Boeing and Airbus developed a special testing procedure to investigate the compressive response of laminates that have been impacted (following standards ASTM D 7137 and DIN 65561). This study focuses on both experimental and numerical analysis of Kevlar plates subjected to compression after impact. To ensure high quality and appropriate mechanical properties, the composite plates were manufactured using autoclaving. The DIN 65561 protocol was followed for all three test systems. Initially, ultrasonic C-scanning was performed on all plates before testing to confirm they were free of any significant defects arising from the manufacturing process. Subsequently, low-energy impact testing was conducted at levels ranging from 0 to 8 Joules. Three specimens were tested at each energy level. After the impact, all specimens underwent ultrasonic C-scanning again to assess the internal delamination damage caused by the impactor. Finally, both pristine and impacted specimens were subjected to compressive testing using the special jig specified in DIN 65561. The compressive impact strength results obtained from these tests were plotted against the delamination area measured by C-scanning. This data was then compared to results obtained from specimens with artificial damage. Semi-empirical equations were used to fit both sets of curves. The same procedure (impact testing, C-scanning, and data analysis) was repeated to investigate the relationship between impact energy and total delamination area. Lastly, finite element modeling was employed to predict the buckling stresses that develop under compression in the impacted systems studied. These modelling approaches have demonstrated good accuracy in reproducing experimental results for CAI tests.

Although the influence of climate on the fire regime is unanimously recognized, most publications are studies on this influence are at the global scale. Therefore, this study aims to demonstrate the role of climate in the incidence of wildfires at the country and regional scale using statistical analysis and machine learning methods. Mainland Portugal was chosen as a case study due to its climate and because it is the European region most affected by wildfires. Results demonstrate the climate signature in the spatial and temporal distribution of the wildfire incidence. The conclusions of the study include (i) the existence of two pyro-regions, with different types of climate (Csb and Csa) composed of NUTS II regions: the northern region composed of the Norte and Centro regions and the southern region composed of Alentejo and Algarve; (ii) the intra-annual variability in the incidence of wildfires, characterized by two peaks, one in spring and the other in summer, are a consequence of the country's type of climate; and, (iii) how the annual cycle of wildfire incidence varies over the years depends on the weather conditions throughout each year. These results are of fundamental importance for wildfire managers, especially in the context of climate change.

In this study, data analysis methods from ecology were applied to litter surveys to evaluate patterns among urban litter items found in two types of streets in England (High Streets and Central Business Districts). Results indicate that sites characterised as a High Street (predominantly leisure activities such as shopping and dining) contained lower densities, less variety, yet featured items with higher potential for environmental contamination than sites categorised as Central Business District (identified by high numbers of professional workers and transport links). Although litter were significantly different between sites, the litter community structure was not. Our results suggest that litter typologies and associated activities can lead to specific knowledge of key influential items in a site and inform future evidence based and sustainable mitigation systems.

In 2011, commercial aviation contributed approximately 3.5% of global anthropogenic climate change through the emission of greenhouse gases during flight and operational non-CO2 climate effects. Over the last few years, numerous aviation-related organisations have set goals to reduce aviation’s climate impact. These goals, however, lack alignment, are poorly or ambiguously defined, or are internally inconsistent. This increases uncertainty about what aviation should work towards, how various stakeholders can contribute, and introduces problems with respect to accountability. In order to address this issue, this paper presents a comprehensive definition of a climate neutral air transport system as an “air transport system of which the climate effects of all its greenhouse gases and non-carbon dioxide effects throughout the entire life-cycle of each element of the system is balanced”. The proposed definition spans relevant system and encompasses all life cycle phases. To achieve a climate neutral air transport system by 2050, all life-cycle greenhouse gas emissions and non-CO2 climate effects remaining after in-sector reduction should be neutralised, as should all remaining non-CO2 climate forcing from emissions prior to 2050. Clarity on governance is furthermore needed, as the goal and associated targets proposed should be adopted globally.

When asked to estimate the carbon footprint of a bundle of relatively low carbon footprint items and relatively high carbon footprint items, people typically report a lower value compared to estimating the high carbon footprint items alone. This finding is called the negative footprint illusion and suggests people report the average rather than sum of the combined items’ carbon footprint. In a recent paper by Gorissen et al. (2024), the authors claimed that people are immune to this illusion if the question is framed differently. Specifically, they found that estimates of the environmental friendliness of a set comprising a burger (high carbon footprint) and an organic apple (low carbon footprint) was higher than for a set comprising the burger alone, whereas no difference was found between the two sets when participants were asked to estimate how environmentally damaging they were. Using larger item categories wherein the degree of the items’ environmental impact is clearly communicated, here we show it does not matter whether participants are required to estimate how friendly or damaging the items are. The roles of attribute substitution, dependent variables, and independent variables (stimulus characteristics) in modulating the negative footprint illusion is discussed.

The aim of this research work is to study the influence of temperature, solar irradiation and wind dust on the production of solar energy. In addition, it aims to study the assessment of water quality, in particular groundwater used for cooling and cleaning photovoltaic panels (quality analysis). it's an important source, stable and sustainable can be used entirely for cooling and cleaning PV modules from the sales dust, in order to improve their performance. To date, all research studies carried out in this context of cooling and cleaning using water have not taken account of the nature of this water. We have taken a sample of water from a well in a rural area in the Darra Tafilalet region of Morocco. This region has an arid and semi-arid climate, with very high temperatures and dust-laden winds, particularly in summer. These meteorological characteristics influence the efficiency of cells, particularly photovoltaic (PV) panels, reducing their performance. Next, the water sample was analysed in the laboratory. The results obtained show that the groundwater in this area is very sensitive to cooling and cleaning photovoltaic panels. Moreover, these results indicate that the temperature, solar irradiation and wind-blown dust have a significant influence on energy production.

In this paper, we aim to present real implementation cases where non-visible elements of environmental impact assessments (EIA), wind flow, are visualized using a 3D digital twin technology. The conventional EIA process serves as a crucial tool in the evaluation of potential environmental impacts prior to the initiation of development projects. This evaluation helps to establish a legal and institutional framework that seeks to minimize the adverse effects on the environment. However, traditional EIA methods present challenges, particularly for non-experts, in comprehending the results of assessments involving non-visible environmental factors such as noise, air quality, and wind flow. These elements are often represented in static images or numerical tables, limiting accurate understanding and engagement. Our proposed method, termed Digital Twin based EIA, addresses these limitations by leveraging digital twin technology. This advanced methodology allows for the visualization of non-visible environmental elements in a spatio-temporal dimension, providing a more interactive and comprehensive user interface/experience for both citizens and stakeholders. In this context, we present a unique case study that focuses on visualizing wind flow using this technology. This paper serves as an example of how digital twin platforms can enhance traditional EIA processes, offering a more immersive and informative experience. The evolution of EIA into the digital realm signifies an important step forward in fostering public understanding and engagement in environmental protection efforts.

Amidst escalating environmental concerns, short natural fiber thermoplastic (SNFT) biocomposites have emerged as sustainable materials for the eco-friendly production of mechanical components. However, their limited durability has prompted research into the experimental evaluation of the deterioration of the mechanical characteristics of SNFT biocomposites, particularly under the influence of ultraviolet rays. However, conducting tests to evaluate the mechanical properties can be time-consuming and expensive. In this study, an artificial neural network (ANN) model was employed to predict the mechanical properties (tensile strength) and the impact performance (resistance and absorbed energy) of polypropylene reinforced with 30 wt.% short flax or wood pine fibers (referred to as PP30-F or PP30-P, respectively). Eight parameters were collected from experimental studies. The ANN input parameters comprised nondestructive test results, including mass, hardness, roughness, and natural frequencies, while the output parameters were the tensile strength, the maximum impact load and absorbed energy. The model was developed using the ANN toolbox in MATLAB. The linear coefficient of correlation and mean squared error were selected as the metrics for evaluating the performance function and accuracy of the ANN model. They calculate the relationship and the average squared difference between the predicted and actual values. The data analysis conducted by the models demonstrated exceptional predictive capability, achieving an accuracy rate exceeding 96%, which was deemed satisfactory. For both the PP30-F and PP30-P biocomposites, the ANN predictions deviated from the experimental data by 3, 5, and 6% about the impact load, absorbed energy, and tensile strength, respectively.

Air pollution poses a significant risk to public health and ecosystems. The use of sophisticated models to simulate the transformation and dispersion of pollutants in the atmosphere is a recognized method to assess air pollution levels and its sources and inform policy decisions for effective mitigation strategies in urban and industrial environments. The reliability of models depends, in part, on the sensitivity to the variance of input parameters, which can introduce uncertainty into the model's predictions. This uncertainty is especially challenging when the input parameters exhibit inherent variability. In this study, we analyse the uncertainty of an integrated emission/dispersion model by evaluating the relationship between input parameters and model outcomes. We uncover new aspects of this relationship while clarifying some previously known dependencies. Wind speed was found to have the most significant effect on calculated concentrations, with small differences leading to substantial concentration variations. The time of day, which reflects prevailing vertical turbulence conditions, was also found to have a notable impact on concentrations, whereas ambient temperature can also significantly influence model’s results. Based on these findings, we offer specific recommendations for regulators and scientists involved in environmental impact assessment to improve the accuracy and reliability of air pollution modelling.

Although child-centred care is increasingly referred to within the nursing literature, a clear definition of child-centred care and clarity around the concept is yet to be achieved. The objectives of this review were to examine: 1) What constitutes the concept of child-centred care in healthcare? 2) How has the concept of child-centred care developed? 3) What is the applicability of child-centred care and what are its limitations? and 4) How does the concept of child-centred care benefit and inform children’s healthcare? In total, 2984 papers were imported for screening, following removal of duplicates and screening, 21 papers were included in the scoping review.The findings suggest that child-centred care is an emerging, ambiguous, poorly defined concept; no clear consensus exists about what constitutes child-centred care. Although it seems antithetical to argue against child-centred care, little robust evidence was identified that demonstrates the impact of, and benefit from, child-centred care. If child-centred care is to be a sustainable, convincing model to guide practice and compete with other models of care it needs to establish robust evidence of its effectiveness, impact on children and their families as well as the wider impacts on the healthcare system.

The pursuit of sustainable wellbeing is one of the research objectives of positive experience design. Driven by this goal, the purpose of this paper is to provide an impact-centered sustainable positive experience design model. Firstly, the literature review method was used to define the research status and concept of impact-centered sustainable design. Secondly, an impact-centered sustainable positive experience design model was constructed, and relevant formulas for concept generation and concept evaluation were proposed. Thirdly, design verification was conducted through a workshop. Finally, the Technology Acceptance Model (TAM) questionnaire was used to evaluate and discuss the design model. An impact-centered sustainable positive design model was proposed, which includes the important impact dimensions of sensory experience and meaningful experience on users’ quality of life at different levels: healthy living (pleasure index, health behavior), harmonious community (social connectivity, social contribution), and livable environment (living environment, environmental contribution). Based on positive experience related theory, this study takes long-term impacts as the starting point for sustainable positive experience design, which helps designers to generate design concepts from a systematic and long-term perspective.

In conclusion, this qualitative exploration has unveiled the profound and essential impact of music on psychological well-being, especially in the post-pandemic world. Through in-depth literature reviews, informal interviews, and observations with thirty CAS participants from SMC, the researcher uncovered ten salient themes that collectively illustrate music's multifaceted role as a potent remedy. These findings showcase how music serves as an emotional outlet, a cognitive enhancer, and a source of inspiration. The emotional depth and spiritual resonance participants associate with music underscore its capacity to address diverse human needs, making it an indispensable tool in navigating the complexities of our post-pandemic reality. Moreover, the cognitive benefits observed, such as improved concentration and focus, are particularly pertinent in the context of remote work and education, highlighting music's necessity in our daily lives. Additionally, this study emphasizes the vital role of virtual music communities in fostering social connections, even amidst physical isolation, further underscoring the enduring relevance of music in these challenging times. This research contributes to the expanding knowledge of music's impact on well-being, offering a holistic perspective encompassing spiritual, emotional, social, and cognitive dimensions. It enriches existing music psychology theories and invites further exploration into the mechanisms underpinning music's diverse effects. These insights have practical implications for fields such as mental health, education, and remote work, where music can be utilized as an essential tool for stress reduction and emotional regulation. This is highlighted further in the Suggested songs that can help sought the mind, body, spirit and soul. Looking ahead, future research could delve deeper into the long-term impact of music engagement on well-being and explore the universality of music's benefits through cross-cultural studies. Overall, music, as illuminated by this study, stands as a timeless and indispensable companion, offering solace, inspiration, vitality, and connection in the face of any contemporary challenges.

To solve the problem of deformation and stress in segments when a full-face hard rock tunnel boring machine (TBM) tunnel for an urban subway passes through existing buildings, a three-dimensional mechanical calculation model of TBM tunneling under existing buildings was established based on numerical analysis to comprehensively study the spatial attributes of tunnel segments during TBM tunneling. The Qingdao Metro Line 1 TBM tunnel in the hard rock stratum of Xiaobei District passes through existing buildings. The results indicated that (1) the stress and deformation of the segments were different at different positions. The horizontal and vertical stress and displacement of the segments in front of the building were significantly affected by the building. When the segment was not in the area below the horizontal plane of the building, the vertical stress of the segment was significantly greater than the two stresses in the horizontal direction. (2) The vertical displacements of the vault and the arch bottom were the largest, and the influence of vertical accessories was stronger when the segment was closer to the building.(3) When the tunnel was excavated to approximately one tunnel diameter in front of the building, the building was affected. If the surrounding rock is unstable, the excavation face may collapse and the ground surface may sink, possibly leading to inclination, cracking, and uneven settlement of the building.

In this research, we investigate the healthcare expenditure patterns in Uzbekistan, analyze their economic implications, and provide policy recommendations. The study focuses on the time frame from 2000 to 2019, employing quantitative data analysis, theoretical frameworks such as Wagner’s Law, and an economic geography perspective. Our objective is to gain insights into the relationship between economic development and healthcare spending, identify spatial disparities, and forecast future trends. The findings reveal fluctuations in per capita healthcare spending, emphasizing the necessity for sustainable financing mechanisms and preventive measures. Ultimately, our study underscores the significance of aligning healthcare expenditure decisions with economic objectives while prioritizing the well-being of the population.

In response to the problem of increasing climate change and energy security, investment in renewable energy sources has increased significantly both in Europe and globally. Wind and solar power plants are expected to be the largest contributors to global decarbonization, ranking first and second in projected capacity by 2050. Since all power plants have some impact on the environment, this also applies to photovoltaic power plants. Because of the large capacities projected for PV installed capacity, their environmental impacts should be evaluated. The environmental impacts of PV power plants change over time. Improving the manufacturing technology of PV system components, increasing the efficiency of solar cells, and using materials that are less harmful to the environment will reduce these impacts. Manufacturing PV system components is a highly energy-intensive process that involves greenhouse gas emissions. As new renewable energy capacity is built, the amount of "green" electricity on the grid increases, reducing CO2 emissions per kWh consumed. The objective of this paper is to analyze the current status of the environmental impact of PV power plants under these changing conditions in terms of CO2 emissions, land use, pollutant and noise emissions, and water consumption. The capacity installed to date will reach the end of its lifetime by 2050, which means that the amount of waste associated with it will increase over time. This can have a significant impact on the environment, which is why part of the work is dedicated to this problem. In addition to the available information from the literature, in the part related to land use, the authors also made their own estimates based on data on newly installed PV power plants and PV modules available on the market. The results of the analysis show that there is enough land both in Europe and worldwide to install the planned capacities of rooftop and ground-mounted PV power plants. CO2 emissions are at the same level as for concentrated solar power, with a decreasing trend. Pollutant emissions, noise and water consumption are not a major problem compared to other types of power plants. Overall, it can be concluded that the expansion of PV capacity has a very positive impact on the environment.

Although the similarity laws were widely used in impact fields, the scaling relations of anisotropic elastic structures often were broken when the geometric distortion (not equal scaling in different spatial directions) and the material distortion (different materials used for scaled model and full-size prototype) were considered. To overcome the difficulty of geometric and material distortion, a directional framework of similarity laws, termed as oriented-density-length-velocity (ODLV) system, is proposed for the anisotropic elastic structure under impact loads. Different from previous similarity law systems using scalar dimensional analysis, the directional similarity law framework mainly considers spatial anisotropy for structural geometry and material parameters. Based on the oriented dimensional analysis and the orthotropic Hooke's law, directional dimensionless numbers and directional scaling relations with geometric power properties for the elastic modulus and the Poisson's ratio are presented systematically. By selecting the dominant material parameters controlling similarity, three important scaling techniques with correction of geometric width and thickness are proposed to compensate for the difficulty of distortion. A clamped square plate with different anisotropic and isotropic elastic materials subjected to dynamic pressure pulse is verified numerically and discussed in detail. The results show that the thin square plate prototype must be scaled to be the thinner/thicker rectangular plate, and the components of displacement, stress and strain between scaled model and full-scale prototype behave good consistency in both spatial and temporal fields.

A toy model for the distribution of the impact factor (IF) of a journal is proposed. The model demonstrates the presence of a heavy tail for the IF distribution, which occurs due to some random non-scientific circumstances. Therefore, the use of IF as an indicator of the quality of scientific papers seems to be inadequate.

Sharing activity is getting higher attention due to increasing popularity in recent years. In the paper, the authors investigated the main elements affecting the sharing activity. (1) Literature review: The theoretical part starts from the revision of definitions of sharing activity; description of the links between sharing and sustainable development, policy recommendations and relevant regulation in the field; later on, the study emphasises the key elements important for sharing. Finally, the authors investigated how the Covid-19 pandemic affected sharing activity; (2) Methods: During empirical research, the authors revised the list of 37 variables. The study uses data for each of the 27 EU countries from 2011 to 2020. The authors investigated correlation between macroeconomics variables to determine key variables for the regression model; (3) Results: The authors constructed a dynamic regression model that can be applied to predict the number of participants visiting sharing platforms in the European Union (EU); (4) Conclusions: The study shows that seeking to forecast the number of visits to sharing platforms it is necessary to use values of main macroeconomic variables such as consumer price index, productivity index, total unemployment rate, the number of users and households connected to the Internet, etc.

The objective of this work is to compare how the gases emitted during the manufacture of the clinker vary in a cement plant, using two types of fuel: petroleum coke and unusable tires (UTs). The study is based on a case study using real time data on more than 40 process variables. Gases are analysed from two points of the production process: Sintering Kiln, main focus of emission to the atmosphere by chimney, and Preheater. The variation of CO and NOx depending on the oxygen and fuel type is studied. The SO2 levels are also analyzed, observing a decrease when using the UTs. The quality of the Clinker has been compared depending on the fuel type. The results are compared, on the one hand, with the quality of the clinker, determined by the content of the majority (C3S, Alite) and minority (Free CaO) phases, and, on the other hand, with the Kiln sintering temperature, the most influential parameter in the productive process. It is verified that Clinker quality is maintained, regardless of the type of fuel used. Concluding that the use of UTs as fuel can generate an important economic and environmental benefit for cement companies and their environment.

One of the main drivers behind the urbanization process is attributed to economic fundamentals of urban growth, which boost migration from rural to urban context. This migration can be studied geographically, with increasing rates of population as the main component in developing countries, over Asia and Africa, specifically. Research has been focusing in creating models and adaptative schemes to manage and plan cities to promote sustainable development for housing large quantities of population and preserve a long-term living environment. The approach from a smart city perspective, adjusted to the rapid urbanization condition can be helpful to deal urban issues by convergence and interaction between urban agents and information technology. At academia, few works have addressed the role of Smart Cities to face the challenge of rapid urbanization. The aim of this study is to research and analyze if strategies with smart city vision can lessen environmental impacts at cases with rapid urbanization, and how can we leverage technology to promote environmental sustainability at rapid urbanization phenomena occurring at developing countries using RIAM environmental assessment method in the case of Beijing, China'.

We report the experiences of the bike sharing system in Ningbo, China. To analyze the impact of the system, system log data are collected for the whole month of May 2014 (with more than 1.7 million usage records), supplemented by questionnaire data from 1,856 respondents. Our results show that public bike usage follows the same pattern as road traffic, with morning and evening peaks on week days. In terms of mode substitution, 16% of public bike trips would have been made by private cars. In average, each public bike is used 3.7 times per day, with each trip lasting around 23 minutes and covering around 3.5 kilometre. This translates into a reduction of car travel by more than 11 million kilometre per year, a significant contribution to the sustainability of urban transport in Ningbo.

The COVID-19 pandemic caused by SARS-CoV-2 poses a devastating threat to human society in terms of health, economy and lifestyle. Establishing accurate and real-time models to predict and assess the impact of the epidemic on the economy is instructive. We have designed a new model to quantitatively assess the impact of the COVID-19 on the economy of China’s mainland. The nominal GDP in the Q1 of 2020 that we predicted for China’s mainland with the Baidu Mi-gration Data is RMB 20,785.7 billion, which is less by 3.59% than that in 2019. The estimated val-ue is confirmed roughly by the official report released in April 17, 2020 (RMB 20,650 billion, 6.8% year-on-year declined). Strict control measures during the epidemic have greatly reduced Chi-na's economic activity and had a serious impact on the country's economy. Orderly promotion of population mobility plays a decisive role in economic recovery.

This paper summarizes opinions on the economic impacts of horticulture research and extension at MSU Coastal Research and Extension Center. More than 8,400 horticulture producers, master gardeners, research and extension staff, and non-profit organizations participated in horticulture events during the last five years. Qualitative assessments of horticulture research and extension performed by the faculty and staff were solicited during voluntary surveys.

Introduction In 2016 the European Union setup its first structured food provision program to combat food insecurity. We aimed to measure the program’s capacity in assisting its beneficiaries to achieve a healthy diet and measure their satisfaction. Methods A computational study was carried out to calculate daily food provision per person under the program for January 2016-December 2017. A cross sectional survey in 3942 beneficiaries took place in December 2017-June 2018 collecting anthropometric, sociodemographic and program satisfaction data. Descriptive statistics were performed and reported as relatively frequencies, mean ± standard deviation. Results Dairy, fresh meat, legumes, sugar, olive oil and tomato concentrate were the most commonly procured items. The program’s contribution to vegetable, dairy and cereal intake was the lowest (3.4%, 6.1%, 6.0% respectively) as opposed to free sugars (12.2%) and oils (24.5%). The program’s algorithm favors greatly (almost 3-fold) single person applications compared to 4+ persons applications. The monetary value was estimated at 21.23±23.4 euros/food provision, however 64.4% of beneficiaries reported a high positive impact on the household budget. 50.7% and 41.6% reported high positive impact on feelings of anxiety and security, respectively. ~70% of the beneficiaries were highly satisfied with the foods provided, with lower scores for quality and shelf-life (50.7% and 58.8% high respectively). Conclusions The program is met by high beneficiary satisfaction and is perceived as a substantial assistance. Increases in the amounts and variety of foods delivered, with a focus on fruit, vegetables and fish should be considered, to further improve the program’s dietary impact.

Due to the high solar irradiance or energy price, certain regions in the U.S. may reach 100% PV penetration and experience degradation of frequency response greater than the interconnection as a whole. Therefore, in this section, the 100% PV penetration region in each interconnection is simulated to study the local high PV penetration effects. The study was performed by quantifying RoCoF, frequency nadir, and settling frequency at different regional PV penetration levels. The impact of high regional PV penetration on the compliance of grid code on frequency response is also studied.

This paper revisits a classic problem in physics - Hertz elastic dynamics of two colliding elastic spheres. This study obtains impact period in terms of hypergeometric function and successfully combines Deresiewicz's three segmental solutions into one single solution. Our numerical investigation confirms that Deresiewicz's inversion is a good approximation. As an essential part of this study, a general Maple code is provided.

Background and Research Highlights: Despite all the concerns and initiatives, natural resources like forests, as well as biodiversity are decreasing at an alarming rate worldwide. Conservation is considered as one of the major tools to prevent such loss and rapid degradation. Evidence around the world shows the adverse effects of conservation laws and policies on indigenous peoples and other local communities. Objectives: This study was conducted in one of the forest-dependent communities situated in Sundarban (world’s largest mangrove forest) to understand the impact of conservation laws and policies on their livelihood. Materials and Methods: A qualitative methodology was designed to collect data, using focus group discussions and case study with community people, and individual interviews with the personnel from NGOs and relevant government departments. Findings: Strict conservation policies and restrictions in accessing forest resources made lives and livelihoods of the local community insecure and unstable, thus putting the community in a vulnerable situation. The had to leave their traditional mode of income and look for alternative livelihood options. Almost no evidence was found in relation to upkeeping their rights in conservation activities. Prohibited movement, provision of punishment for entering into the forest without proper permission and struggles in everyday life were some of the highlighted issues. They had no participation in conservation activities, management of alternative livelihood options, and even they were not sensitized before putting restrictions. Although they had a history of emotional and physical attachment with the forest, existing activities did not consider these issues. In addition, corruption and abuse of power by law enforcement agencies towards the local community intensified the sufferings. Conclusion: This study argues that the realization of human rights in conservation activities and the sensitization of the implementing stakeholders are prerequisites for ensuring the sustainability of both biodiversity and the affected people.

In Ghana, about 73% of households rely on solid fuels for cooking. Over 13,000 annual deaths are attributed to exposure to indoor air pollution from inefficient combustion. In this study, assessment of thermal efficiency, emissions and total global warming impact of three cookstoves commonly used in Ghana was completed using IWA water boiling test (WBT) protocol. Statistical averages of three replicate tests for each cookstove were computed. Thermal efficiency results were: wood-burning cookstove 12.2% (Tier 0), traditional charcoal cookstove 23.3% (Tier 1-2) and improved charcoal cookstove 30% (Tier 2-3). The wood-burning cookstove emitted more CO, CO2 and PM2.5 than charcoal cookstove (coalpot) and improved cookstove. Emission factor for PM2.5 and emission rate for the wood-burning cookstove (Tier 0) were over four times higher than the traditional charcoal cookstove (Tier 3) and improved cookstove (Tier 2). On the basis of WBT, annual global warming impact potential for emissions are estimated at 4 tonnes of CO2e for the wood-burning cookstove, 1.5 tonnes of CO2e for charcoal cookstove (coalpot) and 1 tonne of CO2e for improved cookstove. We conclude that there is the need for awareness, policy and incentives to enable end-users switch to improved cookstoves for increased efficiency, reduced emissions/global warming impact.

This pioneering study explores the geospatial and temporal patterns of natural and human-induced disasters from 1900 to 2024, providing essential insights into their global distribution and impacts. Utilizing the comprehensive international EM-DAT database, our analysis reveals significant trends and disparities in disaster occurrences and their widespread consequences. Results showed a dramatic escalation in both natural and man-made (technological) disasters over the decades, with notable surges in the 1991-2000 and 2001-2010 periods. A total of 25,836 disasters were recorded worldwide, of which 69.41% were natural disasters (16,567) and 30.59% were man-made (technological) disasters (9,269). The most significant increase in natural disasters occurred from 1961-1970, while man-made (technological) disasters surged substantially from 1981-1990. Seasonal trends reveal that floods peak in January and July, while storms are most frequent in June and October. Droughts and floods are the most devastating in terms of human lives, while storms and earthquakes cause the highest economic losses. The most substantial economic losses were reported during the 2001-2010 period, driven by catastrophic natural disasters in Asia and North America. Our research highlights Asia as the most disaster-prone continent, accounting for 41.75% of global events, with natural disasters making up 61.89% of these events. Oceania, despite experiencing fewer total disasters, shows a remarkable 91.51% of these as natural disasters. Africa is notable for its high incidence of man-made (technological) disasters, which constitute 43.79% of the continent's disaster events. Europe, representing 11.96% of total disasters, exhibits a balanced distribution but tends towards natural disasters at 64.54%. Examining specific countries, China, India, and the United States emerged as the most frequently affected by both natural and man-made (technological) disasters. The impact of these disasters has been immense, with economic losses reaching their highest during the decade of 2010-2020, largely due to natural disasters. The human toll has been equally significant, with Asia recording the most fatalities and Africa the most injuries. Particularly, the decade from 2001 to 2010 experienced the greatest economic losses, primarily driven by natural disasters in Asia and North America. These insights highlight the urgent need for tailored disaster risk management strategies that address the distinct challenges and impacts in various regions. By understanding historical disaster patterns, policymakers and stakeholders can better anticipate and manage future risks, ultimately safeguarding lives and economies.

Cement industry is one of the highest energy consuming industries. The quantity of fuel and energy needed accounts for most of the cost of cement manufacturing. Thermal power plants generate electricity but are harmful and ineffective by nature. As a backup mechanism to account for main grid failures, batteries can be utilized. In this paper the first ever investigation on battery’s depth of discharge (DOD) for four different kinds of battery technologies is carried out in the framework of cement industry. The intended battery technologies are the lead-acid battery (LA), lithium-ion battery (Li-ion), vana-dium redox battery (VR), and nickel–iron battery (Ni-Fe). Four hybrid energy generation models (HEGMs) for five cement plants of Pakistan using the HOMER pro software are proposed. Cement plants includes Askari Cement Plant, Wah (ACPW); Bestway Cement Plant, Kalar Kahar (BCPKK); Bestway Cement Plant, Farooqia (BCPF); Bestway Cement Plant, Hattar (BCPH); and DG Cement Plant, Chakwal (DGCPC). HEGM-1 comprises of a diesel generator (DGen), a photovoltaic system (PV), a converter, and a battery system. HEGM-2 comprises of a PV system, a converter, and a battery system. HEGM-3 is the grid-connected version of HEGM-1 and HEGM-4 is the grid-connected version of HEGM-2. A base-model consisting of grid only is used as a reference. A multi-criteria decision analysis (MCDA) is performed by formulating a cumulative objective function (COF) which includes net present cost (NPC), levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions. The principal objective is the maximization of COF while simultaneously minimizing the objectives (NPC, LCOE and GHG emissions), based on optimal battery technology and DOD. The results reveal that VR is the most suitable battery technology with 10% DOD. It is achieved for DGCPC with HEGM-3 with 61.49% of NPC, 78.62% of LCOE and 84.00% of GHG emissions reduction as com-pared to the base model.

ackground: The swift assimilation of Artificial Intelligence (AI) across multiple industries is altering the worldwide economic terrain. Unprecedented opportunities and difficulties are brought about by this revolutionary technology, which has an impact on innovation, trade, labor markets, and security. Objective: The goal of this study is to thoroughly investigate the economic effects of AI by exploring how it may affect labor markets, innovation, trade internationally, and security. The goal is to offer insights that support strategic decision-making and policy formation by examining current trends, opportunities, and difficulties. Results: The research highlights the dual character of artificial intelligence's influence, highlighting both its potential to spur economic expansion and its drawbacks, including the loss of jobs, a lack of standards, and security issues. The study highlights how crucial cooperation is to overcoming these obstacles and realizing AI's full potential. Conclusion: The balancing opportunities and risks becomes critical as AI continues to change the economic landscape. The report promotes proactive steps including ethical AI design guidelines, ongoing worker retraining, and flexible regulatory strategies. As we shape an AI future that puts inclusion, creativity, and responsible governance first, collaboration emerges as a key theme.

The objective of this research is to show the family farms as an energy consumers and producers from renewable sources. It is a possibility for them to reduce operating costs. Time scope of the study covers the period 2014-2022. The data source is the Farm Accountancy Data Network. On the basis of the value of energy output and energy costs the rankings were prepared. After the ranks were awarded, the strong position of the Netherlands and Germany was indicated. It has been shown that the production and consumption of energy depend on the economic size of the farm, and do not depend on the type of production. As such, panel models were built for energy output and costs. The determinants that affect them were indicated. Energy output depends on total inputs – the higher they are, the higher the output. The energy costs are related to utilized agricultural area, total output and family farm income. The results obtained are discussed within the framework of recommendations of the European Commission.

The use of low cost sensors has dramatically increased in recent years in all the engineering sectors. In the field of buildings and automotive, low cost sensors open very interesting perspectives, because they allow to monitor temperature and humidity distributions together with air quality, in a widespread and punctual way and allow control of all energy parameters. The main issue still open remains the validation of the measurements. In this work, we propose an innovative approach to verify the measurements given by some low-cost systems built ad hoc for automotive applications. Two independent low-cost measurement systems have been set to measure Particulate air Matter (PM) concentration, TVOC concentration, CO2 concentration, formaldehyde concentration, air temperature, relative humidity, pressure, air flow velocity and GPS position. These systems have been calibrated by the comparison with standard and certified sensors used by the regional authority of Emilia-Romagna region (ARPAE, Italy) for characterising the air-quality. The innovation of this approach lies in both the in-field comparison of low-cost and high quality sensors and the use of proper conversion approaches for mass concentration measurements. A quantitative analysis of the sensors performance is given, with a focus on effects of time-granularity, relative humidity, mass conversion from particle counts and size detection response. The results show that the low-cost sensors measurements of air temperature, relative humidity and particle number concentration are in a good agreement with high quality sensors measurements, with a strong impact of relative humidity on performance indicators. Overall, a good quality and consistency of the data among the sensors has been achieved.

African scientific research faces formidable challenges, particularly with limited access to state-of-the-art measurement instruments. The high cost associated with these devices presents a significant barrier for regional research laboratories, impeding their ability to conduct sophisticated experiments and gather precise data. This predicament not only hampers the individual laboratories but also has broader implications for the African scientific community and the advancement of knowledge in developing nations—the financial cost barrier considerably impacts the research quality of these laboratories. Reflection on technical and economical solutions needs to be quickly found to help these countries advance their research. In civil Engineering, the thermal conductivity property is the most important measurement for characterising heat transfer in construction materials. Existing devices (i.e., conductometers) in a laboratory are expensive (approximately 30,000 euros) and unavailable for some African laboratories. The study proposes a new and affordable device to evaluate thermal conductivity in construction materials. The method involves establishing a thermal flux between a heat source ( from the Joule effect provided by steel wool where a current is circulating) and a cold source (generated by ice cube) under steady-state conditions. The development of the cylindrical prototype is based on the comparative flux-meter method outlined in the measuring protocol of the ASTM E1225 standard document. Experiments were conducted on four distinct materials (polystyrene, wood, agglomerated wood, and rigid foam). The results indicate a correct correlation between the experimental values obtained from the newly developed prototype and the reference values found in the literature. For example, concerning the experimental polystyrene study, the detailed case analysis reveals a good correlation, with a deviation of only 4%. The percent error found falls within the acceptable range indicated by the standards recommendations of the ASTM E1225 standard, i.e., within 5% acceptable error.

This study was to identify clinical cancer biomarkers for recurrent gastric cancer survivors using artificial intel-ligence. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random forest with MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive ex-Planations (SHAP) for feature importance analysis in this study. Our proposed Random forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86% and F1 of 88.2% on re-current category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI(body mass index), and gender, which significantly affect the prediction model's output, are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

Recent literature has seen a rapid expansion in the reference to front-end forensics as an indication of the untapped value of forensic science. While some of these contributions have centered on development of forensic intelligence from a single area of investigation, others call for a more fundamental change in the relationship between crime laboratories and policing, particularly relating early laboratory analysis with big datasets to provide leads to investigators. We highlight several recently implemented tactical strategies of crime laboratories that contribute to the body of forensic intelligence. Beyond the scientific gains from these tactical applications, the corresponding details on associated efficiencies, costs, time savings, and quality improvements offer insights towards patterns of success for the community of crime laboratories. Further details expand an interpretation of what constitutes success with an eye on the contributions of the crime laboratory towards public health, safety, and protection of the innocent in addition to societal gains from conviction of the guilty. The economic interpretation of the value provided by the forensic laboratory assists in the cost-benefit review of strategic and tactical decisions and supports the justification for laboratory public funding with measures of the return on investment from public support of the forensic laboratory

The study of velocimetry is important for characterizing and comprehending the effects of fluid flow, and the Particle Image Velocimetry (PIV) technique is one of the primary approaches for understanding the velocity vector field in a test section. Commercial PIV systems are expensive, with one of the main cost factors being high-speed camera equipment capable of capturing images at high frames per second (fps), rendering them impractical for many applications. This study proposes an evaluation of utilizing smartphones as image acquisition systems for PIV technique application. An experimental setup inspired by the known angular displacement of synthetic particles is proposed. A stepper motor rotates a plate containing an image of synthetic particles on its surface. The motion of the plate is captured by the smartphone camera, and the images are processed using PIVlab-MatLab® software. The use of two smartphones is assessed, with acquisition rates of either 240 fps or 960 fps and varying angular velocities. The results were satisfactory for velocities up to 0.7 m/s at an acquisition rate of 240 fps and up to 1.8 m/s at 960 fps, validating the use of smartphones as a cost-effective alternative for the PIV technique.

This work presents a new model to obtain the minimum cost design for a rectangular isolated footing, taking into account that the column is located in any part of the footing. The methodology is developed by integration to obtain the moments, bending shear and punching shear according to the American Concrete Institute ACI 318-14. This document presents the simplified and precise equations of the four moments, four bending shears and one punching shear acting on the footing. Some designs have been developed by the trial and error method to determine the footing dimensions, and later the thickness and steel area of the footing are obtained. Some authors present the minimum cost design for a rectangular isolated footing taking into account that the column is located in the center of gravity of the footing, and other authors present very complex algorithm. Numerical examples are presented to obtain the minimum cost design of rectangular isolated footings under biaxial bending, and some results are compared with those of other authors considering the same conditions. The new model presents a smaller contact area with the soil and a lower design cost than those presented by other authors.

We study the robustness of the cμ-rule for the optimal allocation of a resource consisting of one unreliable server to parallel queues with two different classes of customers. The customers in queues can be served with respect to a FCFS retrial discipline, when the customers at the head of queues repeatedly tries to occupy the server in a random time. It is proved that for the scheduling problem in the system without arrivals the cμ-rule minimizes the total average cost. For the system with arrivals it is difficult directly to prove the optimality of the same policy with explicit relations. We derived for an infinite-buffer model a static control policy that also prescribes for the certain values of system parameters the service exclusively for the class-i customers if both of queues are not empty with the aim to minimize the average cost per unit of time. It is also shown that in a finite-buffer case the cμ-rule fails.

Most of the literature on the optimization problem of transportation in supply chain networks (SCN) considered fixed costs (FC). However, in the practical applications of this problem it is important to study the effect of FC. This paper examines the impact of fixed cost increase as well as the variable cost on the optimization of a Two-Stage SCN. To do so, two mathematical models for mixed-integer nonlinear programming are developed. The first model optimizes fixed and variable costs in addition to the opening cost, whereas the second model only optimizes variable and opening costs. To evaluate the effect of considering FC on the optimization supply chain problem, four groups of instances are randomly generated, and solved using Lingo. The results of the two models are compared utilizing the average percentage deviation. In addition, sensitivity analysis is performed to determine the impact of changes in opening and variable costs on the considered optimization problem. The computational results and the sensitivity analysis show that the first model with minimized FC outperforms the second model, which does not consider the FC in minimization and FC affect the optimization.

Among all Brazilian economic sectors, the livestock sector stands out due to its large production and high export volume. However, beef production is associated to significant environmental impacts, such as deforestation and greenhouse gas (GHG) emission. The Paris Agreement was settled to avoid that global mean temperature rise up to 1.5 – 2º C by 2100. In 2020, Brazil committed in its nationally determined contribution (NDC) to reduce its GHG emission by 43% until 2030. This study aims to identify the association of beef production and beef cattle emissions, as well as assess predictive GHG emission scenarios for 2030 and value these emissions. To translate the environmental impacts of beef production into economic impacts, and thus amplify the discussion, we valued GHG emissions using the social cost of carbon (SCC). The results showed that the business as usual (BAU) GHG emission derived from beef production would range between 0.423 and 0.634 GtCO₂e in 2030, whereas the maximum emission estimated to meet the NDC should be 0.257 GtCO₂e. The SCC revealed the opportunity to reduce between US $18.8 and $42.6 billion in the cost of BAU emissions from beef production in 2030 if the NDC is met. Lastly, assessing a scenario where climate targets and beef exports are prioritized, between 2-10 kg of beef per capita would be available in the domestic market in 2030. Our results reveal the need and urgency of changes in livestock production to emit less GHG per kg of beef produced, and the avoided monetary cost of reducing emissions.

Industrial effluents contain contaminants that pose threats to the environment and human health. Bioremediation is an environmentally friendly, sustainable, and cost-effective approach to degrade or transform pollutants using microbial enzymes. Laccase is a versatile enzyme that oxidizes a wide range of substrates, such as dyes, phenolic compounds, pesticides, and polycyclic aromatic hydrocarbons (PAHs), with the consumption of molecular oxygen. Laccase can also remove heavy metals by forming complexes with organic ligands or reducing them to fewer toxic forms. However, the application of laccase in bioremediation is limited by its low production, stability, and specificity. Recombinant technology has been employed to enhance the expression, activity, and stability of laccase in various bacterial hosts. Immobilization techniques have been developed to improve the reusability and stability of laccase in different environmental conditions. This review summarizes the recent developments in the production optimization of recombinant laccase enzymes and their role in the bioremediation of industrial effluents. It also discusses the challenges of laccase-based biocatalytic systems for environmental cleanup.

Medical tests' cost-effectiveness analysis reveals a strong correlation between their accuracy and analysis results. Theoretically, we provide two lower bounds that medical tests' accuracy must exceed to be considered cost-effective. Theoretically, we provide two lower bounds that the accuracy of medical tests meeting cost-effectiveness must exceed. First, medical tests' accuracy should surpass the lower bound of matching requirements for each patient to receive the most appropriate intervention based on their test results. Second, the overall lower limit should be exceeded for the medical testing to be cost-effective for the patients as a whole. Furthermore, the conclusions from this model also provide an economic explanation for the under-diagnosis of rare diseases and the challenges faced in implementing precision medicine for minority patients. A numerical simulation example validates the conclusions of this paper.

As traditional supply chains face increasingly severe environmental issues and countries promote green development and sustainable development policy concepts, cultivating green supply chain operation models is gradually being highly valued by current governments and enterprises. Generally speaking, the production of green products incurs higher additional costs and thus their total production costs also increase. In this work, the product green level is related to the random demand. Under the green supply chain buy-back contract with the green product R&D cost sharing between the manufacturer and the retailer, both the product green level and the order quantity need to be decided to maximize the channel profit. In order to coordinate the green supply chain, the manufacturer needs to share both the risk of good salvage and the green product R&D cost with the retailer. We find that both the wholesale price and buy-back price increase in the manufacturer’s proposition of the green product R&D cost, but decrease in emission reduction efficiency coefficient or carbon trading price. In addition, the product green level, the optimal order quantity and the channel profit increase in emission reduction efficiency coefficient, but decrease in the R&D cost coefficient of the product green level. Interestingly, we find that if the carbon trading price is low, the manufacturer will set a low product green level and the product carbon emission trading is a cost for the supply chain. The increment of the carbon trading price leads to a higher cost such that the channel profit is decreased. However, if the carbon trading price is high, the manufacturer will set a high product green level and the product carbon emission trading is a revenue for the supply chain. The increment of the carbon trading price leads to a higher revenue such that the channel profit is increased.

3D printing is commonly used to create complex objects at a low cost. It has also been applied in the fabrication of metamaterials and metasurfaces, which alter the propagation path of electromagnetic waves. These structures have diverse applications, including enhancing beam direction, improving antenna gain and signal-to-noise ratio, and creating filters and reflectors. Metasurfaces are cheap to fabricate and their use is expected to boost antenna efficiency in 5G telecommunications and beyond. However, accurately characterizing their profile remains a significant challenge. This paper presents a low-cost fully automated 4-axis instrument for microwave metasurface charac-terization, overcoming limitations of manual methods and offering an efficient and accurate approach. This research represents a significant advancement in microwave metasurface characterization, enabling sophisticated techniques to advance wireless communication technolo-gies, as it is the case of the future 5G and millimeter-wave communication systems. The equipment has an approximate cost of $1550 USD and was able to characterize a metalens with a focal distance of 20 cm designed for signals at 30 GHz. It was possible to create 2D and 3D profiles of the intensity distribution focused by the metalens and extract parameters such as the gain (8.05 dB), 3dB depth of focus (11 cm) and full width at half maximum (2.17 cm). The comparison of the measurements with the diffraction calculations of the metalens showed a very good agreement between the in-tensity distributions and the parameters of the metalens.

Background Out-of-pocket costs are key expenses that many individuals incur in order to receive health services. They have been identified as a key access barrier for vulnerable populations, in particular for populations affected by neglected diseases with a chronic progression, such as Chagas disease. It is important to understand the costs of accessing healthcare services that are borne by patients with T. cruzi infection. Methodology We prepared a structured survey for patients with T. cruzi infection/Chagas disease who were all treated by the healthcare system in endemic municipalities in Colombia. The results were analyzed according to three categories: 1. the socioeconomic profiling of the patients; 2. the costs of and time spent on transportation; and 3. the opportunity costs (money that was not earned) related to treatment at the local primary care hospital or at the high-complexity reference hospital. Main findings Ninety-one patients answered the survey voluntarily. The data revealed that, when treated at the specialized reference hospital, patients spent 5.5 times more on food and accommodation, transportation costs were five times higher, and the loss of earnings was three times higher than when they were treated at the local primary care hospital. Moreover, the amount of time spent on transportation was 4 times higher at the reference hospital. Conclusions Providing comprehensive healthcare services for Chagas management at local primary healthcare hospitals would allow the most vulnerable patients to save on expenses related to medical and non-medical costs (out-of-pocket costs), in turn leading to higher adhesion to treatment thus benefiting the health system as a whole. These findings are in alignment with the WHO’s World Health Assembly 2010 Resolution on the importance of treating Chagas at local primary care hospitals, thereby saving patients time and money, allowing for timely care, and promoting access to healthcare.

BACKGROUND: The National Lung Screening Trial (ILST) and the NELSON study showed that lung cancer-specific mortality can be reduced by 20-24% using low-dose computed tomography (LDCT) screening in high-risk populations, due to an increase in early-stage diagnoses. RESEARCH QUESTION: How much lung cancer-related direct costs may be reduced using a LDCT screening programme based on the ILST protocol in a public healthcare system?STUDY DESIGN AND METHODS: Cost analysis of lung cancer screening (LCS) vs. usual care in the framework of the retail price of the Catalan public healthcare system. The LCS group included costs of screening (ILST protocol), treatment cost according to weighted average distribution of TNM staging in the NLST and NELSON trials, lung cancer detection rate (CDR) and smoking cessation intervention. The usual care group included treatment costs based on distribution of TNM staging registered in the Spanish index hospital. RESULTS: In the usual care group, treatment costs were €91,959. In the 5-year duration of the LCS programme, the average expected costs per subject were €1,342 (range €1,054-1,832 depending on malignancy in detected nodules) for screening and €32,431 for treatment, with an expected reduction of €952 based on an average CDR of 1.6%. The decrease in cost resulting from stage shift offsets 70.6% of the costs of the screening programme. INTERPRETATION: Baseline 5-year LCS costs are low according to the ILST protocol. In the Catalan public healthcare system, the expense reduction from the stage shift due to the LCS programme compensates a substantial part of its costs.

As China put forward its “carbon emissions peak and carbon neutrality” goals, how to achieve carbon reduction had become a key for China’s goal. The manufacturing industry is an important source of carbon dioxide emissions. For a manufacturing country like China, adjustments in various aspects of the industry would have a huge impact on carbon emissions. As an important reform of contemporary production mode, the process of production automation in China will inevitably affect China's carbon emissions. Therefore, the analysis of the impact of production automation on carbon dioxide emissions was an important basis for judging the future carbon reduction in China. Refer to the traditional study of carbon Kuznets curve, this paper analyzed the impact of average wage on production automation and the role of production automation in the carbon Kuznets curve(CKC). This paper proposed that production automation plays a mediating role in the process of carbon emissions, and gives a verification model of the mediating role. By analyzing the relationship between average wage and production automation process, the U-shaped curve relationship between them was verified. By examining the relationship between carbon dioxide emission data and production automation industry in China, we verified that production automation plays a partial mediating role in the change of carbon Kuznets curve. Combined with the analysis of the two parts, this paper believed that with the continuous development of China's intelligent manufacturing industry, China's carbon reduction prospects were more optimistic, and there was a good industrial foundation to achieve the “carbon peaking and carbon neutrality” goals. Finally, this paper proposes policy suggestions as increase research investment in production automation, help promote the application of production automation, encourage the research and application development of low-carbon technology, especially encourage modular design, so as to give full play to the role of production automation in the process of carbon neutrality in China.

Primary and secondary cardiovascular prevention is less effective than expected due to the concern about polymedication by professionals and the lack of patient adherence to medications prescribed in the medium and long term. Polypills have been presented as a possible solution. A comprehensive bibliographic review is presented about polypills as mechanisms for facilitating adherence and a proposed guide for the use of polypills for the prevention of cardiovascular risk. 41 articles were included, showing options for the polypill as a method of primary and secondary cardiovascular prevention.The polypill increases therapeutic adherence in the medium and long term, also increasing the therapeutic results compared to the administration of the various drugs separately. Based on the evidence, a flow diagram is proposed for the prescription of a polypill.Polypills increase the effectiveness and adherence of patients to primary and secondary cardiovascular prevention programs, without increasing the cost of the intervention. The use of a polypill in cardiovascular prevention can be effective as a prescription tool.

River valley bottoms have hydrological, geomorphological, and ecological importance and are buffers for protecting the river from upland nutrient loading coming from agriculture and other sources. They are relatively flat, low-lying areas of the terrain that are adjacent to the river and bound by increasing slopes at the transition to the uplands. These areas have under natural conditions, a groundwater table close to the soil surface. The objective of this paper is to present a stepwise GIS approach for the delineation of river valley bottom within drainage basins and use it to perform a national delineation. We developed a tool that applies a concept called cost distance accumulation with spatial data inputs consisting a river network and slope derived from a digital elevation model. We then used wetlands adjacent to rivers as a guide finding the river valley bottom boundary from the cost distance accumulation. We present results from our tool for the whole country of Denmark carrying out a validation within three selected areas. The results reveal that the tool visually performs well and delineates both confined and unconfined river valleys within the same drainage basin. We use the most common forms of wetlands (meadow and marsh) in Denmark's river valleys known as Groundwater Dependent Ecosystems (GDE) to validate our river valley bottom delineated areas. Our delineation picks about half to two-thirds of these GDE. However, we expected this since farmers have reclaimed Denmark's low-lying areas during the last 200 years before the first map of GDE was created. Our tool can be used as a management tool, since it can delineate an area that has been the focus of management actions to protect waterways from upland nutrient pollution.

The residential sector in the United States is in need of comprehensive policy-making reforms that concurrently address housing affordability and environmental sustainability. This study investigates the feasibility of state-wide zero-energy affordable housing by analyzing historical data on climate, energy use, and solar system costs in the Commonwealth of Virginia. The hypothesis examined is that the net present cost of implementation of rooftop residential solar systems to achieve zero-energy Low-Income Housing Tax Credit (LIHTC) buildings is lower than the discounted present cost of energy of otherwise identical conventional buildings that run without renewable energy generation systems. The authors propose a generalizable framework for analyzing the feasibility of achieving region- or state-wide zero-energy LIHTC developments. To validate the framework, the authors employ a longitudinal sample of monthly energy use data from 2013-2016 obtained from 310 residential units of 15 LIHTC developments across the state. Based on statistical regression analysis, energy simulation, and simulation-based risk analysis, the authors find that the net present value of zero-energy LIHTC investments can be positive with a low risk. The investment value varies often depending on the zero-energy building definition, weather characteristics, retail price of electricity, and incentive rate. This study can help housing policymakers and industry professionals analyze and benchmark the feasibility of innovative zero-energy housing policies and projects.

Microsystems are key enabling technologies, with applications found in almost every industrial field, including in-vitro diagnostic, energy harvesting, automotive, telecommunication, drug screening, etc. Microsystems, such as microsensors and actuators, are typically made up of components below 1000 microns in size that can be manufactured at low-unit cost through mass-production. Yet, the development of microsystems for commercial or educational purposes, has typically been limited to upper income countries due to the initial investment costs associated with the microfabrication equipment and processes. However, recent technological advances have enabled the development of low-cost microfabrication tools. In this paper, we describe a range of low-cost approaches and equipment (below £1000), developed or adapted and implemented in our laboratories. We describe processes including photolithography, micromilling, 3D printing, xurography and screen-printing used for the microfabrication of structural and functional materials. The processes that can be used to shape a range of materials with sub-millimetre feature sizes are demonstrated here in the context of Lab-on-Chips, but they can be adapted for other applications. We anticipate that this paper, which will enable researchers to build a low-cost microfabrication toolbox in a wide range of settings, will spark a new interest in microsystems.

Face milling is a well known commercial process highly used in heavy industries that consumes high amount of power. Besides power issue, modern manufacturing industries are aiming for per part cost reduction keeping the product quality unimpaired. Unexpectedly if the part is rejected in any stage of manufacturing, the cost of manufacturing dramatically increases. Major cause of part rejection is excessive tool wear that imparts poor surface profile or catastrophic tool failure that causes adherence of broken tool debris onto machined surface. Furthermore, the tool wear is associated with sliding distance (frictional distance) and the tool life quantifies the cost of tools. As such, from the perspective of manufacturing industries it is imperative to optimize the surface quality parameter, cost of part, power consumption, and material removal – this is exactly what is accomplished here. By this work, it is possible to conserve power consumption, produce parts with lower cost, manufacture with uncompromising surface quality and enhanced material removal rate. Moreover, as intermediate factors of interest, the influences of sliding distance, tool life and tool flank wear on the overall machining performance are evaluated. The multi-objective optimization by Grey Relational Analysis (GRA) revealed that for improved product performance and fast manufacturing (case 1) optimum results are: feed per tooth fz = 0.25 mm/tooth, cutting speed vc = 392.6 m/min and cutting length l = 0.5 mm; for resource conservation (case 2) the optimum results are: feed per tooth fz = 0.125 mm/tooth, cutting speed vc = 392.6 m/min, cutting length l = 0.5 mm.

Information regarding the cost of a construction project is available to the investor and project participants in order to determine the subsequent success of a project, given that the information they collect has an impact on the decisions they make. Cost calculations, especially in the initial phase of a project, often generate large errors. This paper presents the new approach based on a combination of the Case Based Reasoning method (CBR) with the originally selected criteria for the description of a construction project (as a result of Pearson correlation coefficient and Spearman's rank correlation coefficient) and Building Information Modeling (BIM) technology. The CBR method fulfils expectations for a simple and fast system supporting the cost estimation process. It does not require any specialist knowledge, so it will be comprehensible to cost estimation practitioners. The BIM-based model gives the opportunity for the calculation of quantity take-offs and enables the use of the information contained in the BIM model in the cost estimation process. In order to prepare the model an appropriate relational database had to be developed. With extensive research, a database of 173 construction projects, including the construction of a sports field, was obtained. There were 14 variables defined originally by authors; however, only 10 (as a result of the correlation analysis) were used for the calculation. Data related to the project were collected in the BIM model. Results estimating the project’s unit price, using the CBR method, were presented and discussed. The Mean Absolute Estimate Error was used to evaluate the model.

In this study, the probabilistic exergoeconomic analysis was performed for four industrial gas turbine (GT) units comprising of two (GT16 and GT19) units of 100MW GE engine and two (GT8 and GT12) units of 25MW Hitachi engine at Transcorp Power Limited, Ughelli. These four industrial GT engine units were modelled and simulated using natural gas as fuel. The design point (DP) simulation results of the modelled GT engines were validated with the available DP thermodynamic data from original equipment manufacturer (OEM). This was done before the off-design point (ODP) simulation was carried out which represents the plant operations. The results obtained from exergy analysis at full load operation show that the turbine has the highest exergy efficiency followed by compressor and combustion having the least. For turbines these were 96.13% for GT8 unit, 98.02% for GT12 unit, 96.26% for GT16 unit, and 96.30% for GT19 unit. Moreover, the combustion chamber has the highest exergy destruction efficiency of 55.16% GT8 unit, 56.58% GT12 unit, 43.90% GT16 unit, and 43.30% GT19 unit respectively. The exergy analysis results obtained from the four units show that the combustion chamber (CC) is the most significant exergy destruction with lowest exergy efficiency and highest exergy destruction efficiency of plant components. The exergoeconomic analysis results from four units showed combustion chamber energy destruction cost of 531.08 $/h GT8 unit, 584.53 $/h GT12 unit, 2351.81$/h GT16, and 2315.93$/h GT19 unit. The probabilistic results analysis based on the input parameters distributions evaluated and discussed.

Metagenomic analysis of soil bacterial communities based on 16S rRNA reflects typical a community composition containing a low number of high abundance types and a very high number of low abundance types. Here, the formation of characteristic rank order functions of bacterial abundance is investigated by modelling the dynamics of soil bacterial communities assuming a succession of different bacterial populations that grow rapidly and decay more slowly. It was found that the characteristic shape of typical rank order functions is well reflected by the simulations. In addition, the model allowed to investigating strong disturbances of the soil, which could be expected in case of strongly changing local environmental conditions in the soil, e.g. by translocation and covering of soil material. Such events could lead to the formation of shoulders in the rank order functions. Abundance rank orders observed in case of some archaeological soil samples do indeed show such a shoulder and could be well interpreted by simulated rank order functions. As a result, it can be concluded that the investigations support the hypothesis, that abundance rank orders contain information about the temporal order of developing bacterial types in changing communities and thus store information about local environmental conditions in the past, including ancient human impacts on soil.

The transition to renewable energy sources is critical for sustainable development, particularly in rural regions with limited access to electricity. Solar-powered microgrids offer a promising solution for rural electrification by providing reliable, clean energy that can enhance economic opportunities and improve quality of life. This paper presents a techno-economic analysis of solar-powered microgrids for rural areas, evaluating their feasibility, costs, and benefits. The analysis encompasses technological aspects, such as solar panel efficiency, battery storage, and grid management, alongside economic factors including initial investment, maintenance costs, and potential returns. Additionally, the study assesses the social impact of solar-powered microgrids, exploring their effects on local communities, including improvements in education, health, and economic activities. The findings indicate that solar microgrids can be a viable and impactful solution for rural electrification, with significant long-term benefits for both economic development and social well-being.

Lifecycle assessment (LCA) quantified changes in environmental impact categories (global warming, eutrophication, etc.) from 2021 to 2030 due to genetic trends in (re)production traits in pig lines of breeding company Genus-PIC. The 2030 levels were projected with se-lection index theory based on weightings of traits in the breeding goals and genetic covari-ances among them. Projected improvement was 0.9% annually for most impact categories. Another LCA compared impacts of 2021 North American pig production based on PIC ge-netics versus the industry average. Software openLCA converted material and energy flows to impact categories of frameworks ReCiPe-2016, PEF-3.1 and IPCC-2021. Flows came from data recorded by customers (1.1/4.7 million sows/finishing pigs) and by subscribers to a third-party data-aggregator (1.3/9.1 million). PIC genetics have a 7-8% better impact than industry average for 13/18 categories of ReCiPe-2016, 19/25 of PEF-3.1, and all categories of IPCC-2001. Pig breeding delivers positive environmental outcomes as correlated respons-es to selection for profitability-oriented breeding goals. This trend is additive; technology development will increase it. Different investment levels in breeding population structure and technology, and different operational efficiencies of breeding companies, cause substan-tial differences in the environmental impact of pig production.

Users with Autism Spectrum Disorder may find human-computer interaction (HCI) challenging due to a number of symptoms experienced, one of which is difficulty coping with change. Through capturing, comparing and statistically analysing the reactions of autistic and neurotypical users to seven individual design changes, it has been possible to identify the changes that cause significant difficulty in autistic users. These difficulty points were then used to form heuristics that can followed by HCI practitioners in the industry to reduce the negative impact of software interface design change on autistic users, hence making software updates more accessible.

Iron tailings are solid waste generated after the mining of iron mines, which have caused serious damage to the surrounding ecology and environment and have attracted widespread attention. By analyzing the formation causes, main components, and environmental effect mechanisms of iron tailings, the article systematically elaborates on the degree and mechanism of the harm of iron tailings to water bodies, atmosphere, soil, and ecosystems, and evaluates its impact on human health and sustainable development of society. On this basis, specific prevention and control measures have been proposed to reduce iron tailings emissions, realize resource recycling, and restore ecosystems. Research shows that iron tailings containing heavy metals can widely pollute the environment through dissolution and migration, and have significant biological toxicity effects. The research results can provide a theoretical reference for decision-making departments to formulate scientific and reasonable iron tailings disposal and ecological protection policies. It is recommended to strengthen specific research on the infiltration of toxic and harmful components in tailings in the future, and develop efficient and stable solidification technology, and vegetation-microbial joint restoration models to further reduce the ecological and environmental risks of iron tailings.

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a systematic literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID’s epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management.; Conclusion: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Ad-dressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition.

Cultural routes are a composite set of heritage, referring to any ancient routes of human communication. As one of the key products of cultural tourism, they providing visitors with a rich cultural experience across regions. We systematically review reports and studies related to the tourism development of 38 cultural routes cases around the world, with a special focus on their distribution, typology, planning patterns and tools for cultural tourism. We summarized eight tools, there are some differences in how often these eight tools are used by the different types of routes and different planning patterns for routes tourism. The study also made an evaluation system based on the conservation principles of cultural routes to find out how different tools of tourism affect the conservation and development of the historical region. It was found that although many efforts have been made by tourism decision-makers to protect and develop cultural routes there are still many problems and challenges in the process of tourism development along cultural routes. We close the paper by making a few recommendations for decision makers and researchers concerning future routes’ tourism planning and study.

The article presents a methodology for modeling the impact of factors of both on-farm activity and environmental factors on the resulting indicators of an international company. The dataset includes the company's profit, revenue, valuation, share price, and market share from 2012 through 2022. This empirical period is optimal for such a type of modeling. Modeling the impact of carbon emissions factors on the resulting indicators is considered based on complex systems theory. Endogenous model variables include indicators of the development of the international company. Predefined model variables reflect the influence of both the external environment and internal factors on the development indicators of an international company. An approach of picture fuzzy rough sets based on time series of endogenous and exogenous variables can provide an opportunity to analyze and consider the consequences of feedback changes in the systems of which they are a part. Based on the results of the analysis of the model construction, it is concluded that picture fuzzy rough sets can be an excellent way to model interdependent social processes.

Bulk composition, mineralogy and microchemistry of various fractions of the filling of the Crater No. 4 at Emmerting were investigated. Here we present mainly the fine fractions, which, in contrast to pebbles larger than ca. 4 cm, are relatively poor in material affected by melting. A 0.1 mm long meteorite fragment without ablation features was found, and remelted fragments of the same body have been identified. The projectile was dominated by enstatite, also containing forsterite, basic plagioclase, Ni-rich pyrrhotite and troilite, kamacite, silica, and probably merrillite. The molten fragments contain porous Mg-rich glass (indicating temperature > 1500 °C), minor Fe oxides, and occasionally uncommon Ni-rich minerals. The bulk composition and electron microprobe show that the amount of meteoritic material is low (<< 1 %), and it is not unequivocally manifested even in platinum-group elements abundances and osmium isotope ratios (the latter, however, were only measured in two samples). This can be explained by dilution of the filling by particles brought after the crater formation, and by probably achondritic composition of the projectile. Relatively large hollow spheroid Fe oxide particles were observed in thin sections from the magnetic fraction. A Mn oxide hollow spherule has also been found. In magnetically separated filling from the nearby Crater No. 5, bulk chemical composition points to contamination with several metals and metalloids probably due to influence of recent alluvial sediments. Therefore, the extent of meteoritic contamination in this crater may be even smaller.

The COVID-19 pandemic necessitated a profound shift to online education, impacting students across various educational levels. This research, drawing from a comprehensive survey of 1,000,000 students, delves into the surge in demand for online education during the pandemic and its potential enduring implications. The study scrutinizes factors steering this transition, the perceived effectiveness of online education, challenges encountered by students, and their anticipated preferences for the future. Results unveil nuanced perspectives among K-12, undergraduate, and postgraduate students, with safety, flexibility, and accessibility emerging as pivotal influencers. The findings offer valuable insights into challenges faced and future preferences, enlightening educational stakeholders about the dynamic needs of students and contributing to the ongoing evolution of the post-pandemic educational landscape.

Myocastor coypus is a pest animal present in Africa, Europe, North America, and Asia that causes agricultural and ecological damages. Moreover, it has to be considered as a potential risk for public health. Forty-four Nutrias from the “Parco Naturale La Mandria” (Piedmont region, Northwest Italy) have been analysed. A complete necropsy and a whole histological evaluation of liver, kidney and lung have been carried out on all the animals. Moreover, the positivity to Hepatitis E Virus (HEV), Encephalomyocarditis virus (EMCV), Francisella spp., Toxoplasma gondii and Neospora caninum have been investigated. None of the animal resulted positive for HEV, EMCV, Francisella spp. or Neospora caninum. Two animals tested positive for Toxoplasma gondii. A high presence of histological lesions has been identified in different organs, suggesting that lesions could be induced by different pathogens. As previously reported, Nutria can act as a host for several pathogens, including important agents for human and animal health, and surveillance is necessary, to fully understand the biological role and the importance of coypu as a disease reservoir in our country.

Obesity, characterized by the excessive accumulation of body fat, contributes to a multitude of physiological dysfunctions. This paper explores the complex relationship between obesity and various risk factors and complications, shedding light on critical health implications. Obesity triggers alterations in insulin, leptin, adiponectin, cytokines, and insulin-like growth factors, fostering conditions conducive to cancer initiation. Aberrations in nutrient-dependent intracellular signaling pathways, driven by the excess nutrition characteristic of obesity, contribute to the neoplastic transformation of cells. The Body Mass Index (BMI) correlates directly with adiposity, underlining its significance in cancer risk. Furthermore, insulin and insulin-like growth factors, notably IGF-2, play pivotal roles in this relationship. The expression of IR-A receptors is elevated in cancer. Obesity and cardiovascular diseases share a strong association. Obesity elevates the risk of fatal events like myocardial infarction. High cholesterol levels contribute to atherosclerosis in the aorta and coronary arteries. The severity of coronary artery disease is influenced by plaque formation characterized by calcium deposits. Obesity is also linked to hypertension and increased ventricular mass, exacerbating cardiovascular risks. Hypercholesterolemia and hypertension correlate with a high Body Mass Index (BMI). Obesity is intricately connected to insulin resistance, particularly evident in childhood obesity. It entails a gradual decline in insulin sensitivity, leading to elevated insulin levels in the bloodstream. Insulin resistance is a central factor in the development of Type 2 Diabetes Mellitus. Obesity also results in elevated triglyceride levels and reduced high-density lipoproteins, contributing to atherogenic dyslipidemia and a heightened risk of atherosclerosis. Additionally, obesity is associated with various other disorders, including epilepsy, depression, and neuropsychological problems. Beyond its physiological impact, obesity is associated with significant psychosocial challenges. Studies indicate that individuals with obesity face a higher risk of depressive symptoms, often related to overeating and unhealthy dietary patterns. The social withdrawal tendencies of obese individuals exacerbate these symptoms, with higher rates of depression observed in this group. OSA, a sleep disorder characterized by intermittent breathing cessation during sleep, is strongly correlated with obesity. Approximately 58% of obese individuals experience OSA, with higher Body Mass Index (BMI) associated with an increased risk. Weight reduction has been found to mitigate the severity of OSA and related arrhythmias. Continuous positive airway pressure (CPAP) therapy demonstrates effectiveness in reducing visceral fat accumulation and leptin levels. This comprehensive review underscores the intricate web of health implications associated with obesity, emphasizing the critical need for preventive measures and intervention strategies to address the multifaceted challenges posed by this global health concern.

This paper investigates the impact of sediment deposition and inflow conditions on horizontal impact pressure and frequency analysis of bridge deck vibrations during flooding. Flooding-induced pressure and vibrations contribute to bridge collapse, and sediment deposition influences water flow and impact pressure. The study explores the relationship between sediment deposition height and impact pressure, revealing a significant increase as sediment approaches 50% of bridge deck clearance. Sediment amplifies impact pressure response to flow velocity changes. The dimensionless sediment deposition height has a greater influence on impact pressure compared to the inflow Froude number. Two distinct frequencies, dominant and secondary, are identified for impact pressure and water level fluctuations. Dominant frequencies positively correlate with sediment deposition height and Froude number, indicating an increasing trend. Secondary frequencies remain stable (0.31-0.58 Hz). These findings enhance understanding of flow dynamics and bridge-flow interaction in sediment-deposited channels, providing theoretical support for evaluating and managing disasters related to bridges in such environments. Overall, this research contributes to the field of bridge engineering and supports improved design and maintenance practices for bridges exposed to sediment-deposited channels.

Covid-19 has had a significant impact on the lives of populations across the world. Since the first reported case of the coronavirus in Wuhan, China, the world faced a situation of dealing with a novel virus. While the physical health effects of the coronavirus was the center of focus for much of the pandemic, Covid-19 was accompanied with significant social and psychological consequences on the world populations. In this review, we aim to assess how the coronavirus pandemic has affected the African continent at large, highlighting the socio-psychological consequences. Through citing some examples of a few countries in Sub-Saharan Africa, the review will detail the experiences of the populations within this region which remain plagued with economic and health vulnerabilities that were further exposed by the pandemic.

The opportunities and potential of Artificial Intelligence (AI) in Environmental Assessment (EA) are often mentioned. However, do we in the EA field understand the implications of what is happening in other biological sciences, and are we preparing for the changes that are coming? This interdisciplinary letter focuses on AI-driven developments in biodiversity data and analysis as a starting point for stimulating discussion about what AI means in practice for the field of EA. We highlight implications for training, transformation of practice and decision making as first steps in a research agenda.

Single parenting is a social phenomenon that has always been in existence and is as old as mankind, and today the number of single-parent families has been rampantly increasing. As a result, the researcher conducted a study in the Gambella region of Ethiopia to investigate the economic and educational implications of single parenting on female adolescent students. The study employed a qualitative research approach with a case study research design. The researchers used the purposive sampling technique to select the research area and research participants for in-depth interviews and focus group discussions, and eleven interviewees, seventeen participants in focus group discussions within two groups, and seven key informants participated. Interviews were audio-recorded, transcribed, translated, and thematically analyzed. Interviews with research participants revealed that adolescent girl students from single-parent homes experience financial difficulties. The study also explored that students with single parents are more likely to be absent from school, to come late to school, to score low marks, and to drop out of school. Therefore, having an understanding of the benefits of having intact parents for the well-being of adolescents and raising children together should be advocated.

The effect of coal hydrophilic particles in water-glycerol drops on the maximum diameter of spreading along a hydrophobic solid surface is experimentally studied by analyzing the velocity of internal flows by Particle Image Velocimetry. The grinding fineness of coal particles was 45-80 μm and 120-140 μm, their concentration was 0.06 wt.% and 1 wt.%. The impact of particle-laden drops on a solid surface occurred at Weber numbers (We) from 30 to 120. It is revealed the interrelated influence of We and the concentration of coal particles on changes in the maximum absolute velocity of internal flows in a drop within the kinetic and spreading phases of the drop-wall impact. A physical model is formulated for internal convective flows in the longitudinal section of a drop parallel to the plane of the solid wall. The kinetic energy of translational motion of coal particles in a spreading drop compensates for the energy expended by the drop on sliding friction along the wall. At We=120, the inertia-driven spreading of the particle-laden drop is mainly determined by the dynamics of the deformable Taylor rim. An increase in We contributes to more noticeable differences in the convection velocities in spreading drops. When the drop spreading diameter rises at the maximum velocity of internal flows, a growth of the maximum spreading diameter occurs. The presence of coal particles causes a general tendency to reduce the drop spreading.

Mass mortality events and anthropogenic impacts were increasingly documented affecting Paramuricea clavata (Risso, 1826) during the last decades. These impacts enhance the settling of epibiontic organisms on the injured colonies. The epibiosis was studied by photographic sampling carried out on the granitic outcrops of the Tavolara Channel within the Tavolara-Punta Coda Cavallo Marine Protected Area (NE Sardinia) between 2017-2023 at 35-55 m. The number of colonies and percent surface involved in epibiosis, the specific richness of the epibiontic community and the temporal evolution of the phenomenon were investigated. Almost all the investigated gorgonians (93%) showed parts involved in epibiosis, with a high percentage of covering (one-third of the surface). Out of the 37 epibiontic species recorded, the most recurrent described an ecological succession dominated by hydrozoans, sponges, bryozoans, serpulids and the parasitic soft coral Alcyomiun coralloides. Nevertheless, single colonies studied through time revealed the unpredictability of the colonization process. The peculiar habitat of a high naturalistic value of the granitic outcrops hosting the P. clavata forests demonstrates a widespread suffering condition, supported both by environmental and anthropogenic sources of stress. Such considerations make it necessary to review the current zonation of the area, where the actual vulnerability and usability evaluations are based on obsolete information.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

The article's purpose is a citation analysis of the impact of scientific publications by authors of different gender compositions. The PageRank method was chosen to calculate the citation impact of scientific publications, and the citation has also estimated the impact of scientific publications based on the number of citations. The normalized citation impact of scientific publications is calculated according to nine subsets of scientific publications that correspond to patterns of different gender compositions of authors. Also, these estimates were calculated for each country with which the authors of the publications are affiliated. The Citation database was chosen for the scientometric analysis Network Dataset ( ver . 13). The dataset includes more than 5 million scientific publications and 48 million citations. The main subject areas of scientific publications in this database are computer science, artificial intelligence, mathematics, engineering, etc. The results indicate that articles with a predominantly male composition are cited more than articles with a mixed or female composition of authors in this direction. Analysis of advantages in dynamics indicates that in the last decade for developed countries, there has been a decrease in the connection between the citation impact of scientific publications and the gender composition of their authors. However, the obtained results still confirm the presence of gender inequality in science, which may be related to socioeconomic and cultural characteristics, natural homophily, and other factors that contribute to the appearance of gender gaps. An essential consequence of overcoming these gaps, including in science, is ensuring the rights of people in all their diversity.

This experimental study investigates the effect of scarf geometry in restoring the impact response of scarf patched 3 mm thick glass-fibre reinforced polymer (GFRP) matrix composite laminates. Traditional circular along with rounded rectangular scarf patch configurations considered as repair patches. Experimental measurements revealed that the temporal variations of force and energy response of the pristine specimen are close to that of circular repaired specimens. The predominant failure modes were witnessed only in repair patch which include the matrix cracking, fibre fracture, delamination and no discontinuity in adhesive interface was witnessed. When compared with the pristine samples, the top ply damage size of the of the circular repaired specimens is larger by 9.91 %, while that of the rounded rectangular repaired specimens is larger by 434.23 %. The results show that circular scarf repair is more suitable choice of repair approach under the condition of 37J low-velocity impact event even though the global force-time response is similar.

Affective prosody is an indispensable cognitive cue that moderates social activities, and has become a prevailing research topic in psychology-related disciplines. The present study conducts the first bibliometrics-based visualization analysis concerning affective prosody to evaluate the influential cases, including countries/regions, institutions, publication venues, academic articles, and disciplinary contributions, and the diachronic changes of publication trends and research hotspots. With the combination of statistical results and a qualitative literature inspection, limitations of extant studies and promising research directions were also proposed. The present study extracted the bibliographic data of 1,624 articles retrieved from the Web of Science Core Collection, which were published over the past 25 years (1997-2021). Statistical results revealed four leading powers (the U.S., Germany, England, and Canada) and four emerging fronts (China, France, Netherlands, and Switzerland), and identified three primary research themes in this field, including clinical implication, measurable index, and modality-specific issues. Literature inspection demonstrated current limitations in individual characteristics control and experiment-related influential factors, and proposed two prosperous research directions. Findings of the present study could facilitate academic retrieval of affective prosody research, help concerned researchers identify thematic hotspots and seek appropriate collaboration, and provide convenience for research policy and management in this field.

The COVID-19 disease has infected many countries with generalised impacts on the different income categories. To test this hypothesis, we carried out a survey among households (n = 412) representing different income groups in Nigeria. We used validated food insecurity experience and socio-psychologic tools. We analysed the data obtained using descriptive and inferential statistics. The earning capacities of the respondents range from US$145/month for the low-income earners to US$1945/month for high-income earners. A total of 173 households (42%) ran out of food during the COVID-19 pandemic. All categories of households have experienced increasing dependency from the general public and perception of increasing insecurity, with the high-income earners having the greatest shift. In addition, increasing levels of anger and irritations have been experienced with all categories. Of the socio-demographic variables, only gender (p = 0.012), level of education of household head (p = 0.000), work hours per day (p = 0.006), and family income based on society class (p = 0.000) were significantly associated with food security and hunger due to the COVID-19 pandemic. Household heads with medium (OR: 4.36, 95% CI: 2.64 – 7.21, p < 0.001) and high (OR: 30.27, 95% CI: 3.99 – 229.90, p < 0.001) family income based on society class were more likely to have satisfactory experience on food security and hunger than respondents with low family income. Irrespective of the social class of the respondents, some respondents had negative experiences such as movement/change of location within the same city (17.68%), begin a new relationship (14.43%), recent change of job/loss of job (11.55%), movement to another city (10.81%), and separation from spouse or long-term relationship (10.07%). However, 231 (60.16%) reported satisfaction with their jobs despite the pandemic. Psychological stress due to impact of COVID-19 was observed to be more in the low income earning group than others. It is recommended that socio-economic groups should be mapped and support systems should target each group as per the needed support in terms of health, social, economic, and mental wellness; the government should show political commitments and transparency in food security and counselling supports. National authorities should prioritize empirical-based interventions on resources allocation during crises.

The objectives of the research are to investigate the characteristics of the board of directors on the financial performance of the enterprise. Using a sample data from 52 construction and real estate enterprises listed on Vietnam stock exchange in the period 2006-2020. Using typical regression methods such as pooled OLS, FEM, REM and assessing the defects of the research model, the FGLS method is selected. At the same time, due to the existence of endogenous phenomena and the nature of interdependence among enterprises in Vietnam, research using the instrumental variables two-step generalized method of moments (IV-GMM) in order to correct for cross-sectional dependence, autocorrelation, endogeneity, and heteroskedasticity in the analysis. Research results suggest that board size, female board members, meeting frequency, and board members' education have a positive influence on financial performance. Moreover, the independence of the Board of Directors increases, the business efficiency decreases. The research also found a positive relationship of tangible fixed assets, and a negative relationship between capital structure choice, firm size and corporate financial performance.

Preprints are regularly cited in peer reviewed journal articles, books and conference paper. Are preprint citations somehow less important than citations to peer reviewed research papers? This study investigates citation patterns between 2017 and 2020 for preprints published in three preprint servers, one specializing in biology (bioRxiv), one in chemistry (ChemRxiv), and another hosting preprints in all disciplines (Research Square). As evaluation of scholarship continues to largely rely on citation-based metrics, this analysis and its outcomes will be useful to inform new research-based education in today’s scholarly communication.

With the development of Internet technology, teachers are constantly seeking innovative teaching methods to match the potential of enhanced technology. Although many studies have been performed before , they aren’t enough in this field. The purpose of this paper is to explore innovative teaching designs and examine the impact of Internet-assisted English teaching of reading based on constructivism. The case is carried out in NO.9 middle school of Bengbu, a underdeveloped area of China, most of students aren’t interested in learning English .We compared Internet-assisted with traditional textbook literature methods to improve the reading proficiency of students, using a questionnaire survey,pre-test and post-tests comparisons. The result showed Internet-assisted English reading teaching is better than textbook. It can arouse students' interest and motivation,reading proficiency and exam result of students have been improved significantly, created a positive learning situation.

The EigenAnt algorithm has been proposed to find the shortest path between two nodes with a proof of convergence. Two novel features are noticeable in EigenAnt compared to the conventional ant colony optimization algorithms. Pheromone evaporation in the EigenAnt algorithm is done locally for the selected path and it does not use heuristic information in its selection phase. On the other hand, a simple version of ant colony optimization that also does not use heuristic information has been used for analyzing convergence, considering parameter impact analysis, in the problem of finding the shortest path for 1-node binary chain problems. In this paper, we propose to improve the EigenAnt algorithm by adding additional parameters in such a way as to be able to take advantage of the analysis developed for the simple ant colony optimization algorithm. We demonstrate through our analysis that since the Improved EigenAnt algorithm has one parameter more than ant colony optimization algorithms, tuning of convergence speed is decoupled from tuning of convergence features in the algorithm. Thus, IEigenAnt, which can be interpreted as having two uncorrelated intensification and diversification components, makes it possible to achieve a balance between intensification and diversification. In order to illustrate the advantages of this decoupling, we present experimental results for the routing network problem.

Structural vibration induced by dynamic load or natural vibration is a nonnegligible factor in failure analysis. Based on vibrating boundary condition, impact resistance of shape memory alloy reinforced composites is investigated. In this investigation, modified Hashin’s failure criterion, Brinson’s model and visco-hyperelastic model are implemented into the numerical model to charactering the mechanical behavior of glass fiber/epoxy resin laminates, SMAs and interphase, respectively. First, fixed boundary condition is maintained in simulation to verify the accuracy of material parameters and procedures by comparing with experimental data. Then, a series of vibrating boundaries with different frequencies and amplitudes are applied during the simulation process to reveals the effect on impact resistances. The statistics of absorbed energy and contact force indicate that impact resistance of the composite under high frequency and large amplitude is lower than that under low frequency and small amplitude, and summarized by a mathematical expression.

This paper focused on impact localization of composite structures, which possess more complexity in the guided wave propagation because of the anisotropic behavior of composite materials. In this work, a composite plate was manufactured by using a compression molding process with proper pressure and temperature cycle. Eight layers of woven composite prepreg were used to manufacture the composite plate. A structural health monitoring (SHM) technique is implemented with piezoelectric wafer active sensors (PWAS) to detect and localize the impact on the plate. There are two types of impact event are considered in this paper (a) low energy impact event (b) high energy impact event. Two clusters of sensors recorded the guided acoustic waves generated from the impact. The acoustic signals are then analyzed using a wavelet transform based time-frequency analysis. The proposed SHM technique successfully detect and localize the impact event on the plate. The experimentally measured impact locations are compared with the actual impact locations. An immersion ultrasonic scanning method was used to visualize the composite plate before and after the impact event. A high frequency 10 MHz 1-inch focused transducer was used to scan the plate in the immersion tank. Scanning results show that there is no visible manufacturing damage in the composite plate. However, clear impact damage was observed after the high-energy impact event.

Outer particles collision with certain dynamic object is not a pure impact wear behavior; it is typically accompanied by sliding wear phenomena. This study aimed investigating the impact-sliding wear performance of three different TC17 titanium alloys. One was untreated, and the other two were subjected to laser shock peening (LSP) by 5 and 7 J pulse energy, respectively. Wear test was performed on a novel impact-sliding wear testing rig, which can realize multiple impact-sliding motions by changing motion parameters in x and z directions. Present results showed that wear resistance of both treated samples improved compared with the untreated alloy. Given the increase in wear cycles, increment in wear rate of the untreated sample was constantly higher than those of treated samples. All results can be attributed to the increase in surface hardness of the material and residual compressive stress, which was also introduced after LSP.

The combination of increased pressures for high-volume, high-impact publications in English language with the high rejection rates of submitted manuscripts for publications presents an often unsurpassable obstacle for (early career) researchers. At the same, the register requirements of peer-reviewed journals -that can contribute to whether a paper is accepted for publication- has received little attention. This paper redresses this gap, by investigating the linguistic choices in 60 published manuscripts in four journals, with impact factor (IF) above 2; all 4 journals, publish original research papers in the field of chemical engineering science and specifically focus on wastewater treatment. Our survey shows that chemical engineering research publications tend to comply to a set of unwritten requirements: multidisciplinarity, brevity, co-authorship, focus on the description of practical results (rather than methods), and awareness of non-specialised audiences. It is found that less discipline-specific vocabulary was used in higher IF journals and this is interpreted within the current context of manuscript publication and consumption. Also, a complex relationship between the advertised scope of each journal and the actual published papers exists, indicating that guide for authors and aims and objective published by the journal's editorial office should be critically evaluated.

Nicaragua is preparing the construction of an interoceanic canal that will be the longest and largest canal on earth. An environmental and social impact assessment has been published in 2014 supporting a general viability of the canal. Nonetheless, several scientist and societal actors raised serious concerns regarding the social, economic and ecological sustainability. Despite an open dispute within the Nicaraguan society, no independent, transparent and scientifically sound assessment has been carried out. Only the environmental and social impact assessment, charged by the canal constructor, has so far been realized. The aim of this study is to contribute to an open scientific debate through an objective and independent quantification of land use and hydrological impacts. This article presents a transparently documented and comprehensible impact assessment investigation of the West Canal Segment of the Nicaragua Canal. Based on publically available data and scientifically sound and recognized methods land use, hydrological (water availability) and socio-economic impacts (streets, population) are described, quantified and compared with official declarations in the impact assessment. While some results support official declarations other do not. The number of affected population and the water use of the Brito Lock resulted much higher in this study, for instance. Hence, society and water availability could be affected much higher than estimated in the impact assessment.

The study investigates methods to enhance the reliability of NO2 monitoring using low-cost electrochemical sensors to measure gaseous pollutants in air by addressing the impacts of temperature and relative humidity. The temperature within a plastic container was controlled using an internal mica heater, an external hot air blower or cooling packs, while relative humidity was adjusted using glycerin solutions. Findings indicated that the Auxiliary Electrode (AE) signal is susceptible to temperature and moderately affected by relative humidity. In contrast, the Working Electrode (WE) signal is less affected by temperature and relative humidity; however, adjustments are still required to determine gas concentrations accurately. Tests involving on/off cycles showed that the AE signal experiences exponential decay before stabilizing, requiring the exclusion of initial readings during monitoring activities. Additionally, calibration experiments in zero air allowed the determination of the compensation factor nT across different temperatures and humidity levels. These results highlight the importance of compensating for temperature and humidity effects to improve the accuracy and reliability of NO2 measurements using low-cost electrochemical sensors. This refinement makes the calibration applicable across a broader range of environmental conditions. However, the experiments also show a lack of repeatability of the zero calibration.

Waveform generation as part of an on-chip built-in self-test (BIST) circuitry often necessitates sufficient linearity without expensive hardware overhead. Achieving high linearity is critical for accurate signal generation, especially in applications requiring high precision, such as biomedical and instrumentation. Currently, achieving the high linearity and precision required in signal generators often relies on costly hardware such as automated test equipment (ATE). This paper presents a DAC based hardware synthesizable arbitrary waveform generator. We use a low-cost DAC and a fully digital on-chip testing and calibration approach to nullify the effect of the DAC’s non-linearity on the generated waveform. The ultra-low cost and high linearity benefit of the proposed waveform generator makes it highly suitable for integration into resource-constrained systems. The proposed approach is validated using simulation results of the small-area DAC designed in TSMC 0.18um technology and the testing and calibration algorithms implemented in MATLAB. The DAC, designed with a matching accuracy at only the 5-bit level, is able to generate a signal with an ENOB of 12 bits alongside a SFDR and THD surpassing 100 dB. This high level of signal purity is consistently maintained across 100 Monte-Carlo simulations, demonstrating the robustness of the architecture against PVT variations as well as random mismatches.

In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is fundamental. This paper presents a decision-making structure for large consumers having flexibility to manage electricity or natural gas consume to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural-gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural-gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of U$ 3.98 million over a six-month analysis period.

Harvesting is the collection of mature crops from the field. A harvesting procedure involves cutting, installation, collecting, transferring, and then stacking the cut produce. Mechanization of harvesting operations is critical to lowering harvesting costs, crop production costs, crop loss, turnaround time, weather risk, and increasing benefit through proper technology. To achieve the desired purpose, a manually operated reaper machine is created and developed to assist farmers by lowering the cost of crop cutting and collection in the field while achieving the best efficiency possible within the limits. Research technique is a set of acts or procedures that must be completed in order to do research properly, as well as the intended sequence of these steps. Identify the problem statement. Studying the current design of the reaper machine Review the literature. Product development general design process steps for reaper harvester’s machine include planning, concept development, system-level design, detail design, testing and refining, and product ramp-up. In this step, the material properties are defined based on design. To simulate the reaper machine using Catia software, Prototyping, testing for validation, Interpret and report. Material is chosen based on the strength requirements of the different parts of the Reaper machine. The machine is built with locally accessible materials. This self-propelled reaper moves at a forward speed of 2.54 m/s. The cutting bar measures 120 cm in length and the bundling mechanism is dropped. The field capacity is 0.306 ha/hour, respectively. The needed manpower for harvesting one hectare of wheat and rice reaper harvesting field operation is two man-hours per ha. The amount of fuel required to completely fill the tank after harvesting the plot was measured to determine the amount of fuel consumed for reaping the test plot, which was 1.17 l/h.

Under the new pattern of "Double-Cycle" economy, how to restructure the domestic economic structure to cope with the continuous softening of the global economic structure is an urgent issue. This paper empirically examines the impact of digitalization level on the division of labor in National Value Chain (NVC) within cities using panel data from 263 cities between 2001 and 2016, employing a spatial Durbin model.The study demonstrates that the digitization level can enhance division of labor in NVC in neighboring regions through spatial spillovers. An increase in digitization not only positively deepens the construction of NVC but also contributes to the development of NVC in adjacent areas.The digitization level can deepen the division of labor in NVC through the impact of cost reduction, consumption upgrading, and market integration. This effect exhibits regional variations, with consumption upgrading playing a crucial role in expanding the division of labor in NVC in the eastern region through improving digitization levels, while cost reduction is a key factor in the central region. The research results of this paper provide some empirical evidence for further progress and transition of China's NVC developing mode from the perspective of digital level.

Detecting and evaluating pain in people with cognitive impairment, especially dementia, is a challenge. Their ability to accurately report pain and comprehend related questions decreases the reliability of their self-report. This has contributed to the fact that pain is underdiagnosed and undertreated in this population, which can lead to involuntary ageism. The design and assessment of this training capsule under the context of the European COST-Action TD1005 responds to the need for education and training in "Pain Assessment In Cognitive Impairment, especially dementia" and the development of the internationally agreed observational PAIC15 scale. The 3-hour capsule, intended for healthcare workers and caregivers, consists of theoretical-practical levels: 1) basic concepts and challenges in pain in aging, cognitive impairment/dementia, 2) available scales and PAIC15, 3) video presentation of clinical cases illustrating a 3×2 matrix of situations (rest, transfer and experimental pain) and stages of disease (mild and moderate). The objectives focused on training the ability to observe, detect, and assess the signs of pain using PAIC15 and its feasibility. The pre-post analysis in a Master educational setting showed agreement with the results obtained in the Spanish national survey on 1) scarce knowledge of observational tools and their use, and 2) uncertainty in the identification of signs of pain and feasibility in moderate/severe scenarios. The capsule improved the ability to identify and evaluate the pain items, especially facial expressions, and their confidence on observational tools. Debriefings highlighted the relevance of observational scales in dementia and the gain obtained using the new observational instrument.

Supplier collaboration and partnership in procurement are essential elements for enhancing organizational efficiency, innovation, and resilience in today's globalized markets. This qualitative study investigates the dynamics of effective supplier relationships, focusing on trust, communication, innovation, quality, cost savings, and resilience as critical factors. Data were gathered through semi-structured interviews, case studies, and document analysis across diverse industries, highlighting insights from procurement professionals and supplier representatives. Key findings underscore the foundational role of trust and communication in fostering successful collaborations. Establishing transparent, ongoing communication channels facilitates mutual understanding, reduces conflicts, and enhances overall satisfaction. Collaborative innovation emerged as pivotal, enabling organizations to pool resources and expertise for product development and process improvement. Quality and reliability were identified as significant outcomes of close partnerships, particularly in industries with stringent standards such as aerospace and healthcare. Furthermore, the study reveals substantial cost savings and efficiency gains through collaborative efforts in process optimization and waste reduction. Effective risk management practices within these partnerships enhance supply chain resilience, enabling organizations to anticipate and mitigate disruptions proactively. Despite these benefits, challenges such as cultural differences, technological integration, and regulatory compliance require strategic mitigation strategies. In conclusion, organizations can optimize supplier collaborations by prioritizing trust-building, fostering a culture of innovation, and investing in robust relationship management practices. This approach not only enhances operational performance but also positions organizations to navigate market uncertainties and achieve sustainable growth in a competitive landscape.

Abstract: Effectiveness of a Single Fixed Dose 3 mg Rasburicase for Prevention and Management of Hyperuricemia of Tumor Lysis Syndrome in adult Cancer Patients Background: Tumor lysis syndrome (TLS) is a potentially life-threatening complication associated with certain types of cancer. Rasburicase is an essential medicine required to prevent and treat the hyperuricemia associated with TLS. Due to a shortage of rasburicase during the COVID-19 pandemic, a fixed dose strategy of 3 mg rasburicase had been used in many adult cancer patients in our center. Objective: The objective of this study was to assess the effectiveness of a 3 mg fixed dose of rasburicase in preventing and managing hyperuricemia associated with TLS in adult cancer patients. Methods: We conducted a retrospective, observational cohort study between March 2020 and November 2022. The study included adult patients who received a fixed dose of 3 mg rasburicase. The primary outcome measure was the reduction in serum UA levels of

Anxiety disorders affect patient quality of life (QoL). This study aimed to examine the associations between improved QoL and reduced clinical symptoms and Korean medicine (KM) in patients with anxiety disorders. Medical records of patients with anxiety who were treated with KM (acupuncture, Anxiety disorders affect patient quality of life (QoL). This study aimed to examine the associations between improved QoL and reduced clinical symptoms and Korean medicine (KM) in patients with anxiety disorders. Medical records of patients with anxiety who were treated with KM (ac-upuncture, psychotherapy, Chuna therapy, aromatherapy, or herbal medicine) for at least 4 weeks were retrospectively analyzed. Clinical, QoL, and cost outcomes were measured at baseline and at 4 and 12 weeks (Anxiety: State-Trait Anxiety Inventory[STAI X-1(state), X-2(trait)], Beck Anxiety Inventory[BAI]; anger: State-Trait Anger Expression Inventory State[STAXI-S(state), T(trait)], Anger Expression Inventory[AXI-K-I(anger-in), AXI-K-O(anger-out), AXI-K-C(anger-control); depression: Beck Depression Inventory-II[BDI II], QoL: QoL-related instruments Euro Quality of Life 5 Dimensions utility score[EQ-5D], Euro QoL Visual Analog Scale[EQ-VAS]). The quali-ty-adjusted life years (QALYs) and average cost-effectiveness ratio of KM for anxiety were esti-mated. The medical records for 67 patients were evaluated. KM treatments were found to be as-sociated with decreased anxiety (STAI X-1; STAI X-2; BAI, p

Varicella (chickenpox) is one of the most common infectious diseases in preschool children and can be prevented by immunization. While immunization program promotes higher vaccine coverage, there are still challenges with implementing vaccination programs particularly in low-income countries. Economic barriers can increase inequality in vaccination, which highlights the importance of distributing cost-effective varicella vaccines. Varicella vaccines have been developed with two main Varicella-Zoster Virus (VZV) strains globally: MAV/06 and Oka strains. Most of the vaccines are based on the Oka strain, while MAV/06 strain vaccines were exclusively developed by GC Biopharma. Although more than 30 million doses of MAV/06 vaccines as cost-effective vaccines have been distributed internationally, there is no comprehensive review on safety, immunogenicity, and effectiveness of MAV/06 vaccines in the literature. This paper aims to summarize and present more than 30 years of accumulated evidence from research on safety, immunogenicity, and effectiveness of MAV/06 vaccines. We expect that MAV/06 vaccines as cost-effective varicella vaccines make a significant contribution to improving global public health and health equality in children.

Evolutionary Machine Learning (EML) has demonstrated its effectiveness in modeling various real-world application domains, including the dynamics of diseases and the creation of predictive models across diverse fields. However, the challenge of data imbalance adversely impacts the performance of EML models. While strategies involving misclassification costs or cost-sensitive learning exist to address this issue, their integration into EML has yet to be thoroughly explored. This paper aims to fill this gap by investigating the application of cost-sensitive EML for intelligent health risk prediction. More specifically, this paper delves into the utilization of cost-sensitive genetic programming (CSGP) and cost-sensitive genetic algorithms (CSGA), which are among the most widely used algorithms in the EML category. The study entails training CSGP and CSGA to predict the early onset of three chronic conditions (hypertension, diabetes, and fatty acid-related disorders) through the development of an EML model. Subsequently, the model's performance is evaluated through standard fitness functions such as sensitivity, specificity, and F1-score. From the experimental results, EML models demonstrate promising results in identifying the occurrence of chronic diseases. Further optimization of the cost-sensitive EML model holds the potential for enhanced outcomes in modeling medical problems.

Addressing the contemporary challenges of mitigating and adapting to climate change, conserving biodiversity, and ensuring human well-being constitutes a central focus for humanity. These challenges, though often treated in isolation, are intricately interconnected, sharing common drivers. Current and future research emphasizes the pursuit of an integrated approach that minimizes trade-offs and fosters synergies among the Sustainable Development Goals (SDGs). The nexus between ecosystem service value (ESV) and the social cost of carbon (SCC) is pivotal in informing national and governmental decisions regarding human well-being and climate change mitigation and adaptation, respectively. This study employs the Zhoushan Archipelago as a case study, exploring ESV and SCC dynamics from 2010 to 2020. An in-depth analysis of spatial development characteristics and the temporal and spatial correlation between ESV and SCC is conducted. The findings reveal an increase in Zhoushan Archipelago's land area from 2010 to 2015, stabilizing thereafter, with construction land exhibiting the most notable proportional growth. Carbon emissions were observed during the study period, with forests identified as the primary carbon sink, followed by mudflat and waterbody, while construction land contributed significantly to carbon emissions. Notably, the SCC in Zhoushan Archipelago increased by 2452%, contrasting with a modest 1.5% decrease in ESV during the study period. Global spatial correlation analysis demonstrated a significant positive correlation between ESV and SCC in Zhoushan Archipelago throughout the study period, validated by passing the P-value test. However, local spatial correlation analysis revealed a specific nature of the global spatial correlation between ESV and SCC in the island area. This nuanced understanding enhances our comprehension of the intricacies surrounding ESV and SCC dynamics, contributing valuable insights to the broader discourse on sustainable regional development, economic decarbonization, and human well-being improvement.

Aims: The objective of this study was to assess the cost-effectiveness of the CardioMEMS HF system in a HF Clinic in Spain by evaluating the real-time remote monitoring of pulmonary artery pressures, which has shown to reduce heart failure (HF) related hospitalizations and improve the quality of life for selected HF patients. Particularly, the study aimed to determine the value of CardioMEMS in Southern Europe, where healthcare costs are significantly lower and its effectiveness remains uncertain. Methods: This single-centre study enrolled all consecutive HF patients who had been implanted with a pulmonary artery pressure sensor (CardioMEMS-HF system, Abbott Laboratories, Abbott Park, IL, USA). The number of HF hospitalizations in the year before and the year after the sensor implantation was compared and quality-adjusted life years (QALY) gained based on a literature review of previous studies was calculated. Results: The rate of HF hospitalisations was significantly lower at 1 year compared with the year before CardioMEMS implantation (0.25 versus 1.10 events/patient-years, HR 0.22, p=0.001). At the end of first year, the usual management outperformed the CardioMEMS HF system, resulting in a net monetary value difference of 2,540€ per patient and a benefit-cost ratio of 0.38. However, by the end of the second year, the CardioMEMS system is estimated to reduce costs compared to usual management. Conclusions: Based on the results, we suggest that remote monitoring of pulmonary artery pressure with the CardioMEMS HF system represents a long-term cost-effective strategy in a healthcare setting in Southern Europe.