Technical Analysis Research Articles

Incidence of hip fractures in Mexico 2006-2019: increasing numbers but decreasing rates.

This study is to examine the incidence, rates, and time trends of hip fractures from 2006 to 2019 in Mexico. Additionally, an analysis of the follow-up of the birth cohorts was carried out. Hip fractures registered during the period of the study were obtained through the Mexican Social Security Institute (IMSS) national discharge records. The incidence per 100,000 individuals was calculated from the IMSS population at risk. A time trend analysis was conducted using linear regression, and the identification of breakpoints in linear trends. There was an increase of hip fractures for both sexes ≥ 60years (43% for women and 41%, for men). However, the rates diminished from 167.8/100,000 in 2006 to 138.5 /100,000 in the population 60 and over (1.9% and 0.9% per year in women and men respectively). When the information was analyzed by age groups, hip fracture rates were similar in both sexes but higher in women. The most significant contribution to the total number of fractures is due to the groups ≥ 70years; people born before 1937 are accounting for the burden of fractures over the total data. In contrast, the younger generations appear to have lower rates. Rates of hip fracture have steadily declined in Mexico since 2006; however, with the population aging in the coming decades, current rates declines could be expected to reverse.

Technical and economic analysis of floating solar photovoltaic systems in coastal regions of India: a case study of Gujarat and Tamil Nadu

Technical and economic analysis of floating solar photovoltaic systems in coastal regions of India: a case study of Gujarat and Tamil Nadu

Using Machine Learning Techniques to Forecast Mehram Company's Sales: A Case Study

Sales forecasting, situated at the intersection of art and science, is critical for inspiring managers toward achieving profitable outcomes. Its precision sustains production levels and capital and plays a pivotal role in the company's and its leaders' overall success and career progression. In the context of Mahram Food Industries, the challenge arises from diverse investor perspectives and the impactful nature of numerous variables. To address this, a new sales forecasting algorithm has been introduced to enhance accuracy. The aim is to predict future sales through a comprehensive approach, leveraging technical analysis, time series modeling, machine learning, neural networks, and random forest techniques. The research methodology integrates various advanced techniques to improve sales forecasting for Mahram Food Industries. Technical analysis, time series modeling, machine learning, neural networks, and random forest methods are combined to create a robust framework. The focus is on predicting sales for a future period within the artificial intelligence-based machine learning domain. The study employs metrics such as Mean Absolute Deviation (MAD), MAD Percentage (MADP), and Mean Squared Error (MSE) to evaluate and compare the performance of the proposed neural network against traditional methods like multiple variable regression and time series modeling. The study's results highlight the superior performance of the neural network in sales forecasting for Mahram Food Industries. The Mean Absolute Deviation (MAD) for the neural network is 28.33, outperforming multiple variable regression (28.54) and time series modeling (29.45). Additionally, the neural network demonstrates a better MAD Percentage (MADP) with a value of 10.2%, surpassing the values associated with multiple variable regression (10.35%) and time series modeling (10.30%). The Mean Squared Error (MSE) further confirms the neural network's superiority with a value of 6452 compared to 6472 and 7865 for multiple variable regression and time series modeling, respectively. In conclusion, the study showcases the effectiveness of integrating advanced techniques, particularly the neural network, in enhancing the accuracy of sales forecasting for Mahram Food Industries. The comprehensive approach, combining technical analysis, time series modeling, machine learning, neural networks, and random forest, is a valuable strategy for predicting future sales. The superior performance of the neural network, as evidenced by lower MAD, MADP, and MSE values, suggests its potential for guiding informed decision-making in goal setting, hiring, budgeting, and other critical aspects of business management.

Analyzing Microsoft stock price trends, factors, and market efficiency for optimal investment strategies

Microsoft, one of the tech giants, has seen significant fluctuations in its stock prices in recent years. This article delves into an analytical study of these changes using data sourced from Yahoo Finance. The background for this research stems from the desire to understand the intricacies of stock price movements and the factors influencing them, especially for prominent companies like Microsoft that have a vast impact on global markets. The methodology adopted for this study is the technical approach, where the moving average is calculated to determine the stocks trend. Moving averages are a cornerstone of technical analysis and can provide insights into potential buy and sell signals. By employing this method, the research aims to validate the appropriateness of certain investment strategies based on historical data. The primary objective of the study is not just to chart the course of the stocks price but to delve deeper into the causative factors behind its movement. Various external and internal factors can influence stock prices, from global economic trends to company-specific news. By analyzing these factors, the research also seeks to test the efficiency of the market, a long-debated topic among economists and investors. In conclusion, while past data can offer insights, the stock markets volatile nature demands continuous adaptation of investment strategies. The findings from this study can serve as a foundation for developing more refined prediction tools and investment tactics. Future studies might consider integrating more sophisticated models or incorporating other predictive variables to enhance accuracy and investment outcomes.

Technical, Environmental, and Economic Analysis Comparing Low-Carbon Industrial Process Heat Options in U.S. Poly(vinyl chloride) and Ethylene Manufacturing Facilities.

Electrification and clean hydrogen are promising low-carbon options for decarbonizing industrial process heat, which is an essential target for reducing sector-wide emissions. However, industrial processes with heat demand vary significantly across industries in terms of temperature requirements, capacities, and equipment, making it challenging to determine applications for low-carbon technologies that are technically and economically feasible. In this analysis, we develop a framework for evaluating life cycle emissions, water use, and cost impacts of electric and clean hydrogen process heat technologies and apply it in several case studies for plastics and petrochemical manufacturing industries in the United States. Our results show that industrial heat pumps could reduce emissions by 12-17% in a typical poly(vinyl chloride) (PVC) facility in certain locations currently, compared to conventional natural gas combustion, and that other electric technologies in PVC and ethylene production could reduce emissions by nearly 90% with a sufficiently decarbonized electric grid. Life cycle water use increases significantly in all low-carbon technology cases. The levelized cost of heat of viable low-carbon technologies ranges from 15 to 100% higher than conventional heating systems, primarily due to energy costs. We discuss results in the context of relevant policies that could be useful to manufacturing facilities and policymakers for aiding the transition to low-carbon process heat technologies.

Feasibility study: Economic and technical analysis of optimal configuration and operation of a hybrid CSP/PV/wind power cogeneration system with energy storage

In this study, a hybrid photovoltaic-wind-concentrated solar power renewable energy system and two cogeneration models are proposed. Evaluation criteria are employed, including the levelized cost of energy (LCOE) and the loss of power supply probability (LPSP). The optimal configuration and dynamic dispatch strategy of the hybrid system are determined through multi-objective optimization using the natural resources of Xining City. The economic feasibility of the system is assessed through comparison and analysis. The findings reveal that both cogeneration modes of the system effectively meet the power output requirements and dynamic thermal load. In thermal energy storage tanks' heat production mode without a battery storage system, the system achieves a minimum LCOE of 0.0526$/kWh and a maximum LPSP of 6.86%. With a battery storage system in this mode, the system attains a minimum LPSP of 4.83% and a maximum LCOE of 0.160$/kWh. Additionally, in the turbine spent vapor recovery heat supply mode, the system exhibits an LCOE of 0.127$/kWh and an LPSP of 4.96%, the system has better flexibility and wind-solar complementarity in this mode. This study also analyzed the importance of affordable electric energy storage for stable energy supply in hybrid energy systems.

Analisis Teknikal Menggunakan Moving Average (MA), Moving Average Convergence-Divergence (MACD), dan Relative Strength Index (RSI) Untuk Mengoptimalkan Dalam Pengambilan Keputusan Investasi Pada Saham Sektor Manufaktur Index LQ45 BEI Tahun 2022-2023

This research examines technical stock analysis techniques for six manufacturing sector companies listed on the Indonesia Stock Exchange for the 2022–2023 period, using the Moving Average (MA), Moving Average Convergence and Divergence (MACD) and Relative Strength Index (RSI) indicators. . Astra International Tbk (ASII), PT Indofood Sukses Makmur Tbk (INDF), PT Indofood CBP Sukses Makmur Tbk (ICBP), PT Semen Indonesia Persero Tbk (SMGR), PT Indah Kiat Pulp & Paper Tbk (INKP), and PT Kalbe Farma Tbk (KLBF) are some of them. The analysis was conducted using charts from the stockbit.com website to evaluate the accuracy of signals and the investment performance of these three indicators. The research results indicate that RSI has the highest signal accuracy rate, namely 92%, while MA and MACD have accuracy rates of approximately 58% and 55%, respectively. Despite MACD producing more signals, RSI remains accurate with fewer signals. In terms of return on investment, RSI achieved a total return of 238%, followed by MACD with a total return of 161%, and MA with a total return of 101%. RSI proves to be a reliable indicator by generating positive returns without any negative returns on the studied stocks. In conclusion, RSI is the primary choice in making investment decisions in the manufacturing sector stocks on the Indonesia Stock Exchange due to its accuracy and positive investment returns. However, MA remains useful for trend analysis, and investors are advised to pay attention to the entire stock market, consider additional indicators, and have sufficient understanding of technical analysis. For future research, it is recommended to consider other sectors and a broader range of indicators.

Comparative Technical and Economic Analyses of Hydrogen-Based Steel and Power Sectors

Decarbonizing the current steel and power sectors through the development of the hydrogen direct-reduction iron ore–electric arc furnace route and the 100% hydrogen-fired gas turbine cycle is crucial. The current study focuses on three clusters of research works. The first cluster covers the investigation of the mass and energy balance of the route and the subsequent application of these values in experiments to optimize the reduction yield of iron ore. In the second cluster, the existing gas turbine unit was selected for the complete replacement of natural gas with hydrogen and for finding the most optimal mass and energy balance in the cycle through an Aspen HYSYS model. In addition, the chemical kinetics in the hydrogen combustion process were simulated using Ansys Chemkin Pro to research the emissions. In the last cluster, a comparative economic analysis was conducted to identify the levelized cost of production of the route and the levelized cost of electricity of the cycle. The findings in the economic analysis provided good insight into the details of the capital and operational expenditures of each industrial sector in understanding the impact of each kg of hydrogen consumed in the plants. These findings provide a good basis for future research on reducing the cost of hydrogen-based steel and power sectors. Moreover, the outcomes of this study can also assist ongoing, large-scale hydrogen and ammonia projects in Uzbekistan in terms of designing novel hydrogen-based industries with cost-effective solutions.

Disability-adjusted Life Years of Hepatitis B in Iran during 2009–2019: An Analysis Based on the Global Burden of Disease Study 2019

Background and Purpose Hepatitis B virus infection is currently among the ten leading causes of death from infectious diseases in the world. The aim of the current study is spatial analysis related to life years adjusted by hepatitis B disability in Iran from 2009 to 2019. Materials and Methods The study is ecological. Using data from the Global Burden of Diseases (GBD), cause-specific mortality served as the basis for estimating disability-adjusted life years (DALYs). Time trend analysis of DALYs attributed to hepatitis B from 2009 to 2019 and spatial pattern analysis and identification of high-risk and low-risk clusters of DALYs attributed to hepatitis B in Iranian provinces were performed. Time trend changes were evaluated using joinpoint regression analysis. Results The most likely high-risk cluster with LLR=238.59 in the West of Iran includes the western provinces of the country (Lorestan, Kermanshah, Hamedan, Markazi, Khuzestan, and Ilam) (relative risk of occurrence 2.31). The three provinces of Lorestan (RR=2.22), Sistan and Baluchistan (RR=1.73), Golestan (RR=1.46) have the highest relative Khazar, and the three provinces of Gilan (RR=0.41), Mazandaran (CIR=0.48) and Kurdistan (CIR=0.51) had the lowest relative risk. During the years 2009 to 2019, the total DALYs decreased by 1.5% annually (p<0.05). Conclusion According to the results of the disease control and prevention programs, it can be effective in reducing the disease burden in the country by giving priority to the provinces that are among the high-risk disease clusters.

Bubbles in Bitcoin and Ethereum: The role of halving in the formation of super cycles

This study examines the price dynamics of Bitcoin and Ethereum between 2013 and 2022 using two distinct approaches: financial market technical analysis and econometric analysis. Financial market technical analysis employs indicators such as the Relative Strength Index (RSI) and the Hull moving average, while econometric analysis involves the Hodrick-Prescott filter and an Autoregressive Distributed Lag (ARDL) model. The study shows that Bitcoin and Ethereum experienced supercycle years in 2013, 2017, and 2021. The Bitcoin cycle, which averages 3.5 years, was particularly emphasized. The impact of the Bitcoin halving is also noteworthy, especially in the formation of supercycle bubbles in 2021, which affected altcoins such as Ethereum. The implications of this extend to portfolio management advice. It is recommended to carefully evaluate portfolio diversification and adopt a proactive regulatory approach, especially during the Bitcoin halving period.

Intriguing Occupations at Gran Dolina (Atapuerca, Spain): the Acheulean Subunits TD10.3 and TD10.4

This paper presents the zooarchaeological, technological, use-wear, and spatial analyses of the earliest sedimentary subunits of TD10 (TD10.3 and TD10.4) of the Gran Dolina site (Sierra de Atapuerca, Burgos, Spain), dated to c. 400 ka. Both units have yielded Acheulean technology, with occupational models characterized by the superimposition of multiple and independent events paired with short, sporadic occupations. Subunits TD10.3 and TD10.4 formed during a period in which the cave was largely reopened after a temporary closure. This period of reopening is evidenced by several blocks that fell from the ceiling and walls. Fifty-seven groups of refits and anthropic conjoins, of which 43 resulted from deliberate hominin activity, confirm the low disturbance of the deposits. Contrary to TD10.4, TD10.3 shows good preservation of faunal remains, although anthropogenic modifications are very scarce. Technologically, both deposits represent well-developed Acheulean assemblages, with high proportions of large-shaped tools and percussive material, which place this area among those that have yielded the most evidence of this type among all the excavated Atapuerca sites. The question of why these subunits contain so many hammerstones, manuports, and large tools associated with faunal remains that have been so scarcely modified is discussed based on data from spatial, technical, and use-wear analyses, which have identified butchery activities, and for the first time in the Pleistocene Atapuerca record, borer elements and possible thrusting stone spear tips. Furthermore, the occupational and technological characteristics of these subunits were compared with other western European archaeological sites, including the nearby site of Galería, with which a broad correlation can be made.

An inferential spatiotemporal approach for knowledge synthesis to identify trends in public health research

Background.Decisions follow patterns that are introduced by human perception. Research and development (R&D) are influenced by these patterns. Furthermore, R&D publications can represent repetitive attempts to solve similar, or the same problems. Literature reviews serve as an important tool for identifying these trends, but they are time consuming. The time commitment of a literature review can be reduced by using a sample of research. This will allow an infinite population of research to be generalized. Additionally, spatiotemporal analysis is most appropriate for fields that follow time and geographic trends, such as public health. Also, using research locations to perform this analysis potentially captures the social return of R&D, as knowledge gained. As a result, an inferential spatiotemporal methodological framework is introduced to quickly identify research trends using public health research. This was applied to a childhood Pb exposure case study. Methods.A body of more than 1000 childhood elevated blood lead (Pb) level (EBLL) research articles were used to extract publication years, research locations, and subtopics. These publications were grouped into research locations (i.e., U.S. states where research was conducted; not publication location) and averaged over years published (i.e., 29 years). Binary indicator variables were derived using the subtopics extracted and the periods identified in time trend analyses. Explanatory variables were used to conduct hypothesis testing. Significant variables were used to generalize the population of the annual average EBLL articles written per state. Results.The range of the annual average of EBLL research articles by state was 0–1.7 articles, with a mean of 0.3 articles. Thirty-eight explanatory variables suggested a significant effect on research article production. These included temporal, sociodemographic, education, structure age, environmental, and economic variables. The strongest effect on research production for U.S. states came from the number of structures built before 1950. A predictive model was selected to generalize the population of articles using time-periods 1990-95, environmental subtopic, and structures built before 1950. The locations with the most research production for this topic were California and New York. The locations with the least research production for this topic were Alaska, Hawaii, Nevada, Wyoming, North Dakota, South Dakota, Mississippi, Delaware, and New Hampshire. Conclusion.If the trend for R&D is to make fast decisions, more human bias will be introduced into the decision-making process. Analytical tools that enable researchers to identify trends and ask more questions about their field will mitigate these biases. This hypothesis testing and predictive modeling methodology provide researchers and other decision makers with analytical tools they can use to quickly identify research trends and narrow their field of research. Additionally, this analysis potentially captures the impact of discovered ideas, as a social return spillover, for this topic.

Technical and cost analysis of zero-emission high-speed ferries: Retrofitting from diesel to green hydrogen

This paper proposes a technical and cost analysis model to assess the change in costs of a zero-emission high-speed ferry when retrofitting from diesel to green hydrogen. Both compressed gas and liquid hydrogen are examined. Different scenarios explore energy demand, energy losses, fuel consumption, and cost-effectiveness. The methodology explores how variation in the ferry's total weight and equipment efficiency across scenarios impact results. Applied to an existing diesel high-speed ferry on one of Norway's longest routes, the study, under certain assumptions, identifies compressed hydrogen gas as the current most economical option, despite its higher energy consumption. Although the energy consumption of the compressed hydrogen ferry is slightly more than the liquid hydrogen counterpart, its operating expenses are considerably lower and comparable to the existing diesel ferry on the route. However, constructing large hydrogen liquefaction plants could reduce liquid hydrogen's cost and make it competitive with both diesel and compressed hydrogen gas. Moreover, liquid hydrogen allows the use of a superconducting motor to enhance efficiency. Operating the ferry with liquid hydrogen and a superconducting motor, besides its technical advantages, offers promising economic viability in the future, comparable to diesel and compressed hydrogen gas options. Reducing the ferry's speed and optimizing equipment improves fuel efficiency and economic viability. This research provides valuable insights into sustainable, zero-emission high-speed ferries powered by green hydrogen.

The Global Road Traffic Death Rate and Human Development Index from 2000 to 2019: A Trend Analysis.

Numerous studies on the association between the human development index (HDI) and road traffic death rate (RTDR) merely focus on developed countries, not reflecting the relationship between the HDI components and RTDR in a time-trend analysis. Accordingly, this study analyzes the trends of RTDR and their association with the HDI and its components from 2000 to 2019. The RTDR data of 154 countries were imported into the unconditional latent growth model (LGM) to assess the RTDR trends. The impact of the HDI and its components (viz., education, income, and life expectancy [LE viz]) on the trajectory of RTDR was also evaluated using the conditional LGM. The results of the unconditional LGM indicated an overall decreasing trend in RTDR. The conditional LGM results revealed the negative effect of the HDI and its components on the model parameters. The findings of random forests indicated that education and LE were the most crucial variables. Overall, this study emphasizes the significance of HDI and its components, particularly education and LE, in lowering the number of traffic fatalities. In this sense, improving formal education and LE could be one of the main policies that policymakers could consider to reduce RTDR.

Single well geothermal heating systems: Technical and economic assessment of two widely-used configurations

Benefiting from the closed wellbore space, the single well geothermal heating system (SWGHS) could avoid a large number of environmental problems compared to conventional geothermal systems. Combined with heat pump, this technology is attracting growing interest for the development of district heating based on medium-depth geothermal resources. Efforts of the scientific community and of business operators now focus on the technical optimization and commercial viability of the different SWGHS concepts already available. Here, we numerically investigate the heat extraction performance of a butted- and a vertical-well SWGHS possibly operational in a geothermal prospect area in Xi’an, central China. We addressed the performance of the two systems in terms of outlet temperature, heat production rate, heating area, and economic benefits. Sensitivity analysis suggests that large circulation rates and low inlet temperatures have beneficial effects on both thermal efficiency and economic benefits of the project. Our integrated technical and economic analysis suggests that the butted-well SWGHS configuration is particularly suitable for long-run, large-scale applications, compared to the vertical-well design. This work can provide valuable references for the applications of SWGHS, which is of criterial importance for reaching carbon peaking and carbon neutrality goals.

Absorption Chiller Efficiency Increasing at Waste Heat Recovery of Cogen-eration Plants using a Vapor Compression Chiller as a Backup Cold Source

Cooling efficiency in a trigeneration cycles is one of the most frequently problems. A single-stage hot water absorption chiller is a universal solution for the gas engine waste heat utilization. How-ever, trigeneration centers exploitation experience shows the need for a more detailed technical and economic analysis to achieve maximum efficiency of the three-generation cycle. The purpose of this article is to substantiate the use of two-stage absorption cycles increasing the utilization rate of waste gas heat. The study presents the results of assessing the efficiency of using energy resources on the example of a three-generation center with more than 14 years of exploitation experience, including two single-stage absorption chillers (Q0= 0.65 MW each) and a chiller with a screw compressor (Q0= 0.8 MW). A comparison of actual energy consumption with designed indicators was carried out. The influ-ence of external and internal factors on the efficiency of heat recovery from a gas engine in single-stage absorption refrigeration machines with a water-heated generator is considered. The dependence of the change in the average annual cooling coefficient during the calendar year was obtained. Based on the study, proposals were formulated to improve the energy efficiency of refrigeration supply, giving an increase in refrigeration capacity of 6.1% with a commensurate reduction in the load on the screw chiller. The option of using a combined two-stage cycle chiller (type 2) under similar operating conditions showed a COP=1.43, which provides savings of 67.45 MWh of electricity or 5.4%, on an annualized basis (assuming only waste heat is used). Additional advantages of such a cycle include increased accu-racy and stability of maintaining the water temperature at the absorption chiller evaporator due to more flexible adjustment of the temperature of the lithium bromide solution in the high-temperature generator.

Reduced pertussis disease severity in infants following the introduction of pertussis vaccination of pregnant women in Spain, 2015–2019

BackgroundMaternal pertussis vaccination during the third trimester of pregnancy was implemented in 2015 in Spain, reaching a national coverage of 84% in 2019. In this ecological study, we investigated whether there was a change in the disease severity for pertussis in infants upon introduction of prenatal pertussis vaccination. MethodsWe performed a time-trend analysis of infant pertussis hospitalizations during 2005–2019 in Spain using national register data. Annual hospitalization rates per 100,000 population and the mean length of hospitalization were calculated for infants < 3 months of age (target group benefiting from the prenatal vaccination) and a reference group aged 3–11 months. We compared overall rates and annual percent changes of the above variables in both groups for the time period before (2005–2014) and after vaccination introduction (2015–2019), using segmented Poisson regression. ResultsDuring the pre-vaccination period, infants aged 0–2 months had a 5-times higher rate of pertussis hospitalization and spent on average 50 % longer in hospital than the reference group. After the maternal vaccination introduction, the hospitalization rate decreased more rapidly in infants aged 0–2 months than in infants aged 3–11 months: annual reduction of 34 % (95 % CI: 31–38) versus 26 % (95 % CI: 21–31) in the hospitalization rate and 13 % (95 % CI: 11–15) versus 6 % (95 % CI: 2–9) in the mean hospital stay, respectively. In 2019, the mean hospital stay for pertussis was about 4.5 days in both groups. ConclusionsMaternal pertussis vaccination in Spain led to a reduction in disease severity in the target group as compared to older infants, highlighting the need for increased efforts on educating healthcare professionals on the importance of maternal vaccinations.

Subnational inequalities in years of life lost and associations with socioeconomic factors in pre-pandemic Europe, 2009–19: an ecological study

Health inequalities have been associated with shorter lifespans. We aimed to investigate subnational geographical inequalities in all-cause years of life lost (YLLs) and the association between YLLs and socioeconomic factors, such as household income, risk of poverty, and educational attainment, in countries within the European Economic Area (EEA) before the COVID-19 pandemic. In this ecological study, we extracted demographic and socioeconomic data from Eurostat for 1390 small regions and 285 basic regions for 32 countries in the EEA, which was complemented by a time-trend analysis of subnational regions within the EEA. Age-standardised YLL rates per 100 000 population were estimated from 2009 to 2019 based on methods from the Global Burden of Disease study. Geographical inequalities were assessed using the Gini coefficient and slope index of inequality. Socioeconomic inequalities were assessed by investigating the association between socioeconomic factors (educational attainment, household income, and risk of poverty) and YLLs in 2019 using negative binomial mixed models. Between Jan 1, 2009, and Dec 31, 2019, YLLs lowered in almost all subnational regions. The Gini coefficient of YLLs across all EEA regions was 14·2% (95% CI 13·6-14·8) for females and 17·0% (16·3 to 17·7) for males. Relative geographical inequalities in YLLs among women were highest in the UK (Gini coefficient 11·2% [95% CI 10·1-12·3]) and among men were highest in Belgium (10·8% [9·3-12·2]). The highest YLLs were observed in subnational regions with the lowest levels of educational attainment (incident rate ratio [IRR] 1·19 [1·13-1·26] for females; 1·22 [1·16-1·28] for males), household income (1·35 [95% CI 1·19-1·53]), and the highest poverty risk (1·25 [1·18-1·34]). Differences in YLLs remain within, and between, EEA countries and are associated with socioeconomic factors. This evidence can assist stakeholders in addressing health inequities to improve overall disease burden within the EEA. Research Council of Norway; Development, and Innovation Fund of Hungary; Norwegian Institute of Public Medicine; and COST Action 18218 European Burden of Disease Network.

A magnetic cross-linked alginate-biobased nanocomposite with anticancer and hyperthermia activities

This research study focuses on a new magnetic nanobiocomposite designed and synthesized by the formation of cross-linked alginate (Alg) hydrogel using CaCl2 cross-linker agent, its modification with flaxseed mucilage hydrogel and silk fibroin (SF) biopolymer extracted, and as well, the in-situ synthesis of Fe3O4 magnetic nanoparticles (Fe3O4 MNPs) in the presence of this biopolymeric substrate. FT-IR, EDX, FE-SEM, XRD, VSM, and TG technical analyses clarified the physical and chemical features of magnetic cross-linked Alg/flaxseed mucilage hydrogel/SF nanobiocomposite. Following the structural characterization of this magnetic natural-based composition, the in-vitro cytotoxicity and hemolysis assay studies with different concentrations resulted in prominent biological outcomes. The survival rates of normal HEK293T cells (95.74%, 94.18%) and breast cancer BT549 cells (79.23%, 77.76%) after 48 and 72 h verified the biocompatibility and anticancer properties of this new nanobiocomposite. Also, less than 5% of the hemolytic effect disclosed its hemocompatibility. Furthermore, a high specific absorption rate value (72.42 W/g) is generated by 1 mg/mL of this magnetic nanobiocomposite. Overall, it can be deduced that magnetic responsive cross-linked Alg/flaxseed mucilage hydrogel/SF nanobiocomposite could functionally perform in magnetic hyperthermia treatment.

Multivectority of ecological and economic assessment of water resources of Ukraine

The financial and economic mechanism of balanced use of natural resources includes a wide specification of environmental, organizational, economic and financial instruments. The author's vision of the multi-vector nature of the ecological and economic assessment of water resources is outlined, which is a comprehensive approach to the analysis of the use and management of water resources for making informed decisions with the determination of priorities for Ukraine. It is substantiated that formation of fundamental scientific bases for the evaluation of water resources of Ukraine should be based on the use of ecological and economic approaches, in particular: ecological dimension, economic analysis, social dimension, technical analysis, legal and regulatory context, risk analysis, climate change analysis, water infrastructure projects, water conflict management, environmental impact monitoring and assessment, alternative scenarios. A study of publicly available data on the assessment of the use of water resources of Ukraine was conducted. Based on the results of the study, we proposed the structure of a multi-vector model of the tools of the ecological and economic mechanism of water resources assessment, which is systematized according to interrelated instrumental blocks: ecological dimension — assessment of the impact of any water projects or activities on natural ecosystems, aquatic biological resources, and water quality; economic analysis — consideration of economic indicators; social dimension — assessment of the impact of projects on society; technical analysis — analysis of technical solutions, engineering aspects and technological parameters of water projects; legal and regulatory context — consideration of relevant legislative and regulatory requirements; analysis — risk assessment of possible risks and development of strategies for their management. The ecological and economic approach helps ensure balanced use of water resources, taking into account the needs of humanity and the requirements of the environment. On the basis of the multi-vector nature of the ecological and economic assessment of water resources, recommendations on environmental protection, optimal use of resources, social impact of projects, risk management strategies and other important aspects can be provided. The author's approach to theoretical-methodological approaches and methodological provisions regarding the formation of a model of tools for the ecological-economic mechanism of water resources assessment, the effective influence of which is aimed at balancing the ecological, economic and social components of the use of water resources of Ukraine, is proposed. It is substantiated that the functioning of multi-directional tools of the ecological and economic mechanism will ensure both greening and increasing the economic and social effectiveness of the use of water resources, the consolidation of management aspects around strategic tasks and priorities determined by the Basic principles of the state environmental policy of Ukraine for the period up to 2030.