Reduction In Consumption Research Articles

Breaking the habit: The impact of tobacco taxation on smoking behavior

Objective: This study investigates the influence of tobacco prices on consumption habits among 200 smokers in Lisbon, Portugal, focusing on generational preferences and perceptions of tobacco taxes. Methods: A cross-sectional survey was conducted using a quantitative approach. Participants were categorized by generational cohort, and data on tobacco consumption types, awareness of tobacco taxes, and opinions on tax increases were collected. Statistical analyses were used to explore relationships and predictors. Results: Findings reveal that 46.5% of participants favored heated tobacco, 37.0% smoked cigarettes, and 16.5% consumed other types like roll-your-own tobacco and electronic cigarettes. Significant generational differences were observed, with older cohorts predominantly smoking cigarettes (51.5%), while Generation Z showed a preference for heated tobacco (55.2%). Most smokers (79.5%) were aware of tobacco taxes, with diverse opinions on their purpose: revenue generation (44.0%), consumption reduction (44.5%), and indifference (11.5%). Despite this awareness, 60.5% reported no change in consumption habits due to tax increases. Conclusion: The study underscores the complexity of tobacco consumption behaviors influenced by price and generational factors. While heated tobacco gains popularity among younger smokers, traditional cigarettes remain prevalent among older cohorts. The findings highlight challenges in tobacco control policies, suggesting a need for comprehensive strategies integrating price measures with targeted educational and cessation interventions to effectively reduce tobacco use across different generations.

AN OVERVIEW OF ENERGY CONSUMPTION AND CO2 EMISSIONS IN IRAN'S RESIDENTIAL SECTOR: ENERGY TRANSITION AND SUBSIDY POLICIES

The transition from fossil fuels to renewable energy sources has become a critical global issue, particularly in response to climate change. This study aims to analyse the trends in energy consumption and CO2 emissions within Iran's household sector. The findings reveal a significant increase in energy consumption in Iran between 2001 and 2019. Despite the household sector's heavy reliance on fossil fuels, a shift in fuel consumption patterns can be observed, with a transition from oil to natural gas starting in 2008. Electricity generation in Iran is also predominantly fossil fuel-based, with natural gas playing a major role. This underscores the urgent need to reinforce renewable energy sources to mitigate CO2 emissions from the household sector. Another key factor influencing energy consumption in Iran is the country's extensive energy subsidies. The disparity in fuel prices compared to neighbouring countries has also led to fuel smuggling. However, the results show that the twophase subsidy reform plan implemented in 2010 and 2013 did not lead to a reduction in energy consumption. Therefore, further reforms are needed to improve energy equity and reduce CO2 emissions in the household sector.

Enhancing data management and real‐time decision making with IoT, cloud, and fog computing

AbstractThe convergence of Internet of Things (IoT), Cloud computing, and Fog computing, termed as Interconnected Intelligence (II), has revolutionised data management and real‐time decision‐making across various industries. This study introduces a hybrid architecture that integrates these technologies to optimise resource allocation, reduce latency, and improve decision accuracy. Unlike traditional models that rely heavily on centralised Cloud computing, our approach distributes computational tasks between IoT devices, Fog nodes, and Cloud servers, ensuring efficient real‐time processing closer to the data source. The proposed system demonstrated a 20%–30% reduction in latency compared to Cloud‐only architectures, and a 25% improvement in resource utilisation through dynamic load balancing between Fog and Cloud layers. Additionally, the system showed an increase in decision accuracy by 15%, enhancing real‐time decision‐making capabilities in critical applications such as industrial automation, healthcare, and smart urban environments. Data security and privacy were also significantly improved, achieving a 20% reduction in energy consumption by reducing reliance on centralised Cloud resources. These results were validated using real‐world datasets from industrial, healthcare, and urban environments, underscoring the architecture's capability to support large‐scale IoT deployments. Future research will focus on real‐world validation and the development of enhanced dynamic resource management techniques.

Power-consumption analysis for different IPoWDM network architectures with ZR/ZR+ and long-haul muxponders

Operators are constantly faced with the need to increase optical-network capacity to accommodate rapid traffic growth while minimizing the cost-per-bit and power-per-bit. The drastic reduction of the power consumption of IP routers and ZR/ZR+ pluggable transponders seen in the past several years has renewed the interest in “opaque” optical-network architectures, where no optical bypassing is allowed. In this work, we aim to quantify and compare the power consumption of four “IP over wavelength division multiplexing” (IPoWDM) transport network architectures employing ZR/ZR+ modules versus long-haul muxponders, considering different grooming, regeneration, and optical bypassing capabilities. We first propose a power consumption model for different IPoWDM node architectures with ZR/ZR+ modules and long-haul muxponders. Then, to obtain the power consumption of different architectures, we propose a compact auxiliary-graph-based network-design algorithm extensible to different network architectures. Moreover, we investigate how the continuous decrease in the power consumption of ZR/ZR+ and IP routers can impact the power consumption of different architectures through a sensitivity analysis. Illustrative numerical results on networks of different sizes show that, despite drastic reductions of power consumption at the IP layer, optical bypassing is still the most power-efficient solution, reducing consumption by up to 48%.

Can China's national comprehensive medical reform increase medical resources and reduce healthcare burden: evidence from Chinese provinces.

China's national comprehensive medical reform (NCMR) is an important attempt in the reform of healthcare system, and quantitative evaluation of its effect is of great significance for continuously deepening medical reform, grasping the reform direction, and building a healthy China. Therefore, focusing on medical resources and medical burden, this study aims to systematically explore the policy effectiveness and the provincial heterogeneity of NCMR, as well as the potential influencing factors. Utilizing the collected multi-period panel data of 31 provinces in mainland China in 2006-2021, we regarded the release of the two batches of pilot provinces in NCMR as a quasi-natural experiment and comprehensively adopted a Staggered difference-in-differences (DID) model and Synthetic Control Method (SCM), combined with word frequency statistics and grouping regression analysis. NCMR can effectively increase the number of licensed physicians by 12.6% and reduce the per capita medical expense for in-patients by 7.2% in the pilot provinces. Furthermore, the NCMR policy effect in different pilot provinces shows various characteristics, and only Jiangsu, Zhejiang, and Chongqing achieve both the growth of medical resources and the reduction of medical expenditure. Meanwhile, word frequency statistics are conducted based on related policy descriptions and news reports on the official websites, so as to summarize the specific policy means in the three provinces, and provide a reference for other provinces to practice the healthcare reforms. Besides, extensibility analysis shows that the effect of NCMR is affected by the population aging and health status. Groups with low degree of population aging (low-AG)/high population health status (high-HE) performed a more obvious reform effect. This study provides beneficial policy implications for increasing medical resources, reducing medical burden, and promoting medical reform process.

Evidence Map of Interventions to Reduce Alcohol ConsumptionMapa de la evidencia sobre intervenciones para reducir el consumo de alcohol

Systematize evidence on the effect of global interventions to reduce the consumption and/or sale of alcoholic beverages. Evidence map based on searches in nine bibliographic databases, including 182 studies of systematic reviews with or without meta-analysis, reviews of interventions, and reviews of reviews. The studies evaluated the effect of interventions grouped into comprehensive sets of actions: communication for behavior change; health-promoting environments; and systemic changes. Two outcomes of interest were considered: reduction in alcohol consumption and reduction in its purchase/sale. A total of 207 associations between different interventions and outcomes were recorded, with emphasis on communication for behavior change (81.64%) and reduction of consumption (98.55%). Most of the associations showed a positive (40.58%), inconclusive (28.99%), or potentially positive (26.57%) effect. The main interventions with positive or potentially positive results were: a government monopoly on the sale of alcoholic beverages, control of the density of points of sale, charging a minimum price per unit, health warnings on alcoholic beverage labels, and multiple integrated interventions. It is hoped that this map will help public policy makers and healthcare professionals adapt experiences to their own contexts, stimulating intersectoral actions to reduce alcohol consumption.

One-pot green synthesis, biological evaluation, and in silico study of pyrazole derivatives obtained from chalcones

Abstract Several chalcones and their pyrazole derivatives have been synthesized using traditional methods under microwave (MW) and ultrasonic (US) irradiation. The latter were synthesized using US-assisted and MW-assisted one-pot techniques. The use of this technology led to a reduction in reaction time and energy consumption, as well as an increase in the yield of the final products, which means more efficient synthesis. An in silico study was conducted and the plant growth-stimulating effects of the synthesized compounds were revealed. To study the growth-regulating activity of the synthesized compounds, a study of aqueous suspensions at a concentration of 50 and 25 mg·L−1 was carried out on the viability, germination, and growth of seeds.

Pain Control and Opioid Consumption in Patients Undergoing Total Hip or Knee Arthroplasty Receiving a Preoperative Low Dose of Gabapentin

Background: Meta-analyses and randomized controlled trials were inconclusive regarding the role of gabapentinoids in patients undergoing joint arthroplasties. The aim of the present study was to investigate the effect of a preoperative low dose of gabapentin in patients undergoing total hip (THA) and knee arthroplasties (TKA). Methods: A retrospective observational study was conducted on 135 patients undergoing THA and TKA at the National Orthopedic Hospital Cappagh, Dublin, from July to December 2022. The primary outcome was the assessment of numerical rating scores (NRS) for postoperative pain at various time intervals. Results: During the observation period, 55 patients received a preoperative dose of gabapentin, while 80 patients did not. Statistically significant differences in numerical rating scores (NRS) were found at 6 (3 vs. 0, p < 0.001), 12 (4 vs. 2, p < 0.001), 18 (4 vs. 3, p < 0.001), and 24 h (4 vs. 3, p = 0.010) after surgery, in favor of the group receiving gabapentin. A reduction in opioid consumption, measured as morphine equivalents, was also noted in the gabapentin group (40 vs. 30 mg, p = 0.040). Conclusions: A low preoperative dose of gabapentin was associated with reduced postoperative pain and opioid consumption in patients undergoing TKA and THA, without impacting hospital stay. Prospectively designed trials are encouraged to assess the safety and effect on pain control of a preoperative low dose of gabapentin.

The Effects of an Adaptive Ventilation Control System on Indoor Air Quality and Energy Consumption

Indoor air quality (IAQ) and energy consumption (Q) are well-known building estimators, but they are used separately. Energy consumption is used during the design stage, while IAQ is used during operation. The novelty of our approach is that we propose using both estimators simultaneously during building operations. The purpose of this study was to find an adaptive ventilation strategy that maintained good indoor air quality with minimal energy consumption. The second novelty of our approach consists of IAQ estimation. While the operation of ventilation systems depends only on the indoor carbon dioxide (CO2) concentration at present, our novel approach uses a more global IAQ index that includes four different air pollutants. Physical models are used for the hourly prediction of the two indices: global IAQ and Q. This study presents a comparative analysis of several ventilation operations strategies: fixed versus adaptive. The main findings show that a decrease in the ventilation rate, na, from 3.5 h−1 to 2.0 h−1 leads to a diminishment in energy consumption of 42.9%, maintaining the global IAQ index under the limited health risk value (VRL). Moreover, an adaptive ventilation strategy of na, maintaining the global IAQ index value under VRL, achieves a further reduction in energy consumption of 72.9%, highlighting its efficiency.

Green IN Artificial Intelligence from a Software Perspective: State-of-the-Art and Green Decalogue

This work presents a structured view of the state-of-the-art research on Artificial Intelligence (AI), from the point of view of efficiency and reduction of the energy consumption of AI software. We analysed the current research on energy consumption of AI algorithms and its improvements, which gave us a starting literature corpus of 2,688 papers that we identified as Green AI with a software perspective. We structure this corpus into Green IN AI and Green BY AI, which led us to discover that only 36 of them could be considered Green IN AI. After some quick insights about Green BY AI, we then introduce our main contribution: a systematic mapping of Green IN AI. We provide an in-depth analysis of the AI models that we observed during the mapping, and what solutions have been proposed for improving their energy efficiency. We also analyse the energy evaluation methodologies employed in Green IN AI, discovering that most papers opt for a software-based energy estimation approach and 27% of all papers do not document their methodology. We finish by synthetising our insights from the mapping into a Decalogue of Good Practices for Green AI.

The impact of leadership on employees’ innovation behavior: evidence from China’s energy listed companies

This paper provides an in-depth analysis of how management efficiency affects sustainable development in China’s top 10 private energy companies from 2005 to 2021, using the CUP-FM technique. The study finds a notable correlation: a 1% improvement in management efficiency results in a 0.21% reduction in energy expenditure. This highlights the significance of efficient management practices, such as streamlined processes, better resource allocation, and advanced technology use, in optimizing energy consumption and promoting sustainability. Conversely, a 1% increase in the number of employees leads to a 0.49% increase in energy expenditure due to increased operational activities and resource needs. The research also explores the impact of other variables, including earnings per share (EPS), tax payments, and technology spending, on energy expenditure among listed energy companies in China. To foster innovation among employees through improved management efficiency, the paper suggests practical policies such as enhancing sustainable literacy, providing green loans, implementing standardized reporting, and encouraging collaboration and knowledge sharing among energy companies.

Enhancing energy efficiency in Bangladesh’s readymade garment sector: the untapped potential of LED lighting retrofits

Purpose Previous studies emphasized the substantial energy-saving potential of light emitting diode (LED) lighting systems, especially in the clothing industry. However, the specific quantification of energy conservation potential in industrial factories, particularly in Bangladesh’s readymade garment (RMG) sector, remains unexplored. The purpose of this study is to investigate the potential energy savings and efficiency improvements of lighting systems in Bangladesh’s RMG sector using LED technology. Design/methodology/approach Understanding and optimizing energy consumption is crucial in the RMG sector because this sector contributes significantly to the country’s export earnings. For this, an RMG factory was surveyed and possible lighting system retrofitting was estimated and compared. Findings The adoption of energy-efficient lighting options, particularly LED, could decrease the current lighting energy usage from 15% to 7.5% in Bangladesh. First, this study reveals, that the reduction of annual energy consumption was determined to be 18,220 kWh due to the retrofitting of the lighting system with LED tube. Second, it conducts real-time measurements to assess the suitability of in-building lighting systems, providing insights into the current scenario. Lastly, it evaluates the economic and environmental benefits of the proposed lighting system in the RMG industries. Due to the retrofitting of the lighting system, the reduction of equivalent CO2 gas emissions was found to be 119.896 tCO2. Originality/value For the first time, this study explored the potential for enhancing energy-efficient lighting system design through retrofitting in the RMG industry, with a focus on Bangladesh. By addressing these aspects, this study aims to contribute to the advancement of energy efficiency and conservation efforts in the RMG sector, ultimately fostering sustainable industrial development in Bangladesh and beyond.

Investigation of Inflation and Wage Dynamics in Nigeria: New Empirical Insights

The current inflationary pressure in Nigeria is eroding the purchasing power of the salaried workers and the value of the national currency with the proposition that it could worsen the welfare of the citizens despite the abject and extreme poverty that prevails in the country. The paper therefore made an empirical investigation into the inflation and wage dynamics in Nigeria. The variables were tested for unit roots using ADF tests. The unit roots shows that all the variables are non-stationary at levels except the Consumer Price Index of Transportation (CT) and Wages and Salaried Workers as Proportion of Total Employment (WSW). Employee compensation including remittances (COMP), inflation rate (INFR), WSW and Consumer Price Index of Transportation (CT) are stationary at first difference. Autoregressive Distributed Lag (ARDL) model was used in the methodology. The ARDL long-run result shows that the Consumer Price Index for Food (CF) has the highest impact on the Compensation of Employees (COMP). For every 1 percent change in COMP, CF changes by 19 percent. As INF rises, COMP falls. This is shown by the negative coefficient of INFR. The long-run result also suggests that for every 1 percent change in COMP, CT increases by 9%.The short-run dynamic model showed that a 6% fall in the lag period of inflation level led to a 1% increase in employee compensation and a one-year previous period fall of 30% in WSW, bringing about I% increase in employee compensation. The long-run model showed that the variables are co-integrated which indicates that variation in the short run will be corrected in the long run with 59% speed of adjustment. The study shows that the main drivers of inflation in Nigeria are Consumer Price Index for Food (CF) and Consumer Price Index for Transportation (CT) which directly have negative impact on Employee Compensation (COMP). In line with the above findings, It was recommended that maximum price legislature, demonetisation of currency, exercising great caution in incurring public debt, drastic reduction in government expenditure and adoption of rational wage policy can be a viable macroeconomic policy option.

Health and Economic Effects of Salt Reduction Interventions for Preventing Noncommunicable Diseases in Japan: A System Dynamics Simulation Study

Reducing salt intake is a vital public health measure for combating noncommunicable diseases and mitigating rising social security expenditures in Japan. We developed a system dynamics model to analyze the potential health and cost effects of salt reduction interventions among the Japanese population aged 40 years and above from 2012 to 2040. The simulation findings derived from the model indicate that, in the base run, the disability-adjusted life years (DALYs) for cardiovascular disease (CVD) and chronic kidney disease (CKD) are projected to be approximately 55 and 9.5 per 100,000 people, respectively, contributing approximately 40 trillion yen in social security expenditures by 2040. The model predicts that implementing mandatory reformulation could decrease DALYs for CVD and CKD by 5.7% and 6.2%, respectively, resulting in an approximately 6.7% reduction in social security expenditure. Additionally, voluntary reformulation is estimated to reduce the DALYs for CVD and CKD by 4.7% and 5.2%, leading to a 5.6% decrease in social security expenditure. Finally, accelerating the adoption of a low-salt diet is expected to lower the DALYs for CVD by 2.8% and CKD by 3.2%, thereby reducing social security expenditures by 3.4%. Thus, product reformulation initiatives have a greater impact on health and economic outcomes.

A novel thermoplastic material: Pre‐polymerized PMMA liquid resin and continuous glass fiber‐reinforced composite initiated by benzoyl peroxide/N,N‐dimethylaniline

AbstractThermoplastic PMMA was rarely exploited in continuous fiber‐reinforced composites due to its viscous high‐temperature molten fluid as well as pessimistic wettability into fiber fabric. Redox‐active polymerization is a green route to develop a new liquid PMMA resin at room temperature to provide an in situ curing with the advantages of energy saving and consumption reduction. In this paper, BPO/DMA was adopted as a redox initiator pair, and the effect of MMA:BPO:DMA ratio on curing time, Mn, Tg, and mechanical properties of PMMA were systematically studied. When the ratio of MMA:BPO:DMA is 200:1.2:1, PMMA‐200 achieved optimistic mechanical properties at 20°C (tensile strength, 64.7 MPa; tensile modulus, 3352 MPa; bending strength, 125.3 MPa; bending modulus, 3023 MPa). Moreover, the mechanical properties were further improved at low temperatures. The maximum tensile strength and tensile modulus were up to 97.43 and 4297 MPa (−40°C) respectively. The tensile strength (0°, 1103 MPa; 90°, 52.3 MPa) and tensile modulus (0°, 47.5 GPa; 90°, 14.2 GPa) of glass‐fiber‐reinforced PMMA composite at 20°C were found to be comparable with epoxy resin‐based composites and even higher at lower temperature. In summary, redox‐initiated PMMA and its fiber‐reinforced composites are promising thermoplastic materials as new lightweight alternatives.Highlights Preparation method of PMMA resin and glass fiber composite. Research on the mechanical properties, molecular weight, glass transition temperature, curing time, etc. of PMMA resin. Testing of mechanical properties of PMMA glass fiber composites at room temperature and low temperature. Current applications and prospects of PMMA glass fiber composites.

Preoperative Narcotic Education in Spine Surgery: A Retrospective Study.

Background/Objectives: The objective of this study was to determine whether preoperative opioid education reduces opioid consumption after spine surgery and which educational methods are the most effective. Orthopedists are the most likely to prescribe opioids among all specialists. To alleviate the prescription opioid crisis, studies have identified ways to taper narcotic dosage and use following surgery. The role of preoperative education and its varying modalities on opioid consumption following spine surgery has yet to be reported in the literature. Methods: The study group received formal education describing the use of opioids, side effects, and alternatives to pain management. Patients were to choose their preferred modality of a 2 min narrated video and two handouts to be watched and read in their individual time, attending a small class led by a physician assistant where they watched the 2 min narrated video along with reading the two handouts or receiving a one-on-one session with the treating spine surgeon. Meanwhile, the control group received standard preoperative education. Refill prescriptions were collected from patients' electronic medical record charts at the 2-week, 1-month, 3-month, and 6-month postoperative follow-ups. The primary outcome measure was morphine equivalents (MME) of prescription opioids at six months following spine surgery. Results: At 2 weeks postoperatively, there were no statistically significant differences between patients who received any formal narcotic education and those who did not. At 1 and 3 months postoperatively, the video education group (p-value < 0.001), class education group (p-value < 0.001), and the one-on-one education group (p-value < 0.05) all had significant reductions in opioid consumption. At 6 months postoperatively, only the video education group (p-value < 0.001) and the class education group (p-value < 0.01) had significant reductions in opioid consumption. Conclusions: A two-fold approach with a video and handouts significantly decreases the prescription dosage at six months postoperatively and allows for early opioid cessation after undergoing spine surgery.

Exergy efficiency improvement by compression heat recovery for an integrated natural gas liquefaction-CO2 capture-NGL recovery process

For liquefied natual gas production, cryogenic distillation offers lower thermal energy consumption and a more compact footprint for carbon capture unit than the widely used chemical absorption. However, the reduction in thermal energy consumption comes at the cost of increased power consumption. To reduce the power consumption of cryogenic distillation based natural gas lqiuefaction plants, an integrated process for liquefied natual gas production, cryogenic CO2 capture and natural gas liquids recovery is proposed, which is called the base process. This base process is further integrated with a heat recovery unit (Organic Rankine cycle or Kalina cycle) to investigate the optimal utilization of compression heat in the system. The proposed processes are modeled in Aspen HYSYS and optimized using a genetic algorithm installed in Matlab. The results show that specific power consumption of the base case is 0.385 kWh/Nm3 NG. Due to the lack of compression heat recovery, significant exergy loss occurs at the water coolers, accounting for approximately 37 % of the total system exergy destruction. Among the evaluated methods, the supercritical Organic Rankine cycle, using R1234ze as the working fluid, recovers approximately 60 % of the exergy from compression heat with an 8.7 % improvement in system exergy efficiency. The subcritical Organic Rankine cycle, using R600a as the working fluid, achieves a slightly lower exergy efficiency improvement of 7.1 %. The Kalina cycle, while less efficient, still improves the system’s exergy efficiency by 6.3 %. Economic analysis reveals that the total annualized cost of the base process is $8,441,416, with a levelized cost of $0.1411/kg. The subcritical Organic Rankine Cycle provides the most cost-effective solution, with the lowest total annualized cost of $8,305,154 and a levelized cost of $0.1402/kg. The Kalina cycle ranks second in cost-effectiveness, with a total annualized cost of $8,345,914 and a levelized cost of $0.1405/kg NG. Although the supercritical ORC requires the highest capital investment, it proves more cost-effective than the base process due to its reduced annual operating costs.

Time-Series Forecasting and Sequence Learning Using Memristor-based Reservoir System

Pushing the frontiers of time-series information processing in the ever-growing domain of edge devices with stringent resources has been impeded by the systems’ ability to process information and learn locally on the device. Local processing and learning of time-series information typically demand intensive computations and massive storage as the process involves retrieving information and tuning hundreds of parameters back in time. In this work, we developed a memristor-based echo state network accelerator that features efficient temporal data processing and in-situ online learning. The proposed design is benchmarked using various datasets involving real-world tasks, such as forecasting the load energy consumption and weather conditions. The experimental results illustrate that the hardware model experiences a marginal degradation in performance as compared to the software counterpart. This is mainly attributed to the limited precision and dynamic range of network parameters when emulated using memristor devices. The proposed system is evaluated for lifespan, robustness, and energy-delay product. It is observed that the system demonstrates reasonable robustness for device failure below 10%, which may occur due to stuck-at faults. Furthermore, 247 × reduction in energy consumption is achieved when compared to a custom CMOS digital design implemented at the same technology node.

Investigation of hip flexibility training on dancesport optimization using machine learning video analysis

Dancesport, particularly the Paso Doble, requires high agility, coordination, and flexibility, especially in the hips. This study investigates the impact of an eight-week targeted Hip Flexibility Training (HFT) program on the performance of professional Paso Doble dancers. The need for this research stems from the lack of objective, data-driven evaluations in the field, where traditional methods rely heavily on subjective assessments. Previous studies have examined general flexibility in dance, but few have focused on the direct Biomechanical Effects (BF) and Physiological Effects (PE) of specific HFT on dancers. Further, such studies could not accurately measure hip joint movements and their coordination in order to achieve dance performance efficiency. The proposed study used motion-capturing devices to collect key movement data that impacts performance efficiency. The collected data is analyzed using the hybrid receptive field block (RFB) and residual network (ResNET) ML models to study the pre- and post-HFT results. Twelve highly trained dancers were assigned to have biomechanical and physiological metrics measured after and before the training. The data analysis has shown that there has been a significant increase in hip flexion from 65.4 ± 4.5° to 75.2 ± 3.7° (P &lt; 0.05), hip extension from 25.3 ± 2.4° to 30.1 ± 2.1° (P &lt; 0.05), and joint velocity from 1.18 ± 0.15 m/s to 1.32 ± 0.12 m/s (P &lt; 0.05). Physiological metrics also showed improvements, such as a reduction in Oxygen Consumption (OC) from 2.02 ± 0.21 L/min to 1.85 ± 0.18 L/min (P &lt; 0.05) and Energy Cost (EC) from 50.1 ± 7.2 kJ/min to 45.6 ± 6.4 kJ/min (P &lt; 0.05).

Main channels and consequences of the influence of war on educational inequality in society

A new, difficult and tragic research page is opening in domestic sociology – a detailed study of the effects of the Russian-Ukrainian war on all spheres of life of Ukrainian society, its social structure, institutional transformations, economic capabilities, political organization, as well as the daily life of citizens. An integral component of both the institutional structure of society and the everyday life of citizens is the sphere of education with its inherent and constantly reproduced educational inequality. A large-scale war has the potential to quickly and for a long period of time disrupt social order and change established patterns of social inequality in society, particularly in education, unevenly distributing stratified negative effects. With the beginning of large-scale hostilities, the educational infrastructure of Ukraine has suffered almost the greatest destruction since the Second World War. Schools and preschool education institutions have suffered the greatest damage and destruction. A large number of families with their children have been forced to move internally or externally, thus temporarily interrupting the opportunities for children’s education. The article summarizes the results of research in various countries that have experienced short or long-term periods of international or civil wars, which made it possible to identify the main channels of the war’s impact on educational inequality and the corresponding short- and long-term effects of the war. Seven main direct and indirect channels of the war’s impact on educational inequality have been identified, including the destruction of educational infrastructure; lack of teachers due to internal and external displacement, recruitment into the army or death; reduction of state expenditures on education; movement of a large number of adults and children; redistribution of power and wealth in society; the growth of poverty, the reassessment and change of priorities regarding education within the family; deterioration of children’s physical and mental health, malnutrition, stress, trauma, feeling of insecurity. Short- and longterm effects on the educational achievements of children are formed through channels of influence, which take the form of stratified educational losses, a decrease in family expenditures on education, as well as losses in the future lifetime income of individuals.