Nitrogen (N) is an essential macro nutrient for crop growth; therefore, N deficit can greatly limit crop growth and production. In the North China Plain (NCP), winter wheat is one of the main food crops, and its yield has increased from approximately 4000 kg ha-1 to 6000 kg ha-1 in the last two decades. Determining the proper N application rates at different growth stages and in all seasons is very important for the sustainable and high production of wheat in the NCP. A field experiment with five N application rates (250, 200, 150, 100, and 40 kgN·ha-1, designated as N250, N200, N150, N100, and N40, respectively) was conducted during the 2017-2018 and 2018-2019 winter wheat seasons to investigate the effects of the N application rate on water- and fertiliz-er-utilization efficiency, and on the crop growth and yield of winter wheat under sprinkler fer-tigation conditions. The results showed that, in the N application range of 40-200 kg ha-1, crop yield and water- and fertilizer-use efficiencies increased as the N application rate increased; however, further increases in the N application rate did not have additional benefits. The N up-take after regreening of winter wheat linearly increased with crop growth. Considering the wheat yield and N-use efficiency, the optimal N application range was 200 kg ha-1, and the best top-dressing strategy was equal amounts of N applied at the regreening, jointing, and grain-filling stages. The results of this study will be useful for optimizing field N management to achieve high wheat yield production in the NCP and in regions with similar climatic and soil environment conditions.

In the 21st century, climate change and its consequences are getting more serious. The changes in temperature and precipitation alter the run-off conditions, subsequently influencing the channel processes of rivers. The study aims to analyse the hydrological changes of a small, sub-alpine river (Rába River, Central Europe) and the bank erosional processes since the 1950s. The bank erosion was determined based on topographical maps, aerial photographs, and RTK–GPS surveys. Short (2–3 days) floods were common between 1950–1980, and low stages occurred in 65–81% of a year. However, in the 21st century, extreme regimes developed, as record-high, flashy floods alter with long low stages (91–96% of a year). The bank erosion shows a cyclic temporal pattern, gradually increasing until it reaches a high value (4.1–4.9 m/y), followed by a limited erosional rate (2.2–2.8 m/y). However, the magnitude of the bank erosion is decreasing. It could be explained by (1) the lower transport capacity of the more common low stages and (2) the seasonal shift of the flood waves, appearing in the vegetational period when the riparian vegetation can more effectively protect the banks from erosion.

Introduction: The aim is to investigate the possibility of altering the delusional perceptions of psychotic patients by exposing them to a cognitively flexible virtual environment. A flexible vir-tual reality (VR) environment could challenge and enhance the ability to adapt to changing situa-tions and generate novel solutions to core psychotic symptoms. Materials and methods: A systematic review was conducted using different combinations of keywords in different databases. This study was conducted using the PRISMA statement. Results: There is a growing literature on the use of VR to manipulate and normalise perceptual distortions in psychosis. Over the last decade, the number of published studies on VR in mental health has increased 14-fold. Conclusions: A cognitive flexibility virtual environment can alter delusional perception by ex-posing the person to different scenarios that require them to question their assumptions, test their hypotheses, and revise their beliefs. Commonly used biosensors measure heart rate, skin con-ductance and body temperature in relation to different emotional states. Recently, there has been a major shift towards the use of neuroimaging techniques to better understand the pathophysiology of mental disorders. This is where the new wave of biosensor-integrated virtual reality (VR) sys-tems comes in.

We propose a pricing formula for a defaultable zero-coupon bond with imperfect information under a regime-switching model using a structural form of credit risk modelling. While the value of the firm’s equity is observed continuously, we assume that the total value of the firm is only observed at discrete times, such as the dates of the release of the firm’s annual reports, or quarterly reports. This uncertainty about the true value of the firm results in credit spreads that do not approach zero as the debt approaches maturity, which is a problem with many structural models. The firm’s value is typically defined as its equity and debt; however, we consider the asset-to-equity ratio, an accounting ratio used to examine a firm’s financial well-being. A dependent regime-switching process models the components of this ratio, and the Markov chain represents the states of the economy. The main contribution is to study this problem when the dynamics of a firm’s assets have different parameters with regime changes.

According to the Water Framework Directive, the Ecological Flow (Eflow) is assumed to be the minimum water discharge required to achieve and maintain the environmental objectives of “good quality status” in a natural water body. It is highly recognized that, the hydrological regime of natural flow plays a primary and crucial role influencing the physical conditions of habitats, which in turn determines the biotic composition and sustainability of aquatic ecosystems. Furthermore, the simple assumption to supply a minimum instream during dry periods is not enough any longer in order to protect the river environment. The recent hydro-ecological understanding states that all flow components might be considered as operational targets for water management, starting from base flows (including low flows) to high and flood regimes in terms of magnitude, frequency, duration, timing and rate of change. Several codes have been developed and applied on different case studies in order to define common tools to be implemented for the Eflow assessment. The study proposes the application of the Indicators of Hydrologic Alteration methodology (IHA by TNC) coupled to the valuation of the Index of Hydrological Regime Alteration (IARI by ISPRA) as an operative tool to define the ecological flow in each monitoring cross section to support the sustainable water resources management and planning. The case study of Agri River, in Basilicata (Southern Italy) is presented. The analyses have been carried out on monthly discharge data derived applying the HEC-Hydrological Modelling System at the basin scale using the daily rain data measurements obtained by the regional rainfall gauge stations and calibrated through the observed inlet water discharge registered at the Lago del Pertusillo reservoir station.

Drought affects human and natural systems, human and animal life and health, and socioeconomic activities. Drought consequences depend on its type and class, but also on the preparedness and resistance of communities to this climate disturbance. In the last decades, droughts accounted for about 16% of the total number of disasters but were responsible for 95% of the number of deaths and 26% of economic losses in Africa. This study aims to assess the drought regime in Southern Africa based on drought and vegetation indices. The SPI and SPEI were calculated at different timescales, using ERA5 data for the 1971 – 2020 period. The spatiotemporal distribution of drought descriptors was analyzed and compared with the patterns of the NDVI, EVI and VCI vegetation indices. The results reveal (i) the occurrence of droughts of various classes and at different timescales throughout the study period and region, (ii) high spatial variability in the number, duration, severity and intensity of drought, which tends to decrease with increasing timescale, (iii) high spatial-temporal agreement between drought and vegetation indices that confirm the dryness of vegetation during drought. These results aim to support policymakers in defining legislation to manage drought and water resources.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

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.

This paper investigates five different GARCH models (GARCH, EGARCH, IGARCH, Component GARCH (CGARCH) and GJR-GARCH) along with six distributions (Normal, Student’s t, GED and their skewed forms), which are used to forecast the volatility for the Bulgarian Stock index SOFIX. We use a GARCH model to predict how much time it will take, after the latest crisis, for the SOFIX index to reach its historical peak once again. The empirical data covers the period between the years 2000 and 2024, including the 2008 financial crisis and the COVID-19 pandemic. The purpose is to answer which of the five models is the best at forecasting the volatility of SOFIX and which distribution is most appropriate. The results, based on BIC and AIC information criteria, show that the ARMA(1,1)-CGARCH(1,1) specification with the Student t-distribution is preferred for forecasting. With the help of 5000 simulations, it is estimated that the chances of Index SOFIX reaching its historical peak value of 1976.73 (08.10.2007) are higher than 90% at 13.08.2087.

GR4J (Genie Rural a 4 parame`tres Journalier) is a rainfall-runoff model widely used to modelling rainfall into discharge. In this model, the input data used are daily rainfall and evapotranspiration data, calibrated using daily observed discharge data. This model seeks the optimum parameter value that produces the minimum deviation or error. The Nash-Sutcliffe Coefficient and Relative Volume Error (RVE) are used to estimate the errors that occur. One of the modelling parameters, namely X4 (peak time), has a value that does not match the observed hydrograph peak time (Tp). For this reason, it is necessary to adjust the modelling equation so that the unit hydrograph of the model appropriately in terms of value and shape with observed unit hydrograph. This study examines ten watersheds in Java Island so that it is expected to represent catchment conditions in tropical areas and developing countries. A relationship was obtained between the difference peak time from modelling (X4) and observed Tp. Adjustments Formula can be made to the general GR4J modelling equation for unit hydrograph in Java Island watersheds.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

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.

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

Distributed/semi-distributed models are considered to be sensitive to the spatial resolution of the data input. In this paper, we take a small catchment in high urbanized Yangtze River Delta, Qinhuai catchment as study area, to analyze the impact of spatial resolution of precipitation and the potential evapotranspiration (PET) on the long-term runoff and flood runoff process. The data source includes the TRMM precipitation data, FEWS download PET data, and the interpolated metrological station data. GIS/RS technique was used to collect and pre-process the geographical, precipitation and PET series, which were then served as the input of CREST (Coupled Routing and Excess Storage) model to simulate the runoff process. The results clearly showed that, the CREST model is applicable to the Qinhuai catchment; the spatial resolution of precipitation had strong influence on the modelled runoff results and the metrological precipitation data cannot be substituted by the TRMM data in small catchment; the CREST model was not sensitive to the spatial resolution of the PET data, while the estimation fourmula of the PET data was correlated with the model quality. This paper focused on the small urbanized catchment, suggesting the influential explanatory variables for the model performance, and providing reliable reference for the study in similar area.

This study analyzes future hydrological droughts in LCKW using the SWAT model and data from 2010-2021, evaluating the Streamflow Drought Index (SDI) for 5, 10, 25, and 50-year return periods (RP) for 2029 and 2039 under RCP4.5 and RCP8.5 scenarios. The model shows high accuracy (R² = 0.82, NSE = 0.78). Under RCP4.5, streamflow may increase by 34.74% and 18.74%, while RCP8.5 predicts significant decreases of 37.06% and 55.84%. Historical data reveal frequent short-term droughts during SDI-3, notably in 2014–2016 and 2020–2021, with SDI-6 indicating less frequent but severe droughts, especially in 2015 and 2020. Future projections under RCP8.5 suggest wors-ening drought conditions in 2029 and 2039, with critical drought periods from January to April and November. Wavelet analysis indicates a high risk of severe hydrological drought in LCKW due to low annual recurrence rates, with the highest drought severity over a 50-year RP. The study high-lights an increasing likelihood of frequent and severe droughts, particularly under high emission scenarios such as RCP8.5, which could result in significant water shortages and ecosystem disrup-tions. It emphasizes the significance of adaptive water resource management strategies in mitigating negative impacts on water security and ecosystem health.

As one of the typical deposits in Sichuan-Yunnan-Guizhou Pb-Zn metallogenic province, the Daliangzi Pb-Zn deposit has a close genetic relation with the structural system of “black/fracture zone” formed under the action of NWW-approx. EW strike-slip structures in the metallogenic province, but the mechanism of rock and ore-controlling action of the structural system remains unclear. Based on detailed analysis of tectonite-mineralized alteration lithofacies of R1 “black/fracture zone”, the tectonite-mineralized alteration lithofacies zones can be divided into 4 types in succession outward from the Pb-Zn mineralization center, i.e., ① brecciated and stockwork-like Pb-Zn mineralization-complex breccia facies zone, ② stockwork-like Pb-Zn mineralization-simple breccia and cataclasite facies zone, ③ veined pyrite-sulfide-dolomitic cataclasite facies zone, and ④ fine-veined calcite-black carbonized dolomite facies zone; Cl- and SO42--rich high-temperature oxidizing ore-bearing fluid mixes with reducing fluid in Zone ① while migration and precipitation occur in Zone ④. With the evolution of ore-forming fluid, the homogenization temperature decreases from Zone ① to Zone ④, the salinity increases from Zone ① to Zone ② and then decreases to Zones ③ and ④, and the fluid density has little change on the whole; the contents of Zn, Pb, Cu, Ga, Ge, Cd, Ag, and other metallogenic elements, the Zn/Pb ratio, and the CaO/MgO mole ratio decrease gradually from Zone ① to Zone ④; and REE fractionation, calcilization, silicification, and pyritization enhance gradually from Zone ① to Zone ④. This series of changes are the product of diapirism (cryptoexplosion) of strike-slip structures and “black/fracture zone”, among which the second-order structures (F5, F100, and other faults) derived from NWW-approx. EW striking dextral shear-tension faults F1 and F15 control the brecciated and stockwork-like Pb-Zn mineralized complex breccia facies zones and the stockwork-like Pb-Zn mineralized simple breccia and cataclasite facies zones. Therefore, this paper establishes the zoning mode of tectonite-mineralized alteration lithofacies of “black/fracture zone” and proposes that Zones ① and ② are important prospecting criteria. conclusions.

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.

Aim of the study was to determine the influence of climatic and hydrological changes on the growth of Scotch pine (Pinus sylvestris L.) and Black alder (Alnus glutinosa (L.) Gaertn) in the Narew National Park over past 50 years. The researches were based on tree increment cores extracted from 42 pine trees and 57 alder trees ranging in age from 25 to 88 years and climatic (temperature and precipitation for Bialystok) and hydrological (water level of the Narew River) data. Standardized data (5-year index) were analysed by species, generation (Y - 21-40 years, M - 41-60, O - 61-90) and decade using correlation analysis. The results of the study show that pine responded more strongly to changes in air temperature and changes in precipitation totals, while alder growth was more strongly related to fluctuations in the water level of the Narew River. The most variable climatic and hydrological conditions and the most difficult conditions for tree growth prevailed in the first and last decades (1971-1980, 2011-2020). The decrease in the water level of the Narew River that occurred over the last 50 years did not adversely affect the condition of the trees. Analysis of DBH growth rates showed that the younger generations (Y, M) grow faster than the older generation (O). One of the reasons for the accelerated tree growth and increased resistance to the decline in the water level of the Narew River may be the increase in CO2 concentration in the atmosphere. Accelerated tree growth and increased resistance to drought may have certain consequences like increased damage from wind as a result of the decrease in wood density or decline in the sensitivity of trees to climate and hydrological changes. However, less sensitivity to changes in climatic conditions may only apply to older trees.

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.

:. Background and Objectives: Pulmonary embolism, PE, incidence had been increasing in the last ten years. Computed thoracic pulmonary angiography, CTPA, had a major role in confirming PE di-agnosis.The main purpose of the study was to establish the prognostic value of a CTPA parameter: pulmonary artery obstruction index, PAOI, for PE risk assessment . A second objective of the re-search was to investigate the predictive accuracy of biomarkers (D-dimer, and cardiac Troponin T, c-TnT ), and PAOI, in 7-day mortality. The third objective of the study was the relationship between PAOI, and these biomarkers, in different etiologies of PE. Materials and Methods: The study com-prised 109 patients with PE, hospitalized, and treated between February 2021, and August 2022. They had different etiologies: deep vein thrombosis, DVT; persistent atrial fibrillation, AF; chronic obstructive pulmonary disease, COPD, exacerbation; Covid; and cancers. The investigations were the following: clinical examination; D-dimer testing, as a mandatory method for PE suspicion( values ≥ 500 µg/L were highly suggestive for PE); c-TnT , as a marker of myocardial injury(values ≥ 14 ng/L were abnormal); CTPA, with right ventricle dysfunction, RVD, signs, and PAOI. Treat-ments were according to PE risk: systemic thrombolysis (in high risk , and hemodynamic instability); low weight molecular heparins, LWMH, after systemic thrombolysis, or in high risk PE, with he-modynamic stability; direct oral anticoagulants, DOAC (in low, and intermediate risk). Results: The relationship PAOI- D-dimer, and PAOI- c-TnT, had very strong statistical correlation, for the entire sample, and for DVT, AF, COPD, Covid subgroups ( Rho = 0.815-0.982). PAOI had a high predic-tive accuracy for intermediate , and high risk together (area under curve, AUC=0.948), and high risk PE (AUC= 0.993). For 7-day mortality, D-dimer , and c-TnT had high predictive accura-cy(AUC=0.921, and 0.979). PAOI had statistical significance for 7-day mortality in Covid (p=0.045), and cancer (p=0.038) patients. Conclusions: PAOI was an important tool for PE risk as-sessment. D-dimer , and c-TnT were valuable predictors, for 7-day mortality in PE. PAOI, and D-dimer; PAOI, and c-TnT were strongly correlated, for the entire PE sample, and for DVT, AF, COPD, and Covid patients.

Purpose: The purpose of this study is to apply the Composite Radiographic Index modified (CRIm) in CBCT scans of patients with Medication related osteonecrosis of the jaws (MRONJ) in order to detect its validity, and corelate the radiologic findings with the clinical staging of the disease. Methods: This study included 43 patients with MRONJ diagnosis and CBCT scans performed in the School of Dentistry and approved by the Research Ethics Committee. Clinical staging for every patient (0-3) was provided according to AAOMS 2022 guidelines. In cases of patients with both jaws affected, each jaw was evaluated independently resulting to 52 CBCT scans. The 52 CBCT scans were assessed under standardized viewing conditions by 2 observers who evaluated independently the following 8 radiologic features: lytic changes, sclerosis, periosteal reaction, sequestration, non-healing extraction sockets and other findings (sinus implication, inferior alveolar canal involvement, jaw fracture). The CRIm index was constructed to assess the extent of osseous changes. The radiologic features were scored as absent (0), localized/single (1), extensive/multiple (2), yielding a theoretical range of 0–12. For statistical analysis Fisher’s exact test and Spearman’s correlation coefficient were performed. Results: A statistically significant association of clinical stage with lytic changes, sequestration and inferior alveolar canal involvement was found. Also, a statistically significant correlation of clinical stage with CRIm index classification was obtained. Conclusions: The CRIm index tends to increase as the clinical stages of MRONJ advance, suggesting a correlation between the clinical stage of MRONJ and the CRIm index.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

.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.

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.

Background: The Advanced Lung Cancer Inflammation Index (ALI) is a novel, comprehensive index that integrates inflammation and nutritional status, incorporating parameters such as albumin, body mass index (BMI), and the neutrophil-to-lymphocyte ratio (NLR). Unlike traditional inflammation biomarkers, this study aims to evaluate the prognosis of IPF patients by considering both inflammation and nutritional status. Method: A total of 102 patients with IPF were included in the study. Clinical data were obtained from the patients’ medical records. NLR and ALI score were calculated based on data collected at the initiation of antifibrotic treatment using the following formula: Neut/Lym and albumin × BMI / NLR. Results: IPF subject subgroups in terms of ALI based on gender–age–physiology (GAP) stages (1,2,3), FVC (median split, <70% vs ≥70%), DLCO (<51% vs ≥51%), 6-Minute Walk Test (6MWT) (<350 vs ≥350) and CCI (≤1 vs >1). ALI showed significant difference depending on the categories of GAP stage, FVC, DLCO, and 6MWT but these differences were not observed based on the charlson comorbidity index (CCI) categories (sırasıyla p=0.000, p=0.000, p=0.000, p=0.001, p=0.233). Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the sensitivity and specificity of ALI, albumin, NLR, and BMI in determining the mortality risk in IPF patients. ALI demonstrated a sensitivity of 63.6% and a specificity of 98.9% at a threshold of 11.2 (AUC = 0.945, 95% CI 0.892–0.998, p < 0.000). Conclusion: We determined that ALI levels are significantly associated with disease severity and mortality in patients with IPF.

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.

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.

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.

The effective utilization of medium-high temperature geothermal energy is pivotal in reducing carbon emissions and plays a crucial role in developing clean energy technologies. The MiDu ge-othermal field, situated in the southeastern region of Dali Prefecture, Yunnan Province, lies within the Mediterranean-Himalayan high-temperature geothermal belt and is characterized by abundant geothermal resources. However, due to its considerable depth, exploration poses significant risks, resulting in a total utilization rate of less than 0.5% of the total reserves. This study employs natural seismic data to perform a tomographic analysis of the geothermal system in the Midu basin. By examining the P-wave velocity (Vp) and velocity ratio of P-wave and S-wave (Vp/Vs) at various depths, the findings reveal that the basin comprises two distinct structural layers: the thrust basement of the Mesozoic and Paleozoic eras and the strike-slip extensional sedimentary layer of the Cenozoic era. A low-velocity anomaly in the central basin corresponds to the loose Cenozoic sedimentary layer. In contrast, high-velocity anomalies at the basin edges correlate with boundary faults and the Mesozoic-Paleozoic strata. Below a depth of 4 km, the Red River Fault and MiDu Fault continue to dominate the basin's structure, whereas the influence of the Malipo Fault dimin-ishes. The MiDu Fault exhibits higher thermal conductivity than the Yinjie Fault. It interfaces with multiple carbonate and basalt formations characterized by well-developed pores and fractures, making it a crucial conduit for water and a control point for geothermal storage. Consequently, the existence of high temperature geothermal resources for power generation should be concentrated around the Midu fault on the western side of the basin, while the Yinjie fault area is more favorable for advancements in heating and wellness.

While DNA serves as the fundamental genetic blueprint for an organism, it is not a static entity. Gene expression, the process by which genetic information is utilized to create functional products like proteins, can be modulated by a diverse range of environmental factors. Epigenetic mechanisms, encompassing DNA methylation, histone modification, and microRNAs, play a pivotal role in mediating the intricate interplay between the environment and gene expression. Intriguingly, alterations in the epigenome have the potential to be inherited across generations. Ethanol abuse poses significant health issues worldwide. Ethanol has the capability to induce changes in the epigenome, which can be inherited by offspring, thus impacting them even in the absence of direct ethanol exposure. This review article reviewed the alterations caused by ethanol on the epigenome. We thoroughly gathered all relevant papers investigating the behavioral and molecular consequences of parental ethanol exposure on their offspring. In conclusion, the comprehensive analysis of the literature supports the notion that ethanol exposure induces lasting epigenetic alterations, which can influence the behavior and health of future generations. This knowledge emphasizes the significance of addressing the potential transgenerational effects of ethanol and highlights the importance of preventive measures to minimize the adverse impact on offspring.

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

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.

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

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.

Background: Obesity remains a widely debated issue, often criticized for the limitations in its identification and classification. This study aims to compare two distinct systems for classifying obesity: Body Mass Index (BMI) and body fat percentage (BFP) as assessed by bioelectrical impedance analysis (BIA). By examining these measures, the study seeks to clarify how different metrics of body composition influence the identification of obesity-related risk factors. Methods: The study enrolled 1255 adults, comprising 471 males and 784 females, with a mean age of 36 ± 11.90 years. Participants exhibited varying degrees of weight status, including optimal weight, overweight, and obesity. Body composition analysis was conducted using the TANITA Body Composition Analyzer BC-418 MA III device (T5896, Tokyo, Japan), evaluating the following parameters: current weight, basal metabolic rate (BMR), adipose tissue (%), muscle mass (%), and hydration status (%). Results: Age and psychological factors like cravings, fatigue, stress, and compulsive eating were significant predictors of obesity in the BMI model but not in the BFP model. Additionally, having a family history of diabetes was protective in the BMI model (OR: 0.33) but increased risk in the BFP model (OR: 1.66). The BMI model demonstrates exceptional predictive ability (AUC=0.998). In contrast, the BFP model, while still performing well, exhibits a lower AUC (0.975), indicating slightly reduced discriminative power compared to the BMI model. Conclusions:BMI classification demonstrates superior predictive accuracy, specificity, and sensitivity. This suggests that BMI remains a more reliable measure for identifying obesity-related risk factors compared to the BFP model.

Climate change is a global issue that draws widespread attention from the international society. As an important component of the climate system, the water cycle is directly affected by climate change. Thus, it is very important to study the influences of climate change on the basin water cycle with respect to maintenance of healthy rivers, sustainable use of water resources, and sustainable socioeconomic development in the basin. In this study, by assessing the suitability of multiple General Circulation Models (GCMs) recommended by the Intergovernmental Panel on Climate Change, Statistical Downscaling Model (SDSM) and Automated Statistical Downscaling model (ASD) were used to generate future climate change scenarios. These were then used to drive distributed hydrologic models (Variable Infiltration Capacity, Soil and Water Assessment Tool) for hydrological simulation of the Yangtze River and Yellow River basins, thereby quantifying the effects of climate change on the basin water cycle. The results showed that suitability assessment adopted in this study could effectively reduce the uncertainty of GCMs, and that statistical downscaling was able to greatly improve precipitation and temperature outputs in global climate mode. Compared to a baseline period (1961–1990), projected future periods (2046–2065 and 2081–2100) had a slightly decreasing tendency of runoff in the lower reaches of the Yangtze River basin. In particular, a significant increase in runoff was observed during flood seasons in the southeast part. However, runoff of the upper Yellow River basin decreased continuously. The results provide a reference for studying climate change in major river basins of China.

This paper explores the Wilsonian renormalization group of probe-D-branes, focusing on the Dirac-Born-Infeld (DBI) action. The analysis involves deriving the constant of motion and formulating the Wilsonian renormalization group equation. The study extends to the infrared regime, considering both zero and non-zero temperatures. Additionally, thermodynamic aspects related to the functional form of the grand potential are discussed. The investigation provides insights into the renormalization of probe-D-branes and their thermodynamic properties.

Droughts have negative impacts on agricultural productivity and economic growth. Effective monitoring and accurate forecasting of drought occurrences and trends are crucial for minimizing drought losses and mitigating their spatial and temporal effects. In this study, trend dynamics in monthly total rainfall time series measured at Cape Town International Airport were analyzed using Mann-Kendall (MK) test, Modified Mann-Kendall (MMK) and innovative trend analysis (ITA) were examined. Additionally, we utilized hybrid prediction method that combined the model with the complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique, the autoregressive integrated moving average (ARIMA) model, the long short-term memory (LSTM) network (i.e. CEEMDAN-ARIMA-LSTM) to forecast SPI values of 6-, 9-, and 12-months using rainfall data between 1995 and 2020 from Cape Town International Airport meteorological rainfall stations. The results demonstrate the following essential points: (1) The trend analysis results of the total monthly rainfall values indicate a significant decreasing trend with the negative z-score (MK= -3.7541 and MMK= - 4.0773). ITA also indicated a significant downwards trend of rainfall in the study area. (2) As the forecasting horizon increases, the prediction accuracy of the models and CEEMDAN-combined models gradually improves, reaching their optimum performance at the 12-month horizon. (3) CEEMDAN efficiently stabilizes time-series data, resulting in greater prediction accuracy in the hybrid model compared to individual models at all timescales. (4) The RMSE and R2 values for the hybrid CEEMDAN-ARIMA-LSTM model at a 12-month forecasting horizon are 0.042 and 0.995, demonstrating the applicability of this hybrid approach for drought forecasting.

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.

Unquestionably the rapidly changing climate and, therefore, alterations in the associated bioclimate, constitute an alarming reality with implications in daily practice and natural capital management. In this research the present and projected bioclimate evolution over the phytogeographical regions of Greece is displayed. For this purpose, ultrahigh-resolution computation results on the spatial distribution of the Emberger index’s Q2 classes of bioclimatic characterisation are analysed and illustrated for the first time. The assessments are performed over the reference period (1970–2000) and two future time frames (2021–2040; 2041–2060) under the RCP4.5 and RCP8.5 emission scenarios. By 2060 and under the extreme RCP8.5, intense xerothermic trends are demonstrated owing to the resulting significant spatial evolution mainly of the Arid-Hot, Semi-Arid-Very Hot, Semi-Arid-Hot and Semi-Arid-Temperate Q2 classes, respectively, over the phytogeographical regions of Kiklades (up to 29% occupation), Kriti and Karpathos (up to 30%), West Aegean Islands (up to 26%), North East (up to 56%)–North Central (up to 31%). The RCP8.5 long-term period exhibits the strongest impacts over approximately the right half of the Greek territory the bioclimate of which appears as more dry-thermal in the future.

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.

The present article seeks to analyse the period 1938-1940, when the Romanian interwar democracy was suspended through the promulgation of the anti-liberal Constitution of 27 February 1938. The Constitution abolished the political parties and trade unions, replacing them with new institutions established according to royal decrees: the royal single party, known as the National Renaissance Front (Frontul Renaşterii Naţionale, FRN) and corporations of workers and employers, respectively. Starting from that moment, the regime, through its representatives, made recourse to a nationalist rhetoric directed against the democratic parliamentary system. Moreover, a cult of personality of the monarch can be identified in the speeches of the royal corporatist ‘parliament’, as well as in the doctrine of FRN and the Nation’s Party (its successor), but also in the regime’s youth organisation, ‘The Country’s Sentinel’ (Straja Ţării), whose First Sentinel was the authoritarian monarch himself. Thus, the cult of personality of Carol II represented one of the sources of inspiration for the dictator Nicolae Ceauşescu and for the leaders of this totalitarian regime.

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.

Pro-inflammatory cytokines play a role in the failure of β-cells in type 1 and type 2 diabetes. While existing data from ‘omics’ experiments allow for some understanding of the molecular mechanisms behind cytokine-induced dysfunction in β-cells, no report thus far has provided information on the direct imaging of the β-cell landscape with nanoscale resolution following cytokine exposure. In this study, we use Airyscan-based optical super-resolution microscopy of Insulinoma 1E (INS-1E) cells to investigate the structural properties of two subcellular membranous compartments involved in the production, maturation and secretion of insulin-containing granules, the Endoplasmic Reticulum (ER) and the Golgi Apparatus (GA). Our findings reveal that exposure of INS-1E cells to IL-1β and IFN-γ for 24 hours leads to significant structural alterations of both compartments. In more detail, both ER and GA fragment and give rise to vesicle-like structures with markedly reduced characteristic area and perimeter and increased circularity with respect to the original structures. These findings complement the molecular data collected thus far on these compartments and their role in β-cell dysfunction using and lay the ground for future optical-microscopy-based ex-vivo and in-vivo investigations.

Monte Carlo techniques have been extensively used for planning laser-based clinical procedures such as photobiomodulation. However, the effect of several biological tissue characteristics, including morphological structure and physiological parameters, has not been carefully addressed in many applications. Specifically, many questions remain concerning the effect of skin phototype and body mass index on the efficacy of photobiomodulation for extraoral therapies. To address these questions, a Monte Carlo simulation model was developed to analyze the effects of body mass index-dependent skin structure and Fitzpatrick skin type, specifically tailored for the morphological characteristics of cheek tissue. The model describes the settings of a typical oral photobiomodulation treatment protocol for pain relief, namely the use of 660 nm and 808 nm laser wavelengths and a therapeutic dose of 2.0 J/cm² on the masseter muscle. The simulations were used to train a machine learning predictive model aimed at accelerating the treatment planning stage and assessing the importance of patient-specific parameters. A multiple regression approach was adopted to predict muscle dose and treatment time for the effective delivered dose.

The International tax regime (ITR) has been transformed after the Great Recession of 2008–2009. The G20/Organization for Economic Cooperation and Development (OECD)’s Base Erosion and Profit Shifting (BEPS) project (2013–2015) has fundamentally changed the ITR, giving new life to the single tax principle (income should be taxed once, i.e., no double taxation and no double non taxation). Reaction to BEPS has varied dramatically between the EU and the US, the two largest markets in the world. In the EU BEPS is taken very seriously, as shown for example by the new Anti-Tax Avoidance Directives that implement the single tax principle. In the US BEPS is almost invisible; while the US model tax treaty has been amended to incorporate it the US has refused to sign the Multilateral Instrument to implement BEPS in its treaties and the only other BEPS action that the US has taken is country by country reporting. It thus appears that the future of BEPS and the ITR depends on whether the EU or the US view prevails, i.e., whether multinationals can be forced to pay significant tax on the 160–240 billion that are currently not taxed annually because of BEPS. While US multinationals as well as EU multinationals are exposed to the EU ATAD and related measures while operating in Europe, they are less subject to EU anti BEPS measures elsewhere in the world. It therefore is crucial to assess the reaction to BEPS in the other large economy that was involved in its development, namely China. This article attempts to assess China’s reaction to BEPS based on Chinese sources. It shows that China takes BEPS seriously. Therefore, given the reactions of China (as well as India, which is even more aggressive than China for example in taxing the digital economy) it seems likely that eventually the EU view of BEPS will prevail and US based multinationals will eventually be forced to pay tax on the over 100 billion they shift offshore each year.

The aim of this article is three-fold: firstly, it is to highlight how the different Bantustans with the focus to Transkei, Bophuthatswana, Venda, and Ciskei also know as the (TBVC) States secured extra territories. However, these Bantustans remained unrecognized in the international community because of their financial dependence to the apartheid regime. Secondly, the successes and failures of this process are fundamental in understanding the territorial monopolies of the Bantustans and thirdly we will interrogate how the Bantustan residents who were against the process mobilized other residents to reject the proposal and attempts of territorial expansion. Furthermore, this article contributes to the broader Bantustan’s historiography on the intended economic spin-offs with these endeavors. We contend that the above have received little scholarly attention. The methodology of this article draws from an historical approach and utilizes a range of different archival documentary sources, most importantly material housed in South Africa’s national archives and British Commonwealth archives. In conclusion, we argue in this article that these developments of territorial expansion had little benefits for the Bantustans and the extended territories adjacent to them.

The refractive index of seawater is one of the essential parameters in ocean observation, so it is necessary to achieve high-precision seawater refractive index measurements. A seawater refractive index measurement system based on position-sensitive detectors is an effective means to achieve high-precision measurement of seawater refractive index. However, in the actual seawater refractive index measurement process, the impact of the measurement error caused by the jitter signal obtained from the measurement on the measurement results cannot be ignored. In this paper, we theoretically analyse the causes of the long jitter signals during seawater refractive index measurement and quantify the influencing factors. Through the analysis, it can be seen that the angle between the two windows in the refractive index measurement area of seawater causes a great error on the measurement results, so the angle between the two windows should be controlled within 2.06° in order to effectively reduce the measurement error. At the same time, the factors affecting the measurement accuracy of the position-sensitive detector are analysed, and the factors leading to the reduction of the measurement accuracy of the position-sensitive detector are mainly the background light, the size of the photosensitive surface, and the change of the temperature of the working environment. For the above factors, we add a narrow-band filter with a bandwidth of 0.9nm in front of the photosensitive surface of the position-sensitive detector during the construction of the measurement system, so as to filter out stray light other than the signal light source. On the premise of ensuring the measuring range of the refractive index of seawater, a position-sensitive detector with a photosensitive surface size of 4 mm×4 mm was selected. In order to reduce the temperature variation of the working environment of the position-sensitive detector, the measurement system was partitioned. In order to validate the testing error range of the optimised test system, standard seawater samples under the same conditions were measured. It can be seen that the jitter signal of the measurement system has been reduced from 0.0022mm before the optimisation to 0.0011mm after the optimisation, and the deviation of the refractive index has been reduced by 1.09×10−8RIU. The experimental results show that the refractive index of seawater has been effectively reduced by adjusting the optical path and the structure of the seawater refractive index measurement system.

Multifunctional landscapes are complex systems that integrate biophysical, cultural-historical and socio-economic components into unique territorial structures and regional ensembles. Facing increasing pressures generated by urbanization, climate change and overexploitation of natural resources, assessing the sustainability of these landscapes has become an urgent priority. The present research is based on the development and parametrization of a new tool for evaluating the sustainability of multifunctional landscapes that aims to measure the level of biocultural resilience of a landscape, integrating biological, cultural and socio-economic indicators in a single analytical framework. This index, called the biocultural resilience index (BRI), provides a holistic perspective on the dynamics of landscapes, allowing the identification of vulnerability areas and the development of conservation and sustainable management strategies. The evaluation of the of multifunctional landscapes sustainability requires a comprehensive approach that has to integrate both biological aspects, such as biodiversity and ecosystem health, as well as identity and cultural aspects, such as cultural value and the relationship of the local communities with the environment. In this context, this study highlights the fact that the development of appropriate tools and methods for assessing and monitoring the sustainability of multifunctional landscapes becomes essential for their sustainable management and for protecting the benefits they offer to society. Our findings show that the biocultural resilience index (BRI) can be used in a variety of contexts and fields, including spatial planning, biodiversity conservation, sustainable rural development and ecotourism. In the meanwhile, this index offers a robust and flexible analytical framework, adaptable to the needs and particularities of different regions and communities.

Background and Objectives: To investigate the relationship between the SII index and the micro-macro complications and death that develop in the first year and the following 3 years, following the calculation of the index in type 2 diabetic retinopathy patients. Materials and Methods: This study was performed retrospectively with 523 type 2 diabetic retinopathy patients admitted to the endocrinology outpatient clinic of our hospital between January 2019 and December 2019. The demographic, and clinical characteristics of the patients were evaluated using descriptive statistics. Shapiro-Wilk test was used for the normal distribution of quantitative data; Mann-Whitney U, Mc Nemar Chi-square, and Cochran's Q tests were used to analyze SII values between groups and complication rates by years; sensitivity and specificity were determined by ROC analysis and considered statistically significant with a significance level of P

This paper proposes a method to utilize weather and land cover models to generate future environmental scenarios, and presents the watershed models to simulate the hydrological impact on watershed-scale hydrology. The Weather Generator model and General Circulation Model were applied to produce rainfall and local temperature under different climate conditions, and the Conservation and Land Use and its Effects model was incorporated to simulate future land cover variability. The circumstances of future climate and land cover changes were used as inputs to drive the HEC-HMS rainfall runoff model for obtaining surface runoff in a mountainous area. The WASH123D model was then utilized for the entire watershed simulation. Modeling results were then examined to discuss hydrological impacts on three different time periods: near future (2020-2039), future (2050-2069), and distant future (2080-2099). The Fengshan Creek basin in northern Taiwan was selected as study site. Simulations results indicated that the influence of climate change revealed more relevant effects when compared to local land cover changes. The ground water levels tended to diminish as the land cover area changed. In addition, both river and groundwater levels reveal that it is drier in dry season and wetter in wet season in future.

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.

We investigated the dynamics of a simple master equation describing the evolution of a probability distribution between two states, \( p_1 \) and \( p_2 \) (with \( p_1 + p_2 = 1 \)). Our focus is on the behavior of the entropy \( S \), the distance \( D \) from the uniform distribution (\( p_1 = p_2 = 1/2 \)), and the free energy \( F \). We define two ratios, \( \eta_S = \frac{dS/dt}{dF/dt} \) and \( \eta_D = \frac{dD/dt}{dF/dt} \), and find that both diverge to plus-minus infinity as the system evolves towards the uniform distribution. This divergence marks a critical transition point where the master equation temporarily loses physical meaning. However, after this divergence, the system settles into a new, well-behaved regime where the solutions stabilize at finite values, representing a new equilibrium or steady state. This two-regime behavior underscores the intricate dynamics of simple probabilistic systems as they approach and surpass equilibrium, providing insights into the complex interplay of entropy, distance, and free energy in statistical mechanics.

Chronic obstructive pulmonary disease (COPD) patients are particularly susceptible to respiratory infections like influenza, which exacerbate symptoms and increase healthcare utilization. While smoking cessation and influenza vaccination are recommended preventive measures, their combined impact on healthcare resource utilization is underexplored. The Charlson Comorbidity Index (CCI) assesses comorbidity burden in COPD patients and may influence healthcare outcomes. We conducted a retrospective analysis of 357 COPD patients, evaluating smoking cessation success over one year and influenza vaccination receipt, stratifying patients by CCI scores. Healthcare utilization outcomes included emergency room visits, hospitalizations, and medical expenses. Results showed that 51.82% of patients quit smoking and 59.66% received influenza vaccination, with higher comorbidity prevalence in advanced COPD stages (p=0.002). Both smoking cessation and influenza vaccination independently correlated with decreased emergency room visits, hospital admissions, days, and costs. Patients who both quit smoking and received influenza vaccination exhibited the lowest healthcare utilization rates. In conclusion, smoking cessation and influenza vaccination significantly reduce healthcare resource utilization in COPD patients, with the combination yielding synergistic benefits, particularly in those with lower CCI scores. Integrating these interventions and comorbidity management in COPD strategies is essential for optimizing patient outcomes and healthcare efficiency.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

The presence of the quantum Rayleigh scattering, or spontaneous emission, inside a dielectric medium such as a beam splitter or an interferometric filter, prevents a single-photon from propagating in a straight-line. Modelling a beam splitter by means of a unitary transformation is physically meaningless because of the loss of photons. Additional missing elements from the conventional theory are: 1) the quantum Rayleigh stimulated emission which can form groups of photons of the same frequencies, and 2) the unavoidable parametric amplification of single-photons in the original parametric crystal. An interference filter disturbs, through multiple internal reflections, the original stream of single-photons, thereby confirming the existence of groups of photons being spread out to lengthen the coherence time. The approach of modelling individual, single measurements with statistical ensemble probability amplitudes leads to the counterintuitive explanations of the experimental outcomes and should be replaced with pure states describing instantaneous measurements which are afterwards averaged.

One of the solutions of the Einstein equations, called McVittie solution, signifying a black hole embedded by the dynamic spacetime is studied. In the stationary spacetime the Mcvittie metric becomes the Schwarzschild-de Sitter metric (SdS). The geodesic of a freely falling test particle towards the black hole is examined in the SdS spacetime. It is found that unlike Schwarzschild case the potential of such particle becomes maximum at a point where it eventually stops to follow an unstable circular motion and then resumes its motion towards black hole center. It is shown that an observer or system of particles is spaghettified near the black hole singularity in the SdS spacetime. The dynamic of the universe in the framework of McVittie metric, being a generalized time dependent SdS solution, is represented in terms of that point, called stationary or turning point. The motion of the stationary point is studied in various regimes of the expanding universe and the possible outcomes are discussed in brief.

Poultry litter was converted to biochar by torrefaction and to hydrochar by hydrothermal carbonisation. Many parameters were measured for the resulting chars, to investigate the effect of production method and production temperature. SEM showed the presence of large quantities of crystalline material on the surface of the biochars. The elemental composition of some crystals was determined as 35% K and 31% Cl. This was confirmed as sylvite (KCl) crystals, which explains the high levels of water extractable potassium in the biochar and may also be important in germination inhibition. Biochars almost totally inhibited germination, whilst hydrochars decreased germination. Although germination occurred on hydrochar, root growth was severely inhibited. Consequently, germination index may be better to determine total phytotoxicity as it measures both effects and could be used as a bioassay for chars used as soil amendments. Washing removed germination inhibition in a low temperature char (3500C), possibly by removing KCl, however root toxicity remained. There were very low levels of heavy metals, suggesting they are not the source of toxicity. In biochars, pore mean size decreased with temperature from 3500C to 6000C, due to changes in pore size distribution. Mean pore size was measured directly using SEM. The merits of this method are discussed. Low temperature biochars seem best suited for fuel as they have high calorific value, high hydrophobicity, low ash content and high yield. Higher temperatures are better for soil amendment and sequestration applications with a smaller mean pore size, higher surface area, and higher pH.

Accurate and reliable mid-long runoff prediction (MLTRP) is of great importance in water re-sources management. However the MLTRP is not suitable in each basin and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index is developed in this study based on the predictor selection method using mutual information (MI) and partial MI (PMI). The relationship between the TMI and the predictive performance of five models is analyzed by applying five models in 222 forecasting scenarios in Australia. The results over 222 forecasting scenarios demonstrate that, compared with the MI, the developed TMI index can better represent the available information in the predictors, and has more significant negative correlation with the RRMSE with the correlation coefficient between -0.62 and -0.85. This means the model's predictive performance will become better along with the increase of TMI, and there-fore the developed TMI index can be used to evaluate the applicability of MLTRP. When TMI is more than 0.1, the available information in the predictors can support the construction of MLTRP models. In addition, the TMI is used to partly explain the difference of predictive performance among five models. In general, the complex models, which can better utilize the contained infor-mation, are more sensitive to the TMI, and have more significant improvement in terms of predic-tive performance along with the increase of TMI. This research can provide support for the study of MLTRP.

Background: The transversus abdominis plane (TAP) block has gained increasing importance as a very effective pain relief in for caesarean section. This study aimed to compare bupivacaine (Group B), bupivacaine with dexmedetomidine (Group BD) and bupivacaine with dexamethasone (Group BDx) applied in ultrasound-guided TAP block in the treatment of CS postoperative pain. Material and Method: American Society of Anesthesiologists I and II pregnant women who underwent cesarean section were included in the study. Forty patients were admitted in each group. All patients were applied TAP block with ultrasound guidance by administering the medications of the group in which they were included. Results: Body mass index (BMI) and operation duration were higher in Group B (p*=0.01 and 0.004, respectively). Instant tramadol requirement and amount were higher in Group B at some of follow up times. Patient satisfaction scale were better in Group BD and Group BDx. Conclusion: TAP block significantly reduces pain after cesarean section, prolongs the time to first analgesic request, and reduces the need for additional opioid analgesics. The addition of adjuvant to the TAP block usually improves the postoperative clinical condition. However, some special conditions such as body mass index (BMI) may negatively affect the clinical situation. Comprehensive, standardized, randomized controlled studies are needed to compare results under different conditions.

The objective of this paper was to verify the applicability of statistical learning (SL) compared to human reasoning with respect to the Universal Thermal Climate Index (UTCI), a complex tool for the assessment of outdoor thermal stress. UTCI is an equivalent temperature index based on the 48-dimensional output of an advanced model of human thermoregulation formed by 12 variables at four consecutive 30-minute intervals, which were calculated for 105642 thermal conditions from extreme cold to extreme heat. Comparing the performance of SL algorithms to the results accomplished by an international endeavor involving more than 40 experts from 23 countries, we found that random forests and k-nearest neighbors closely predicted UTCI values, but that clustering applied after dimension reduction algorithms (principal component analysis and t-distributed stochastic neighbor embedding) were inadequate for risk assessment in relation to the UTCI stress categories. This indicates a potential supportive role for SL, as it will not (yet) fully replace the bio-meteorological expert knowledge.

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

Heat index (HI) is a biometeorological indicator that combines temperature and relative humidity. This study aimed to investigate the relationship between heat index and daily counts of diarrhoea hospitalisation in Dhaka, Bangladesh. Data on daily diarrhoea hospitalisations and meteorological variables from 1981–2010 were collected. We categorised heat index of >94.3°F, >100.7°F and >105°F as high, very high and extremely high heat index, respectively. We applied time-series adjusted generalised linear model (GLM) with negative binomial distribution to investigate the effects of heat index and extreme heat index on hospitalisations for diarrhoea. Effects were assessed for all ages, <5 children and by gender. A unit higher HI, and high, very high and extremely high HI were associated with 0.8%, 8%, 7% and 9% increase in diarrhoea hospitalisation in all ages, respectively. The effects varied slightly by gender and were most pronounced in <5 children with a rise of 1°F in high, very high and extremely high HI associated with a 14.1% (95% CI: 11.3% – 17.0%), 18.3% (95% CI: 13.4% – 23.5%) and 18.1% (95% CI: 8.4% – 28.6%) increase of diarrhoea, respectively. This suggest that heat index may serve as an alternative indicator for measuring the combined effects temperature and humidity on diarrhoea.

Accurate streamflow forecasting is crucial for effectively managing water resources, particularly in countries like Colombia, where hydroelectric power generation significantly contributes to the national energy grid. Although highly interpretable, traditional deterministic, physically-driven models often suffer from complexity and require extensive parameterization. Data-driven models like Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) networks offer simplicity and performance but cannot quantify uncertainty. This work introduces Sparse Variational Gaussian Processes (SVGPs) for forecasting streamflow contributions. The proposed SVGP model reduces computational complexity compared to traditional Gaussian Processes, making it highly scalable for large datasets. The methodology employs optimal hyperparameters and shared inducing points to capture short-term and long-term relationships among reservoirs. Training, validation, and analysis of the proposed approach consider the streamflow dataset from 23 geographically dispersed reservoirs recorded during twelve years in Colombia. Performance assessment reveals that the proposal outperforms baseline Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) models in three key aspects: adaptability to changing dynamics, provision of informative confidence intervals through Bayesian inference, and enhanced forecasting accuracy. Therefore, the SVGP-based forecasting methodology offers a scalable and interpretable solution for multi-output streamflow forecasting, thereby contributing to more effective water resource management and hydroelectric planning.

Bifenthrin is a synthetic pyrethroid insecticide. It is used worldwide against different agricultural pests. Nervous system (NS) is the primary target organ for the pyrethroid group of insecticide which causes hyper excitation. The aim of this study to determine the effects of bifenthrin on the brain of rabbits. The animals were treated for 14 days with three different doses (1/5th, 1/10th and 1/15th of LD50) of bifenthrin. Neurotransmitters and Histopathological alterations were observed at the end of the experiments. Neurochemical parameters were checked 24 hours after the last dose. Significant changes in the level of biogenic amines were observed. The levels of epinephrine (EPN), dopamine (DA), 3, 4 dihydroxyphenylacetic acid (DOPAC) were decreased as compared to controls group with the increase in insecticide. However, norepinephrine (NE) and homovanillic acid (HVA) levels were found to be significantly higher than those of the controls. A significant reduction in the activity of the acetyl cholinesterase enzyme was found in the frontal cortex’s erythrocyte, plasma and brain of rabbit with the increase in administered bifenthrin. The oxidative stress showed significantly decrease in the activity of glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT) and glutathione S- transferase (GST) with the increase in dose of bifenthrin. Histopathological study of brain tissues showed normal GC (glial cells) and NC (neuronal cells) in the frontal cortex of brain tissue of control groups while the treated groups showed evacuation (odema), elongation of pyramidal nucleus, glial cell damage and brain haemorrhage.

Heritage bridges constitute an integral feature of the urban landscape in numerous cities. However, it is common for these structures to surpass their life cycle, rendering them ill-equipped to withstand the dynamic demands of users and extreme events, particularly hydrological occurrences. This research presents a methodology for the assessment of heritage riverine bridges, with a focus on the Grau Bridge in Peru as a case study. The investigation commences with an exhaustive literature review, complemented by a historical examination, followed by a preliminary diagnosis. Subsequently, hydrological and hydraulic studies are conducted, encompassing drone surveys of the riverbed and the bridge, soil analyses, and the application of 1D and 2D models in HEC-RAS. The outcomes of this comprehensive analysis reveal the high vulnerability of the Grau Bridge. Finally, strategic recommendations for its conservation are recommended.

Although congenital sensorineural hearing loss (SHL) in the bilateral cochleae mainly results from genetic abnormalities, chronic SHL progressing in later life is often influenced by systemic immune disturbances, including autoimmunity, chronic inflammation, and immunosenescence. We have investigated the relationship between the inner ear and systemic immunity and reviewed the possibilities to prevent SHL, including autoimmune SHL and age-related SHL. We also demonstrated two lymphocyte populations, interleukin 1 receptor type II (IL-1R2)-positive T cells (T1R2) and naturally occurring regulatory T cells (nTregs) in CD4⁺ T cells, which increase with aging, suppress host immune function and promote organ degeneration. Alterations in systemic immunity by fewer microbial antigen challenges in the living environment, elimination of immune suppressive lymphocytes, or immune rejuvenation with a reconstituted thymus may contribute not only to renew the cochlear function in SHL, but also to extend the healthy life of functional organs in a vigorous and youthful body, one of humanity’s greatest dreams.

Wound healing is a multi-factorial response to tissue injury, aiming to restore tissue continuity. Numerous recent experimental and some clinical studies, clearly indicate that probiotics applied topically promote the wound healing process. However, the precise mechanism by which they contribute to healing is not yet clear. Each strain appears to exert a distinctive, even multi-factorial action on different phases of the healing process. Given that a multi-probiotic formula exerts better results than a single strain, the pharmaceutical industry has embarked on a race for the production of a formulation containing a combination of probiotics, capable of playing a role in all the phases of the healing process. Hence, the object of this review is to describe what is known to date of the distinctive mechanisms of each of the most studied probiotic strains in order to further facilitate research towards the development of combinations of strains and doses, covering the whole spectrum of healing. Eleven probiotic species have been analyzed, the only criterion of inclusion being a minimum of two published research articles.

Groundwater represents a pivotal asset in conserving natural water reservoirs for potable consumption, irrigation, and diverse industrial uses. Nevertheless, human activities intertwined with industry and agriculture contribute significantly to groundwater contamination, highlighting the critical necessity to appraise water quality for safe drinking and effective irrigation. This research primarily focused on employing the Water Quality Index (WQI) to gauge water's appropriateness for these purposes. However, the generation of an accurate WQI can prove time-intensive owing to potential errors in sub-index calculations. In response to this challenge, an artificial intelligence (AI) forecasting model was devised, aiming to streamline the process while mitigating errors. The study collected 422 data samples from Mirpurkash, a city nestled in the province of Sindh, for a comprehensive exploration of the region's WQI attributes. Furthermore, the study probed into unraveling the interdependencies amidst variables in the physiochemical analysis of water. Diverse machine learning classifiers were employed for WQI prediction, with findings revealing that random forest and gradient boosting eclipsed other algorithms, achieving an accuracy rate of 99%. In close pursuit were SVM and XGBoost, registering accuracy scores of approximately 95% and 93%, respectively, while KNN and Decision Trees garnered accuracy rates of 88% and 87%, respectively. In addition to WQI prediction, the study conducted an uncertainty analysis of the models using the R-factor, providing insights into the reliability and consistency of predictions. This dual approach, combining accurate WQI prediction with uncertainty assessment, contributes to a more comprehensive understanding of water quality in Mirpurkash and enhances the reliability of decision-making processes related to groundwater utilization

This work presents a heat transfer and boiling model that computes the evolution of the temperature field in a representative steel workpiece quenched from 850 or 930°C by immersion in water flowing at average velocities of 0.2 or 0.6 m/s, respectively. Under these conditions, all three boiling regimes were present during cooling: stable vapor film, nucleate boiling, and single-phase convection. The model was based on the numerical solution of the heat conduction equation coupled to the solution of the energy and momentum equations for water. The mixture phase approach was adopted using the Lee model to compute the rates of water evaporation-condensation. Heat flux at the wall was calculated for all regimes using a single semi-mechanistic model. Therefore, evolution of boiling regimes at every position on the wall surface was automatically determined. Predictions were validated using laboratory results, namely: a) Videorecording the upward motion of the wetting front along the workpiece wall surface, and b) cooling curves obtained with embedded thermocouples in the steel probe. Wall heat flux calculations were used to determine the importance of the simultaneous presence of all three boiling regimes on the heat flux distribution. It was found that this simultaneous presence leads to high heat flux variations that should be avoided in production lines.

The origin of the nucleus remains a great mystery in life science, although nearly two centuries have passed since the discovery of nuclei. To date, studies of eukaryogenesis have focused largely on micro-evolutionary explanations. Here, we examined macro-patterns of C-values (the total amount of DNA within the haploid chromosome set of an organism) for over 110,000 species and the chromosome numbers for over 11,000 species and their potential links with the state of atmospheric oxidation over geological time. Eukaryogenesis was in sync with an over 2.5 order-of-magnitude increase in genome size from prokaryote to eukaryote, and also with a rapid rise of atmospheric oxidation, suggesting that eukaryogenesis would have resulted from a regime shift of genomes driven by the oxidation-driven complexification and structuralization (e.g. chromatin packing).

All allergic responses to food indicate failure of immunological tolerance but it is unclear why cow’s milk and egg (CME) allergies resolve more readily than reactivity to peanuts (PN). We sought to identify differences between PN and CME allergies through constitutive immune status and responses to cognate and non-cognate food antigens. Children with confirmed allergy to CME (n=6), PN (n=18) non-allergic (NA) (n=8) controls were studied. Constitutive secretion of cytokines was tested in plasma and unstimulated mononuclear cell (PBMNC) cultures. Blood dendritic cell (DC) subsets were analyzed alongside changes in phenotypes and soluble molecules in allergen stimulated MNC cultures with or without cytokine neutralization. We observed that in allergic children constitutively high plasma levels IL-1β, IL-2, IL-4, IL-5 and IL-10 but less IL-12p70 than in non-allergic children was accompanied by spontaneous secretion of sCD23, IL-1β, IL-2 IL-4, IL-5, IL-10, IL-12p70, IFN- and TNF- in MNC cultures. Furthermore, blood DC subset counts differed in food allergy. Antigen-presenting cell phenotypic abnormalities were accompanied by higher B and T cell percentages with more Bcl-2 within CD69+ subsets. Cells were generally refractory to antigenic stimulation in vitro but IL-4 neutralization led to CD152 downregulation by CD4+ T cells from PN allergic children responding to PN allergens. Canonical discriminant analyses segregated non-allergic and allergic children by their cytokine secretion patterns, revealing differences and areas of overlap between PN and CME allergies. Despite an absence of recent allergen exposure, indication of in vivo activation, in vitro responses independent of challenging antigen and the presence of unusual costimulatory molecules suggest dysregulated immunity in food allergy. Most important, higher Bcl-2 content within key effector cells implies survival advantage with potential to mount abnormal responses that may give rise to the manifestations of allergy. Here, we put forward the hypothesis that the lack of apoptosis of key immune cell types might be central to the development of food allergic reactions.

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Artificial intelligence has garnered significant attention in recent years as a rapidly advancing field of computer technology. With the continual advancement of computer hardware, deep learning has made breakthrough developments within the realm of artificial intelligence. Over the past few years, applying deep learning architecture in medicine and Industrial anomaly inspection has significantly contributed to solving numerous challenges related to efficiency and accuracy. Despite excellent results in radiological, pathological, endoscopic, ultrasonic, and biochemical examinations, this paper utilizes deep learning combined with image processing to identify spinal canal and vertebral foramen dimensions. In existing research, technologies such as corrosion and expansion in magnetic resonance image (MRI) processing have also strengthening the accuracy of results. Indicators such as area and Intersection over Union (IoU)are also provided for assessment. Among them, the mean average precision (mAP), for identifying intervertebral foramen (IVF) and intervertebral disc (IVD) through YOLOv4 is 95.6%. Resnet50 mixing U-Net was employed to identify the spinal canal and intervertebral foramen and achieved IoU scores of 79.11% and 80.89%.

Reference evapotranspiration (ET0) plays an irreplaceable role in regional dry/wet conditions under the background of climate change. Based on the FAO Penman-Monteith method and daily climate variables, ET0 was calculated for 22 stations in and around Songnen Grassland, northeast China, during 1960-2014. The temporal and spatial variations of ET0 and precipitation (P) were comprehensively analyzed at different time scales by using the Mann-Kendall test, Sen’s slope estimator, and linear regression coupling with break trend analysis. Sensitivity analysis was used to detect the key climate parameter attributed to ET0 change. Then, the role of ET0 in regional dry/wet conditions was discussed by analyzing the relationship between ET0, P and aridity index (AI). Results shown a higher ET0 in the southwest and a lower in the northeast, but P was opposite to that of ET0. Evidently decreasing trend of ET0 at different time scales was detected in almost the entire region, and the significant trend mainly distributed in the eastern, northeastern and central. For the whole region, sensitivity analysis indicated decreasing trend of ET0 was primarily attributed to relative humidity and maximum air temperature. The positive contribution of increasing temperature rising to ET0 was offset by the effect of significantly decreasing relative humidity, wind speed and sunshine duration. In addition, the value of ET0 shown higher in drought years and lower in wet years.

One of the most extensively studied topics in dozens of studies is the alteration process of ilmenite, the formation of leucoxene and the presence of some impurity oxides; SiO2 and Al2O3. The altered Egyptian black sand ilmenite grains of relatively lower magnetic characters are studied using the binocular microscope and the Cameca SX-100 microprobe instrument. Both of individual brown and black altered grains separated at 0.5 and 1 ampere values are investigated. The detection of the Various alteration phases, the mechanism of formation, their molecular formulas &amp; limits, and the role of SiO2&amp;Al2O3 in alteration mechanisms are detected. The alteration phases includes: pseudorutile (psr) and leached pseudorutile (lpsr) of different phases in addition also to rutile. Few analyzed spots are detected to be leached ilmenite (lilm). Several Excel softwares are adopted to calculate the chemical formulas of each alteration phase. The contents of TiO2 and Fe2O3 of all the investigated psr-lpsr in the study range between 59.16-86.56%, and 37.3-6.68%, respectively. The Ti/(Ti+Fe) ratio for these formulas ranges between 0.60 and 0.88. The psr-lpsr chemical formulas of all the investigated grains range as follows: Fe2.01-0.50Ti3O8.97-4.50(OH)0.03-4.50 . The concluded lowest cationic iron content of the well defined accepted lpsr phase is 0.5 with a corresponding molecular formula of Fe0.50Ti3O4.5(OH)4.5. It was concluded that in the region of 68-70 TiO2%, the mechanism of ilmenite alteration may be changed where neither all the analyzed TiO2 of the spot nor all the calculated structural water are contained within the molecular formula of lpsr. There are other associated mineral phases containing for some TiO2 and also some structural water which most probably are removed from the lpsr phase. As the analyzed spots are located at highly fissured locations, as the alteration process is relatively faster and the lpsr phase can be broken into rutile and hematite. Also, as the analyzed TiO2 and structural and/or molecular water contents increase, as the darkness of the BSE image areas of the grain increases; this may reflect the existence of an individual TiO2 phase; most probably rutile, mixed in homogeneity with the existed lpsr component. As the content of TiO2 increases; within a definite TiO2 range (80-85%), as the associated contents of Al2O3&amp;SiO2 increase. When the contents of the structural and/or molecular water contained within the lpsr phases decreases; the sum total oxides is more than 98%, the contents of Al2O3 are highly depleted. In the late alteration stages, the lpsr structure does not suddenly collapse but gradually producuing other associated mineral phases. The relatively enriched contents of SiO2 and/or Al2O3 in some secondary rutile grains can be explained as most of the SiO2% is associated with mol water or bearing for mol and/or str water necessary for the leachability of Fe3+ from the psr structure. The XRD patterns of the investigated grains before and after roasting at 1100 oC for one hour are detected and interpreted.

Background and aims: Despite recent advances in advanced prostate cancer treatments, there are no clinically useful biomarkers or treatments for men with such cancers. Targeted therapies have shown promise, but there remain fewer actionable targets in prostate cancer than in other cancers. This work aims to characterize BRD9, currently understudied in prostate cancer, and investigate its co-expression with other genes to assess its potential as a biomarker and therapeutic target in human prostate cancer. Materials and methods: Omics data from a total of 2053 prostate cancer patients across 11 independent datasets were accessed via Cancertool and cBioPortal. mRNA expression and co-expression, mutations, amplifications, and deletions were assessed with respect to key clinical parameters including survival, Gleason grade, stage, progression and treatment. Network and pathway analysis was carried out using Genemania, and heatmaps were constructed using Morpheus. Results: BRD9 is overexpressed in prostate cancer patients, especially those with metastatic disease. BRD9 expression did not differ in patients treated with second generation antiandrogens versus those who were not. BRD9 is co-expressed with many genes in the SWI/SNF and BET complexes, as well as those in common signaling pathways in prostate cancer. Summary and conclusions: BRD9 has potential as a diagnostic and prognostic biomarker in prostate cancer. BRD9 also shows promise as a therapeutic target, particularly in advanced prostate cancer, and as a co-target alongside other genes in the SWI/SNF and BET complexes, and those in common prostate cancer signalling pathways. These promising results highlight the need for wider experimental inhibition and co-targeted inhibition of BRD9 in vitro and in vivo, to build on the limited inhibition data available.

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

This cross-sectional, analytical, and observational study aimed to investigate the relationship between Visceral Adiposity Index (VAI) and anthropometric, biochemical, and insulin resistance (IR) parameters in Brazilians at risk of CVD. Biochemical parameters and anthropometric measurements were evaluated. The Pearson test was used to assess the correlation between VAI and anthropometric, biochemical, and IR parameters, with a predefined significance level of 5%. The analyzed sample consisted of 88 men and 72 women, with an average age of 58.78±13.48. VAI revealed noteworthy and positive correlations with all anthropometric parameters assessed (p&lt;0.0001). Furthermore, significant positive associations were noted between VAI and total cholesterol in women (p=0.0064), glycemia in men (p=0.0105), and LDL-c (p&lt;0.01) and triglycerides in both genders (p˂0.0001). A significant negative association was observed between VAI and HDL-c in both genders (p&lt;0.0001). Notably, the correlation between VAI and total cholesterol in men, glycemia in women, and CRP in both genders was not found to be significant. However, a significant relationship between VAI and IR parameters was observed in both sexes (p&lt;0.05). The results obtained from our study suggest that VAI functions as a simple and non-intrusive instrument, demonstrating significant effectiveness in identifying metabolic changes primarily associated with adipose tissue dysfunction, particularly dyslipidemia.

Quantifying different stocking rates effects in three study areas placed at Mediterranean forest (Cuenca, Spain) was conducted by applying a multiparametric soil quality index, SQI, developed in undisturbed forest soils (> 40 years). The main objective is to advance in the development and application of multiparametric indexes which allow for soil condition assessment. For it, is analyse the effectiveness of a multiparametric soil quality index (SQI) as an indicator livestock impacts on the soil in mediterranean forests. Control areas without stocking rates were compared in forest stands with different age (Thicket forest stand, < 30 years; High polewood forest stand, 30-60 years; Old growth forest stand, > 60 years); with various intensity grazing areas (permanent livestock passage: inactive sheepfold for 2-3 years, and active sheepfold; intermittent livestock passage: bare soil, pine stand, scrubland). The multiparametric soil quality index (SQI) applied sensitive to changes in forest ecosystems depending of different stocking rates. However, for even more preci-sion to assess cattle alteration, multiparameter index recalibrated, creating a new one; Soil Status Index by Livestock (SSIL). Correlation between quality ranges obtained with both indexes in dif-ferent study areas suggest that SSIL can be considered a livestock impact reference indicator in Mediterranean forest soils.

Drought is one natural disaster with the greatest impact worldwide. Southern Africa (SA) is susceptible and vulnerable to drought due to its type of climate. In the last four decades, droughts have occurred more frequently, with increasing intensity and impacts on ecosystems, agriculture and health. The work consisted of a systematic literature review on the drought regime’s characteristics in the SA, under current and future climatic conditions, conducted on the Web of Science and Scopus platforms, using the PRISMA2020 methodology, with usual and appropriate inclusion and exclusion criteria to minimize/eliminate the risk of bias, which lead to 41 documents published after the year 2000. The number of publications on the drought regime in SA is still very small. The country with the most drought situations studied is South Africa and the fewer studies are Angola and Namibia. The analysis revealed that the main driver of drought in SA is the ocean-atmosphere interactions including the El Niño Southern Oscillation. The documents used drought indices, evaluating drought descriptors for some regions, but it was not possible to identify one publication that reports the complete study of the drought regime, including the spatial and temporal distribution of all drought descriptors in SA.

Abstract: Mast cell (MC) specific proteases are of particular interest for space biology and medicine due to their biological activity in regulating targets of a specific tissue microenvironment. MC tryptase and chymase obtain the ability to remodel connective tissue through direct and indirect mechanisms. Yet, MC specific protease expression under space flight conditions has not been adequately investigated. Using immunohistochemical stainings, we analyzed in this study the protease profile of the jejunal, gastric and hepatic MC populations in three groups of Mongolian gerbils - vivarium control, synchronous experiment, and 12-day orbital flight on the Foton-M3 spacecraft, - and in two groups - vivarium control and anti-orthostatic suspension - included in the experiment simulating effects of weightlessness in the ground-based conditions. After a space flight, there was a decreased number of MCs in the studied organs combined with an increased proportion of chymase-positive MCs and MCs with a simultaneous content of tryptase and chymase; the secretion of specific proteases into the extracellular matrix increased. These changes in the expression of proteases were observed both in the mucosal and connective tissue MC subpopulations of the stomach and jejunum. Notably, the relative content of tryptase-positive MCs in the studied organs of the digestive system decreased. Space flight conditions simulated in the synchronous experiment caused no similar significant changes in the protease profile of MC populations. The space flight conditions resulted in an increased chymase expression combined with a decreased total number of protease-positive MCs apparently due to participating in the processes of extracellular matrix remodeling and regulating the state of the cardiovascular system.

Discovery of microRNAs (miRNAs) twenty years ago, has advocated a new era of “Molecular Genetics”. About 2000 miRNAs are present, that regulate one third of the genome. MiRNAs dysregulated expression may contribute to several diseases including tumor growth. Their presence in body fluids, reflecting levels alteration in various cancers, merit circulating miRNAs as the “next generation biomarkers” for early stages tumor diagnosis and/or prognosis. Herein, we performed a comprehensive literature search focusing on the origin, biosynthesis and role of miRNAs and summarized the foremost studies centering on miRs value as non-invasive biomarkers in different non-communicable diseases, including various cancer types. Moreover, during chemotherapy many miRNAs were linked to multidrug resistance, via modulating numerous biological processes and/or pathways that will be highlighted as well.

The Um Ara granites are a suite of granitoid rocks located in the south Eastern Desert of Egypt. The combination of Back Scattered Electron imaging (BSE), X-ray compositional mapping, and the data of the Electron Probe Micro Analyzer (EPMA) has provided valuable insights into the alteration process of zircon in the Um Ara granite. The investigated zircon grains have measurable amount of non-formula elements such as U, Th, Hf, REEs, P, Al, Ca, Fe, and Ti, along with extensive structural features indicative of radiation damage. These characteristics point to significant hydrothermal alteration of the zircon following its initial crystallization. The textural and geochemical evidence suggests the alteration of the Um Ara zircons was driven by coupled dissolution-reprecipitation processes influenced by aqueous fluids. The breakdown of accessory minerals like xenotime, thorite, monazite, and apatite during a major hydrothermal event around 1.8 Ga released the non-formula elements (U, Th, P, Ca, Al, Fe, REEs) that were then incorporated into the zircon structures. Subsequent pluvial periods around 50,000-159,000 years ago may have allowed further uptake of these elements during low-temperature alteration. The shear zones within the Um Ara granites facilitated the mobilization and transport of the non-formula element-bearing fluids, likely as carbonate and fluoride complexes. The temperature regime, with fluids remaining below 300°C, was crucial in preserving the radiation damage features in the zircons despite the extensive chemical changes.

This paper assesses the performance of an embankment constructed in 2010 with a stabilised expansive soil. Two types of treatment were employed at construction time: 4% lime and a mix of 2% lime and 3% cement. A sampling campaign was carried out in 2021 to evaluate the long-term performance of the stabilised soil properties. To assess the compressibility of the soil, oedometer tests were carried out on samples from different parts of the embankment. The results were compared to the compression curve of the untreated soil, also sampled in the same embankment. Complementary shrinkage tests were performed to investigate the effect of the treatment on swelling and shrinkage. The obtained results showed that the behaviour of the material from the outer part was similar to the mechanical performance of the untreated soil, demonstrating strong alteration in the effect of both treatments over time. This alteration was noticeable to a distance of approximately two metres from the external surface. Beyond this distance, the performance of the soil was comparable to the behaviour of recently treated soil. These observations, similar for each treatment dosage, raise questions as to the durability of the treatment on the outer part of the backfill.

The following article analyses the relationship between the mental health index and the variables of the Environment, Social and Governance-ESG model in the Italian regions between 2004 and 2023. The econometric analysis is aimed at investigating in detail the relationships between the mental health index and the individual components of the ESG model. The results are critically discussed

(1) Background: Parents of children with autism spectrum disorders often experience psychological distress, which can affect the quality of childcare they provide. It is crucial to screen for psychiatric symptoms among these parents. The Core Symptom Index (CSI) is a widely used tool for assessing general symptoms such as depression, anxiety, and somatic symptoms, with demonstrated validity and reliability across various populations. However, there is limited research on the validity and reliability of the CSI in the general Chinese population. This study aimed to investigate the psychometric properties of the Chinese version of the CSI among parents of children with autism spectrum disorders using Confirmatory Factor Analysis (CFA). (2) Methods: A total of 794 Chinese parents raising children with autism participated in this study. All completed the CSI, along with the social inhibition subscale of the Interpersonal Problems Inventory and the Couple Satisfaction Index. Factorial validity was assessed using CFA to determine how well the bifactor three-factor model fits the data. Various structural models were compared using model fit indices. Convergent and discriminant validity were examined by exploring correlations with the social inhibition subscale and the Couple Satisfaction Index. Invariance testing of the CSI was conducted across multiple groups based on gender, age, and education using CFA. The reliability of the CSI was evaluated using McDonald’s omega coefficients. (3) Results: The bifactor model emerged as the best-fitting model for the data, suggesting that the total score of the CSI adequately represents overall psychiatric symptoms. The CSI exhibited significant correlations with the social inhibition subscale (r = 0.41, p &lt; 0.01) and smaller correlation coefficients with the Couple Satisfaction Index (r = -0.16, p &lt; 0.05), indicating both convergent and discriminant validity. Invariant tests supported scalar invariance levels based on gender and age but only partial invariance for education. The Chinese version of the CSI demonstrated high consistency, with McDonald's omega coefficients ranging between 0.86 and 0.95. (4) Conclusions: The bifactor model of the Chinese version of the CSI is validated, making it a suitable tool for measuring depression, anxiety, and somatization symptoms among parents of children with autism spectrum disorders. Further research on other Chinese populations is encouraged.

When earthquake damage occurs, it is extremely important to quickly identify the presence or absence of such damage. In this study, we developed and evaluated a new remote sensing index to automatically determine "damage" by image analysis when damage greater than partial destruction of a house by an earthquake or tsunami occurs. The accuracy of the houses estimated as "damaged" was high and sufficient for the initial assessment of damage. The results of this research are expected to be utilized for more rapid damage assessment after a disaster.

This study assessed the hydrological performance and runoff water quality of 12 green roof (GR) modular systems located at the Universidad de los Andes campus (Bogotá, Colombia). Based on 223 rainfall events spanning a 3-year period, average rainfall retention was 85% (SD = 25%). T-tests, Welch Test, multiple linear regressions and correlation analysis were performed in order to assess the potential effect of air temperature, substrate type, vegetation cover, relative humidity, antecedent dry weather period (ADWP), rainfall duration and rainfall maximum intensity. In some cases, GR design variables (i.e. growing media and type of vegetation) were found to be significant for describing rainfall retention efficiencies and, depending on the GR type, some hydrological variables were also correlated with the rainfall retention. Rainfall and GR runoff were monitored for Total Kjeldahl Nitrogen (TKN), Nitrates, Nitrites, Ammonia, Total Phosphorus (TP), Phosphates, pH, Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Color, Turbidity, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Coliforms, metals and Poliaromatic Hydrocarbons (PAHs). The results obtained confirmed that GR systems have the ability to neutralize pH, but are source of the rest of the aforementioned parameters, excluding PAHs (with concentrations below detection limits), Ammonia, TSS, Se and Li, where differences with reference values (rainfall and plastic panel runoff) were not statistically significant. Substrate type, event size and rainfall regime are relevant variables for explaining runoff water quality.

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.

This study investigates water consumption in two areas with limited water resources – the Salar de Atacama and Salar de Atacama-Vertiente Pacifico basins in Chile's Antofagasta Region – with the aim of developing strategies that incorporate social and environmental aspects into water management. A qualitative approach was employed that involved a focus group with four water management representatives and surveys of the general population (156 responses). Additionally, the current state of water rights in the basins was examined and the feasibility of the proposed strategies was assessed. The findings reveal that the mining industry's development approach is viewed negatively, mainly due to inadequate community engagement, confidential consumption data, and limited government oversight. Adopting a comprehensive water stewardship approach that considers social and environmental factors would help mitigate the adverse effects of mining on communities. Therefore, improved management and transparent collaboration among stakeholders are essential for responsible water resource use in mining.

Globally, bridges fail mostly due to hydrological causes such as scour or flooding. Therefore, under a hydrological approach, this study proposes a methodology that contributes to prioritize the intervention of bridges to prevent their collapse. Through an exhaustive literature review, an evaluation matrix subdivided into 4 dimensions was developed and a total of 18 evaluation parameters were considered, distributed as follows: 4 environmental, 6 technical, 4 social and 4 economic. This matrix was applied to eight bridges with a history of hydrological problems in the same river and validated through semi-structured interviews with specialists. Data were collected through field visits, journalistic information, review of the gauged basin historical hydrological flow rates and consultations with the population. Then, the modeling, which considered the influence of gullies that discharge additional flow, was carried out using HEC-HMS and HEC-RAS and subsequently calibrated. The application of the matrix revealed that five bridges have a high vulnerability, and three bridges have a medium vulnerability. The multidimensional approach can be adapted for studies of other riverine bridges.

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.

The gut microbiome offers numerous advantages to the hosts, through a variety of physiological mechanisms like firming up gut integrity or shaping the intestinal epithelium. Studies showed 2172 species are identified and isolated from human beings, ordered into twelve different phyla, of which 93.5% belonged to Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria. Out of the 12, three phyla are identified. Human microbial communities are affected by the host external factors like dietary patterns, lifestyle factors, antibiotic usage, internal factors gender, host genotype, age and race. To analyze the dysbiosis and bacterial variation in different areas of District Faisalabad 10,000 individuals of age 25–35 years were recruited from the two different rural and urban localities. The oral swab and fecal sample were collected according to prescribed manner. The collected samples from demographically and geographically distinct regions of District Faisalabad were subjected to DNA extraction and quantification. The amplification of 16s rRNA was carried out by PCR and visualized through a transilluminator. The results revealed significant elevated, % abundance of fecal microbial profile Blautia spp, Firmicutes, Ruminococcaceae, in rural population however non-significant difference % abundance of total Bifido, E. coli, Faecali bacteria, total Lactobacillus were identified in both demographically distinct regions. The pathogenic Gamma Protebacteria, Fusobacterium, Campylobacter coli were not detected in both study areas. Out of five orally detected microbial profiles, elevated % abundance of Firmicutes was detected in rural population however non-significant difference was observed in % abundance of total Bifido and E. coli in both populations. Total Lactobacillus and Fusobacterium were not detected in oral sample of both urban and rural population. Conclusively, this research accomplished the potential effects of demographic and geographical induced dysbiosis in the normal microbiome of the oral cavity and intestine that might cause dysbiosis associated disorders.

The environmental vulnerability diagnosis of a river basin depends on a holistic analysis of its environmental aspects and degradation factors. Based on this diagnosis, the definition of priority areas where interventions for environmental recovery should be carried out is fundamental, since financial and natural resources are limited. In this study, we developed a methodology to assess these fragilities using an Environmental Vulnerability Index (EVI) that combines physical and environmental indicators related to the natural sensitivity of ecosystems and their exposure to anthropogenic factors. The EVI developed was applied to the headwater’s region of the São Francisco River basin, Brazil. The proposed index was based on the AHP multi-criteria analysis and was adapted to include four variables representative of the study area: Land Use Adequacy, Burned Area, Erosion Susceptibility and Quantitative Water Balance. The EVI analysis highlighted that the presence of easily erodible soils, associated with sloping areas and land uses above their capacity, generate the most vulnerable areas in the headwaters of the São Francisco River basin. The results of this study indicate where resources should be applied for environmental preservation in the basin under study, directing the allocation of efforts to areas with lower resilience in maintaining ecosystem services.

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

One of the factors in the mobility of a nation's economy is the stock exchange which plays a decisive role in sustainable economic development. Accordingly, and for the special place of the stock exchange in the economy, we decided to investigate the relationship between the interest and exchange rates and the Tehran stock exchange dividend and price index (TEDPIX). Using the autoregressive distributed lag method, the present study is conducted utilizing the annual data over the period of 1991 to 2020. The results indicate that the exchange rate has a positive long-run relationship with the TEDPIX, but no statistically significant relationship was found between the TEDPIX and the interest rate. Furthermore, the results of the estimation of the error correction model show that 30.786% of the disequilibrium in each period is adjusted to the long-run equilibrium.

The prevalence of diabetes mellitus (DM) continues to rise globally, posing significant health challenges and burdens. This metabolic disorder, characterized by elevated blood glucose levels, contributes to various complications including cardiovascular diseases, kidney failure, and stroke. While conventional diabetic drugs exist, they often come with adverse side effects, necessitating the exploration of safer and more cost-effective alternatives, particularly from natural sources like medicinal plants. This study investigates the potential of Neocarya macrophylla (Nm) Ethyl acetate leaf fraction in managing DM. Utilizing a high-fat diet/streptozotocin-induced diabetic rat model, the study explores several key aspects including effective dose determination, biological activity, impact on body mass index (BMI), and complete blood count. Statistical analysis was conducted using GraphPad Prism version 9.1. The determination of the minimum effective dose reveals that 120mg/kg of Ethyl acetate fraction of Nm reduced the blood glucose by 28.9% after 4 hours. In addition, ethyl acetate fraction (120 mg/kg) possessed the most hypoglycemic activity compared to the other fractions of Nm. The Ethyl acetate fraction of Nm at 120mg/kg significantly reduced fasting blood glucose levels compared to the diabetic control(p=0.001) and slightly decreased BMI. Furthermore, the fraction demonstrated significant improvement in the parameters of some of the blood count indices such as red blood cells (p<0.001), total white cells (p<0.01) and platelet (p<0.001) compared to the diabetic control. These findings underscore the potential of Nm as a holistic therapeutic option for managing DM and its haematological complications. In conclusion, this study sheds light on the hypoglycemic potential of Nm Ethyl acetate leaf fraction, offering valuable insights into its effectiveness, safety, and broader physiological impacts. Further research into the mechanisms underlying its therapeutic effects is warranted to fully harness its therapeutic potential in diabetes management.