J — Multidisciplinary Scientific Journal

Hydrogen is set to become an important energy carrier in Germany in the next decades in the country’s quest to reach the target of climate neutrality by 2045. To meet Germany’s potential green hydrogen demand of up to 587 to 1143 TWh by 2045, electrolyser capacities between 7 and 71 GW by 2030 and between 137 to 275 GW by 2050 are required. Presently, the capacities for electrolysis are small (around 153 MW), and even with an increase in electrolysis capacity of >1 GW per year, Germany will still need to import large quantities of hydrogen to meet its future demand. This work examines the expected green hydrogen demand in different sectors, describes the available technologies, and highlights the current situation and challenges that need to be addressed in the next years to reach Germany’s climate goals, with regard to scaling up production, infrastructure development, and transport as well as developing the demand for green hydrogen. Full article

This paper focuses on the estimation of multicomponent stress–strength models, an important concept in reliability analyses used to determine the probability that a system will function successfully under varying stress conditions. Understanding and accurately estimating these probabilities is essential in fields such as engineering and risk management, where the reliability of components under extreme conditions can have significant consequences. This is the case in applications where one seeks to model extreme hydrological events. Specifically, this study examines cases where the random variables X (representing strength) and Y (representing stress) follow extreme value distributions. New analytical expressions are derived for multicomponent stress–strength reliability (MSSR) when different classes of extreme distributions are considered, using the extreme value $\mathbb{H}$-function. These results are applied to three l-max stable laws and six p-max stable laws, providing a robust theoretical framework for multicomponent stress–strength analyses under extreme conditions. To demonstrate the practical relevance of the proposed models, a real dataset is analyzed, focusing on the monthly water capacity of the Shasta Reservoir in California (USA) during August and December from 1980 to 2015. This application showcases the effectiveness of the derived expressions in modeling real-world data. Full article

The process of siting municipal solid waste landfills in Greece faces significant challenges due to land resource limitations, the country’s mountainous and water-permeable terrain, and strong public opposition. This study introduces a novel methodology for optimizing landfill sites on Lemnos Island in the North Aegean Sea using a Fuzzy Spatial Multiple Criteria Analysis (FSMCA) approach. By combining fuzzy sets theory, Geographic Information Systems (GIS), Analytic Hierarchy Process (AHP), spatial autocorrelation, spatial clustering and sensitivity analysis, this methodology addresses the uncertainties and complexities inherent in landfill siting. The decision problem is structured hierarchically into five levels to manage multiple criteria effectively. Criteria weights are determined using AHP, with discrete criteria graded according to Greek and EU guidelines, and continuous criteria evaluated through fuzzy sets theory. The region’s suitability is assessed using multiple criteria analysis, revealing that 9.7% of Lemnos Island is appropriate for landfill placement. Sensitivity analysis confirms the robustness of the methodology to changes in criteria weights. The case study demonstrates the practical application and benefits of FSMCA in a real-world scenario, underscoring its potential to improve sustainable waste management practices and inform policy making. Full article

Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, presents a growing health challenge in Spain. This review examines the current understanding of IBD through the lens of genetics, epigenetics, and metabolism, offering insights into future directions for research and clinical management. Recent advancements in genetic studies have identified numerous susceptibility loci, highlighting the complex interplay between genetic predisposition and environmental triggers. Epigenetic modifications, including DNA methylation and histone modification, further elucidate the pathogenesis of IBD, underscoring the role of gene–environment interactions. Metabolic alterations, particularly in the gut microbiome, emerge as crucial factors influencing disease onset and progression. The integration of multi-omics approaches has enhanced our comprehension of the molecular mechanisms underlying IBD, paving the way for personalized medicine. Looking forward, this review emphasizes the need for longitudinal studies and advanced bioinformatics tools to decode the intricate networks involved in IBD. Additionally, we discuss the potential of novel therapeutic strategies, including epigenetic drugs and microbiome modulation, as promising avenues for improved patient outcomes. This comprehensive overview provides a foundation for future research aimed at unraveling the complexities of IBD and developing innovative treatments tailored to the Spanish population. Full article

Weight regain (WR) after bariatric surgery, particularly sleeve gastrectomy, is a significant challenge, often driven by a combination of metabolic, behavioral, and lifestyle factors. Non-surgical interventions to manage WR are critical, given the increased risks and reduced efficacy of revisional surgeries. In this context, very low-calorie ketogenic diets (VLCKDs) have gained attention for their potential to promote weight loss and improve body composition in individuals struggling with WR. This study assessed the safety and efficacy of a VLCKD in 11 patients who experienced WR following sleeve gastrectomy. Over an 8-week period, patients demonstrated a significant average weight loss of 6.3% (p = 0.005), along with improvements in body composition, including reductions in body fat percentage (p = 0.003) and waist circumference (p = 0.003). Metabolic markers, such as insulin resistance (HOMA-IR), also improved significantly (p = 0.041). Although a decrease in the glomerular filtration rate was observed (p = 0.007), this finding is unlikely to be clinically relevant over the short term. Importantly, no major adverse events were reported, with only mild constipation observed. These results suggest that VLCKDs may be a promising non-surgical approach for managing WR post-bariatric surgery, though further studies are needed to assess long-term effects, especially on renal function. Full article

Air pollution contributes significantly to morbidity and mortality globally. The Niger Delta Region of Nigeria flares the second largest amount of natural gas in the world, with residents of oil-producing communities bearing the burden of outdoor pollution that may have adverse effects on their health and well-being. Our study aimed to investigate the haematological indices of residents of a selected gas-flaring site. We conducted a cross-sectional study, wherein a total of eighty adults aged 24 to 73 years were recruited from communities located within a radius of approximately 5 to 10 km from the gas-flaring facility. Blood specimens were collected from consenting participants and analysed for various haematological parameters, including Red Blood Cell (RBC) count, Packed Cell Volume (PCV), Haemoglobin (HB), Mean Cell Haemoglobin (MCH), platelet count (PLT), White Blood Cell (WBC) count, neutrophil (NEU), lymphocytes (LYMs), and Monocyte + Basophil + Eosinophil (MXD). The analysis was performed using an automated Sysmex KX21N haematological analyser. Overall, there was a significant decrease in RBC counts (p < 0.001) and a significant elevation in WBCs (p < 0.001) among people residing within a 5 km radius compared to those residing within a 10 km radius. About 42.5% of males residing within a 5 Km radius exhibited low RBC counts in contrast to only 15% of males residing within a 10 km radius. The WBC levels were found to be significantly higher (p < 0.001) than the reference range among both males and females residing within a 5 km radius compared to those residing at a distance of 10 km. In the female population, 15% of individuals residing within a 5 km and 10 Km radius exhibited RBC levels below the reference category, while 7.5% showed RBC levels above the reference range. Exposure to gas flaring may alter haematological indices. It is, therefore, recommended that a comprehensive longitudinal study be conducted among residents of oil-producing communities and workers at gas-flaring facilities in the Niger Delta region of Nigeria to assess the potential environmental and health implications of their exposure to chemical pollutants. Full article

Understanding natural killer (NK) cell functionality is essential in developing more effective immunotherapeutic strategies that can enhance patient outcomes, especially in the context of cancer treatment. This review provides a comprehensive overview of both traditional and novel techniques for evaluating NK cell functionality, focusing on multiparameter assays and spatial methods that illuminate NK cell interactions within their microenvironment. We discuss the significance of standardized assays for assessing NK cell function across various research and clinical settings, including cancer immunotherapy, infectious diseases, and transplantation. Key factors influencing NK cell functionality include the origin of the sample, target–effector ratios, the functional state of NK cells, and the impact of pre-treatment conditions and their natural aging effect on NK cell activity. By emphasizing the importance of selecting a suitable technique for reliable measurements, especially for longitudinal monitoring, this review aims to give an overview on techniques to measure NK cell functionality in vitro and show the interaction with their microenvironment cells by spatial imaging. Ultimately, our understanding of NK cell functionality could be critical to biomarker development, drug design, and understanding of disease progression in the field of oncology or infectious disease. Full article

The decarbonization of industrial process heat is one of the bigger challenges of the global energy transition. Process heating accounts for about 20% of final energy demand in Germany, and the situation is similar in other industrialized nations around the globe. Process heating is indispensable in the manufacturing processes of products and materials encountered every day, ranging from food, beverages, paper and textiles, to metals, ceramics, glass and cement. At the same time, process heating is also responsible for significant greenhouse gas emissions, as it is heavily dependent on fossil fuels such as natural gas and coal. Thus, process heating needs to be decarbonized. This review article explores the challenges of decarbonizing industrial process heat and then discusses two of the most promising options, the use of electric heating technologies and the substitution of fossil fuels with low-carbon hydrogen, in more detail. Both energy carriers have their specific benefits and drawbacks that have to be considered in the context of industrial decarbonization, but also in terms of necessary energy infrastructures. The focus is on high-temperature process heat (>400 °C) in energy-intensive basic materials industries, with examples from the metal and glass industries. Given the heterogeneity of industrial process heating, both electricity and hydrogen will likely be the most prominent energy carriers for decarbonized high-temperature process heat, each with their respective advantages and disadvantages. Full article

Local energy networks, known as microgrids, can operate independently or in conjunction with the main grid, offering numerous benefits such as enhanced reliability, sustainability, and efficiency. This study focuses on analyzing the factors that influence energy performance in East-West microgrids, which have the unique advantage of capturing solar radiation from both directions, maximizing energy production throughout the day. A predictive pipeline was also developed to assess the performance of various machine learning models in forecasting energy output. Key input data for the models included solar radiation levels, photovoltaic (DC) energy, and the losses incurred during the conversion from DC to AC energy. One of the study’s significant findings was that the east side of the microgrid received higher radiation and experienced fewer losses compared to the west side, illustrating the importance of orientation for efficiency. Another noteworthy result was the predicted total energy supplied to the grid, valued at €15,423. This demonstrates that the optimized energy generation not only meets grid demand but also generates economic value by enabling the sale of excess energy back to the grid. The machine learning models—Random Forest, Extreme Gradient Boosting, and Recurrent Neural Networks—showed superior performance in energy prediction, with mean squared errors of 0.000318, 0.000104, and 0.000081, respectively. The research concludes that East-West microgrids have substantial potential to generate significant energy and economic benefits. The developed energy prediction pipeline can serve as a useful tool for optimizing microgrid operations and improving their integration with the main grid. Full article

Quantum-secure cryptography is a dynamic field due to its crucial role in various domains. This field aligns with the ongoing efforts in data security. Post-quantum encryption (PQE) aims to counter the threats posed by future quantum computers, highlighting the need for further improvement. Based on the learning with error (LWE) system, this paper introduces a novel asymmetric encryption technique that encrypts entire messages of n bits rather than just 1 bit. This technique offers several advantages including an additive homomorphic cryptosystem. The robustness of the proposed lightweight public key encryption method, which is based on a new version of LWE, ensures that private keys remain secure and that original data cannot be recovered by an attacker from the ciphertext. By improving encryption and decryption execution time—which achieve speeds of 0.0427 ms and 0.0320 ms, respectively—and decreasing ciphertext size to 708 bits for 128-bit security, the obtained results are very promising. Full article

The COVID-19 pandemic is caused by a novel and rapidly mutating coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although several drugs are already in clinical use or under emergency authorization, there is still an urgent need to develop new drugs. Through the mining and analysis of 2776 genomes of the SARS-CoV-2 virus, we identified papain-like protease (PLpro), which is a critical enzyme required for coronavirus to generate a functional replicase complex and manipulate post-translational modifications on host proteins for evasion against host antiviral immune responses, as a conserved molecular target for the development of anti-SARS-CoV-2 therapy. We then made an infection model using the NCI-H1299 cell line stably expressing SARS-CoV-2 PLpro protein (NCI-H1299/PLpro). To investigate the effect of targeting and degrading PLpro mRNA, a compact CRISPR-Cas13 system targeting PLpro mRNA was developed and validated, which was then delivered to the aforementioned NCI-H1299/PLpro cells. The results showed that CRISPR-Cas13 mediated mRNA degradation successfully reduced the expression of viral PLpro protein. By combining the power of AAV and CRISPR-Cas13 technologies, we aim to explore the potential of attenuating viral infection by targeted degradation of important viral mRNAs via safe and efficient delivery of AAV carrying the CRISPR-Cas13 system. This study demonstrated a virus-against-virus gene therapy strategy for COVID-19 and provided evidence for the future development of therapies against SARS-CoV-2 and other RNA viral infections. Full article

Background: The objective of this study was to compare the facial pattern according to Steiner’s cephalometric analysis with other facial measurement methods (Ricketts, Björk-Jarabak, and McNamara). Methods: 200 patients from a university orthodontic clinic were studied. Measurements were taken using Ricketts, Steiner, Björk-Jarabak, and McNamara methods. Results were compared using standard deviation proportions. Results: Significant differences were found between Steiner’s method and the gold standard. No differences were observed between mixed and permanent dentition groups. Errors were noted in facial type classification: 54.8% in the brachyfacial group, 80% in the mesofacial group and 14.5% in the dolichofacial group. Conclusion: The mandibular angle of Steiner tends to make a diagnosis more towards the dolichofacial type compared to other methods. A protocol is proposed to adjust the value of the mandibular angle of Steiner to the other three methods in a Spanish population. Full article

Haebara and Stocking–Lord linking methods are frequently used to compare the distributions of two groups. Previous research has demonstrated that Haebara and Stocking–Lord linking can produce bias in estimated standard deviations and, to a smaller extent, in estimated means in the presence of differential item functioning (DIF). This article determines the asymptotic bias of the two linking methods for the 2PL model. A bias-reduced Haebara and bias-reduced Stocking–Lord linking method is proposed to reduce the bias due to uniform DIF effects. The performance of the new linking method is evaluated in a simulation study. In general, it turned out that Stocking–Lord linking had substantial advantages over Haebara linking in the presence of DIF effects. Moreover, bias-reduced Haebara and Stocking–Lord linking substantially reduced the bias in the estimated standard deviation. Full article

The discovery of natural products has been pivotal in drug development, providing a vast reservoir of bioactive compounds from various biological sources. This narrative review addresses a critical research gap: the largely underexplored role of gut microbiota in the mediation and biotransformation of medicinal herb-derived natural products for therapeutic use. By examining the interplay between gut microbiota and natural products, this review highlights the potential of microbiota-mediated biotransformation to unveil novel therapeutic agents. It delves into the mechanisms by which gut microbes modify and enhance the efficacy of natural products, with a focus on herbal medicines from Ayurveda and traditional Chinese medicine, known for their applications in treating metabolic and inflammatory diseases. The review also discusses recent advances in microbiota-derived natural product research, including innovative methodologies such as culturomics, metagenomics, and metabolomics. By exploring the intricate interactions between gut microorganisms and their substrates, this review uncovers new strategies for leveraging gut microbiota-mediated processes in the development of groundbreaking therapeutics. Full article

Due to climate change, population increase, and the urban heat island effect (UHI), the demand for cooling energy, especially in urban areas, has increased and will further increase in the future. Technologies such as radiative cooling offer a sustainable and energy-free solution by using the wavelength ranges of the atmosphere that are transparent to electromagnetic radiation, the so-called atmospheric window (8–13 µm), to emit thermal radiation into the colder (3 K) outer space. Previous publications in the field of textile building cooling have focused on specific fiber structures and textile substrate materials as well as complex multi-layer constructions, which restrict the use for highly scaled outdoor applications. This paper describes the development of a novel substrate-independent coating with spectrally selective radiative properties. By adapting the coating parameters and combining low-emitting and solar-reflective particles, along with a matrix material emitting strongly in the mid-infrared range (MIR), substrate-independent cooling below ambient temperature is achieved. Moreover, the coating is designed to be easily applicable, with a low thickness, to ensure high flexibility and scalability, making it suitable for various applications such as membrane architecture, textile roofs, or tent construction. The results show a median daytime temperature reduction (7 a.m.–7 p.m.) of 2 °C below ambient temperature on a hot summer day. Full article

Recently, the United States has experienced, on average, costs of USD 20 billion due to natural and climate disasters, such as hurricanes and wildfires. In this study, we focus on wildfires, which have occurred more frequently in the past few years. This paper examines how various factors, such as the PM10 levels, elevation, precipitation, SOX, population, and temperature, can influence the intensity of wildfires differently across counties in California. More specifically, we use Bayesian analysis to classify all counties of California into two groups: those with more wildfires and those with fewer wildfires. The Bayesian model incorporates prior knowledge and uncertainty for a more robust understanding of how these environmental factors impact wildfires differently among county groups. The findings show a similar effect of the SOX, population, and temperature, while the PM10, elevation, and precipitation have different implications for wildfires across various groups. Full article

Chest X-ray imaging is an essential tool in the diagnostic procedure for pulmonary conditions, providing healthcare professionals with the capability to immediately and accurately determine lung anomalies. This imaging modality is fundamental in assessing and confirming the presence of various lung issues, allowing for timely and effective medical intervention. In response to the widespread prevalence of pulmonary infections globally, there is a growing imperative to adopt automated systems that leverage deep learning (DL) algorithms. These systems are particularly adept at handling large radiological datasets and providing high precision. This study introduces an advanced identification model that utilizes the VGG16 architecture, specifically adapted for identifying various lung anomalies such as opacity, COVID-19 pneumonia, normal appearance of the lungs, and viral pneumonia. Furthermore, we address the issue of model generalizability, which is of prime significance in our work. We employed the data augmentation technique through CycleGAN, which, through experimental outcomes, has proven effective in enhancing the robustness of our model. The combined performance of our advanced VGG model with the CycleGAN augmentation technique demonstrates remarkable outcomes in several evaluation metrics, including recall, F1-score, accuracy, precision, and area under the curve (AUC). The results of the advanced VGG16 model showcased remarkable accuracy, achieving 98.58%. This study contributes to advancing generative artificial intelligence (AI) in medical imaging analysis and establishes a solid foundation for ongoing developments in computer vision technologies within the healthcare sector. Full article

Due to global development and increased public awareness of food’s effects on health, demands for innovative and healthy products have risen. Biodegradable and environmentally friendly polymer usage in modern food products is a promising approach to reduce the negative health and environmental effects of synthetic chemicals. Also, desirable features such as flavor, texture, shelf-life, storage condition, water holding capacity, a decrease in water activity, and an oil absorption of fried food have been improved by many polysaccharides. One of the important polymers, which is applied in the food industry, is alginate. Alginates are a safe and widely used compound in various industries, especially the food industry, which has led to innovative methods for for the improvement of this industry. Currently, different applications of alginate in stable emulsions and nano-capsules in food applications are due to the crosslinking properties of alginate with divalent cations, such as calcium ions, which have been studied recently. The main aim of this review is to take a closer look at alginate properties and applications in the food industry. Full article

Background: The lack of knowledge about physical responses to pickleball creates a clear gap about performance in this sport. The purpose of this study was to investigate neuromuscular fatigue caused by playing doubles pickleball. Methods: Recreational pickleball players (n = 32, mean age = 60.0 years) were recruited to perform sets of four countermovement jumps (CMJs) on a force plate before and after doubles pickleball matches. Results: For players who had not played a match prior to testing, there was a significant learning effect across trials within the baseline set of jumps for five outcomes from the CMJ test, including propulsive peak force (p = 0.005); however, there was no significant learning effect for jump height. There were significant improvements in the large effect size for all except one dependent variable (propulsive phase time) between the first and second set of jumps (i.e., after one match). Neither further increases nor decreases were seen after the second set of jumps. Conclusions: Participants saw significant increases in CMJ performance across trials after one pickleball match, indicating learning and potentiation effects. After three matches of doubles pickleball, no fatigue effect was detected. Full article