Major Indices Research Articles

Factors associated with postoperative coronal imbalance in adult patients with severe and rigid scoliosis: a retrospective study

BackgroundExtensive studies examined coronal imbalance (CIB) in adolescent and adult degenerative scoliosis; however, few studies addresses on CIB in adult with severe rigid scoliosis (SRS). Therefore, we analyzed postoperative SRS patients to identify factors associated with postoperative CIB.MethodsIn this retrospective study, we investigated SRS patients undergoing one-stage posterior column osteotomy (PCO) and fusion at our hospital between August 2012 and January 2019. The preoperative, postoperative and follow-up whole-spine anteroposterior (AP) radiographs were evaluated. Potential risk factors for postoperative CIB were analyzed using the LASSO regression, and independent risk factors were identified using binary logistic regression. A nomogram prediction model was constructed and validated.ResultsNinety eligible SRS patients were included. Postoperative radiographs showed a main curve correction rate of 54.17 ± 14.02%; however, follow-up CIB persisted in 26.67% of patients. Three independent variables affecting follow-up CIB were identified by LASSO regression, including preoperative CIB+ [OR = 12.414 (95% CI: 2.228, 69.162), P = 0.004], major curve flexibility index < 10% [OR = 14.300 (95% CI: 2.200, 92.957), P = 0.005], and immediate postoperative CIB [OR = 5.169 (95% CI: 1.387, 19.263), P = 0.014]. ROC and DCA analysis demonstrated that the nomogram had good predictive performance.ConclusionsPreoperative CIB+, major curve flexibility index < 10%, and immediate postoperative CIB were significantly associated with postoperative CIB. These findings offer valuable guidance to improve surgical outcomes and reduce complications.

Exploring the connectedness between major volatility indexes and worldwide sustainable investments

Exploring the connectedness between major volatility indexes and worldwide sustainable investments

Visualization and Assessment of Copula Symmetry

Visualization and assessment of copula structures are crucial for accurately understanding and modeling the dependencies in multivariate data analysis. In this paper, we introduce an innovative method that employs functional boxplots and rank-based testing procedures to evaluate copula symmetries. This approach is specifically designed to assess key characteristics such as reflection symmetry, radial symmetry, and joint symmetry. We first construct test functions for each specific property and then investigate the asymptotic properties of their empirical estimators. We demonstrate that the functional boxplot of these sample test functions serves as an informative visualization tool of a given copula structure, effectively measuring the departure from zero of the test function. Furthermore, we introduce a nonparametric testing procedure to assess the significance of deviations from symmetry, ensuring the accuracy and reliability of our visualization method. Through extensive simulation studies involving various copula models, we demonstrate the effectiveness of our testing approach. Finally, we apply our visualization and testing techniques to three real-world datasets: a nutritional habits survey with five variables, stock price data for the five top companies in the NASDAQ-100 stock index, and two major stock indices, the US S&P500 and German DAX.

Vector SHAP Values for Machine Learning Time Series Forecasting

ABSTRACTWe propose a new vector SHapley Additive exPlanations (SHAP) to interpret machine learning models for forecasting time series using lags of predictor variables. Unlike the standard SHAP measuring the contribution of each lag of each predictor variable, the proposed vector SHAP measures the contribution of the vector of the lags of each variable. The vector SHAP has an advantage of faster computation over the standard SHAP. Some desirable properties of the vector SHAP (vector local accuracy, vector missingness, and vector consistency) are established. A Monte Carlo simulation shows that the vector SHAP has a much faster computing time than the SHAP; the difference of the standard SHAP and the vector SHAP is small; the sampling SHAP is sensitive to the sampling proportion in a range of practical application; the vector SHAP mitigates the sensitivity issue. The vector SHAP is applied to the realized volatility of world major stock price indices of 16 countries for forecasting the realized volatility of South Korea stock price index, KOSPI. Further vectoring by regions of Europe, North America, and Asia yields vector SHAP value for each region which is very close to the sum of vector SHAP values of the countries of the region, illustrating usefulness of the strategy of vectoring.

The Effects of COVID-19 on the Returns and Volatilities of Global Stock Indexes

At the beginning of 2020, COVID-19 broke out around the world, and its impact on the global economy exceeded expectations. Countries declared states of emergency one after another. The outbreak not only triggered a crisis of supply, demand, investment, and supply chain disruptions but also transmitted to the financial sector. Global risk aversion is rising rapidly, and global stock markets continue to plummet, threatening to trigger further financial crises. To investigate the impact of COVID-19 on the financial sector and to prevent and mitigate financial risks, this paper examines the impact of COVID-19 on global stock markets from a global perspective. Firstly, selected data of seven global stock indices using WRDS and S&amp;P Capital IQ databases. After processing these data, ARMA-GARCH modeling was carried out using the data before the outbreak and the data for the whole sample period respectively. Then, the residuals of the model were subjected to L-B and ARCH-LM tests to determine the fit of the model for different stock indices and different periods. Next, determine if the return and volatility of the equity index have changed during COVID-19 based on the goodness of fit. The results of the study show that: (1) The outbreak of COVID-19 has had a serious impact on the yields and volatility of major global equity indices. As can be seen from the descriptive statistics of the data, particularly around March 2020, each of the sample equity indices experienced high volatility. (2) By fitting the post-outbreak data using the pre-outbreak fitted model, it was found that the fit was poor. This suggests that the outbreak of the new crown epidemic had a significant impact on the process of generating stock data. (3) The results of this paper show that the data for the China SSE Composite Index after the outbreak still fit the pre-outbreak fitted model well. This also indicates that the Chinese mainland stock market has shown greater stability than other markets when all major world stock indices were significantly hit by COVID-19.

Cardiac adverse events associated with statins in myocardial infarction patients: a pharmacovigilance analysis of the FDA Adverse Event Reporting System.

Despite the advent of new pharmacotherapies, statins remain a cornerstone in the secondary prevention of myocardial infarction (MI). However, the cardiac adverse events (AEs) linked to statins are not well-documented. This pharmacovigilance study used data from the FDA Adverse Event Reporting System (FAERS) to investigate the association between statin use and cardiac AEs in MI patients. Reports from the FAERS database (2004-2023) identifying statins as the primary suspect in MI patients were analyzed. The study evaluated seven types of statins: atorvastatin, fluvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin. Disproportionality analysis using four major indices, Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma-Poisson Shrinker (MGPS), was conducted to detect signals of statin-related cardiac AEs. Of the 20,346,289 reports reviewed, 150 identified statins as the primary suspect drug in MI patients. The most common cardiac AEs were recurrent MI (50 reports), acute MI (14 reports), followed by tachycardia (10), angina pectoris (8), coronary artery occlusion (6), cardiac failure (6), and arrhythmia (6). The analysis revealed no significant signals of statin-induced cardiac AEs. The findings confirm that statin use in MI patients does not significantly increase the risk of cardiac adverse effects, supporting their safety profile in this context.

Investigation of tempo-spatial variability of the Black Sea hydrodynamics by means of neural networks

The tempo-spatial variability of the Black Sea surface circulation was investigated using satellite data from the Archiving, Validation, and Interpretation of Satellite Oceanographic data (AVISO) project. Self-Organizing Maps (SOMs) were utilized, a neural network-based method known for its unsupervised learning capabilities, to analyze and categorize the circulation patterns, for the very first time. To assess the clustering precision achieved by the SOM algorithms the Davies-Bouldin Index (DBI) was employed as an internal validation metric. Through this comprehensive analysis, six distinct spatial patterns were identified, each exhibiting unique temporal variabilities and occurrence rates. Pattern 1: Characterized by the Sevastopol Cyclonic and Batumi Dipole Eddies, occurring 21 % of the time; Pattern 2: Defined by the Cyclonic RIM Current and Anticyclonic Batumi Eddy, with a 16 % occurrence rate; Pattern 3: Consisting of Anticyclonic Sevastopol and Batumi Eddies, occurring 17 % of the time; Pattern 4: Featuring the Cyclonic RIM Current and Cyclonic Batumi Eddy, also with a 21 % occurrence rate; Pattern 5: Marked by the Anticyclonic RIM Current and Batumi Dipole Eddies, with a 15 % occurrence rate; Pattern 6: Characterized by the Anticyclonic RIM Current and Multi Eddies, occurring 10 % of the time. To further validate the identified patterns, their relevance for predicting the hydrodynamics of the Black Sea was examined. This was achieved by exploring potential correlations between these patterns and major climatological indices, such as the North Atlantic Oscillation (NAO), the East Atlantic/West Russian (EAWR) oscillation, and the El Niño-Southern Oscillation (ENSO). These indices are known to influence large-scale atmospheric and oceanographic conditions, and understanding their relationship with the identified patterns can enhance predictive models of Black Sea dynamics. The findings from this study provide valuable insights into the complex circulation patterns of the Black Sea and their temporal behaviors. The use of advanced neural network techniques such as SOMs, combined with rigorous validation methods like the DBI, underscores the robustness of the analysis. Moreover, the established connections with climatological indices offer a promising avenue for improving long-term forecasts and understanding the broader climatic impacts on the Black Sea's surface circulation.

Factors affecting the accuracy of fetal cardiac ultrasound screening in the first trimester of pregnancy.

Most studies on the performance of first-trimester cardiac screening have concentrated on comparing the detection rate between different protocols and not on the actual reason for false-negative results. Herein, we report the performance of first-trimester congenital heart disease (CHD) screening and factors that may affect the detection rate of CHDs. This retrospective observational study included patients who underwent first-trimester screening and subsequently gave birth at our facility. We analyzed the performance of first-trimester screening for CHD and major CHD (CHD requiring cardiac surgery or interventional catheterization within 12months of birth). Of the 6614 fetuses included, 53 had CHD and 35 had major CHD. For the prenatal diagnosis of CHD, the detection rate, specificity, positive predictive value, negative predictive value, and first-trimester detection rate for CHD were 64.1%, 99.9%, 94.4%, 99.7%, and 82.9%, respectively; the respective values for major CHD were 85.7%, 99.96%, 93.75%, 99.92%, and 85.7%. The detection rate was not significantly different when classified by crown-rump length or number of fetuses. A weak correlation was observed between low detection rate of major CHD and lower maternal body mass index (BMI) (correlation ratio: 0.17). The detection rate was significantly higher when the fetus was scanned with its spine at the 5-7 o'clock position (posterior spine) than at other positions (odds ratio: 3.82, 95% confidence interval: 1.16-12.5, p = 0.02). Posterior spine contributes to an improved diagnostic rate in first-trimester CHD screening. In addition, sonographers must recognize that low maternal BMI is a risk factor of false-negative results.

Exploring the Relationship Between Visceral Fat and Coronary Artery Calcification Risk Using Metabolic Score for Visceral Fat (METS-VF).

Metabolic Score for Visceral Fat (METS-VF) is a novel indicator for estimating intra-abdominal fat, yet its connection with coronary artery calcification (CAC) remains uncharted. Our research aims to explore the novel METS-VF indicator's link to CAC while comparing its performance against relevant anthropometric indices. This study enrolled participants who underwent health checkups and computed tomography scans for categorizing severity of CAC using the coronary artery calcium score. The METS-VF was calculated and compared with anthropometric indices in estimating the presence of CAC and different CAC severity using receiver operating characteristic curves. Overall, 1217 participants (mean age 50.7 ± 9.9, 53.8% male) were included. METS-VF (odds ratio [OR], 1.506; 95% confidence interval [CI], 1.181-1.921; p = 0.001) was positively associated with the presence of CAC, even after accounting for cardiometabolic factors. Notably, METS-VF was positively associated with mild (OR, 1.450; 95% CI, 1.115-1.886; p = 0.006), moderate (OR, 1.865; 95% CI, 1.137-3.062; p = 0.014), and severe (OR, 2.316; 95% CI, 1.090-4.923; p = 0.029) CAC. Moreover, METS-VF yielded the highest area under curve (AUC) value in the estimation of the CAC presence (AUC = 0.710), mild (AUC = 0.682), moderate (AUC = 0.757), and severe (AUC = 0.807) CAC when compared with body mass index, waist circumference, visceral adiposity index, triglyceride-glucose index, and metabolic score for insulin resistance. The optimal METS-VF cut-off value was 6.4 for predicting CAC. METS-VF emerged as a strong independent marker for detecting CAC presence across mild, moderate, and severe CAC categories, outperforming major anthropometric indices in accurately estimating the presence of CAC and different severity of CAC.

Interconnected Stock Markets: Analysing Cointegration and Correlation among Global Stock Indices

This study examines the long-term and short-term relationships among five major global stock indices—NSE NIFTY (India), S&amp;P 500 (USA), FTSE 100 (UK), Hang Seng (Hong Kong), and Nikkei 225 (Japan)—over the period from 2008 to 2023. Using advanced econometric techniques such as Johansen cointegration tests, Engle-Granger residual cointegration test and the Vector Error Correction Model (VECM), the research explores the degree of interconnectedness and cointegration among these indices. The results indicate strong positive correlations between NSE NIFTY, S&amp;P 500, and Nikkei 225, suggesting a growing synchronization of these markets due to global economic integration. Johansen's test reveals the presence of multiple long-term equilibrium relationships, affirming that despite short-term deviations, these markets tend to move together in response to global macroeconomic factors. The analysis further highlights that the S&amp;P 500 and FTSE 100 indices exhibit significant error correction mechanisms, underscoring their leadership role in global market dynamics. In contrast, NSE NIFTY shows a weaker adjustment toward long-term equilibrium, indicating its reactive nature to changes in other global indices, particularly the S&amp;P 500. The study finds that while Hang Seng and Nikkei 225 are connected globally, their short-term linkages appear weaker, likely influenced by regional factors. Overall, the results emphasize the critical influence of the U.S. and Japanese markets on NSE NIFTY, with both long-term cointegration and short-term market dynamics shaping the Indian stock market’s movements. This research offers key insights for investors seeking to understand global stock market interdependencies and manage portfolio risk.

Analysis of groundwater and surface water quality using modelled water index and multivariate statistics in Kampala and Mbarara Districts, Uganda

The demand for domestic, public and industrial use of water increases with population growth. However, activities from humans and natural environment have resulted into decline in water quality. The aim of this study was to evaluate the quality of groundwater and surface water collected from Kampala and Mbarara districts of Uganda using water quality index and multivariate statistics. A total of 10 physicochemical parameters (pH, water temperature, chloride, sulphate, nitrate, electrical conductivity, total dissolved solids, total suspended solids, total solids, and phosphate) were measured monthly to evaluate the quality of water in the study districts. Results showed that sulphate, electrical conductivity and total dissolved solids were observed with significantly high values in surface water than the groundwater for both seasons. Among all the parameters measured, electrical conductivity was observed with the highest value (2129.67 ± 1.41 µS/cm) while nitrate concentration (0.57 ± 0.02 mg/L) was observed with the lowest during the wet season in surface water. In addition, the mean values of nitrate, electrical conductivity, total dissolved solids and sulphate detected in the groundwater and surface water were within the recommended limits, while phosphate and chloride were observed with mean concentrations above the regulatory limits in 50% of the samples. The correlation analysis revealed strong and positive association between electrical conductivity and total dissolved solids in groundwater and surface water for both seasons. Also, the chemical make-up of groundwater and surface water within the study districts revealed that the determination of water quality rests on two major indices (conductivity and anthropogenic-pollutants) based on the factor analysis. The two indices accounted for 0.619% in groundwater and over 0.70% in surface water, indicating more pollution in surface water. Moreover, the water quality index (WQI) values obtained ranged from 14.81 to 115.73 in dry season and 7.77 to 108.24 during the wet season. According to WQI classification, 42% of the samples collected fell within the “excellent” and “good” categories while others fell within “poor” and “unfit” categories (58%) during the dry season. Based on these findings, appropriate treatment methods, proper sanitation and waste management should be implemented in locations with critical water conditions. Also, frequent monitoring of groundwater and surface water quality by environmental protection agency is highly recommended.

Anthropogenic activities mitigate the impacts of climate extremes on high flow regimes on the Loess Plateau

The hydrological cycle is anticipated to become increasingly variable due to intensified global climate extremes and frequent floods. Understanding the evolution and driving mechanisms of floods in the context of climatic extremes is essential, particularly on the Loess Plateau (LP) where anthropogenic activities are significant. Here, we examined the spatiotemporal variability of climate extremes and their impacts on flood processes on the LP during 1956–2015. We employed a paired year approach to quantitatively assess the driving role of anthropogenic activities on flood changes in 11 major basins. Our findings indicated a general decline in extreme precipitation indices, while temperature has increased across most of the LP. Both annual runoff (Q) and high flow (Q5) magnitude significantly decreased in all basins. We identified that the major climatic indices driving Q5 included erosive precipitation amount, flood season precipitation, heavy precipitation amount, and maximum 7-day precipitation amount. Importantly, anthropogenic activities have mitigated the impact of climate extremes on Q5 regimes. Compared the post-2000 with reference period (1956–1979), under similar climatic conditions, we observed a reduction in the average Q5 magnitude by 30.19–78.14% and a decrease in the average Q5 duration by 46.48–100.00% across the basins. The contributions of climate variability and anthropogenic activities to Q5 magnitude changes among 11 basins ranged from –37.58% to 22.02% and –56.84% to –15.08%, respectively, highlighting the crucial role of ecological restoration in reducing Q5 magnitude. These results underscore the importance of ecological restoration in flood regulation and offer valuable insights for basin management in the Yellow River Basin.

Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market

The role of cryptocurrencies within the financial systems has been expanding rapidly in recent years among investors and institutions. It is therefore crucial to investigate this phenomenon and develop statistical methods able to capture their interrelationships, the links with other global systems and, at the same time, the serial heterogeneity. Here we introduce hidden Markov regression models for jointly estimating quantiles and expectiles of cryptocurrency returns using regime-switching copulas. The proposed approach allows us to focus on extreme returns and describe their temporal evolution by introducing time-dependent coefficients, evolving according to a latent Markov chain. Moreover to model their time-varying dependence structure, we consider elliptical copula functions defined by state-specific parameters. Maximum likelihood estimates are obtained via an expectation-maximization algorithm. The empirical analysis investigates the relationship between daily returns of five cryptocurrencies and major world market indices.

Extreme downside risk connectedness between green energy and stock markets

This study addresses the need to understand the transmission of tail risk across financial markets, especially in the context of green energy and stock markets. Utilizing the Time-Varying Parameter Vector Autoregressive (TVP-VAR) methodology combined with the Conditional Autoregressive Value-at-Risk (CAViaR) framework, the model analyzes data from September 30, 2013, to October 11, 2023. This study focuses on five major stock indices (S&P500, CSI300, Nikkei225, STOXX50, and FTSE100), West Texas Intermediate (WTI) crude oil, and three sectors within green energy markets (Green bond, Global Clean Energy, and Renewable Energy and Clean Technology), highlighting the significant role of these sectors in risk propagation. The model can capture dynamic changes and asymmetries in financial returns, thus providing a precise estimation of extreme downside risks. Key findings show that three stock indices (S&P500, STOXX50, and FTSE100) and one green energy sector (Renewable Energy and Clean Technology sectors) are the predominant sources of risk, with significant connectedness around events, such as the COVID-19 pandemic. These insights are crucial for developing effective risk-management strategies and supporting the transition to a sustainable energy sector. This study concludes that understanding these risk dynamics is essential for strategic planning and market stability.

SOURCES OF MAGMAS OF PERMIAN GABBROS OF THE KHANGAI MOUNTAINS (Western Mongolia)

We present Sm–Nd and Rb–Sr isotope composition data on mafic–ultramafic massifs in the Khangai Mountains of Western Mongolia: Oortsog-Uul, Nomgon, and Yamaat-Uul. The U–Pb age of zircon and its Lu–Hf isotope and trace-element compositions were determined by LA–ICP–MS. New and previous geochronological data obtained by SIMS and LA–ICP–MS support the Permian age of the studied gabbros. The trace-element composition of zircon, characterized by strong HREE enrichment ((Lu/Gd)n &amp;gt; 7) and cerium positive (Ce/Ce* &amp;gt; 6.6) and europium negative (Eu/Eu* = 0.16–0.49) anomalies, indicates its magmatic genesis and the possibility of using isotope characteristics to assess the origin of mafic magmas. The formation of zircon from a residual mafic melt is inferred from the enrichment of zircon in U and Th with increasing Th/U, reflecting the accumulation of these highly incompatible elements in the residual melt, and from the crystallization temperature of zircon (810–880 °С). The geochemical characteristics of the rocks, their isotopic composition, the absence of xenogenic ancient zircons, and the lack of correlation between εNd(T) and major indices of crustal contamination indicate that crustal contamination did not influence the composition of the gabbros. Isotopic data on rocks and zircon indicate the involvement of two mantle sources in the formation of the mafic–ultramafic massifs of the Khangai Mountains: (a) depleted, predominant for the Nomgon and Yamaat-Uul massifs (εHf = 16.1–2.0; εNd = 4.5–0.0; and ISr = 0.70385–0.70537), and (b) enriched, predominant for the second phase of the Oortsog-Uul massif (εHf = 1.4–0.2; εNd = –3.6… –5.7; and ISr = 0.70704–0.70933).

Research on the micro-mechanism and factors of hot recycled asphalt binder cracking

The poor low-temperature performance of recycled asphalt is the primary cause of the recycled asphalt disease. However, further strengthening is required to analyze the molecular-level cracking of recycled asphalt. This article presented a comprehensive investigation of the cracking phenomenon of recycled asphalt at both the macro and micro levels. This was achieved through the utilization of experimental tests and molecular dynamics simulations. In this study, pressure-aged asphalt was subjected to 40 h of aging. The aged asphalt was divided into three groups: 30% RAP (reclaimed asphalt pavement) recycled asphalt, 50% RAP recycled asphalt, and 70% RAP recycled asphalt. The three groups were then analyzed in terms of three major indexes. Linear amplitude scanning (linear amplitude sweep, LAS) was conducted on the three groups. The mechanical response law of asphalt was obtained, and it was found that the coefficient of strength of recycled asphalt increased with the increase of RAP dosage. At the same time, the fracture energy density decreased subsequently. Furthermore, the fracture energy density of aged asphalt was 7% lower than base asphalt's. Subsequently, this study examined the four fractions and C=O and S=O functional groups of five types of asphalt and constructed the molecular structures and models of stable base asphalt and aged asphalt. Subsequently, this article constructed a fusion model of new and old asphalt, analyzed the fusion process of new and old asphalt, and studied the factors affecting the blending degree of new and old asphalt. Finally, the factors affecting the cracking performance of rejuvenated asphalt, including the blending degree, the content of the four fractions, and the addition of the rejuvenator, were investigated. The impact of each influencing factor on the cracking performance of recycled asphalt was analyzed from multiple perspectives. In conclusion, the findings of this study provide a valuable guide for interpreting the tensile properties of reclaimed asphalt and the influence of rejuvenators.

Groundwater geochemistry using modified integrated water quality index (IWQI) and health indices with special emphasis on nitrates and heavy metals in southern parts of Tirupati, South India.

Groundwater is particularly vulnerable to pollution in places with a high population density and extensive human usage of the land, especially in southern parts of Tirupati, India. To assess this, 60 bore-well samples were obtained and assessed for physical specifications, ion chemistry, and heavy metals during the pre- and post-monsoon seasons 2022. The current investigation employed a modified integrated water quality index (IWQI), conventional graphical and human health risk assessment (HHRA) of nitrates and heavy metals to know the groundwater chemistry and its detrimental health effects on humans. The major ions were analyzed using American public health association (APHA)standards, whereas heavy metals were analyzed using inductively coupled plasma optical emission spectrometry(ICP-OES). Additionally, pH Redox Equilibrium and C (PHREEQC),a geochemical model written in C programming language was employed to determine the saturation indices of mineral facies and ArcGIS 10.3.1 was used for spatial distribution patterns of IWQI. Then, the HHRA of nitrates and heavy metals was performed using United States environmental protection agency (USEPA)guidelines. The noteworthy outcomes include elevated levels of Ca2+, Mg2+, Cl-, NO3-, Cu,Fe, Mn, and Pb, demonstrating rock-water interaction, silicate weathering, Ca-Mg-HCO3 followed by mixed water facies, dissolution/precipitation, reverse exchange, and anthropogenic contamination are the major controlling processes in groundwater of southern Tirupati, India. The modified IWQI reveals that most groundwater samples (38%) fall under the bad quality class, with (47%) in the poor quality class and only (15%) classified as medium qualityclass in pre- and post-monsoon seasons. Elevated IWQI were observed in all directions except in the east, which is suitable for drinking. Moreover, the major hazard quotient (HQ) and hazard index (HI)for nitrates (NO3-) and heavy metals like copper(Cu), iron (Fe), manganese (Mn), lead (Pb) and zinc (Zn) are above the critical value of 1, revealing potential risk to humans, especially infants, followed by children and adults, entailing the instantaneous implementation of proper remedial measures and stringent policies to reduce the risk associated with groundwater pollution in the southern parts of Tirupati.

A thermodynamic consideration on the synthesis of methane from CO, CO2, and their mixture by hydrogenation

The synthesis of methane from CO and CO2 by hydrogenation is now considered as a promising route in effectively storing hydrogen energy as well as sustainably producing fuels and chemicals, while many reaction details involved in such processes, in particular for the hydrogenation of the CO and CO2 mixture, are not yet adequately understood. As a supplement to our previous works on the hydrogenation of CO and CO2 into alcohols and hydrocarbons, a thermodynamic consideration is made in this work to evaluate the potential and limit for the synthesis of methane from CO, CO2, and their mixture in particular. The results consolidate that in comparison with single CO or CO2, their mixture is probably more credible in practice for the production of methane by hydrogenation, where the overall C-based methane yield can be used as the major index to evaluate the process efficiency. The hydrogenation of CO shows a higher equilibrium yield of methane than the hydrogenation of CO2, while the overall C-based equilibrium yield of methane for the hydrogenation of the CO and CO2 mixture just lies in between and decreases almost lineally with the increase of the CO2/(CO+CO2) molar ratio in the feed, despite the great change in the equilibrium conversions of CO and CO2 with the feed composition. Nevertheless, an adequate overall C-based equilibrium yield of methane (> 85%) can be achieved at a temperature lower than 400 °C and a pressure higher than 0.1 MPa for the stoichiometric hydrogenation of CO, CO2, or their mixture whichever. These results should be beneficial to the design of more efficient catalysts and processes for the hydrogenation of CO/CO2 to methane.

REACTION AND ADAPTATION OF THE STOCK MARKETS TO THE FULL-SCALE INVASION OF UKRAINE

This article investigates the reaction and adaptation of stock markets in response to the Full-Scale Invasion of Ukraine in February 2022. It examines the immediate effects on the Ukrainian stock market, highlighting the significant decline in trading volumes and stock prices due to geopolitical uncertainty. The study analyzes the behavior of major indices, including the PFTS and S&amp;P 500, and explores investor sentiment during this crisis. Notably, while the S&amp;P 500 experienced an initial drop, it rebounded as investors perceived a buying opportunity, reflecting resilience in more diversified markets. In contrast, the Ukrainian market faced severe disruptions, prompting regulatory responses and measures to restore confidence. The paper also considers gold’s reaction as a safe-haven asset, emphasizing its role in mitigating risks amid heightened geopolitical tensions. The findings underline the complexities of market dynamics during crises and the varying impacts on domestic and international investors.

Efficacy of methylene blue in refractory septic shock: study protocol for a multicenter, randomized, placebo-controlled trial

BackgroundSeptic shock is now the leading cause of mortality in intensive care units (ICUs). Refractory septic shock requires high doses of vasopressors. Some previous studies have revealed that methylene blue could improve hypotension status and help reduce the dosage of catecholamines. This study aims to investigate the clinical effect of methylene blue in septic shock and explore whether it can increase arterial pressure and reduce the usage of vasopressors.MethodsThis study is a multicenter, randomized, placebo-controlled trial planning to include 100 refractory septic shock patients. The protocol is to administer a bolus of 2 mg/kg methylene blue intravenously followed by a continuous infusion of 0.5 mg/kg/h for 48 h. The primary outcome is the total dose of vasopressor required in refractory septic shock in the first 48 h. Secondary outcomes include other hemodynamic parameters, oxygen metabolism indexes, tissue perfusion indexes, major organ function indexes, and certain plasma cytokines and other factors.DiscussionThis protocol aims to evaluate the safety and efficacy of methylene blue as adjuvant therapy for refractory septic shock. The main outcome measure will be vasopressor requirements and hemodynamic parameters. Additionally, bedside ultrasonography, blood gases, and cytokines will be assessed to evaluate perfusion, respiratory, and metabolic effects. The results are intended to provide evidence on the safety and efficacy of methylene blue in refractory septic shock, guiding clinical decision-making.Trial registrationThis clinical trial has been registered at ChiCTR (https://www.chictr.org.cn/) on March 16, 2023. ChiCTR registration number: ChiCTR2300069430.