Trend Analysis Research Articles

Sustainable Energy Consumption Analysis through Data Driven Insights

Energy is the backbone of our society, supporting our daily activities and driving progress. It plays a crucial role in shaping our modern way of life. The future of global energy consumption is influenced by many factors, including demographics, economic dynamics, technological developments, political actions, environmental demands and geopolitical considerations. As the world's population continues to grow and urbanize, the demand for energy is increasing. At the same time, rapid technological innovations are shaping the energy landscape and changing production, distribution and consumption patterns. In the midst of this development, it is very important to optimize energy consumption, accurately anticipate needs, curb climate change, limit emissions of greenhouse gasses, fight against pollution and promote sustainability. This study includes an in-depth analysis of historical consumption trends, assessing the multiple benefits of renewable energy integration, estimating carbon emissions, formulating practical policy recommendations and providing empirically informed insights. The work is based on various data obtained from platforms such as Kaggle and using advanced visualization techniques such as Power BI dashboards. The study provides invaluable perspectives on future energy needs, the penetration of renewable sources into the energy mix, and the strategic needs to achieve sustainable energy use.

Assessment of energy self-sufficiency of a smart farm through integrated modeling of air-source heat pumps and solar power generation

This study explored methods to operate a sustainable system by improving energy independence and integrating renewable energy into a microgrid. However, there are challenges associated with the intermittency of renewable energy and difficulties in predicting the energy demand of energy systems. Therefore, this study emphasizes the need to analyze solar power generation and predict the cooling and heating demands of energy systems. The target system was a smart farm in which hot and cold water was supplied to the smart farm using a heat pump during seasonal changes. A prediction model for the smart farm was developed to calculate power consumption according to the ambient temperature in summer and winter. The results suggested that additional consideration is needed to optimize system operation and renewable energy use to improve the balance between energy consumption and supply. A comparison of the total power consumed to solar energy generation highlighted the challenge of attaining 100% self-sufficiency rates, reaching 44% in summer and 40% in winter. Analysis of solar power generation and air-source heat pump usage trends provided insights into strategies for achieving energy independence in smart farms. In conclusion, this study provides a model for managing energy demands on smart farms and insights into the optimization of system operation with renewable energy. It also provides a foundational framework for evaluating microgrid systems based on renewable energy and contributes to identifying methods to increase the energy self-sufficiency rates to enable sustainability of smart farms.

Exploring the Impact of Urban Morphology on Building Energy Consumption and Outdoor Comfort: A Comparative Study in Hot-Humid Climates

Research simultaneously examining building energy consumption and outdoor thermal comfort within urban environments remains limited. Few studies have delved into the sensitivity of design parameters based on building energy consumption and outdoor thermal comfort. The purpose of this study is to investigate the correlations between urban morphological design parameters and performance indicators, focusing on building energy consumption and outdoor thermal comfort (UTCI), across different urban block layouts in hot-humid regions, like Guangzhou. By establishing six fundamental morphological models—three individual unit layouts and three group layouts—the research explores both control and descriptive parameters through extensive simulation studies. Scatter plot visualizations provide insights into the impacts of various design parameters on energy consumption and UTCI, facilitating a comprehensive analysis of trends and quantitative relationships. Additionally, the study conducts sensitivity analyses on design parameters under different layout conditions to highlight their influences on target performance indicators. The findings reveal common trends, such as the significant impacts of plan dimensions and the Floor Area Ratio (FAR) on energy efficiency and outdoor comfort, as well as differential patterns, such as the varying sensitivities of the Shape Factor (S/V) and the Sky View Factor (SVF), across individual and collective layouts. Ultimately, this study offers a nuanced understanding of urban block morphology’s role in creating sustainable, comfortable, and energy-efficient urban environments, providing valuable guidelines for urban form design in hot-humid climates.

The impact of land use and cover changes on river flows in Wundanyi Catchment of Taita Hills, Kenya (1970–2030)

<p>Taita hills are one of the most important biodiversity hotspots of Kenya but experiencing a high rate of deforestation due conversion of its original forestland to agriculture and settlement during the last century. These landscape dynamics coupled with rainfall fluctuations in these critical ecosystems may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of land use/cover change (LUCC) in Wundanyi catchment from 1970 to 2030 and predict their specific and combined effects on surface runoff and stream flow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modeling using both historical and primary data from Wundanyi catchment, and Landsat TM and ETM+ imagery of Taita Hills for 1990, 2000, and 2010. Results show highly variable mean seasonal and annual values of discharge in Wundanyi catchment probably attributed to environmental changes affecting Taita Hills in general and Wundanyi catchment in particular. Compared to 1990, major land use/cover changes in 2010 were featured by the expansion of built-up area (250%), plantation forest (23.7%), broadleaved forest (17.4%), and thicket (15.9%). Was also notable the decrease in woodland (−30.3%), cropland (−21.6%), and shrubland (−0.8%). Dynamic spatial trends by the year 2030 will be evidenced by increased thicket by 0.41% per annum (<em>R</em><sup>2</sup> = 81.6%), and by decreased plantation forests (−0.13%; <em>R</em><sup>2</sup> = 91.3%), woodland (−0.10%; <em>R</em><sup>2</sup> = 77.6%), shrubland (−0.11%; <em>R</em><sup>2</sup> = 85.2%), broadleaved forests (−0.03%; <em>R</em><sup>2</sup> = 56.6%) and cropland (−0.09%; <em>R</em><sup>2</sup> of 84.4). These changes will shape the catchment landscape and influence its hydrology, unless the existing forest and agricultural policy interventions are enforced. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in the Wundanyi catchment.<strong></strong></p>

Smart Growth and Smart Shrinkage: A Comparative Review for Advancing Urban Sustainability

Smart Growth and Smart Shrinkage: A Comparative Review for Advancing Urban Sustainability

Analysis of inpatient data on dengue fever, malaria and leishmaniasis in Ecuador: A cross-sectional national study, 2015–2022

BackgroundDespite concerted efforts in South America, these diseases continue to pose a significant burden of morbidity and mortality in endemic regions. This study aimed to analyse hospital data and investigate the hospitalisation rates of dengue fever, leishmaniasis, and malaria in Ecuador between 2015 and 2022. MethodsOpen-access databases from the National Institute of Statistics and Censuses of Ecuador between 2015 and 2022 were analysed. Data were filtered using specific terms for each disease (ICD-10), and descriptive statistics of geographical distributions were calculated using Microsoft Excel, Stata 14.2, and Rstudio. ResultsDengue had the highest burden, with 31,616 reported cases, followed by malaria (1,316) and leishmaniasis (283). From 2015 to 2022, the highest hospitalisation rate per 105 inhabitants for dengue was observed in Sucumbios province (697.2), for malaria in Pastaza province (108.4), and for leishmaniasis in Morona Santiago province (18.8). The data’s trend analysis revealed a slight increase in dengue and mild downward trends in hospitalisation for malaria and leishmaniasis. ConclusionsThe results suggest that vector-borne disease control has failed in Ecuador. Unfortunately, there was no significant trend towards a decrease in dengue, malaria, and leishmaniasis in Ecuador during the years studied. This study highlights the need to optimise sustainable vector control programs and emphasises continuous monitoring of disease incidence and control measures.

Analysis of extreme precipitation variation characteristics in mountain grasslands of arid and semi-arid regions in China

Introduction: With global warming, the disaster losses caused by extreme precipitation events are increasing. The poor natural conditions and climate change make the arid and semi-arid mountainous grassland area a sensitive region of climate change. The study on the spatio-temporal variation characteristics of extreme precipitation events in this region is helpful to improve the ability of climate prediction and disaster prevention and reduction in grassland.Methods: Based on the daily precipitation data of four meteorological monitoring stations in the Yinshanbeilu from 1970 to 2020, the trend analysis, M-K test and wavelet analysis were used to select seven typical extreme precipitation indicators to analyze the temporal and spatial characteristics of extreme precipitation.Results and Discussion: The results showed that the precipitation in the Yinshanbeilu increased in the past 51a, and the number of heavy rain days increased significantly. The significance test of CDD and CWD showed that the number of continuous dry days and continuous wet days decreased abruptly. The spatial analysis showed that the high value areas of R95p, R95d and PRCRTOT were all located in Siziwang Banner, and it could be concluded that the extreme precipitation risk was the highest in Siziwang Banner, while the low value areas of SDII, Rx1day, R95p and PRCRTOT were all located in Sonid Right Banner, which could be inferred that the Sonid Right Banner was relatively dry. The first main cycle of the seven indexes of extreme precipitation almost runs through the whole time series, and the starting point of the minimum main cycle changes inconsistent. In addition to the number of consecutive dry days, the other indices have a good correlation with annual precipitation, flood season and monthly precipitation from June to September, and July is the peak period of extreme precipitation events.

Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering

The study of the expansion potential of artificial oases based on remote sensing data is of great significance for the rational allocation of water resources and urban planning in arid areas. Based on the spatio-temporal relationship between morphogenetic landform types and the development of artificial oases in Xinjiang, this study explored the development pattern of artificial oases in the past 30 years by using trend analysis and centroid migration analysis, constructing a series of landform–artificial oasis change indices, and investigating the suitability of different landforms for the development of artificial oases based on geomorphological location by adopting a hierarchical clustering method. The following conclusions are drawn: (1) From 1990 to 2020, the area of artificial oases in the whole territory continued to increase, with significant expansion to the south from 2005 to 2010. (2) Six categories of landform types for artificial oasis development were created based on the clustering results. Of these, 7.39% and 6.15% of the area’s geomorphological types belonged to the first and second suitability classes, respectively. (3) The optimal scale for analyzing the suitability of landforms for the development of artificial oases over the past 30 years in the whole area was 8 km, which could explain more than 96% of the changes in the growth of artificial oases. The distribution of landforms of first- and second-class suitability within the 8 km buffer zone of an artificial oasis in the year 2020 was 10.55% and 9.90%, respectively, and landforms of first-class suitability were mainly concentrated in the near plain side of the urban agglomerations located on the northern and southern slopes of the Tianshan Mountains, and the urban agglomerations at the southern edge of Altai Mountains. This study quantified the potential of different geomorphological types for the development of artificial oases and provided a basis for site selection in future artificial oasis planning and urban construction.

Associations among neighborhood walkability, metal exposure, and sex steroid hormone levels: Results from Hangzhou Birth Cohort Study Ⅱ

BackgroundNeighborhood walkability may influence maternal-fetal exposure to environmental hazards and maternal-fetal health (e.g., fetal growth restriction, reproductive toxicity). However, few studies have explored the association between neighborhood walkability and hormones in pregnant women. MethodsWe included 533 pregnant women from the Hangzhou Birth Cohort Study II (HBCS-II) with testosterone (TTE) and estradiol (E2) measured for analysis. Neighborhood walkability was evaluated by calculating a walkability index based on geo-coded addresses. Placental metals were measured using inductively coupled plasma mass spectrometry (ICP-MS). TTE and E2 levels in umbilical cord blood were measured using chemiluminescence microparticle immunoassay (CMIA). Linear regression model was used to estimate the relationship between the walkability index, placental metals, and sex steroid hormones. Effect modification was also assessed to estimate the effect of placental metals on the associations of neighborhood walkability with TTE and E2. ResultsNeighborhood walkability was significantly linked to increased E2 levels (P trend=0.023). Compared with participants at the first quintile (Q1) of walkability index, those at the third quintiles (Q3) had lower chromium (Cr) levels (β = −0.212, 95% CI = −0.421 to −0.003). Arsenic (As), cobalt (Co), manganese (Mn), molybdenum (Mo), nickel (Ni), lead (Pb), antimony (Sb), selenium (Se), tin (Sn), and vanadium (V) were linked to decreased TTE levels, and cadmium (Cd) was linked to increased TTE levels. No metal was significantly associated with E2 levels in trend analysis. In the analysis of effect modification, the associations of neighborhood walkability with TTE and E2 were significantly modified by Mn (P = 0.005) and Cu (P = 0.049) respectively. ConclusionNeighborhood walkability could be a favorable factor for E2 production during pregnancy, which may be inhibited by maternal exposure to heavy metals.

Changing Tourism Trends and Vulnerability Assessment of Built Environment in Hill Stations of Indian Himalayan Region.

Tourist arrivals in the Indian Himalayan region have led to an increase of 1.6 times the population of the native residents in 2019. The trend of winter tourism among foreign tourists, along with adventure and pilgrimage tourism, has resulted in an average annual growth of 28.78% between 2002 and 2013. This study focuses on the changing tourism and climatic trends in tourist hotspots of the Indian Himalayan Region (IHR) to evaluate the vulnerability of the built environment, which arises from the increasing demand for tourist infrastructure. The approach taken in this research is based on secondary literature available and case studies of emerging tourist centers in and around Shimla region of Himachal Pradesh. According to records from 2019-20, domestic tourism has increased in Himachal Pradesh by 4.57% and in Shimla by 5.51%. However, the changing trends and the tourist demand for fast, unplanned infrastructure growth can lead to over-tourism and disaster vulnerability. Therefore, there is a need to consider the risk and change management in the fragile ecosystem of IHR through analysis of climatic and tourism trends. To achieve this, computerized tools such as Real-Time Systems, Intelligent Transport Systems, and Neural networks projects are suggested for feasibility and assessment of proposed tourism infrastructure projects. The suggested process will strengthen the project vision by benefiting the policymakers, stakeholders, and tourists while maintaining eco-friendly tourism opportunities through project performance management.

Hype or hope? Ketamine for the treatment of depression: results from the application of deep learning to Twitter posts from 2010 to 2023.

To investigate societal perceptions of ketamine's use in depression therapy by analysing Twitter posts from January 1, 2010 to April 1, 2023. Using Twitter as the social media platform of choice, and employing search terms based on (depression OR depressed OR depressive) AND (ketamine OR esketamine OR Spravato), we collected English-language tweets from January 1, 2010, to April 1, 2023. Using unsupervised machine learning and natural language processing (NLP) techniques, including Bidirectional Encoder Representations from Transformers (BERT) and BERTopic, the study identified prevalent topics surrounding public chatter around the use of ketamine in depression treatment. Manual thematic analyses further refined these topics into themes. Out of an initial dataset of 99,405 tweets, after removing duplicate tweets, re-tweets and tweets posted by organizations over Twitter, 18,899 unique tweets from presumably individual users were analysed. Analysis of temporal trends revealed a shift in public attitudes, particularly after the United States Food and Drug Administration (FDA)'s 2019 approval of ketamine for depression. Three major themes emerged: a changing regulatory landscape, cautious optimism, and personal experiences with the drug. There was an initial spike in discussions post-FDA approval in 2019. Thereafter, cautious optimism (Theme 2) decreased among the general public, with more personal accounts (Theme 3) highlighting the potential benefits for some treatment-resistant patients. Limitations of the study include Twitter's inherent biases towards younger, English-speaking demographics. In summary, the public's multifaceted perception leans towards a hopeful stance on ketamine's therapeutic potential for depression.

Trends in Gender Diversity Among Total Hip Arthroplasty Surgeons.

A pronounced gender imbalance is evident among orthopaedic surgeons. In the field of arthroplasty, there exists a dearth of comprehensive data regarding gender representation. This study aimed to analyze the gender diversity, or lack thereof, within the field of total hip arthroplasty (THA). In addition, this study used literature review to identify possible reasons for the gender disparity among THA surgeons and identify the best next steps to promote gender equity within orthopaedics. A retrospective analysis was conducted using the Medicare Provider Utilization and Payment Data: Physician and Other Practitioners data set to quantify orthopaedic surgeons who performed primary THA procedures from 2013 to 2020. To assess trends in the number of hip surgeons by sex and the evolving female-to-male ratio, two-sided correlated Mann-Kendall tests were conducted. Overall, 3,853 to 4,550 surgeons billed for primary THA annually. Of this number, an average of 1.7% was female. The mean number of services billed for by male surgeons was 31.62 ± 24.78 per year and by female surgeons was 26.43 ± 19.49 per year. Trend analysis of female-to-male ratio demonstrated an increasing trend of statistical significance (P = 0.009). The average number of procedures by female surgeons annually remained stable throughout the study, whereas there was a steady increase in that for male surgeons. Results showed a notable and sustained upward trajectory from 2013 to 2020 in the number of female surgeons billing for THA along with the female-to-male ratio. However, female surgeons constitute a mere 2% of surgeons engaging in primary THA billing. Furthermore, the annual average number of THAs conducted by female surgeons exhibited constancy, whereas there was a gradual increase in the median number of annual procedures performed by their male counterparts. Future studies should aim to identify and resolve specific barriers prohibiting female medical students from pursuing and obtaining a career as an orthopaedic THA surgeon. Retrospective analysis using the Medicare Provider Utilization and Payment Data: Physician and Other Practitioners data set.

Impact of Urbanization on Air Quality of Dehradun District

The increasing trend of urbanization poses a significant challenge to environmental sustainability, particularly concerning air quality. This study examines the impact of rapid urbanization on the Dehradun district land use and land cover (LULC), with the built-up area increasing from 44.2 km² to 276.5 km² between 2000-2019. The LULC analysis highlights a significant expansion of built-up areas influencing regional air quality. A comprehensive analysis of air pollutants and environmental factors spanning 2000 to 2019, utilizing TROPOMI, OMI, MODIS, MOPITT, and CHIRPS data, was also conducted. Spatial variations of air pollutants, including CO i.e. carbon monoxide, HCHO i.e. formaldehyde and NO2 i.e. nitrogen dioxide demonstrate higher concentrations in urbanized areas. Temporal variations exhibit seasonal peaks during the summer months. A 15-year trend analysis indicates a consistent rise in NO2 and HCHO, attributed to urbanization and anthropogenic activities. The correlation matrix highlights strong positive correlations among air pollutants, suggesting common sources or influences. The correlation between NO2 and CO stands at 0.652, between HCHO and CO is 0.583, and between HCHO and NO2 is 0.619. Higher correlation values of more than 0.4 are observed between the land surface temperature and pollutant concentrations, highlighting the influence of anthropogenic activities on temperature rise. In an attempt to mitigate the negative effects of uncontrolled urban sprawl on the district of Dehradun's air quality and overall environmental health, the study underscores the pressing need for sustainable urban planning. These findings contribute valuable insights for decision-makers to formulate effective strategies for environmental conservation against the unfavourable consequences of swift urbanization.

Seasonal Scale Climatic Factors on Grassland Phenology in Arid and Semi-Arid Zones

Influenced by climate change, significant alterations in vegetation phenology have been observed globally. Grassland phenology is highly sensitive to climate change. However, research on the variations in grassland phenology and its responses to seasonal climatic changes in arid and semi-arid regions remains scarce. This study, utilizing Solar-Induced Chlorophyll Fluorescence (SIF) data, meteorological station data, and grassland type data, employs trend analysis and time series analysis to explore the trends of seasonal climatic variability and the sensitivity response of grassland phenology in Xinjiang to seasonal climates. The findings reveal the following: (1) The region experiences more pronounced warming in winter and spring than in summer and autumn, with ground temperature increments outpacing those of air temperatures. The summer season registers the peak in precipitation volume and rate of increase, where mountainous zones accrue more rainfall compared to basins and plains. The distribution of sunshine duration is characterized by higher values in eastern areas than in the west and more in the plains than in mountainous regions, potentially due to escalating cloudiness, which has contributed to a diminishing trend in sunshine hours across Xinjiang over the past 20 years. (2) Over the past two decades, the perennial greening phase of Xinjiang grasslands has predominantly occurred in early May, showing an overall trend of occurring earlier by approximately 5.47 days per decade, while the yellowing phase mainly occurs at the end of September and the beginning of October, demonstrating a delaying trend (6.61 days/decade). The average length of the growing season is 145 days, generally showing a slightly increasing trend (11.97 days/decade). (3) In spring, the rise in air and ground temperatures, along with increased sunshine duration, all promote grassland growth, leading to an earlier greening phase. Conversely, in autumn, increases in air temperature, ground temperature, and sunshine duration can inhibit grassland growth, resulting in an earlier yellowing phase. Increased precipitation in summer and autumn can delay the yellowing phase and extend the length of the grassland growing season. This research provides new insights into the factors influencing large-scale grassland phenology and offers references for grassland adaptation to future climate changes.

Benefits of Mann–Kendall trend analysis for vibration-based condition monitoring

Rank-based statistics offer an appealing framework to non-parametric robust trend detection. Especially, the Mann–Kendall test detects the presence of a trend in a series. This paper investigates the benefits of using the Mann–Kendall test, which seems to have remained largely unnoticed in the context of vibration-based condition monitoring. Two contributions structure the present paper. First, theoretical foundations of rank-statistics are reminded and the Z-score is introduced, a statistical metric measuring the presence of a trend in a given series. The performance of the Mann–Kendall test is investigated and confronted to different numerical cases involving series of increasing condition indicators. Second, based on this understanding, the Z-score metric is exploited to design two trend-oriented signal processing tools dedicated to vibration-based condition monitoring. Namely, a new tool named the Mannagram is introduced as a dyadic filterbank representation of the trend of indicators series. It shows effective in the informative band selection problem and unveils more interpretable indicators. Besides, a concise representation of trend by frequency bin is introduced and coined the Kendrum. This representation is shown to help the diagnosis by summarising the trend information of series of spectra. Both methods are demonstrated on run-to-failure series of vibration signals from industrial wind turbines.

Quantitative analysis of the impact of climate variability and human activities on grassland productivity of the Qilian Mountain National Park, China.

To quantitatively analyze the impact of climate variability and human activities on grassland productivity of China's Qilian Mountain National Park, this study used Carnegic-Ames-Stanford Approach model (CASA) and Integrated Vegetation model improved by the Comprehensive and Sequential Classification System (CSCS) to assess the trends of grassland NPP from 2000 to 2015, the residual trend analysis method was used to quantify the impact of human activities and climate change on the grassland based on the NPP changes. The actual grassland NPP accumulation mainly occurred in June, July and August (autumn); the actual NPP showed a fluctuating upward trend with an average increase of 2.2 g C·m-2 a-1, while the potential NPP increase of 1.6 g C·m-2 a-1 and human-induced NPP decreased of 0.5 g C·m-2 a-1. The annual temperature showed a fluctuating upward trend with an average increase of 0.1°C 10a-1, but annual precipitation showed a fluctuating upward trend with an average annual increase of 1.3 mm a-1 from 2000 to 2015. The area and NPP of grassland degradation caused by climate variability was significantly greater than that caused by human activities and mainly distributed in the northwest and central regions, but area and NPP of grassland restored caused by human activities was significantly greater than that caused by climate variability and mainly distributed in the southeast regions. In conclusion, grassland in Qilian Mountain National Park showed a trend of degradation based on distribution area, but showed a trend of restoration based on actual NPP. Climate variability was the main cause of grassland degradation in the northwestern region of study area, and restoration of grassland in the eastern region was the result of the combined effects of human activities and climate variability. Under global climate change, the establishment of Qilian Mountain National Park was of great significance to the grassland's protection and the grasslands ecological restoration that have been affected by humans.

Global trends in pharmacovigilance-related events: a 30-year analysis from the 2019 global burden of disease study.

Establishing effective pharmacovigilance systems globally is challenging due to the need for comprehensive epidemiological data on pharmacovigilance-related events, particularly in countries at different stages of development. This study aimed to determine magnitude and drivers of change in the global and regional burden of pharmacovigilance-related events from 1990 to 2019, analyzing variations between age groups and sex, providing data support for policymakers to adjust their pharmacovigilance policies. Pharmacovigilance-related events were defined as Adverse Effects of Medical Treatment (AEMT) and Drug Use Disorders (DUD) in the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Time trend analysis utilized joinpoint regression, age-period-cohort model, and decomposition method. Disease burden was measured in incidence, deaths, and disability-adjusted life years (DALYs). The global burden of pharmacovigilance-related events remained high, driven predominantly by population growth. Children and older adults were identified as particularly susceptible groups. Across various regions and periods of the socio-demographic index (SDI), the risk of death from AEMT showed a decreasing trend. In contrast, the incidence of AEMT and both the incidence and death rates from DUD showed a stable or worsening trend. Significant regional disparities in the burden of these diseases were noted between different SDI levels. The study underscores the critical need for robust pharmacovigilance systems worldwide. The observed trends in the burden of pharmacovigilance-related events offer a clear direction for countries to refine and strengthen their pharmacovigilance policies and practices.

Roadmap for Greening the Economy of Turkmenistan

Over the past decades, interest in renewable energy has grown, this is due to the aggravation of climate change. The emerging trend of decarbonization of the world economy, including transport and energy, which are one of the main sources of air pollution with carbon dioxide emissions. The article discusses issues of climate change, decarbonization scenario, a road map for “greening” the economy, and presents a brief analysis of trends in the development of hydrogen energy and the importance of the development of “green” hydrogen in the world and in Turkmenistan. The main attention is paid to the prospects and scale of development of hydrogen energy to a certain extent will depend on the characteristics of the hydrogen sources proposed for use ­, primary energy sources and hydrogen production technologies, environmental consequences when using different approaches to hydrogen production, expected costs for hydrogen production, potential consumers and volumes of hydrogen consumption within the country and abroad, technologies for storing and delivering hydrogen to consumers, the competitiveness of hydrogen as an energy carrier in the domestic and foreign markets, taking into account all the necessary costs and a potential “transboundary carbon ­tax”.

Anti-artifacts techniques for neural recording front-ends in closed-loop brain-machine interface ICs.

In recent years, thanks to the development of integrated circuits, clinical medicine has witnessed significant advancements, enabling more efficient and intelligent treatment approaches. Particularly in the field of neuromedical, the utilization of brain-machine interfaces (BMI) has revolutionized the treatment of neurological diseases such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. The BMI acquires neural signals via recording circuits and analyze them to regulate neural stimulator circuits for effective neurological treatment. However, traditional BMI designs, which are often isolated, have given way to closed-loop brain-machine interfaces (CL-BMI) as a contemporary development trend. CL-BMI offers increased integration and accelerated response speed, marking a significant leap forward in neuromedicine. Nonetheless, this advancement comes with its challenges, notably the stimulation artifacts (SA) problem inherent to the structural characteristics of CL-BMI, which poses significant challenges on the neural recording front-ends (NRFE) site. This paper aims to provide a comprehensive overview of technologies addressing artifacts in the NRFE site within CL-BMI. Topics covered will include: (1) understanding and assessing artifacts; (2) exploring the impact of artifacts on traditional neural recording front-ends; (3) reviewing recent technological advancements aimed at addressing artifact-related issues; (4) summarizing and classifying the aforementioned technologies, along with an analysis of future trends.

Analysing district-level climate vulnerability pattern in Madhya Pradesh, India, based on agricultural and socio-economic indicators.

Indian agriculture transitioned from a food deficit sector to a food surplus following the Green Revolution. However, the continued progress of Indian agriculture has been hampered by climate change. This research explores the district-wise vulnerability in Madhya Pradesh, India, to climate change by assessing the composite vulnerability index using the agricultural vulnerability index (AVI) and socio-economic vulnerability index (SEVI). The study seeks to understand how agricultural and socio-economic factors lead to variations in vulnerability across districts and influence targeted adaptation and mitigation strategies. The trend analysis results present declining rainfall and inclining temperature from 1951 to 2021 in Madhya Pradesh, directly affecting the agricultural sector and human livelihood. The composite vulnerability index (CVI) results revealed that districts with low values (< 0.394), such as Burhanpur and Balaghat, demonstrate reduced susceptibility due to limited cultivation, low reliance on rainfall, lower drought susceptibility, and decreased population density. Districts such as Panna and Bhopal show moderate vulnerability (0.394-0.423), with lower fallow land, reduced rainfed agriculture, and socio-economic vulnerability. Extensive agriculture and marginalised workers' presence influence high vulnerability (0.423 to 0.456) in districts such as Tikamgarh and Indore. Districts like Barwani and Jhabua have the highest CVI values (> 0.456), indicating substantial susceptibility to climate impacts. The cluster analysis validates the results of the vulnerability index. The findings highlight the urgent need for tailored adaptation strategies to address the diverse agricultural and socio-economic indicators creating vulnerability in Madhya Pradesh. The study helps understand regional vulnerability patterns and provides evidence-based policy approaches for resilience to climate change effects.