations of BMI using anthropometric metrics could be found in [2], where I discuss and analyze many formulae, developed, tested, and simulated by me, using similar new methods, accounting for body shape, physical shape and body function, making the difference between muscle mass and fat, fat and non fat body weight. Nearly all formulae and methods developed and proposed in this new model are new, never published before. Many experiments published before, in highly cited papers show that grip strength and muscle strength is a predictor of health, mortality, morbidity, endocrine and metabolic disease outside the BMI and anthropometric measures. The purpose of my formula is to explain the outcome of those experiments and create a formula which predicts these experiments [21-41].

The classic Body Mass Index, (BMI), developed in the 19^th century by the Belgian mathematician Adolphe Quetelet [1] is an important indicator of the risk of death, of obesity, of negative health consequences, body fat percentage and of the shape of the body. While he BMI is assumed to indicate obesity in sedentary people and in people who do not practice sports, it is undisputed and a consensus among researchers [2][3][4][5][9][25] that Body Mass Index (BMI) is not a good indicator for obesity in people who developed their body through heavy physical work or sport but also in other segments of population such as those who appear to have a normal weight but in fact have a high body fat percentage and obese methabolism. The BMI also does not include all the variables essential for a health predictor. The BMI is not always a good predictor of metabolic disease, people who appear of healthy weight according to BMI have in some cases an obese metabolic syndrome. The BMI was developed as a law of natural sciences and “social physics” [1], as it was called then, before the middle of the 19^th century, and it had been used from the 70s for medical purposes, to detect obesity and the risk of mortality [6][7]. The BMI has a huge importance for modern society, affected by an obesity epidemic [8]. BMI has applications in medicine, sport medicine, sport, fitness, bodybuilding, insurance, nutrition, pharmacology. The main limitation of the BMI is that it does not account for body composition including non fat body mass such as muscles, joints, body frame and makes no difference between fat and non fat components of the body weight. The body composition and the proportion of fat and muscles make a difference in health outcomes [12][13][14][25][26][27][35][36][37] [38][39][40][41][42][43][44]…[100]. Body composition makes a difference also in the level of sport performance for athletes of every level. In nearly two centuries since the Body Mass Index was developed, no formula had been successfully developed to account for body composition and make the difference between muscle and fat in a consistent way. This can be considered a longstanding open problem of major importance for society. The objective of this analysis is to develop new formulae taking into account the health implication of body composition measured through indirect, simple indicators and making the difference between muscles and fat, healthy and non healthy metabolism. The formulae developed in this article are the only formula to successfully generalize BMI and make this difference. I develop a direct generalization of BMI, in the mathematical and physiological sense to account for fat and fat free mass and muscles, small and large body frames. It is the first such generalization because the classic BMI can be determined as a particular case of my formulae in the strict mathematical and practical physiologic sense. No other formula generalized the BMI to make the difference between fat and a large frame and muscles has ever been published in nearly two centuries since the BMI formula had been developed. The formulae I developed explain and generalize the conclusions of a large number of highly cited empirical experiments cited in the reference section. [35][36][37][38][38][39] [40][42][43][44]..[100] Most of the experimental proof I bring in support of my formulae and bodyweight quantification theory comes from many highly cited experimental research publications in medicine, sports medicine, sport science and physiology. My formulae explain also performance in decades of competitive sports and athletics

Seaweeds are regarded as one of the valuable coastal resources because of their usage in human food, cosmetics, and other industrial items. They also play a significant role in providing nourishment, shelter, and breeding grounds for fish and many other sea species. This study introduces a newly developed seaweed enhancing index (SEI) using spectral bands of near-infrared (NIR) and shortwave infrared (SWIR) of Landsat 8 satellite data. The seaweed patches in the coastal waters of Karachi, Pakistan were mapped using SEI, and its performance was compared with other commonly used indices - Normalized Difference Vegetation Index (NDVI) and Floating Algae Index (FAI). The accuracy of the mapping results obtained from SEI, NDVI, and FAI was checked with field verified seaweed locations. The purpose of the field surveys was to validate the results of this study and to evaluate the performance of SEI with NDVI and FAI. The performance of SEI was found better than NDVI and FAI in enhancing submerged patches of the seaweed pixels what other indices failed to do.

Sombor index was recently defined in 2021 as a new vertex degree based topological index by Gutman and has received great attention of mathematicians and chemists. In this work, we determine how much the Sombor index is effected when we delete a vertex or an edge from a graph. Using the formulae obtained here successively, one can calculate the Sombor indices of large graphs by means of Sombor indices of smaller graphs which are obtained by deletion of vertices or edges.

Global change is affecting vegetation cover and processes through multiple pathways. Long time series of surface land surface properties derived from satellite remote sensing offer a unique abilities to observe these changes, particularly in areas with complex topography and limited research infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is limited by moisture availability (dominated by a summer monsoon) at lower elevations and by temperature at high elevations. We analyze normalized difference vegetation index (NDVI) from 1981 to 2015 semimonthly, at 8 km spatial resolution. We use a random forest (RF) of regression trees to generate a statistical model of NDVI as a function of elevation, land use, CO2 level, temperature, and precipitation. We find that NDVI has increased over the studied period, particularly at low and middle elevations and during fall (post-monsoon). We infer from the fitted RF model that the NDVI linear trend is primarily due to CO2 level (or another environmental parameter that is changing quasi-linearly), and not primarily to temperature or precipitation trends. On the other hand, interannual fluctuation in NDVI is more correlated with temperature and precipitation. RF accurately fits the available data and shows promise for estimating trends and testing hypotheses about their causes.

Abstract: Global ecological concern regarding the transfer of fouling organisms to ship hulls is increasing. This study investigated the species composition, dominant species, distribution patterns, community structure, and life-cycle differences of hull-fouling macroinvertebrates on five research vessels (R/Vs: Isabu, Onnuri, Eardo, Jangmok 1, and Jangmok 2) operated by the Korea Institute of Ocean Science and Technology (KIOST). Hull-fouling macroinvertebrates were collected three to five times on quadrats from the upper and middle sectors of the hull sides, bottom, and niche areas (the propellers and shafts and the thrusters). A total of 47 macroinvertebrate species were identified, represented by 8,519 individuals(ind.)/m2 and a biomass of 1,967 gWWt/m2 on the five vessels. The number of species, density, and biomass were greater on the coastal vessels the Eardo, Jangmok 1, and Jangmok 2 than on the ocean-going vessels the Isabu and Onnuri. Among the coastal vessels, barnacles were the most abundant and had the greatest density, while mollusks had the highest biomass. Differences between hull sectors showed that the highest species abundance and density appeared on all hulls in ports and bays where the Jangmok 1 operated, while the highest species abundance, density, and biomass were identified in the niche areas of the Eardo, which operated farther from the coast. The hull-fouling macroinvertebrates that exceeded 1% of all organisms were the barnacles Amphibalanus amphitrite, Balanus trigonus, and Amphibalanus improvisus; the polychaete Hydroides ezoensis; the bivalves Magallana gigas and Mytilus galloprovincialis; and the amphipod Jassa slatteryi. The dominant species were cosmopolitan and globally distributed, and many of them were cryptogenic. Six native species were identified: M. gigas, H. ezoensis, the amphipod Melita koreana, the isopod Cirolana ko-reana, and the barnacle B. trigonus and F. kondakovi. Eight non-indigenous species (NIS) were de-tected: barnacles A. amphitrite and A. improvisus, the bivalve M. galloprovincialis, the polychaete Perinereis nuntia, amphipods J. slatteryi and Caprella californica, and bryozoans Bugulina californica and Bugula neritina. Of the fouling macroinvertebrates found on the vessel hulls, 13% were native and 17% were NIS. The nMDS ordination analysis of the five vessels showed four clusters of fouling macroinvertebrate communities: two ocean clusters (the Isabu and Onnuri), one coastal cluster (the Eardo and Jangmok 2), and one local cluster (the Jangmok 1). More diverse communities developed on the hulls of vessels that operated locally rather than globally or in deep oceans. Spearman rank correlation showed that biological indices such as number of species, density, and biomass correlated highly and positively with the numbers of days on coastal operations and negatively with the number days on ocean operations. The species diversity index correlated positively with the total number of anchoring days and coastal operation days and negatively with the total number of operation days and ocean operation days. The macroinvertebrates differed by the area of operation, the port of anchorage, the number of days in operation and at anchor, and the hull sectors. There is no previous research data on hull-fouling macroinvertebrates in the Republic of Korea, and this study provides a basis for future studies to identify introduced species and their differences based on operation area.

This study aimed to examine the association of blood triglyceride levels with fasting blood glucose levels and type 2 diabetes (T2D) prevalence in Chinese adults with normal triglyceride levels (<1.7 mmol/L), using linear regression and binary logistic regression, respectively. This cross-sectional study included 16,706 Chinese adults, among which 1,067 had T2D. Triglycerides were positively associated with fasting plasma glucose after multivariate adjustment (β=0.034, P<0.001). One natural log unit increase in blood triglycerides was associated with a 61% higher multivari-ate-adjusted risk of T2D (odds ratio [OR], 1.61; 95% confidence interval [CI], 1.19-2.17; P=0.002). The positive associations remained when participants who were treated with lipid-lowering or an-ti-diabetic drugs were excluded. The optimal cut-off of triglycerides for T2D was 1.09 mmol/L (obtained using Receiver Operating Characteristic curve analysis). Participants with triglycerides of ≥1.09 mmol/L had a 28% higher risk of T2D (OR, 1.28; 95% CI, 1.07-1.53; P=0.006) compared to those with triglycerides below the cut-off. In conclusion, this study showed that, in people with normal triglyceride levels, triglycerides at the upper normal range correlated with increased T2D diagnosis risk, with an optimal cut-off of 1.09 mmol/L. Therefore, adults with high “normal” triglyceride levels (1.09-1.69 mmol/L) may need to be closely monitored for the development of T2D.

The purpose of this study is to establish whether digital literacy and insurtech adoption influence insurance inclusion in Uganda. Principally, we sought to determine whether insurtech adoption mediates the nexus between digital literacy and insurance inclusion. This study adopted a cross-sectional and quantitative correlational approach. The study’s sample was 391 individuals who had used digital platforms such as mobile phones and computers to access insurance products and services in Uganda. Data were collected using structured survey questionnaires. Partial Least Squares Structural Equation Modelling (PLSEM) was employed to test the hypothesised relationships. The results demonstrate that both digital literacy and insurtech adoption significantly and positively influence insurance inclusion. We also found digital literacy to be a significant and positive determinant of insurtech adoption. Markedly, it was found that insurtech adoption mediates the association between digital literacy and insurance inclusion in Uganda. However, this study was conducted in a developing country with an underdeveloped insurance market and with low technological advancement. This may affect generalisation of the study findings. This study’s novelty lies in establishing how digital literacy and insurtech adoption interplay to influence insurance inclusion in Uganda. This is the first study to examine the effect of digital literacy and insurtech adoption on insurance inclusion.

The objective of this study was to evaluate the glycemic index and the satiety response of three Mexican kinds of honey. The values of fructose ranged from 272.40-395.10 g/kg, while the glucose value ringed 232.20-355.50 g/kg. The ratio F/G of sample honey was 1.45, 1.00, and 1.17 for Highland, Multifloral, and Avocado honey, respectively. Twenty-six participants completed this study, which was previously approved by the ethics committee of the Facultad de Salud Pública y Nutrición (CE 2/2018-19). Highland and Avocado honey is classified as medium-GI (69.204.07 and 66.365.74, respectively), while Multifloral honey is classified as high-GI (74.245.98). The Highland honey presented the best satiety response. The difference in IG values and the effect of the satiety response of Highland honey could be explained by the different fractions of carbohydrates in samples and other components such as phytochemicals.

Chellali et al. introduced two degree concepts, ve-degree and ev-degree (Chellali et al, 2017). The ve-degree of a vertex equals to number of different edges which are incident to a vertex from the closed neighborhod of v. Moreover the ev-degree of an edge e=ab equals to the number of vertices of the union of the closed neighborhoods of a and b. The most private feature of these degree concepts is, total number of ve-degrees and total number of ev-degrees equal to first Zagreb index of the graphs for triangle-free graphs. In this paper we introduce ve-degree entropy, ev-degree entropy and investigate the relations between these entropies and the first Zagreb index entropy. Finally we obtain the maximal trees with respect to ve-degree irregularity index.

In this short communication, following a brief introduction, we undertake a comprehensive analytical study of the weighted Simpson index. Our primary emphasis concerns the precise determination of the optimal point (minimizer) coordinates and of the minimum value of the index, a differentiable convex function, which is related to the harmonic mean concept. Furthermore, we address and solve the inversion problem and show the tight connection between both approaches. Last, we give some insights and final remarks on this subject.

The Global Hunger Index (GHI) is a vital tool for assessing and understanding the state of hunger and food security across the world. In this review article, we examine the GHI scores of various countries in the years 2000, 2008, 2015, and 2023. We aim to explore the changes in GHI scores over this period, identify trends, and discuss the implications for global food security. The GHI provides a comprehensive snapshot of the world's progress in reducing hunger, and this analysis sheds light on the successes and challenges faced by different countries.

Forest road pavement needs an evaluation methodology based on a comprehensive assessment of road conditions. This research was conducted to evaluate the performance of a method for rating the surface condition of forest roads and eventually to adapt the method to the situation prevailing in a forest road network. The rating method selected as the basis for this experiment was the pavement condition index (PCI) developed by the U.S. Army Corps of Engineers. A 53 km of forest roads were selected contained the most influential factors and conditions variability. Eventually, 201 road segments were delineated between 150-300 m in length. Within the given segments, sample plots were set 20 m in length consecutively. It was concluded that the panel scores for distress and surface condition of sample unit and section differed from forest road pavement condition index (FRPCI) and PCI. Linear regression was used to derive equations between distress and PCI score to determine effective FRPCI parameters that provide a numerical rating for the condition of road segments within the road network, where 0 worlds are the worst possible condition, and 100 is the best possible condition best. Also, regression analysis showed the FRPCI model with a 0.87 correlation for the total of the road is a performance index used for the first time in forest roads. This study showed a range of FRPCI from 7.8 to 96.3, different from PCI and URCI ratings (0.85-45 and 1.2-53). The FRPCI index helps forest managers in road maintenance, harvesting, and planning to use road information.

Droughts occurring more and more frequently in recent years are usually associated with progressive climate changes. Modern monitoring methods is mainly associated with agricultural use due to the high market demand for services protecting against agricultural losses. In natural wetland ecosystem this problem is neglected which is probably due to fact that this are ecosystems rich in water by definition. Nevertheless this droughts might become a problem of wetlands, whose good condition depends on adequate hydration. Therefore this study focused on determination Crop Water Stress Index (CWSI) for natural heterogeneous wetland habitats. CWSI based on remotely sensed land surface temperature and associated basic meteorological (air temperature and humidity) measurements. CWSI was calculated based on high resolution LST measurements from UAV platform and compare with on ground measurements of soil moisture, CCI, fAPAR and meteorological conditions. Results shows that CWSI properly shows water condition of plants in measured habitats and revels high importance of metrological conditions during data acquisition.

The Work Ability Index (WAI) is the most widely used questionnaire for the self-assessment of working ability. Because of its different applications, shorter versions, and widespread use in healthcare activities, it is worthwhile assessing its characteristics. The WAI was distributed online among the workers of a healthcare company; the results were compared with data contained in the workers' personal health records and with absence registers. 340 out of 575 workers (59.1%) participated; 6.5% of them reported poor work ability. Exploratory factor analysis indicated that the one-factor version best described the characteristics of the WAI. The scores of the complete WAI, the shorter form without the list of diseases, and the minimal one-item version (WAS) had equal distribution and were significantly correlated. The WAI score was inversely related to age and significantly lower in women than in men, but it was higher in night workers than in colleagues due to the probable effect of selective factors. The WAI score was also correlated with absenteeism, but no differences were found between males and females in the average number of absences, suggesting that cultural or emotional factors influence the self-rating of the WAI. Workers tended to overreport illnesses in the online survey compared to data collected during occupational health checks. Musculoskeletal disorders were the most frequently reported illnesses (53%). Psychiatric illnesses affected 21% of workers and had the greatest impact on work ability. Multilevel ergonomic and human factor intervention seems to be needed to recover the working capacity of healthcare workers.

This paper studies the contemporaneous relationship between S&P 500 index returns and log-increments of the market volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate how the dependence between the two series varies across different segments of the market return distribution. We find that: (a) the two series exhibit strong, negative, extreme tail dependence; (b) the negative dependence is stronger in extreme bearish markets than in extreme bullish markets; (c) the dependence gradually weakens as the market return moves toward the center of its distribution, or in quiet markets. The unique dependence structure supports the VIX as a barometer of markets' mood in general. Moreover, applying the proposed method to the S&P 500 returns and the implied variance (VIX²), we find that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in general, both effects are weaker than the dependence relation between the market returns and the log-increments of the VIX.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

Fractional flow reserve (FFR) is well recognized as a gold standard measure for the estimation of functional coronary stenosis. Technological progressions in image processing have empowered the reconstruction of three-dimensional models of the coronary arteries via both non-invasive imaging modalities, such as Coronary Computed Tomography Angiography (CCTA), and invasive coronary angiography or intravascular imaging. The application of computational fluid dynamics (CFD) techniques to coronary 3D anatomical models allows the virtual evaluation of the hemodynamic significance of a coronary lesion with high diagnostic accuracy in comparison to the invasive FFR using pressure wires. These opportunities providing hemodynamic information based on anatomy have given rise to a new era of functional angiography and coronary imaging. However, further validations are needed to overcome several scientific and computational challenges before these methods are applied in everyday clinical practice. This review aims to present all the data on the studies and methodologies that have been presented for the virtual estimation of FFR, and the diagnostic execution of the virtual tools for the hemodynamic assessment of coronary lesions compared to the invasive FFR.

Refractive index measurements have been an important task for a long time because that index plays an essential role in describing the optical properties of a material. Many methods have been developed to perform that task. Some of them use interferometry to achieve high precision, however these configurations are complicated. Some measure the critical angle using simple structures, but the accuracy is not satisfactory because it is difficult to judge the exact critical angle with intensity variations. Here we propose several new schemes based on measuring the polarization change in the total internal reflection. The proposed method has the merits of simple structure and easy incident angle determination that gives the maximum phase change. Additionally, it is possible to find the material dispersion by measuring the wavelength dependence of the polarization ellipticity. Some useful formulas relating the refractive index with the maximum phase change are obtained. This work can provide valuable alternatives for index measurement.

The utilization and engineering of thermo-optic effects have found broad applications in integrated photonic devices, facilitating efficient light manipulation to achieve various functionalities. Here, we perform both an experimental characterization and theoretical analysis of these effects in integrated micro-ring resonators in high index doped silica (HIDS), which has had many applications in integrated photonics and nonlinear optics. By fitting the experimental results with theory, we obtain fundamental parameters that characterize their thermo-optic performance, including the thermo-optic coefficient, the efficiency for the optically induced thermo-optic process, and the thermal conductivity. The characteristics of these parameters are compared to those of other materials commonly used for integrated photonic platforms, such as silicon, silicon nitride, and silica. These results offer a comprehensive insight into the thermo-optic properties of HIDS based devices. Understanding these properties is essential for efficiently controlling and engineering them in many practical applications.

Initially, renal resistive index (RRI) was investigated to improve diagnosis in kidney diseases, but failed to meet this goal. Recently many papers highlighted the prognostic significance of RRI in chronic kidney disease, in the estimation of revascularization success of renal artery stenoses or the evolution of the graft and recipients in renal transplantation. Moreover, RRI gained importance in prediction of acute kidney injury in critically ill patients. Along with RRI study in renal pathology have been revealed correlations of this index with parameters of systemic circulation. The theoretical and experimental premises of this connection were reconsidered, and studies for analyzing the link between RRI and arterial stiffness, central and peripheral pressure or left ventricular flow were conducted with this purpose. A high amount of data is currently indicating that RRI is influenced more by pulse pressure and vascular compliance than by renal vascular resistance – assuming that RRI reflects the complex interplay between systemic circulation and renal microcirculation and should be considered as a marker of systemic cardiovascular risk beyond its prognostic relevance for kidney disease. In this review we will go through clinical research that revealed the implications of RRI in renal and cardiovascular disease.

The evaluation of robotic hands is a subjectively biased, complex process. The fields pertaining to robotic hands are human-centric in nature, making human hands a good standard for benchmark comparisons of robotic hands. To achieve this, we propose a new evaluation index, where we evaluate robotic hands on three fronts: their form, features and performance. An evaluation on how anthropomorphic robotic hands are in basic mobility, and appearance constitutes the ``Form'', while features that can be read, changed and actuated for effective control of robotic hands constitutes the ``Features''. We derived these key features from an extensive analysis of robotic hands in literature. Finally, the robotic hands carry out a series of tasks that evaluate their ``Performance''. An individual score for each category is drawn and we carry out a three-pronged analysis. We also propose an additional feature in the form of price to provide context when analysing multiple hands.

The laser host materials undergo relatively small changes in their intrinsic properties due to various sources during an experiment. These sources are often related to temperature change or applied stress, which may cause change in optical properties of the material under study. Consequently, the crystal experiences an optical anisotropy, which may affect the final outcome of the experiments. One way to reduce probable noises is to predict the change in optical properties with respect to load. To predict the changing pattern of the refractive index in a crystal, one needs to know both the elastic and photoelastic constants of the material. In this study, we utilized density functional perturbation theory (DFPT) to extract the photoelastic tensor of Y$_2$SiO$_5$ and Eu-doped Y$_2$SiO$_5$ crystals. Using the photoelastic and elastic constants calculated, a Finite Element (FE) model was developed, which allowed us to apply load and then post-process the results. This methodology enabled us to observe the variation in refractive index ($n$), and consequently, the shift in the resonance frequency of the cavity. The results obtained were in agreement with experimental measurements, falling within a 3\% discrepancy across a temperature range spanning from cryogenic to room temperature. This correlation suggests the feasibility of using the current workflow as a predictive tool for evaluating variations in refractive indices over a specific interval.

Cognitive reserve is the adaptability of cognitive processes in the face of brain aging and pathology. This study aimed to validate the Arabic version of the Cognitive Reserve Index Questionnaire (CRIq) in a healthy Lebanese sample. CRIq assesses cognitive reserve through three domains: education, working activity, and leisure time. Statistical measures, including descriptive and regression analysis along with structural equation modeling, were utilized to investigate the convergent and discriminant validity of CRIq, incorporating fluid intelligence (Gf) and measures of cognitive function, long-term memory encoding and retrieval (Glr), and processing speed (Gs). Results from 174 participants revealed that the activities assessed by CRIq-Arabic were comparable to the original CRIq study, with slight cultural differences. The internal consistency of CRIq-Arabic was good (Cronbach's α = 0.88), indicating reliability. Convergent validity was confirmed, with moderate to high loadings on the cognitive reserve latent construct. Discriminant validity was supported as correlations between cognitive reserve variables and non-target constructs (Gf, Glr, Gs) were less than 1. The findings provide an initial psychometric validation of the CRIq-Arabic. Further research in clinical samples is needed to enhance its utility in neuropsychological practice.

We conducted a retrospective analysis of the immunohistochemical (IHC) staining GRP94, an ER stress protein on large B-cell lymphoma (LBCL) cells, intracellular p53, and 15 factors involved in the metabolism of CHOP regimen :AKR1C3 (HO-metabolism), CYP3A4 (CHOP-metabolism) and HO efflux pumps (MDR1, MRP1). The study subjects were 42 patients with LBCL at our hospital. IHC staining using antibodies against the 17 factors. The odds ratios by logistic regression analysis using a dichotomous variable of CR, non-CR/relapse were statistically significant: for MDR1, MRP1, and AKR1C3. The overall survival (OS) after R-CHOP was compared by the log-rank test. The four groups showed that Very good (5-year OS, 100%) consisted of 4 patients showed negative IHC staining for both GRP94 and CYP3A4. Very poor (1-year OS, 0%), consisted of 3 patients who showed positive results of IHC for both GRP94 and CYP3A4. The remaining 35 patients comprised two subgroups: Good (5-year OS 60-80%.): 15 patients who showed negative staining for both MDR1 and AKR1C3, Poor: 5-year OS, 10-20%) :20 patients who showed positive staining for either MDR, AKR1C3,,MRP1 or p53. The Histological Prognostic Index (HPI) (The four groups: Very poor, Poor, Good, and Very pood) is a breakthrough method for stratifying patients based on factors involved in the development of treatment resistance.

In this paper, a Markov random field model is proposed to determine a site’s light pollution risk level. The specific data of 12 indicators of five typical cities in China is first collected to establish a hierarchical indicator system using an R-type clustering algorithm. Then, the entropy weight method is used to filter, determine 10-factor indicators, three potential impact indicators, and a light pollution risk index, and establish an undirected probability map model. A light pollution measurement based on Markov random field is obtained, and a location-based light pollution risk assessment index (LBLPRAI) is proposed. LBLPRAI of different types of sites is analyzed, and three possible intervention strategies are proposed to solve the light pollution problem: road lighting system planning, increasing vegetation coverage, and building system planning. Finally, the simulated annealing algorithm is used to determine the best intervention strategy, and it is concluded that the use of strategy 1 in the urban community 2 is the most effective measure, which can reduce the risk level of light pollution by 17.2%.

The bond index is an indicator of the grindability of the material and is widely used in the preparation of mineral raw materials and the cement industry. Paper offers new, abbreviated and simplified procedure to determine Bond work index that relies on first-order kinetics law and can be performed with any number of grinding cycles, depending on the desired accuracy of the required data. The parameters G and P80 of each grinding cycle are multiplied by the newly founded coefficients giDT and piDT to obtain values approximately equal to these parameters of the last grinding cycle when the equilibrium state is reached in the standard test. The paper presents comparative results obtained by standard Bond and new shortened procedure on individual samples of andesite, limestone, copper-ore and smelter slag and on composite samples of andesite from limestone and copper-ore with smelter slag in different mass ratios. As the number of grinding cycles increases, the precision of the shortened procedure increases, and the mean square error decrease 3.59%, 2.61% and 1.74% for two, three and four grinding cycles.

The leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of ecosystems productivity and related climate, topography, and edaphic impacts. The spatio-temporal changes of LAI were assessed throughout Ardabil Province, a host of relevant plant communities within the critical ecoregion of a semi-arid climate. In a comparative study, novel data from Google Earth Engine- GEE was tested against traditional ENVI measures to provide LAI estimations. Besides, it is of important practical significance for institutional networks to quantitatively and accurately estimate LAI at large areas in a short time and using appropriate baseline vegetation indices. Therefore, LAI was characterized for ecoregions of Ardabil Province using remote sensing indices extracted from Landsat 8 Operational Land Imager (OLI), including Enhanced Vegetation Index calculated in GEE (EVIG) and ENVI5.3 software (EVIE), as well as Normalized Difference Vegetation Index estimated in ENVI5.3 software (NDVIE). Besides, a new field measurement method, i.e., the LaiPen LP 100 portable device (LP 100), was used to evaluate the accuracy of the derived indices. Accordingly, the LAI was measured on June and July 2020 in 822 ground points distributed in 16 different ecoregions-sub ecoregions having various Plant Functional Types (PFTs) of the shrub, bush, and tree. The analyses revealed heterogeneous spatial and temporal variability in vegetation indices and LAIs within and between ecoregions. The mean (standard deviation) value of EVIG, EVIE, and NDVIE at Province scale yielded 1.1 (0.41), 2.20 (0.78), and 3.00 (1.01), respectively in June, and 0.67 (0.37), 0.80 (0.63), and 1.88 (1.23), in that respect in July. The highest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June are found in Meshginshahr (1.40), Meshginshahr (2.80), and Hir (4.33) ecoregions and in July are found in Andabil ecoregion respectively with values of 1.23, 1.5, and 3.64. The lowest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June were observed for Kowsar (0.67), Meshginshahr (1.8), and Neur (2.70), ecoregions and in July were for Bilesavar ecoregion respectively with values of 0.31, 0.31, and 0.81. High correlation and determination coefficients (r&gt;0.83 and R2&gt;0.68) between LP 100 and remote sensing derived LAI were observed in all three PFTs (except for NDVIE-LAI in June with r=0.56 and R2=0.31). On average, all three examined LAI measures tended to underestimation compared to LP 100-LAI (r&gt;0.42). The findings of the present study can be promising for effective monitoring and proper management of vegetation and land use in Ardabil Province and other similar areas.

The ionospheric scintillation is a rapid phase and amplitude fluctuation of satellite signals due to the small-scale irregularity of electron density in the ionosphere. The characterization of the scintillation index in a proper way is a crucial aspect of the Global Positioning System (GPS) satellite signals for the purpose of space-based navigation, satellite communication, space weather as well as earth observation applications. In the current study, we analyzed the ionospheric scintillation index during the year of 2018 to 2019 over the Nepal region which locates itself almost being sandwiched between India and China and in the vicinity of low latitudes. The characteristic variations of scintillation occurrence are studied during the several geomagnetic storm and quiet days. The results show that the S4 indexes are varying from the 0.05 to 0.45 during the whole year. The S4 indexes behave higher variations during the whole day in the starting of the year and start to decrease at end of the day as well as at the ending months of the year 2019. The S4 values become completely less during the sunset time, while they have higher values during the sunrise. Especially, the S4 index during the storm days are larger than during the quiet days. It is worthy to note that the variations of S4 index studied in this current study do not follow the sunset property during the year of 2019. Consequently, the causes should be discovered and discussed additionally in the next research paper.

Atherogenesis and dyslipidemia increase the risk of cardiovascular disease, which is the leading cause of death in developed countries. While blood lipid levels have been studied as disease predictors, their accuracy in predicting cardiovascular risk is limited due to its high interindividual and interpopulation variability. The lipid ratios: atherogenic index of plasma (AIP=log TG/HDL-C) and the Castelli risk index 2 (CI2=LDL-C/HDL-C) have been proposed as better predictors of cardiovascular risk, but the genetic variability associated to these ratios has not been investigated. This study aimed to identify genetic associations with these indexes. The study population (n=426) included males (40%) and females (60%) aged 18-52 years (mean 39 years), the Infinium GSA array was used for genotyping. Regression models were developed using R and PLINK. AIP was associated with variation on APOC3, KCND3, CYBA, CCDC141/TTN, and ARRB1 (p-value < 2.1E-6) the three former previously associated to blood lipids, while CI2 was associated with variants on DIPK2B, LIPC, and 10q21.3 rs11251177 (p-value 1.1E-7) the latter previously linked to coronary atherosclerosis and hypertension. KCND3 rs6703437 was associated with both indexes. This study is the first to characterize the potential link between genetic variation and atherogenic indexes, AIP and CI2, highlighting the relation between genetic variation and dyslipidemia predictors. These results also contribute to consolidating the genetics of blood lipid and lipid indexes.

To investigate whether high body mass index (BMI) increases the risk of recurrence and corre-lates with higher glucose uptake in recurrent lesions in post-menopausal female patients with breast cancer. The hospital database was searched to retrieve breast cancer patients, who had undergone an [18F]FDG PET/CT scan before neoadjuvant chemotherapy and curative-intent sur-gery. BMI was calculated at the baseline [18F]FDG PET/CT scan. There was a median follow-up of 5 years after the baseline PET/CT scan to identify: recurrence in the breast (T_rec); lymph nodes (N_rec); distant locations (M_rec). Furthermore, SUVmax was measured in the sites of recur-rence. A chi-square test was used to investigate any difference in the frequency of any recur-rence, T_rec, N_rec, and M_rec between overweight women (BMI≥25 kg/m2) and women with a BMI<25 kg/m2 (p<0.05). SUVmax, was compared using a t-test (p<0.05) between the two groups. A total of post-menopausal 142 women (BMI: 26.84±5.59; 84 overweight and 58 with normal weight) were retrieved. There were 48 recurrences at the follow-up. The chi-square test demon-strated in overweight women an increased frequency of any recurrence (35 vs. 13; p=0.025) and T_rec (15 vs. 2; p=0.018) and a higher T_rec SUVmax (4.74±2.90 vs. 1.85 ± 0.63; p=0.09) compared to women with a BMI<25 kg/m2. BMI seems to correlate with an increased rate of recurrence, espe-cially in the breast, and a higher glucose uptake in post-menopausal patients with recurrent breast cancer.

The number of aged individuals is increasing worldwide, rendering essential the comprehension of pathophysiological mechanisms of age-related alterations, that could facilitate the development of interventions contributing to “successful aging” and improvement of quality of life. Cardio-vascular diseases (CVD) include pathologies affecting heart or blood vessels, such as hyperten-sion, peripheral artery disease and coronary heart disease. Indeed, age-associated modifications in body composition, hormonal, nutritional and metabolic factors, as well as a decline in physical activity are all involved in the increased risk of developing atherogenic alterations raising the risk of CVD development. Several factors have been claimed to play a role in the alterations observed in muscle and endothelial cells and leading to increased CVD, such as genetic pattern, smoking, unhealthy lifestyle. Moreover, a difference in the risk of these diseases in women and men has been reported. Interestingly, in the last decades attention has been focused on a potential role of several pollutants which disrupt human health by interfering with hormonal pathways, and more specifically in non-communicable diseases such as obesity, diabetes and CVD. This review will focus on the potential alteration induced by Endocrine Disruptors (Eds) in the attempt to characterize a potential role in the cellular and molecular mechanisms involved in the atheromatic process and CVD progression.

Background: We aimed to assess the association between DII and PD and the mediation effect of DII in the association of PD with systemic inflammation. Using the National Health and Nutrition Examination Survey (NHANES) 2009-2010, 2011-2012 and 2013-2014, participants that received periodontal exam and provided dietary recall data were included. The inflammatory potential of diet was calculated via DII. Periodontitis was defined according to the 2012 case definition. The clinical outcomes of interest were mean periodontal probing (PPD), mean clinical attachment loss (CAL) and thresholds of PPD and CAL. White blood cells (WBC), segmented neutrophils and C-reactive protein (CRP) were used as proxies for systemic inflammation. The periodontal measures were regressed across DII values using adjusted multivariate linear regression. Adjusted mediation analysis appraised the influence of DII in the association of periodontitis and systemic inflammation. 10,178 participants were included. DII was significantly correlated with mean PPD, mean CAL, thresholds of PPD and CAL, WBC, segmented neutrophils and DII (p&lt;0.01). A linear regression logistic adjusted for multiple confounding variables confirmed the association between DII and mean PPD (B = 0.02, Standard Error [SE]: 0.02, p&lt;0.001) and CAL (B = -0.02, SE: 0.01, p&lt;0.001). The association of mean PPD and mean CAL with both white blood cells and segmented neutrophils were mediated by DII (from 2.1 to 3.5%, p&lt;0.001). In the 2009-2010 subset, the association of mean CAL with serum CRP was mediated by DII (52.0%, p&lt;0.01). In conclusion, inflammatory diet and PD may be associated. Also, the inflammatory diet significantly mediated the association of leukocyte counts and systemic inflammation with periodontitis.

Postprandial hyperlipidemia showing postprandial increase in serum triglyceride (TG) is atherogenic and associated with the development of coronary artery disease (CAD). To diagnose postprandial hyperlipidemia, the oral fat loading test (OFLT) should be performed, however, this test is very time-consuming and is difficult to perform. Ele-vated serum TG levels reflect an increase in TG-rich lipoproteins (TRL) such chylomi-crons (CM), very low-density lipoproteins (VLDL) and their remnants (CM remnant [CMR] and VLDL remnant [VLDLR]). Understanding of elevation in CMR and/or VLDLR can lead us to understand the existence of postprandial hyperlipidemia. The measurements of apo B48 which is a constituent of CM and CMR, non-fasting TG which includes TG content in all lipoproteins including CM and CMR, non-high-density lipoprotein-cholesterol (non-HDL-C) which includes TRL and low-density lipoprotein, and remnant cholesterol, are useful to suspect the existence of postprandial hyperlipidemia. Postprandial hyperlipidemia is observed in patients with familial type III hyperlipoproteinemia, familial combined hyperlipidemia, chronic kidney disease, metabolic syndrome and type 2 diabetes. Postprandial hyperlipidemia is closely related to postprandial hyperglycemia, and insulin resistance may be an in-ducing and enhancing factor for both postprandial hyperlipidemia and postprandial hyperglycemia. Remnant lipoproteins and metabolic disorders associated with post-prandial hyperlipidemia have various atherogenic properties such as induction of in-flammation and endothelial dysfunction. A healthy diet, calorie restriction, weight loss and exercise, positively impact postprandial hyperlipidemia. Anti-hyperlipidemic drugs such pemafibrate, bezafibrate, ezetimibe and eicosapentaenoic acid have shown to improve postprandial hyperlipidemia. Anti-diabetic drugs including metformin, alpha-glucosidase inhibitors, pioglitazone, dipeptidyl-peptidase-4 inhibitors and glu-cagon like peptide 1 analogues, have shown to ameliorate postprandial hyperlipidemia. Although sodium glucose cotransporter-2 inhibitors have not been proven to reduce postprandial hyperlipidemia, they reduced fasting apo B48 and remnant lipoprotein cholesterol. In conclusion, it is important to appropriately understand the existence of postprandial hyperlipidemia and to connect it to optimal treatments.

The Solvency II regulatory framework specifies procedures and parameters for determining solvency capital requirements (SCRs) for insurance companies. The proposed standard SCR calculations involve two steps. The Value–at–Risk (VaR) of each risk driver is measured and, in a second step, all components are aggregated to the company’s overall SCR, using the Standard Formula. This formula has two inputs: the VaRs of the individual risk drivers and their correlations. The appropriate calibration of these input parameters has been the purpose of various Quantitative Impact Studies that have been conducted during recent years. This paper demonstrates that the parameter calibration for the equity–risk module—overall, with about 25%, the most significant risk component—is seriously flawed, giving rise to spurious and highly erratic parameter values. As a consequence, an implementation of the Standard Formula with the currently proposed calibration settings for equity–risk is likely to produce inaccurate, biased and, over time, highly erratic capital requirements.

This research paper is mainly aimed to elaborate the initial risk management and measures which government of Pakistan took towards Novel Corona Virus (COVID-2019). This initial response and planning was devised after the early outbreak of COVID-2019 in Wuhan, China in early time of January 2020. Pakistan devised a comprehensive plan that not to evacuate their student from Wuhan, China. The government of Pakistan in compliance with the National Institute of Health (NIH) devised and documented comprehensive plans such as the flight operations postponed related to Umerah pilgrims, which were intended to go to sacred places of KSA (The Kingdom of Saudi Arabia). The process of visa, immigration policy totally changed and the government of Pakistan notified it officially that, no new visas of visit, student, and business would be issued in due course of uncertainty due to COVID-2019. The government of Pakistan also announced medical emergency and notified through the country’s provinces the process of testing and treatment of COVID-2019. The government of Pakistan also allocated funds for medical supplies and named out the particular country’s best laboratories. The government of Pakistan also locked down all the cities with the emergency announcement that people should stay inside the home in quarantine or self-isolation. NIH (The National Institute of Health) played a vital role in executing the planning to cope with COVID – 2019). The National Institute of Health responded as “The Centre for Disease Control”. In aid to the government, the national army of Pakistan responded in a proactive manner towards planed execution. The medical corps of Pakistan army dedicated themselves to treat the suspected patients of COVID – 2019. Due to plans, policies being documented, implemented in such a way productive way that from February 28, 2020 to till date there is not much critical situation and issues are not present. There are much productive results as there is not much boom in a rise of COVID-2019 patients. This lockdown under the authority of the provinces resulted in fruitful outcomes. Background: On January 02, 2020, authorities of the People Republic of China elaborated that they have encountered with a novel type of infectious viral disease 2019. Later on January 12, the authorities from China elaborated the related sequence of Corona Virus diseases 2019 names as COVID – 2019. When COVID-2019 being identified in Wuhan, Hubei China, as an early response the Government of Pakistan in support of the National Institute of Health (Field Epidemiology & Disease Surveillance Division) published a health advisory about novel coronavirus. Methods: According to Global Health Security Index, Pakistan is ranked as 105th country among 195 countries in GHS index. Overall Score of Pakistan is 35.5. The score of Early Detection and Reporting for Epidemics of Potential International Concern is 41.7. A Graphical depiction of the COVID-19 cases placed until April 10, 2020 as well as a graph trend line of recovered as well as death rate is also depicted. According to the graphical facts of Government of Pakistan and World meters, the recovery rate of COVID-19 is about 98 percent and 2.1 percent death rate is reported against the total cases. Trend analysis with line graph was drawn based on available data from official dashboard web portal of the government of Pakistan and worldometers.info. Data figures were incorporated from March to August 18, 2020 in MS Excel and then subsequently deployed to draw trend analysis from managing risk to recovery. Results: The line graph showed a slowdown in the COVID-19 cases and high rate of recoveries from COVID-19 in Pakistan. On March 11, 2020, there were 20 confirmed cases of coronavirus reported in Pakistan. No death was recorded in very first seven days, on March 18, 2020 only two deaths were reported. On August 18, 2020, there were 272128 recoveries, 6201 deaths, total confirmed cases 290445, and total test were 2340072 in Pakistan. As a results, we can report that due to early measures taken by government of Pakistan no mass scale destruction in terms of death and cases been recorded in Pakistan. Conclusions: To till date, the government of Pakistan tried its level best to minimize the coronavirus cases as much as they can. However, the ending of the potential attack of an outbreak would depend upon the well organized and coordinated approach at all levels such as true directed decisions, fully preparedness, as well implementation and evaluation of continuous decisions. As the recovery rate of the cases is 98 percent and merely death rate is 2.1 percent, concluded that in future it would be a good sign to stop the potential outbreak. Also, lock down as well as precautionary measurement taken by the provincial governments resulted a decline number of COVID-19 cases in the country. Another good sign is that merely 4 percent population of Pakistan is of more than 60 years of old it can be concluded that there are less chances of mass death due to outbreak of COVID-19.

Elevated circulating triglyceride levels have been linked to an increased risk of diabetes, although the precise mechanisms remain unclear. This study aimed to investigate whether low-density lipoprotein (LDL) cholesterol, homeostatic model assessment (HOMA) for insulin resistance, and C-reactive protein served as mediators in this association across a sample of 18,435 US adults. Mediation analysis was conducted using the PROCESS Version 4.3 Macro for SPSS. Simple medi-ation analysis revealed that all three potential mediators played a role in mediating the associa-tion. However, in the parallel mediation analysis, where all three mediators were simultaneously included, HOMA for insulin resistance remained a significant mediator (indirect effect coefficient, 0.47; 95% confidence interval [CI], 0.43—0.52; p < 0.05) after adjusting for all tested confounding factors. Conversely, LDL cholesterol (indirect effect coefficient, -0.13; 95% CI, -0.31—0.05; p > 0.05) and C-reactive protein (indirect effect coefficient, 0.01; 95% CI, -0.003—0.02; p > 0.05) ceased to be significant mediators. HOMA for insulin resistance accounted for 49% of the association between triglycerides and diabetes. In conclusion, HOMA for insulin resistance was the dominant mediator underlying the association between triglycerides and diabetes. Therefore, reducing triglyceride levels may hold promise for improving insulin sensitivity in diabetic patients.

Pancreatic cancer (PC) is considered one of the most challenging and formidable malig-nancies to treat because it is usually diagnosed at terminal stage, thus it is characterized with a poor prognosis with 5% of patients living over 5 years. The late diagnosis leads to a lower suc-cess rate of resectability, hence chemotherapy or chemoradiotherapy are the only hopes for most PC patients. However, the available drug combinations for PC treatment did not provide satisfactory clinical outcomes. There is a pressing and urgent need to discover new chemothera-peutics which fight PC with tolerable side effects and less liability for resistance. Pentacyclic triterpenes (PTs) are privileged structures with a multitude of biological activities mitigating several ailments, particularly in neoplasm field. They are characterized by a high therapeutic window and their activity can be highly enhanced through structural modifications. Indeed, several parent PTs such as oleanolic acid, ursolic acid, lupeol, betulinic acid, and celastrol proved effective against different PC phenotypes inhibiting their proliferation, invasion, and metastasis mainly via KRAS modulation. Some PTs worked as adjuvant chemosensitizers in gemcitabine-resistant or TRAIL-resistant cells. Owing to their potential in PC treatment, we pre-sent this review article summarizing PC pathogenesis and the promising role of PTs in the man-agement of PC when used either solely or in combination with other chemotherapies such as gemcitabine and 5-Fluorouracil.

AFM nanoindentation showed variation in stiffness (Elastic modulus) due to heterogenous nature of the collagen fibres. The S values varied from 5 N/m to 11.11 n/m corresponding to an E change of 2.25 to 1.38 GPa. The variation in effective modulus (Eff) with respect to displacement indicated crossing the parabolic limit. A softening index n was proposed due to the heterogenous behaviour of the biomaterials

The main objective of this paper is to develop a readiness index model that can serve as an analytical tool for exploring the achievements of electrification of transportation systems. We have applied this readiness index model to evaluate the readiness positioning of China, Norway, and Sweden to-wards transport electrification. We have chosen these three countries as they represent diversity among countries that are in the process of adopting electric transport system solutions. Our developed readiness index model has four key dimensions, technological readiness, political readiness, societal readiness, and economic readiness. The embeddedness of all four dimensions in one model provides a multi-perspective way of analyzing and evaluating the readiness levels of countries moving towards transforming the transportation system. Therefore, we named the model a “multidimensional readiness index.” Our main conclusions are that the political processes and political decisiveness involved are the most important factors followed by the societal needs and economic ability, with the current technology available as the fourth. Without the participation of dedicated and determined political decision-makers being involved, the other three factors are challenging to obtain. Political decision-makers need to facilitate the use of economic means to support the transformation in the society and affected industries to balance the initial economic disadvantages of the electrically powered systems until they pass the cost disadvantage turning point. The development of the relevant technology is no longer a great barrier as it was at the beginning of this transformation, about 20 years ago. The technology for electrically powered transportation systems and devices is widely available now, although it is continuously evolving and being improved. Associated industries cannot be expected to initiate, finance, take the risk, and take the lead in this global societal transformation without clear and strong political support.

(1) Background: Metabolic syndrome is associated with cardiovascular complications. Therefore, this study aims to establish cut points for the conicity index based on the components of the metabolic syndrome and to associate it with characteristics sociodemographic, food consumption and occupational factors in Brazilian rural workers; (2) Methods: Cross-sectional study carried out with farmers. The receiver operating characteristic curve was calculated and the cutoff points for the conicity index were identified by the area under the curve, sensitivity and specificity. The variables included in the binary logistic regression analysis were selected by considering p &lt; 0.20 in the bivariate test; (3) Results: The cut points were similar in females according to both criteria, resulting in a single cut-off of 1.269. In males, the cut points showed differences, resulting in 1.272 according to the NCEP-ATP III and 1.252 according to the IDF. We have shown that younger people, those who work more than 40 hours a week and the lowest contribution of culinary ingredients are associated with increased odds of abdominal obesity. While the consumption of the products they sell or produce decreases these chances; (4) Conclusions: The conicity index showed high discriminatory power for the identification of abdominal obesity in rural workers.

Obesity is treatment-resistant, and is linked with a number of serious, chronic diseases. Adult obesity rates in the United States have tripled since the early 1960s. Recent reviews show that an increased ratio of omega-6 to omega-3 fatty acids contributes to obesity rates by increasing levels of the endocannabinoid signals AEA and 2-AG, overstimulating CB₁R and leading to increased caloric intake, reduced metabolic rates, and weight gain. Cannabis, or THC, also stimulates CB₁R and increases caloric intake during acute exposures. The present meta-analysis reveals significantly reduced body mass index and rates of obesity in Cannabis users, in conjunction with increased caloric intake. We provide for the first time a causative explanation for this paradox, in which rapid and long-lasting downregulation of CB₁R following acute Cannabis consumption reduces energy intake and storage and increases metabolic rates, thus reversing the impact on body mass index of elevated dietary omega-6/omega-3 ratios.

Forest fire is a major ecological disaster, which has economic, social and environmental impacts on humans and also causes the loss of biodiversity. Forest officials issue the warnings to the public on the basis of fire danger index classes. There is no fire danger index for the country India due to the sparsely distributed meteorological stations. Previous studies suggest that Static Fire Danger Index (SFDI) as well as Dynamic Fire Danger Index (DFDI) have been derived from the satellite datasets. In this study, we have made an attempt to integrate both the Static and Dynamic fire danger indices and also used the Near Real Time (NRT) data sets that can be available for download through NASA FTP server after one hour of the satellite overpass. In this study, DFDI has been calculated from the MODIS Terra NRT Land Surface Temperature (MOD11_L2) and MODIS TERRA NRT surface reflectance MOD09. Finally, The Forest Fire Danger Index (FFDI) has been developed from the static and dynamic fire danger indices by the additive model and the overall accuracy was around 81.27%. Thus, the FFDI has been useful to predict the fire danger accurately and can be useful anywhere, where the meteorological stations are un-available.

.Bacground: Sepsis remains a major health challenge worldwide, characterized by a dysre-gulated host response to infection, leading to high mortality and morbidity in intensive care units (ICUs). The Fibrosis 4 (FIB-4) index, originally developed to assess liver fibrosis in hepatitis C patients, has recently been explored for its potential prognostic value in sepsis patients. Method: This study retrospectively analyzed 309 sepsis patients admitted to the Internal Me-dicine and Anaesthesia ICUs between December 12, 2021, and December 15, 2023, to inves-tigate the relationship between FIB-4 levels, Acute Physiology and Chronic Health Evaluation (APACHE), and Sequential Organ Failure Assessment (SOFA) and clinical outcomes. Results: The study found that higher FIB-4 measurements were statistically significantly asso-ciated with increased 28-day mortality, with a cut-off value of 4.9 providing a sensitivity of 54.92% and specificity of 74.25%. Logistic regression analysis indicated that elevated Conclusion:FIB-4 levels were a significant predictor of early mortality, suggesting that the FIB-4 index could serve as a valuable prognostic tool in assessing the severity and prognosis of sepsis patients.

This work uses a new approach to investigate the Riemann hypothesis, drawing conclusions about its trueness. It is based on the more general method presented in a very recent publication, by the same author, showing in detail how to approach that very well-known and interesting problem. This is achieved by means of the theory of dynamical systems (Poincaré index associated to equilibria of 2-dimensional systems) and the study of the zeros of the Dirichlet eta function, defined by a Dirichlet series. By using the well-known fact that the zeros of the eta function include all zeros of the Riemann zeta function in the (open) critical strip, excluded the critical line, ((0,1/2) ∪ (1/2,1)) × (−∞,∞), the development proceeds using only the eta function. In addition, the open and simply connected region (1/2,1) × (0,∞) is used along the text, taking into account the symmetries of zeros of the functions under analysis in the critical strip. The basic line of proof is to find the mathematical expression for the Poincaré index of the vector field associated to the eta function, assuming the existence of a zero of the eta function outside the critical line (in (1/2,1) × (0,∞)), and investigating the resulting unfoldings. Eventually, an inconsistency occurs and the proof ends by contradiction.

Accurate estimation of chlorophyll content in wheat leaves can not only reflect its growth and nutritional status, but also provide a scientific basis for field management. In order to evaluate the potential of hyperspectral data to estimate the chlorophyll content of wheat leaves, this study focused on the leaves of wheat at the flag-picking stage, flowering stage, grain filling stage and maturity stage. Based on the framework of five vegetation indexes, the spectral index was con-structed by using the combination of 400-1000nm bands, and the correlation between the con-structed spectral index and the measured chlorophyll value was analyzed, and the optimal spectral index was screened by the correlation coefficient. Based on the optimal spectral index, polynomial regression, random forest, decision tree and artificial neural network were used to establish the estimation model of chlorophyll value, and the optimal model for estimating the chlorophyll value of wheat leaves was selected through model evaluation. The results showed that the five optimal spectral indices at the four growth stages were mainly composed of red band, red edge band and near-infrared band, and the five optimal spectral indices at the grain filling stage had the highest correlation with the chlorophyll value, and the absolute value of the cor-relation coefficient was greater than 0.73, the accuracy of the estimation model established in the four growth stages was different, and the estimation accuracy of the flag stage was the best, with R² and RMSE of 0.79 and 2.63, respectively. The above results show that hyperspectral data is suitable for estimating the chlorophyll value of wheat leaves, and the PR model of flag picking period can be used as the optimal model for estimating the chlorophyll value of wheat leaves.

Plums are primarily marketed for fresh consumption, canning, freezing, jam and jelly. Unfortunately, plum consumption has remained steady or declined. Consumers complain about a lack of flavor quality but are willing to pay for higher quality. Thus, lack of flavor and cold storage disorders are the main barriers to consumption. Plum cultivars are susceptible to gel breakdown, flesh browning and ‘off flavors’. Consumer acceptance and postharvest life are highly dependent on genotype, quality attributes, harvest date and proper postharvest handling. A consumer quality index (CQI) based on soluble solids concentration (SSC) and minimum firmness is proposed to maximize flavor and postharvest life. In most cases, late harvest increases quality attributes. Our work and industry experience demonstrated that using critical bruising thresholds (CBT) based on minimum firmness measured at harvest acts as a reliable predictor of how late to harvest safely for maximum visual and sensory quality. Plums are well adapted to late harvest because of their low susceptibility to bruising damage, but proper postharvest temperature management and marketing within the potential market life are necessary to maintain flavor and avoid the onset of storage disorders. Thus, to maximize flavor and postharvest life, a CQI based on SSC and minimum firmness measured at consumption is proposed. This article provides guidance on using this CQI, combined with proper postharvest handling techniques such as correct harvest date determination and temperature management, to maintain quality and increase consumption.

Climate change, the scarcity of fossil fuels, technical advances in clean energy, and the volatility of crude oil prices are just a few of the factors that have prompted the world to recognize clean energy as a viable alternative to dirty energy. As part of the Paris Climate Accord of 2015, many countries agreed to change their economies to be more sensitive to climate change. Due to this Accord, which increased interest from investors and decision-makers, investments in clean energy companies have benefited [1,2]. Clean energy stocks, which are a part of the larger world of tradable reserves, might experience pricing inefficiencies. In this paper, we investigate the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets like gold, crude oil, and natural gas between January 1, 2018, and March 9, 2023, which covers periods of low volatility and financial instability (2020 and 2022 events). To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings demonstrated that both periods exhibit severe multifractal and significant asymmetry, indicating that the price indices under study are not at all efficient.

The present paper is concerned with the study of the quality of life index. Such an index has become an important index for measuring the well-being of individuals. However, the quality of life index is always a subjective, intangible, and often hard to quantify with precision due to the lack of quantitative models dealing with. The main goal of the present paper is thus to propose a mathematical, quantitative model for the measurement of a quality of life index. The main novelty is firstly the construction of a wavelet dynamic multiscale model to quantify and investigate the effect of time scale on the quality of life index measuring. The proposed procedure is acted empirically on a sample corresponding to Saudi Arabia as a case of study during the period from 2003 to 2020 as part of the 2030-vision plan. Saudi Arabia has implemented the so-called 2030-vision plan where the quality of life improvement is one of the main goals to be attempted. The findings show that wavelets are capable to localize the time-wise behavior of the index contrarily to classical studies which estimate a global view of the index. Moreover, the study shows the link between the quality of life behavior and many other indices.

In this paper, a plasmonic refractive index sensor based on metal insulated metal waveguide (MIM) with three rings and a resonant cavity is first proposed and numerically evaluated. Next, we add four teeth to the sensor structure. We study and simulate the resonant wavelengths and refractive index of resonators using the time difference finite difference method. Given that the sensor and the conduction characteristics of plasmonic waves are influenced by the structure parameters,Therefore, by changing the refractive index and changing the dimensions and coordinates of the cavity and rims, we can change the passage coefficient in the resonant modes and measure the sensor performance. As a result, we obtain the sensitivity coefficient, the figure of merit (FOM) and the quality factor Q of the sensor. We modulate the resonance wavelength FWHM using the generated modes and reach a sensitivity of 2166 nm / RIU. These plasmonic sensors with a simple framework and balanced performance and high optical resolution can be used to measure the refractive index in the medical, chemical and food industries.

The fabrication of thin-film multilayer structures by sputtering technique usually requires multi-cathode deposition machine. This study proposes a simpler approach based on the RF power modulation: silicon nitride (SiN$_x$) thin films were prepared by RF reactive sputtering in (Ar + N$_2$) atmosphere at room temperature. The samples were analyzed to highlight the effects of different deposition conditions on the morphological and optical properties of the films in the visible and near/mid-IR regions. The refractive index of the films was changed in the range of 1.5 - 2.5 (at $\lambda$=800 nm) by tuning the sputtering power. IR reflectance measurements revealed the absence of spurious (oxygen- or hydrogen-based) phases, while atomic force and scanning electron microscopies confirmed the presence of flat and defect-free samples surfaces.

Let G be a graph with n vertices and let 1; 2; : : : ; n be the eigenvalues of Randic matrix. The Randic Estrada index of G is REE(G) = Ón i=1 ei . In this paper, we establish lower and upper bounds for Randic index in terms of graph invariants such as the number of vertices and eigenvalues of graphs and improve some previously published lower bounds.

The fatty-acid profiles of five main commercial pistachio cultivars, including Ahmad-Aghaei, Akbari, Chrok, Kalle-Ghouchi and Ohadi, were determined by gas chromatography: palmitic (C16:0), palmitoleic (C16:1), stearic (C18:0), oleic (C18:1), linoleic (C18:2), linolenic (C18:3) arachidic (C20:0) and gondoic (C20:1) acid. Based on the oleic to linoleic acid (O/L) ratio, a quality index was determined for these five cultivars: Ohadi (2.40) < Ahmad-Aghaei (2.60) < Kale-Ghouchi (2.94) < Chrok (3.05) < Akbari (3.66). Principal component analysis (PCA) of the fatty-acid data yielded three significant PCs, which together account for 80.0% of the total variance in the data set. A linear discriminant analysis (LDA) model evaluated with cross validation correctly classified almost all samples: the average percent accuracy for the prediction set was 98.0%. The high predictive power for the prediction set shows the ability to indicate the cultivar of an unknown sample based on its fatty-acid chromatographic fingerprint.

Most of the research of mental fatigue evaluation mainly concentrated on some indexes that require sophisticate and large instruments which make the detection of mental fatigue cumbersome, time-consuming, and difficult to apply on a large scale. A quick and sensitive mental fatigue detection index is necessary so that mental workers can be alerted in time and take corresponding countermeasures. But to date, no studies have compared the sensitivity of common objective evaluation indexes. To solve these problems this study recruited 56 human subjects. These subjects were evaluated using six fatigue indexes: the Stanford sleepiness scale, digital span, digital decoding, short-term memory, critical flicker fusion frequency (CFF), and speed perception deviation. The results of fatigue tests before and after mental fatigue were compared, and a one-way analysis of variance (ANOVA) was performed on the speed perception deviation. The result indicated the significance of this index. Considering individual differences, the relative fatigue index (RFI) was proposed to compare the sensitivity of the indexes. The results showed that when the self-rated fatigue grade changed from non-fatigue to mild fatigue, the ranges of RFI values for digital span, digital decoding, short-term memory and CFF were 0.175–0.258, 0.194–0.316, 0.068–0.139, and 0.055–0.075, respectively. Correspondingly, when the self-rated fatigue grade changed from non-fatigue to severe fatigue, the ranges of RFI values for the above indexes were 0.175–0.258, 0.194–0.316, 0.068–0.139, and 0.055–0.075, respectively. These results suggest that the sensitivity of the digital decoding, digital span, short-term memory, and CFF decreased sequentially when the self-evaluated fatigue grade changed from no fatigue to mild or severe fatigue. The RFI individuality of the speed perception deviation is highly variable and is not suitable as an evaluation index. In mental fatigue testing, digital decoding testing can provide faster, more convenient, and more accurate results.