: This study theoretically investigates the temperature and velocity spatial distributions in the flow of a copper–water nanofluid induced by a rotating rigid disk in a porous medium. Unlike previous work on similar systems, we assume that the disk surface is well polished (coated); therefore, there are velocity and temperature slips between the nanofluid and the disk surface. The importance of considering slip conditions in modeling nanofluids comes from practical applications where rotating parts of machines may be coated. Additionally, this study examines the influence of heat generation on the temperature distribution within the flow. By transforming the original Navier–Stokes partial differential equations (PDEs) into a system of ordinary differential equations (ODEs), numerical solutions are obtained. The boundary conditions for velocity and temperature slips are formulated using the effective viscosity and thermal conductivity of the copper–water nanofluid. The dependence of the velocity and temperature fields in the nanofluid flow on key parameters is investigated. The major findings of the study are that the nanoparticle volume fraction significantly impacts the temperature distribution, particularly in the presence of a heat source. Furthermore, polishing the disk surface enhances velocity slips, reducing stresses at the disk surface, while a pronounced velocity slip leads to distinct changes in the radial, azimuthal, and axial velocity components. The study highlights the influence of slip conditions on fluid velocity as compared to previously considered non-slip conditions. This suggests that accounting for slip conditions for coated rotating disks would yield more accurate predictions in assessing heat transfer, which would be potentially important for the practical design of various devices using nanofluids. Full article

The environmental crisis, growing levels of social inequalities and rising levels of noncommunicable diseases are all symptoms of economic systems that are failing to generate wellbeing. There is increasing support for the notion that addressing these crises requires shifting the focus from economic growth to a broader range of measures that reflect wellbeing, through more comprehensive, consistent and integrated policy approaches to deliver this. In 2019, the EU Finnish Council Presidency Council Conclusions called amongst other things for the development of a new long-term, post-2020 strategy to provide the framework for horizontal assessment and cross-sectoral collaboration, in particular through the European Semester process. This article contextualises this call and explores its follow-up. It draws from key policy documents to explore what Economies of Wellbeing are, why and how the concept has emerged and how they can be put in place. It then explores to what extent this concept is being applied at the EU level, by tracking changes in some of the EU’s key policies and strategies over the past 10 years and in the Semester process, as a mechanism to implement them. It concludes that while progress towards more comprehensive, consistent and integrated policy approaches has been made in the context of the Annual Sustainable Growth Strategy, underpinning the Semester processes, it is limited by the continuing emphasis on economic, over other policy, areas. It also argues that the process needs to be broadened even further, to include other dimensions of wellbeing, which intersect with the economy and impact wellbeing. To strengthen the European Semester process to achieve Economies of Wellbeing, it should be put at the service of an even more consistent and comprehensive EU Strategy that enables policy sectors to deliver wellbeing objectives in a more integrated and coordinated manner. This paper ends with recommendations for action. Full article

Organic agriculture based on the participatory guarantee system (PGS) is frequently touted as a tool for improving ecosystem sustainability and self-reliance and for alleviating the poverty of smallholder farmers in Thailand. However, specific criteria must be fulfilled for products to be certified organic. In this paper, we investigate the similarities and differences between three cases of organic agricultural production (based on the participatory guarantee system) in four provinces in northeastern Thailand: Nong Bua Lam Phu, Nakhon Phanom, Ubon Ratchathani, and Nakhon Ratchasima. A total of 135 smallholder farmers were selected to act as informants, and semi-structured interviews were held. The participatory guarantee system was utilized, considering the farmers’ diverse agricultural backgrounds and socio-economic conditions. For agriculture to be adapted with the ultimate aim of sustainability, policy support will be necessary in the form of financial measures and capacity building. Full article

The aim of the study was to characterize effects of a multi-strain synbiotic in patients with moderate to severe irritable bowel syndrome (IBS) of all stool form types. A total of 202 adult IBS patients were randomized (1:1) and after a four-week treatment-free run-in phase and were treated either with the synbiotic or a placebo for 12 weeks. The primary endpoints were the assessment of the severity of IBS symptoms (IBS-SSS) and the improvement of IBS global symptoms (IBS-GIS). Secondary endpoints comprised adequate relief (IBS-AR scale), stool form type (Bristol Stool Form Scale), bowel movements, severity of abdominal pain and bloating, stool pressure, feeling of incomplete stool evacuation, and adverse events. A total of 201 patients completed the study. Synbiotic treatment, in comparison to placebo, significantly improved IBS-SSS and IBS-GIS scores. At the end of the treatment, 70% of patients in the synbiotic group achieved adequate relief. After 12 weeks of treatment, the secondary endpoints were favorably differentiated in the synbiotic group when compared with the placebo group. Two patients in the synbiotic group reported transient adverse events (headache). The results indicate that treatment of IBS patients with the synbiotic significantly improved all major symptoms of IBS and was well-tolerated. The ClinicalTrials.gov registration was NCT05731232. Full article

Light and active mobility, as well as multimodal mobility, could significantly contribute to decarbonization. Air quality is a key parameter to monitor the environment in terms of health and leisure benefits. In a possible scenario, wearables and recharge stations could supply information about a distributed monitoring system of air quality. The availability of low-power, smart, low-cost, compact embedded systems, such as Arduino Nicla Sense ME, based on BME688 by Bosch, Reutlingen, Germany, and powered by suitable software tools, can provide the hardware to be easily integrated into wearables as well as in solar-powered EVSE (Electric Vehicle Supply Equipment) for scooters and e-bikes. In this way, each e-vehicle, bike, or EVSE can contribute to a distributed monitoring network providing real-time information about micro-climate and pollution. This work experimentally investigates the capability of the BME688 environmental sensor to provide useful and detailed information about air quality. Initial experimental results from measurements in non-controlled and controlled environments show that BME688 is suited to detect the human-perceived air quality. CO₂ readout can also be significant for other gas (e.g., CO), while IAQ (Index for Air Quality, from 0 to 500) is heavily affected by relative humidity, and its significance below 250 is quite low for an outdoor uncontrolled environment. Full article

Navigation systems are extensively used in everyday life, but the conventional A* algorithm has several limitations in path planning applications within these systems, such as low degrees of freedom in path planning, inadequate consideration of the effects of special regions, and excessive nodes and turns. Addressing these limitations, an enhanced A* algorithm was proposed using regular hexagonal grid mapping. First, the approach to map modeling using hexagonal grids was described. Subsequently, the A* algorithm was refined by optimizing the calculation of movement costs, thus allowing the algorithm to integrate environmental data more effectively and flexibly adjust node costs while ensuring path optimality. A quantitative method was also introduced to assess map complexity and adaptive heuristics that decrease the number of traversed nodes and increase the search speed. Moreover, a turning penalty measure was implemented to minimize unnecessary turns on the planned paths. Simulation results confirmed that the improved A* algorithm exhibits superior performance, which can dynamically adjust movement costs, enhance search efficiency, reduce turns, improve overall path planning quality, and solve critical path planning issues in navigation systems, greatly aiding the development and design of these systems and making them better suited to meet modern navigation requirements. Full article

This paper presents a thorough examination of methane capture from Polish coal mines, contextualized within the framework of the European Union’s (EU) climate policy objectives. Through a strategic analysis encompassing the interior of coal mines, the surrounding environment, and the macro environment, this study elucidates the complex dynamics involved in methane emissions and capture initiatives. The key findings include a declining trend in absolute methane emissions since 2008, despite fluctuations in coal extraction volumes, and a relatively stable level of methane capture exceeding 300 million m³/year since 2014. The analysis underscores the critical role of government support, both in terms of financial incentives and streamlined regulatory processes, to facilitate the integration of methane capture technologies into coal mining operations. Collaboration through partnerships and stakeholder engagement emerges as essential for overcoming resource competition and ensuring the long-term success of methane capture projects. This paper also highlights the economic and environmental opportunities presented by methane reserves, emphasizing the importance of investment in efficient extraction technologies. Despite these advancements, challenges persist, particularly regarding the low efficiency of current de-methanation technologies. Recommendations for modernization and technological innovation are proposed to enhance methane capture efficiency and utilization. Full article

Glass waste products represent a significant environmental concern, with an estimated 1.4 billion tons being landfilled globally and 200 million tons annually. This results in a significant use of land resources. Therefore, it would be highly advantageous to develop a new method for disposing of waste glass. Waste glass can be recycled and ground into waste glass powder (WGP) for use in solidified soil applications as a sustainable resource. This study is based on solidified soil research, wherein NaOH, Ca(OH)₂, and Na₂SO₄ were incorporated as activators to enhance the reactivity of WGP. The optimal solidified soil group was determined based on unconfined compressive strength tests, which involved varying the activator concentrations and WGP content in combination with cement. X-ray diffraction (XRD) was used to study the composition of solidified soil samples. Microscopic pore characteristics were investigated using scanning electron microscopy (SEM), and the Image J software was employed to quantify the number and size of pores. Fourier-transform infrared spectroscopy (FTIR) was employed to examine the activation effect of waste glass powder. This study investigated the solidification mechanism and porosity changes. The results demonstrate that the addition of activated WGP to solidified soil enhances its strength, with a notable 12% increase in strength achieved using a 6% Ca(OH)₂ solution. The use of 2% concentration of Na₂SO₄ and NaOH also shows an increase in strength of 7.6% and 8.6%, respectively, compared to the sample without WGP. The XRD and SEM analyses indicate that activated WGP enhances the content of hydrates, reduces porosity, and fosters the formation of a more densely packed solidified soil structure. Full article

Recently, community detection has emerged as a prominent research area in the analysis of complex network structures. Community detection models based on non-negative matrix factorization (NMF) are shallow and fail to fully discover the internal structure of complex networks. Thus, this article introduces a novel constrained symmetric non-negative matrix factorization with deep autoencoders (CSDNMF) as a solution to this issue. The model possesses the following advantages: (1) By integrating a deep autoencoder to discern the latent attributes bridging the original network and community assignments, it adeptly captures hierarchical information. (2) Introducing a graph regularizer facilitates a thorough comprehension of the community structure inherent within the target network. (3) By integrating a symmetry regularizer, the model’s capacity to learn undirected networks is augmented, thereby facilitating the precise detection of symmetry within the target network. The proposed CSDNMF model exhibits superior performance in community detection when compared to state-of-the-art models, as demonstrated by eight experimental results conducted on real-world networks. Full article

The development of offshore wind farms requires robust bonding solutions that can withstand harsh marine conditions for the easy integration of secondary structures. This paper investigates the durability performance of two adhesives: Sikadur 30 epoxy resin and Loctite UK 1351 B25 urethane-based adhesive for use in offshore wind environments. Tensile tests on adhesive samples and accelerated aging tests were carried out under a variety of temperatures and environmental conditions, including both dry and wet conditions. The long-term effects of aging on adhesive integrity are investigated by simulating the operational life of offshore installations. The evolution of mechanical properties, studied under accelerated aging conditions, provides an important indication of the longevity of structures under normal conditions. The results show significant differences in performance between the two adhesives, highlighting their suitability for specific operating parameters. It should also be noted that for both adhesives, their exposure to different environments (seawater, distilled water, humid climate) over a prolonged period showed that (i) Loctite adhesive has a slightly faster initial uptake than Sikadur adhesive, but the latter reaches an asymptotic plateau with a lower maximum absorption rate than Loctite adhesive; and (ii) a progressive deterioration in the tensile properties occurred following an exponential function. Therefore, aging behavior results showed a clear correlation with the Arrhenius law, providing a predictive tool for the aging process and the aging process of the two adhesives followed Arrhenius kinetics. Ultimately, the knowledge gained from this study is intended to inform best practice in the use of adhesives, thereby improving the reliability and sustainability of the offshore renewable energy infrastructure. Full article

Periodontitis is an inflammatory process that starts with soft tissue inflammation caused by the intervention of oral bacteria. By modulating local immunity, it is possible to supplement or replace current therapeutic methods. The aim of this study was to compare the effects of an immunostimulatory treatment with the antibiotherapy usually applied to periodontitis patients. On a model of periodontitis induced in 30 rats (divided into three equal groups) with bacterial strains selected from the human oral microbiome (Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum and Streptococcus oralis), we administered antibiotics, bacterial lysates and saline for 10 days. Clinically, no significant lesions were observed between the groups, but hematologically, we detected a decrease in lymphocyte and neutrophil counts in both the antibiotic and lysate-treated groups. Immunologically, IL-6 remained elevated compared to the saline group, denoting the body’s effort to compensate for bone loss due to bacterial action. Histopathologically, the results show more pronounced oral tissue regeneration in the antibiotic group and a reduced inflammatory reaction in the lysate group. We can conclude that the proposed bacterial lysate has similar effects to antibiotic therapy and can be considered an option in treating periodontitis, thus eliminating the unnecessary use of antibiotics. Full article

Accurate wind power forecasting (WPF) is critical in optimizing grid operations and efficiently managing wind energy resources. Challenges arise from the inherent volatility and non-stationarity of wind data, particularly in short-to-medium-term WPF, which extends to longer forecast horizons. To address these challenges, this study introduces a novel model that integrates Improved Empirical Mode Decomposition (IEMD) with an enhanced Transformer called TransIEMD. TransIEMD begins by decomposing the wind speed into Intrinsic Mode Functions (IMFs) using IEMD, transforming the scalar wind speed into a vector form that enriches the input data to reveal hidden temporal dynamics. Each IMF is then processed with channel attention, embedding, and positional encoding to prepare inputs for an enhanced Transformer. The Direct Embedding Module (DEM) provides an alternative viewpoint on the input data. The distinctive perspectives of IEMD and DEM offer interaction through cross-attention within the encoder, significantly enhancing the ability to capture dynamic wind patterns. By combining cross-attention and self-attention within the encoder–decoder structure, TransIEMD demonstrates enhanced proficiency in detecting and leveraging long-range dependencies and dynamic wind patterns, improving the forecasting precision. Extensive evaluations on a publicly available dataset from the National Renewable Energy Laboratory (NREL) demonstrate that TransIEMD significantly improves the forecasting accuracy across multiple horizons of 4, 8, 16, and 24 h. Specifically, at the 24 h forecast horizon, TransIEMD achieves reductions in the normalized mean absolute error and root mean square error of 4.24% and 4.37%, respectively, compared to the traditional Transformer. These results confirm the efficacy of integrating IEMD with attention mechanisms to enhance the accuracy of WPF. Full article

An electroceutical is a medical device that uses electrical signals to control biological functions. It can be inserted into the human body as an implant and has several crucial advantages over conventional medicines for certain diseases. This research develops a new vagus nerve simulation (VNS) electroceutical through an innovative approach to overcome the communication limitations of existing devices. A phased array antenna with a better communication performance was developed and applied to the electroceutical prototype. In order to effectively respond to changes in communication signals, we developed the steering algorithm and firmware, and designed the smart communication protocol that operates at a low power that is safe for the patients. This protocol is intended to improve a communication sensitivity related to the transmission and reception distance. Based on this technical approach, the heightened effectiveness and safety of the prototype have been ascertained, with the actual clinical tests using live animals. We confirmed the signal attenuation performance to be excellent, and a smooth communication was achieved even at a distance of 7 m. The prototype showed a much wider communication range than any other existing products. Through this, it is conceivable that various problems due to space constraints can be resolved, hence presenting many benefits to the patients whose last resort to the disease is the VNS electroceutical. Full article

Based on the quasi-six-degree-of-freedom flight dynamic equations, considering the changes in the elevation angle caused by an increase in the rolling angle during maneuvering turns, which leads to a rise in the radar cross-section. A computational model for the radar detection probability of aircraft in complex environments was constructed. By comprehensively considering flight parameters such as turning angle, rolling angle, Mach number, and radar power factor, this study quantitatively analyzed the influence of these factors on the radar detection probability. It revealed the variation patterns of radar detection probability under different flight conditions. The results provide theoretical support for the Radar Valley Radius and Turning Maneuver Method (RVR-TM) based on decision trees, and lay the foundation for the development of subsequent intelligent decision-making models. To further optimize the trajectory selection of aircraft in complex environments, this study combines theoretical analysis with reinforcement learning algorithms to establish an intelligent decision-making model. This model is trained using the Proximal Policy Optimization (PPO) algorithm, and through precisely defining the state space and reward functions, it accomplishes intelligent trajectory planning for stealth aircraft under radar threat scenarios. Full article

In just a few short years, the additive manufacturing (AM) technology known as 3D printing has experienced intense growth from a niche technology to a disruptive innovation that has captured the imagination of mainstream manufacturers and hobbyists alike. The purpose of this article is to introduce the use of 3D printing for specific applications, materials, and manufacturing processes that help to optimize heat transfer in heat exchangers, with an emphasis on sustainability. The ability to create complex geometries, customize designs, and use advanced materials provides opportunities for more efficient and stable heat transfer solutions. One of the key benefits of incremental technology is the potential reduction in material waste compared to traditional manufacturing methods. By optimizing the design and structure of heat transfer components, 3D printing enables lighter yet more efficient solutions and systems. The localized manufacturing of components, which reduces the need for intensive transportation and associated carbon emissions, can lead to reduced energy consumption and improved overall efficiency. The customization and flexibility of 3D printing enables the integration of heat transfer components into renewable energy systems. This article presents the key challenges to be addressed and the fundamental research needed to realize the full potential of incremental manufacturing technologies to optimize heat transfer in heat exchangers. It also presents a critical discussion and outlook for solving global energy challenges through innovative incremental manufacturing technologies in the heat exchanger sector. Full article

Mediterranean water-stressed areas face significant challenges from higher temperatures and increasingly severe droughts. We assess the effect of climate change on rainfed barley production in the aridity-prone province of Almería, Spain, using the FAO AquaCrop model. We focus on rainfed barley growth by the mid-century (2041–2070) and end-century (2071–2100) time periods, using three Shared Socio-economic Pathway (SSP)-based scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Using the paired t-test, Spearman and Pearson correlation coefficient, Root Mean Squared Error, and relative Root Mean Squared Error, we verified AquaCrop’s ability to capture local multi-year trends (9 or more years) using standard barley crop parameters, without local recalibration. Starting with a reference Initial Soil Water Content (ISWC), different soil water contents within barley rooting depth were modelled to account for decreases in soil water availability. We then evaluated the efficiency of different climate adaptation strategies: irrigation, mulching, and changing sowing dates. We show average yield changes of +14% to −44.8% (mid-century) and +12% to −55.1% (end-century), with ISWC being the main factor determining yields. Irrigation increases yields by 21.1%, utilizing just 3% of Almería’s superficial water resources. Mulches improve irrigated yield performances by 6.9% while reducing irrigation needs by 40%. Changing sowing dates does not consistently improve yields. We demonstrate that regardless of the scenario used, climate adaptation of field barley production in Almería should prioritize limiting soil water loss by combining irrigation with mulching. This would enable farmers in Almería’s northern communities to maintain their livelihoods, reducing the province’s reliance on horticulture while continuing to contribute to food security goals. Full article

Accelerometers worn by animals produce distinct behavioral signatures, which can be classified accurately using machine learning methods such as random forest decision trees. The objective of this study was to identify accelerometer signal separation among parsimonious behaviors. We achieved this objective by (1) describing functional differences in accelerometer signals among discrete behaviors, (2) identifying the optimal window size for signal pre-processing, and (3) demonstrating the number of observations required to achieve the desired level of model accuracy,. Crossbred steers (Bos taurus indicus; n = 10) were fitted with GPS collars containing a video camera and tri-axial accelerometers (read-rate = 40 Hz). Distinct behaviors from accelerometer signals, particularly for grazing, were apparent because of the head-down posture. Increasing the smoothing window size to 10 s improved classification accuracy (p < 0.05), but reducing the number of observations below 50% resulted in a decrease in accuracy for all behaviors (p < 0.05). In-pasture observation increased accuracy and precision (0.05 and 0.08 percent, respectively) compared with animal-borne collar video observations. Full article

Japanese encephalitis virus (JEV) has a positive-sense single-stranded RNA genome and belongs to the genus Flavivirus of the family Flaviviridae. Persistent JEV infection was previously shown in pig blood cells, which act as a natural reservoir of this virus. We aimed to determine the pathogenicity factors involved in persistent JEV infection by analyzing the pathogenicity and genome sequences of a virus isolated from a persistent infection model. We established persistent JEV infections in cells by inoculating mouse fetus primary cell cultures with the Beijing-1 strain of JEV and then performing repeated infected cell passages, harvesting viruses after each passage while monitoring the plaque size over 100 generations. The virus growth rate was compared among Vero, C6/36, and Neuro-2a cells. The pathogenicity was examined in female ICR mice at several ages. Additionally, we determined the whole-genome sequences. The 134th Beijing-1-derived persistent virus (ME134) grew in Vero cells at a similar rate to the parent strain but did not grow well in C6/36 or Neuro-2a cells. No differences were observed in pathogenicity after intracerebral inoculation in mice of different ages, but the survival time was extended in older mice. Mutations in the persistent virus genomes were found across all regions but were mainly focused in the NS3, NS4b, and 3′NCR regions, with a 34-base-pair deletion found in the variable region. The short deletion in the 3′NCR region appeared to be responsible for the reduced pathogenicity and growth efficiency. Full article

The intelligent warehouse is a modern logistics management system that uses technologies like the Internet of Things, robots, and artificial intelligence to realize automated management and optimize warehousing operations. The multi-robot system (MRS) is an important carrier for implementing an intelligent warehouse, which completes various tasks in the warehouse through cooperation and coordination between robots. As an extension of reinforcement learning and a kind of swarm intelligence, MARL (multi-agent reinforcement learning) can effectively create the multi-robot systems in intelligent warehouses. However, MARL-based multi-robot systems in intelligent warehouses face serious safety issues, such as collisions, conflicts, and congestion. To deal with these issues, this paper proposes a safe MARL method based on runtime verification, i.e., an optimized safety policy-generation framework, for multi-robot systems in intelligent warehouses. The framework consists of three stages. In the first stage, a runtime model SCMG (safety-constrained Markov Game) is defined for the multi-robot system at runtime in the intelligent warehouse. In the second stage, rPATL (probabilistic alternating-time temporal logic with rewards) is used to express safety properties, and SCMG is cyclically verified and refined through runtime verification (RV) to ensure safety. This stage guarantees the safety of robots’ behaviors before training. In the third stage, the verified SCMG guides SCPO (safety-constrained policy optimization) to obtain an optimized safety policy for robots. Finally, a multi-robot warehouse (RWARE) scenario is used for experimental evaluation. The results show that the policy obtained by our framework is safer than existing frameworks and includes a certain degree of optimization. Full article

Heat transfer affects a motor’s sizing, its performance, and, ultimately, the overall vehicle’s range and endurance. However, the thermal literature does not have early-stage models for outrunner brushless DC (BLDC) motors found in small unmanned aerial systems (UASs). To address this gap, we have developed a non-dimensional heat transfer model (Nusselt correlation). Parametric experiments of four different-sized BLDC motors under load in Reynolds-matched wind tunnel tests generated data for model correlation. The motors’ aspect ratios (diameter/length) ranged from 0.9 to 1.5. The freestream Reynolds number of the axial flow over the motors ranged from 20,000 to 40,000. The rotational Reynolds number ranged from 10,000 to 20,000. The results showed that aspect ratio had the largest influence on heat transfer, followed by rotational and freestream Reynolds numbers. A steady-state model used the correlation to predict the motor’s ambient temperature differential within 10 K of experimental data. A case study applied the correlation to predict a hypothetical motor’s continuous torque in different environments. The correlation enables conceptual designers to capture thermally-driven trade-offs in early design stages and reduce costly revisions in later stages. Full article

The urban carbon footprint (UCF) is an important tool for assessing an organization’s ecological impacts and in guiding sustainability efforts. This calculation is usually measured in tons of carbon dioxide equivalent (CO₂-eq). Calculations provide important data to determine strategies to reduce the carbon footprint and establish sustainability targets. Various standards and protocols guide UCF calculation, and many organizations aim to make these data transparent to their stakeholders and the public. This study aims to calculate the UCF of Sarıçam Municipality (SM) in the Adana Province of Türkiye. This study includes the greenhouse gas emission inventories resulting from all activities of the SM main service building, guest house, construction site service building, Cultural Center service building, and additional service buildings between 1 January 2022 and 31 December 2022. The calculations include generator fuel consumption, electricity consumption, the refrigerant gas leaks and refills resulting from these activities, the fuel consumed in vehicles owned by the company or whose fuel consumption is under company control, emissions originating from personal travel, emissions originating from customers and visitors, emissions originating from business travel, purchases, etc. Emissions from products purchased and emissions from waste transportation are included. The findings show that, in 2022, the total UCF of SM was equal to 10,862.46 tons of CO₂-eq. The Paris Agreement aims to reduce the per capita emissions to approximately two tons of CO₂-eq by 2030. The carbon footprint per employee within the municipality was calculated at 12.43 tons of CO₂-eq, as derived from the analyzed data. The results reveal the importance of implementing sustainable practices and strategies within SM, such as energy efficiency measures, waste reduction, and the adoption of renewable energy sources, to mitigate its carbon footprint. This study plans to provide a basis for SM’s reduction efforts by keeping greenhouse gas emissions under control. Full article

The objective of the research is to develop novel materials that are both inexpensive and have a low density, while also being able to endure the transportation of γ-photons with low-to-medium energy levels. The outcome consisted of four epoxy resins that were strengthened with different quantities of heavy metallic waste. The density of the formed composites improved from 1.134 ± 0.022 g/cm³ to 1.560 ± 0.0312 g/cm³ when the waste content was raised from 0 to 40 weight percent. The theoretical investigation was determined using Monte Carlo (MCNP) simulation software, and the results of linear attenuation coefficient were justified experimentally in a low and medium energy range of 15–662 keV. The mass attenuation coefficient results in a low gamma energy range (15–122 keV) varied in between 3.175 and 0.159 cm²/g (for E-MW0 composite) and in between 8.212 and 0.164 cm²/g (for E-MW40 composite). The decrease in mass attenuation coefficient was detected in a medium gamma photon energy range (122–662 keV) with 0.123–0.082 cm²/g (for E-MW0 composite) and 0.121–0.080 cm²/g (for E-MW40 composite). The density of the enhanced composites influenced these parameters. As the metallic waste composition increased, the fabricated composites’ half-value thickness decreased. At 15 keV, the half-value thickness decreased from 0.19 to 0.05 cm. At 59 keV, it fell from 2.70 to 1.41 cm. At 122 keV, it fell from 3.90 to 2.72 cm. At 662 keV, it fell from 7.45 to 5.56 cm. This decrease occurred as the heavy metal waste concentration increased from 0 to 40 wt.%. The study indicates that as metallic waste concentrations rise, there is a rise in the effective atomic number and a decline in the buildup factors. Full article