Index Values Research Articles

The relationship between perception and landscape characteristics of recreational places with human mental well-being.

Being outdoors benefits both humans' physical and mental well-being, but the reasons for this connection are difficult to pinpoint. This study examines 40 recreational areas to understand their individual characteristics' impact on mental well-being. We interviewed 1184 visitors on their perception of the place and feeling of mental well-being. In a second survey, 49 participants were shown images of the areas to assess whether they perceived them in the same way as people on-site did. Biologists then evaluated the areas through bird and biotope surveys, also assessing various other landscape characteristics of the study areas. Analysis using a two-level multivariate GLM revealed that perceived naturalness and perceived bird diversity are significant predictors of improved mental well-being. On the flip side, mental well-being declines with increased human impact, as indicated by the amount of infrastructure and the Human Footprint Index value. Notably, perceived naturalness positively correlates with actual bird diversity (p = 0.005) and negatively with human impact (p = 0.006). A strong perception of birds enhances the mental well-being of greenspace visitors (p < 0.001), while a high birding specialization negatively affects recalled restoration (p = 0.014). The estimated restoration value (p = 0.001) and estimated beauty (p < 0.001) from the online survey correlate positively with emotions experienced on-site. The perception of naturalness in images aligns with on-site perception, suggesting pathways for future research and the design of recreational areas.

The global burden of chronic respiratory diseases attributable to tobacco from 1990 to 2021: a global burden of disease study 2021

BackgroundTobacco is a major risk factor for chronic respiratory diseases (CRDs), yet the global distribution and trends of tobacco-related CRD burdens remain inadequately explored.MethodsThis study extracted data on mortality, disability-adjusted life years (DALYs), age-standardized mortality rate (ASMR), and age-standardized DALY rate (ASDR) related to tobacco-attributable CRDs from the 2021 Global Burden of Disease (GBD) study. Joinpoint regression was used to identify temporal trends in age-standardized rates (ASR), while autoregressive integrated moving average (ARIMA) forecasting was applied to project future trends in ASMR and ASDR for tobacco-related CRDs.ResultsIn 2021, global tobacco-related CRD deaths and DALYs reached 1,545,686 (95% UI: 1,144,476-1,942,541) and 33,014,429 (95% UI: 24,275,462 − 40,930,821), representing increases of 25.43% and 15.64%, respectively, since 1990. Elderly individuals and males showed a higher disease burden. Between 1990 and 2021, ASMR [average annual percentage change (AAPC) = -2.009 (95% CI: -1.8915 to -2.1263)] and ASDR [AAPC = -2.1057 (95% CI: -2.0123 to -2.199)] for tobacco-related CRDs showed a declining trend globally, with autoregressive integrated moving average forecasting suggesting continued declines in ASMR and ASDR in the future. Regionally, South Asia, East Asia, and Oceania had the highest CRD burdens, while country-specific data indicated that Nepal, Myanmar, Papua New Guinea, Kiribati, and the Democratic People’s Republic of Korea bore significant burdens. The ASMR and ASDR of tobacco-related CRDs were highest in regions and countries with Socio-Demographic Index values between 0.4 and 0.5.ConclusionAlthough global tobacco-related CRD deaths and DALYs have continued to increase, ASMR and ASDR are on the decline, with variations across geographic regions. Prevention and control strategies tailored to country-specific disease prevalence are essential to mitigate these burdens.

Short-Wave Infrared Hyperspectral Image-Based Quality Grading of Dried Laver (Pyropia spp.)

Laver (Pyropia spp.) is a major seaweed that is cultivated and consumed globally. Although quality standards for laver products have been established, traditional physicochemical analyses and sensory evaluations have notable drawbacks regarding rapid-quality inspection. Not all relevant physicochemical quality indices, such as texture, are typically evaluated. Therefore, in this study, we investigated the use of hyperspectral imaging to rapidly, accurately, and objectively determine the quality of dried laver. Hyperspectral images of 25 dried laver samples were captured in the short-wave infrared range from 980 to 2576 nm to assess their moisture, protein content, cutting stress, and other key quality indicators. Spectral signatures were analyzed using partial least-squares discriminant analysis (PLS-DA) to correlate the spectral data with three primary quality index values. The performance of PLS-DA was compared with that of the variable importance in projection score and nonlinear regression analysis methods. The comprehensive quality grading model demonstrated accuracies ranging from 96 to 100%, R2 values from 75 to 92%, and root-mean-square errors from 0.14 to 0.25. These results suggest that the PLS-DA regression model shows great potential for the multivariate analysis of hyperspectral images, serving as an effective quality grading system for dried laver.

A matching method for elderly care service personnel with multiple types of service expectations.

With the rapid growth of the global aging population, the problem of providing for the elderly has become increasingly prominent. As a new model of providing for the elderly in China, home-based care has attracted more and more attention from all walks of life. The research on how to realize reasonable and effective matching between elderly care service personnel and the elderly under the home care model deserves attention and has important practical significance. In this paper, a matching method for elderly care service personnel considering multi-type service expectations is proposed. This approach involves first obtaining the actual values of the expectation indexes for each other, as well as the expectation requirements of the elderly and the service personnel. Next, we compute the satisfaction of the elderly and the service personnel for each other based on the elastic service expectation type, and finally, we make a decision about whom to choose based on the inelastic service expectation indexes. On this basis, the situation is considered that there are sufficient and insufficient elderly care service personnel, the two-sided matching models are constructed, respectively, and the optimal matching results are obtained by solving the models. Finally, an example is given to illustrate the feasibility and effectiveness of the proposed method.

Clinical experience of using the ckd progression rate calculator to stratify a group of elderly patients with type 2 diabetes with a very high risk of cardiovascular outcomes

Objective: to analyze the clinical experience of using the CKD progression rate calculator to stratify the prognosis of elderly patients with DM2, belonging to a very high cardiovascular risk group. Material and methods: to determine the systemic coronary risk of elderly patients with DM2, the generally accepted and most relevant SCORE2 and SCORE2-OP algorithms were used to assess the 10-year risk of fatal and nonfatal cardiovascular events. Further more accurate stratification of the risks of CKD was performed using a prognostic Calculator of the rate of progression of CKD in elderly patients with DM2, developed at the Department of Endocrinology of the Samara state medical university. Results: as a clinical example, two 69 and 70-year-old patients were randomly selected from the group of participants used in the development of the mathematical model of the Calculator. According to the SCORE2 and SCORE2-OP algorithms, both patients were assigned to a very high-risk group of cardiovascular diseases, the values of which were 33% for patient XXX; 24% for patient YYY, excluding concomitant DM2 and CKD. To clarify the clinical prognosis, an original Calculator was used, which demonstrated different characteristics of the CKD progression rate in these patients (“low” and “high” with a cut-off value of the GFR reduction index of 3.83 ml/min/1.73 m2 per year), despite the identity of the parameters of the clinical and laboratory status. Conclusions: the use of traditional ASSR risk assessment scales for predicting outcomes in a cohort of elderly with DM2 has significant limitations, since most patients of older age groups fall into a homogeneous group of very high risk without the possibility of further stratification; the use of a Calculator for the rate of progression of CKD allows you to refine the prognosis, optimize the program of follow-up and determine indications for prescribing drugs with proven nephroprotective the effect in elderly patients with DM2.

Improvement and quality evaluation of rutab date paste fortified with wheat germ

This investigation aimed to utilize wheat germ to improve the nutritional value and sensory properties of date pastes. Wheat germ was added to the soft date paste at different concentrations (5, 10%, and 15%). Chemical composition, bioactive compounds, browning index, fatty acids, microbiological quality, and peroxide values were estimated. Substitution with wheat germ significantly increased the ash, protein, and fat contents of the treatments, and decreased total sugars and total carbohydrates. In addition, the incorporation of wheat germ into the date paste led to a decrease in water activity. The color index of fortified date paste was improved and unsaturated fatty acids, such as oleic acid, linoleic acid, and linolenic acid, increased. A reduction in the total bacterial, yeast, and mold counts was observed. The highest score of the index of acceptance was recorded for 15%, followed by 10% and 5%, and the lowest score was for the control sample.

Comparative Study of Plant‐Based Antioxidants on the Stability of Soybean and Beef Tallow Biodiesels

ABSTRACTBiodiesel is a renewable alternative fuel, but its oxidative instability reduces quality and performance over time. This study explicitly aimed to investigate the efficacy of natural antioxidants—acerola, soursop, mango, and pitanga leaves—and compare their performance to the synthetic antioxidant butylated hydroxytoluene (BHT) in enhancing the thermooxidative stability of soybean ethyl and bovine tallow methyl biodiesels. Biodiesels were synthesized and stored under controlled conditions (ambient and 60°C) for up to 1848 h. Analytical results showed that biodiesel treated with BHT maintained acidity index (AI) values below 0.5 mg KOH/g after 1176 h, while untreated biodiesel exceeded 1.0 mg KOH/g within 504 h. Kinematic viscosity for BHT‐treated samples remained under the acceptable limit of 6.0 mm²/s for 1176 h, compared with untreated biodiesel, which surpassed the limit at 504 h. Natural antioxidants exhibited varying degrees of efficacy, with soursop and pitanga extracts achieving 35%–50% improvements in oxidative stability compared with untreated biodiesel. Thermogravimetric analysis indicated that natural additives delayed the onset of degradation temperatures by 10°C–15°C. These findings demonstrate that plant‐based antioxidants significantly enhance biodiesel stability, offering up to 70% of the effectiveness of BHT, and highlight their potential as sustainable alternatives for improving biodiesel quality.

Assessment of forest soil contamination by heavy metals in the Polish National Park near Warsaw

The forest ecosystems are essential for human well-being development and reduction of the risk of natural disasters. Maintaining forest growth and ecosystem services is dependent on soil sustainability. The content of heavy metals is the main parameter determining the degree of soil contamination and degradation. The objective of the study was to assess the extent of soil contamination and identify the sources of potential anomalies. The content of the cadmium, lead, manganese and chromium (using atomic emission spectroscopy with induction-coupled plasma), as well as granulometric composition, pH value and nitrogen and total carbon content, were conducted on soil samples taken from the surface layer (0–10 cm) in the protected area of the Kampinos National Park in Poland. The soil quality assessment was conducted by calculating indicators of contamination including the geo-accumulation index, contamination factor, degree of contamination, ecological risk of individual heavy metals and potential ecological risk index. The results exhibited that the tested soils were very acidic or acidic sands. The content of the determined elements did not exceed the permissible limits as outlined in Polish standards, which are 2 mg/kg, 100 mg/kg and 150 mg/kg for cadmium, lead and chromium, respectively. The indicators show differences in the degree of contamination of the surface soil layer in the studied area, which is predominantly uncontaminated by heavy metals. However, the geochemical index values equal 0.42, 0.71 and 0.98 for certain samples suggesting the anthropogenic impact on the soils of the Kampinos National Park. The pollution appears to have been generated by the metallurgical industry, heating and power plants in the Warsaw agglomeration and transport.

A multi-source data-driven approach for navigation safety integrating computational intelligence and Bayesian networks

Ships often face various risks when sailing at sea, ranging from harsh natural environments to complex traffic conditions. To reduce the impact of these risks on ships and crews, this paper proposes a navigation risk assessment method that integrates computational intelligence (CI) techniques, such as fuzzy logic, with Bayesian networks (BNs) and utility theory. Firstly, a navigation risk assessment system is established using maritime data and expert knowledge, which evaluates risks from a spatial perspective by considering factors such as safeguard and accident conditions across different regions. Secondly, a fuzzy logic-based numerical and expert data transformation method is proposed to derive the prior probabilities of risk factors in BNs. The weighted fuzzy rule base is used to capture the dependencies among the risk factors. Finally, the probability distribution of navigation risk is determined by combining the prior probability and the dependencies, which are converted into risk index values through utility theory. Taking the grid-based navigation risk assessment of the South China Sea as an example, the effectiveness of this method is verified. The results of the study provide theoretical support for navigation risk assessment based on multi-source data and provide a reference for formulate maritime regulatory policies.

Heavy metals pollution in riverine sediments: Distribution, source, and environmental implications.

This research reports heavy metal pollution in riverine sediments from River Kabul, Pakistan, which could endanger human health and ecology via the food web. The results revealed a substantial special variation in the average contents (mg/kg) of chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), lead (Pb), iron (Fe), and aluminum (Al) in riverine sediments, in the order of Fe (20,234.51) > Al (17,550.86) > Mn (375.45) > Zn (149.08) > Ni (89.11) > Cr (83.36) > Pb (45.29) > Cu (19.86) > Cd (7.48) > Co (6.28) > Hg (0.81). Among the heavy metals, Cd exhibited the highest degree of pollution along the river, followed by Hg > Ni > Zn > Pb > Al > Cr > Mn > Fe > Cu > Co. The overall contamination factor (CF) values for the sum of heavy metals were highest at monitoring site S-9, followed by S-8 > S-10 > S-6 > S-5 > S-7 > S-1 > S-4 > S-12 > S-3 > S-2 > S-1 with pollution load index (PLI) > 1, whereas the geo-accumulation index (Igeo) values of Cd and Hg fluctuated between Levels 3, 4, and 6, suggesting moderate to extreme pollution in the river. The correlation statistics determined the fate and distribution of heavy metals by establishing significant positive correlations between the specific metals of bounded sediments. The cluster analysis separates the correlated metals into Groups A and B, and Groups 1 and 2. While the principal component analysis evaluates the qualitative behavior of clustering by discerning industrial, agrochemicals, mining, and domestic wastewater discharges, leakages of lubricants along with multiple geogenic inputs, erosion of mafic and ultramafic rocks, and minimal atmospheric deposition are all potential sources of Cr, Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb, Fe, and Al contamination. In terms of risk, the contaminations of Mn, Co, Cu, Zn, and Pb in riverine sediments were 85, 100, 100, 17, and 11%, respectively, representing a rare biological influence because their value is less than their corresponding threshold effect concentrations (TECs), whereas the levels of Mn, Ni, Cd, and Hg were above their probable effect concentrations (PECs) of 100, 100, 81, and 52%, respectively, representing prominent adverse biological influence. Based on consensus-based TECs and PECs, the contamination levels of Cr, Mn, Zn, Cd, Hg, and Pb were 100, 85, 83, 19, 48, and 90%, respectively, indicating occasionally exhibited adverse biological effects on the riverine population. Besides, the overall potential ecological risk index (PERI) of Cd and Hg, in particular, exhibited the maximum pollution level ( ≥ 320), suggesting a very high potential ecological risk in the drainage that requires special attention from pollution control authorities.

Health and Ecological Risk From Potentially Toxic Elements in Soils and Extra Virgin Olive Oils From Valdichiana Senese, Tuscany (Italy)

ABSTRACTBackgroundExtra virgin olive oils (EVOOs) are widely consumed but rarely analysed for potentially toxic elements (PTEs), whose concentrations in EVOOs can be significantly influenced by contamination in olive grove soils. As food consumption is the main PTE accumulation pathway in humans, thorough investigation on EVOOs is necessary.AimThe concentrations of 12 PTEs were determined in olive grove soils and EVOOs from Valdichiana Senese (Southern Tuscany, Italy), with the aim of identifying any contamination by PTEs in olive grove soils and evaluating the associated ecological risk as well as of assessing the potential risk for human health related to PTE intake from EVOO consumption.MethodsThe soil and EVOO samples were collected from 18 farms, and the concentration of As, Cd, Co, Cr, Cu, Ni, Pb, Sb, Tl, U, V and Zn was determined by inductively coupled plasma mass spectrometry (ICP–MS). The data were used to calculate the health risk index (HRI) for EVOOs and the geoaccumulation index (Igeo) and potential ecological risk index (PERI) for soils.ResultsAnalytical data suggested that the PTE concentrations in the investigated olive grove soils are natural as comparable to their normal geochemical background in soils from Southern Tuscany formed from the same parent rocks of Valdichiana Senese soils or due to local geogenic enrichments in some parent rocks. Among the analysed PTEs in the EVOO samples, Zn, Cu and Ni had the highest concentrations, followed by Cr and Pb. Most PTEs showed a high variability of their concentrations in EVOOs from Valdichiana Senese.ConclusionOn the basis of values of indices applied to PTE concentrations in the soil samples, a low‐to‐moderate Cu contamination emerged only in the olive grove soils of two farms, probably as a consequence of the diffuse use of Cu‐based products in agriculture, and overall, the ecological risk was low. Furthermore, although EVOOs from Valdichiana Senese have somewhat slightly high concentrations of some PTEs such as Cu and Zn, the health risk associated with their intake through the EVOO consumption is definitely negligible.

Multi-Objective Optimization of the Turning Process using the Probability Method

This research aims to determine the optimal values of the cutting parameters when solving the turning process multi-objective problem. Three cutting parameters are considered in this study: spindle speed (nw), feed rate (f), and depth of cut (ap). A turning experiment series was conducted on a conventional lathe, with nine experiments having been designed according to the Taguchi experimental design matrix. In each experiment, the values of the three parameters changed and the material Removal Rate (Q) was measured. The Probability method was used to solve the multi-objective optimization problem. The Method based on the Removal Effects of Criteria (MEREC) technique was employed to calculate the weights of the criteria. The results of the optimization problem using the Probability method were also compared with those obtained using other methods, including the Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Vlsekriterijumska optimizacijaI KOmpromisno Resenje (VIKOR), Multi-Atributive Ideal-Real Comparative Analysis (MAIRCA), Evaluation by an Area-based Method for Ranking (EAMR), Complex Proportional Assessment (COPRAS), Measurement Alternatives and Ranking according to Compromise Solution (MARCOS), Proximity Indexed Value (PIV), and Combined Compromise Solution (COCOSO). All the methods converged on the same unique solution to the multi-objective optimization problem. The optimal values for the parameters were: nw = 1350 rev/min, corresponding to a feed rate of 0.13 mm/rev, and a depth of cut of 0.4 mm. When machining with these optimal cutting parameters, the resulting values for Ra, RE, and Q were 1.057 µm, 0.03 mm, and 13225.68 mm²/min, respectively.

Application of the PSI Method in Selecting Sustainable Energy Development Technologies

The development of renewable energy is not only an urgent solution for addressing climate change but also a driving force for sustainable economic growth. The transition to clean, inexhaustible energy sources not only helps to reduce greenhouse gas emissions and protect the environment but also ensures national energy security, creates employment opportunities, and enhances the quality of life for individuals. Presently, various technologies exist for sustainable energy development, each characterized by multiple criteria, complicating the evaluation of their performance. This study presents a straightforward method for identifying the best option among eight sustainable energy development alternatives: hydropower, geothermal, biomass, wind, solar, concentrated solar power, coal technology, and oil-fired power plants, each of which is characterized by 17 distinct criteria. The simple method utilized is the Preference Selection Index (PSI) method, which eliminates the need for criteria weighting. This absence of criteria weight calculation in the PSI method distinguishes it from other ranking techniques that typically require such calculations. Therefore, the PSI method significantly simplifies the comparison of the available options compared to other ranking methods, as it bypasses the need for criteria weight calculations. The optimal option identified through the PSI method was also compared with the optimal option identified using 6 other methods: Multi Atributive Ideal Real Com parative Analysis (MAIRCA), Evaluation Based on Distance from Average Solution (EDAS), COmplex PRroportional ASsessment (COPRAPS), Multiobjective Optimization On the basis of Ratio Analysis (MOORA), Proximity Indexed Value (PIV), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Notably, all employed methods consistently identified geothermal energy as the optimal choice.

Benefits of movement-based Behaviors on improving erectile function in American men: a nationwide survey study.

Erectile dysfunction (ED) is a prevalent condition with significant psychological and physiological impacts. Recently, a new concept called movement-based behaviors (MBB) has been proposed, which includes four types of PA: vigorous PA (VPA), moderate-intensity PA (MPA), walking/cycling, and muscle-strengthening activities (MSA), and uses an MBB index (range 0-4) to estimate the combined effects of these activities on health outcomes. This study aims to evaluate the relationship between different types of physical activities (PA) and ED using the MBB index in a nationally representative sample of U.S. men. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2001-2004, including 3435 male participants. Multivariate logistic regressions were performed to explore the associations, supplemented with subgroup analysis and sensitivity analysis. The assessment of PA in this study is based on four self-reported questions from the NHANES Mobile Examination Center interview, including VPA, MPA, walking/cycling, and MSA. The MBB index, ranging from 0 to 4, was used to assess combined PA types. ED was evaluated using a single-question self-assessment. Higher MBB index values were associated with lower ED risk. Participants with an MBB index of 2 had a significantly lower risk of ED in Model 3 (OR = 0.65, 95% CI: 0.43-0.97, P = 0.04). Those with an MBB index of 3 or 4 had the lowest risk of ED across all models, with OR_Model1 = 0.29 (95% CI: 0.21-0.40, P < 0.0001), OR_Model2 = 0.52 (95% CI: 0.37-0.73, P < 0.001), and OR_Model3 = 0.61 (95% CI: 0.41-0.90, P = 0.02). However, this relationship was not significant in subgroups with severe ED or comorbid conditions. Our findings can provide clinicians with guidance to help patients personalize their selection of different exercise combinations. We explored the impact of different exercise combinations on reducing ED risk and innovatively proposed the MBB index for a comprehensive assessment of exercise benefits, supported by a large sample size and multivariable adjustments. However, the limitations of cross-sectional design and recall bias cannot be overlooked. The MBB index effectively demonstrates that combined PA can reduce ED risk, supporting tailored exercise recommendations for patients.

Hybrid Multi-Criteria Decision Making Methods: Combination of Preference Selection Index Method with Faire Un Choix Adèquat, Root Assessment Method, and Proximity Indexed Value

This study presents an investigation into the hybridization of Multiple Criteria Decision Making (MCDM) methods. The Preference Selection Index (PSI) method is used in two distinct ways: first, for its traditional purpose of ranking alternatives, and second, to calculate criteria weights. These criteria weights are utilized to rank the alternatives provided by other MCDM methods, including the Faire Un Choix Adéquat (FUCA), Root Assessment Method (RAM), and Proximity Indexed Value (PIV), resulting in the creation of three hybrid models: FUCA-PSI, RAM-PSI, and PIV-PSI. The effectiveness of these hybrid approaches is tested by ranking 20 Vietnamese cities based on their digital transformation efforts. The results demonstrate that the hybrid approaches produce a highly correlated ranking, as evidenced by the Spearman rank correlation coefficient found among these methods, with the lowest being 0.8571. Both the PSI method and the three hybrid models identified the same top alternative, confirming the reliability and accuracy of the rankings.

Evaluating the Impact of Weighting Methods on the Stability of Scores for Alternatives in Multi-Criteria Decision-Making Problems

Criteria weights play a crucial role in Multi-Criteria Decision Making (MCDM) problems when selecting the best alternative from a set of options. This study aims to compare three objective weighting methods: MEthod based on the Removal Effects of Criteria (MEREC), Entropy, and Symmetry Point of Criterion (SPC). These methods were applied to a case study involving the ranking of eight sustainable energy development alternatives, each characterized by seventeen criteria. Four representative MCDM methods, the Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Proximity Indexed Value (PIV), and Root Assessment Method (RAM), were also deployed. The results revealed that the Entropy method provided the most stable and consistent performance, followed by the MEREC method, with the SPC method showing the least stability.

Spatiotemporal discrepancies and risk assessment of toxic heavy metals in surface water of Shitalakhya River around Narayanganj port in Bangladesh

The urban rivers of developing countries like Bangladesh have been severely affected by toxic heavy metal pollution, posing serious ecological and human health risks. This study aimed to investigate the concentrations, spatiotemporal discrepancies, and associated risks of five alarming toxic metals (Pb, Cd, Cr, Cu and Mn) in the surface water of urban Shitalakhya River around Narayanganj port, one of the biggest and most important river ports in Bangladesh. Water samples were collected for three prevailing seasons i.e., pre-monsoon, monsoon, and post-monsoon from five selected sites. Physicochemical properties (color, odor, temperature, DO, pH, EC and TDS) of river water were also assessed, while heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and degree of contamination (CD) were calculated to evaluate the risks associated with toxic metal pollution in river water. The findings revealed that several physicochemical parameters, especially DO, EC and TDS, were not within the standards. The hierarchy of mean heavy metal concentrations in Shitalakhya River water was found as Mn&gt;Cr&gt;Cu&gt;Cd&gt;Pb during pre-monsoon, Mn&gt;Cu&gt;Cr&gt;Cd&gt;Pb during monsoon, and Mn&gt;Cr&gt;Cu&gt;Pb&gt;Cd during post-monsoon season. The metal concentrations were found to be higher in pre-monsoon and post-monsoon seasons, whereas the concentrations of all the heavy metals excluding Mn were within the standards recommended for domestic use, surface water, fisheries and irrigation purposes. The comparative analysis exhibited that the water quality of Shitalakhya River is deteriorating day by day at an alarming rate. HPI showed a critical pollution index value (drinking) for all three seasons, whereas HEI revealed low heavy metal contamination for all sampling stations. The values of CD indicated a high level of contamination in pre-monsoon and post-monsoon but monsoon season. The results confirmed the spatiotemporal discrepancies in toxic metal concentrations and associated ecological and human health risks, possibly resulting from the hydrological and anthropogenic interventions not only associated with port activities. Hence, urgent collective effort and proper monitoring are of utmost importance to safeguard the public health and this urban riverine ecosystem. Int. J. Agril. Res. Innov. Tech. 14(2): 74-84, December 2024

Shock index reference ranges in the first 48h postpartum following elective cesarean delivery: A prospective cohort study.

To determine the reference values for the shock index (SI) in postpartum patients undergoing elective cesarean delivery with regional anesthesia. This prospective study was conducted at our tertiary center between August 1, 2023, and March 1, 2024. We calculated the reference values for the SI within the first 48h postpartum for patients who underwent elective cesarean delivery after the 34th week of gestation. We excluded cases of vaginal delivery, post-term delivery (≥42weeks of gestation), multiple pregnancies, stillbirths, fetal abnormalities, maternal cardiac disease, anemia, untreated hypo- or hyperthyroidism, and any hypertensive disorders diagnosed before or during pregnancy. Data collection, measurement of vital signs, and the administration of fluids pre-, intra-, and post-operatively, as well as the use and dosing of uterotonic agents for the prevention of postpartum hemorrhage (PPH), were standardized for all patients. Our final analysis included 311 patients, with a mean SI value of approximately 0.7 (0.67-0.77) for all measurement performed within the first 48h of the postpartum period. Further analyses revealed that the 90th and 95th percentiles of SI were around 0.9 throughout the study period. Additionally, SI reference values analyzed at different time points were consistent. Our analysis demonstrated that SI values were not influenced by the presence of a previous caesarean section, the administration of oxytocin or carbetocin, or parity in this particular cohort. Our analyses of vital signs also indicated that the 95th percentile of heart rate (HR) ranged from 96 to 100bpm. An SI value of 0.9 represents the 95th percentile of SI values throughout the first 48h of the postpartum period. Any greater value should be evaluated carefully for potential adverse outcomes.

Ecological and Health Risk Assessment of Heavy Metals and Organochlorine Pesticides in Water and Sediments from Otamiri River in Imo State, Nigeria

Ecological and health risk of selected heavy metals and Organochlorine pesticide residues (OCPs) were assessed in Water and Sediments from Otamiri River in Imo state, Nigeria. Water and sediment samples were collected during rainy and dry periods from three different points and mixed together to form a composite sample. Pesticide residues and heavy metals were analysed using gas chromatography-mass spectrometry and atomic absorption spectrophotometer respectively. The concentration of heavy metal during rainy and dry season ranged from ND to 1.56 mg/l and ND to 3.61 mg/l for water samples, 0.005 to 1.8 mg/kg, and 0.008 to 1.0 mg/kg for sediments respectively. The geo-accumulation index Igeo(x) of heavy metals on sediment ranged from 0 to 0.7 while the values of pollution index were greater than one, signifying heavy metal pollution status of the river. The ecological risk index showed that Nickel and Cadmium had moderate to considerable ecological risk ranging from 129.9-348. The OCP residues concentration ranged from ND to 6.35 mg/l and ND to 4.55 mg/l for water samples, ND to 3.22 mg/kg and ND to 3.5 mg/kg for sediments during rainy and dry season respectively, with predominance of BHCs, DDTs and heptachlor epoxide in water and sediment matrixes. The pesticide residues found in the present study were generally below the maximum residues limit (MRL) set by FAO/WHO bodies. Ecological risk using the Risk quotient was found to be (RQ ≥1) during both seasons and shows higher risks for β-HCH, endosulphan sulfate and p,p′-DDT. The non-carcinogenic risk hazard index (HI) values of both exposure routes were less than one. Conversely, the estimated carcinogenic risk by OCPs through ingestion exposure ranged from 8.142E−9 to 1.20E−7 and 6.36E-7 to 6.44E-4 while dermal range from 3.4E-11 to 2.14E-8 and 7.14E-7 to 8.6E-4 for adults and children respectively, showing considerable carcinogenic risk associated to p,p′-DDT, heptachlor epoxide, α- HCH and aldrin. There is need for regular monitoring of the river to ensure water quality sustainability due to environmental and health risk of the levels of heavy metals and OCPs.

The Impact of Gender Factors on Economic Development: A Global Comparative Analysis

The purpose of this study is to determine trends and the current state of the gender issue, as well as the impact of different gender factors, taking into account the period of COVID-19, on the level of Ukrainian GDP compared with the countries of the world in modern conditions and to propose appropriate recommendations for the activation and stimulation of women’s participation in business. The authors emphasize that women are disproportionately affected by various social crises: climate change, wars, conflicts and human rights violations etc. The authors analyze the Ukrainian Gender Inequality Index in and make a conclusion that it more than halved during the last decades. The reason for this, especially in recent years, was the COVID-19 pandemic and the subsequent full-scale Russian invasion of Ukraine that had a very negative impact on business. The authors note that Ukraine is situated in 35th place in the European ranking of countries concerning the value of the Gender Inequality Index. A large number of women are generally not involved in the labor market or other economic activities. At the same time, a continuing consequence of the Russian full-scale invasion of Ukraine was a noticeable lack of qualified personnel on the labor market. This is due to the involvement of exclusively men in certain sectors of the economy and their mobilization. The results of the regression analysis indicate that economic participation has the greatest impact on GDP among all the components of the Global Gender Gap Index in the USA, Canada and Poland. Educational attainment is situated on the second place. As for Ukraine, the authors show that as the level of participation of women in the labor force increases, Ukrainian GDP also increases. Taking into account the results of the calculations, the authors conclude that gender factors have a direct impact on the country's economy Keywords: gender factors, sustainable development, gender equality, Gender Inequality Index, Global Gender Gap Index, GDP, Ukraine, Poland, The USA, Canada.