Search Results (421)

The separation of three proton pump inhibitors (omeprazole, lansoprazole, and rabeprazole) as exemplified molecules containing chiral sulfoxide groups was investigated in polar organic liquid chromatographic mode on seven different polysaccharide stationary phases (Chiralcel OD and OJ; Chiralpak AD, AS, and IA; Lux Cellulose-2 and -4). Different alcohols, such as methanol, ethanol, 1-propanol, 2-propanol, and their combinations, were used as eluents. After method optimization, semi-preparative enantioseparation was successfully applied for the three proton pump inhibitors to collect the individual enantiomers. A detailed investigation was conducted into elution order reversal, thermodynamic parameters, the effect of eluent mixtures, and the hysteresis of retention time and selectivity. Using Chiralpak AS, containing the amylose tris[(S)-α-methylbenzylcarbamate] chiral selector, the separation of the investigated enantiomers was achieved in all four neat eluents, with methanol providing the best results. In many cases, a reversal of the enantiomer elution order was observed. In addition to chiral-selector-dependent reversal, eluent-dependent reversal was also observed. Notably, even replacing methanol with ethanol altered the enantiomer elution order. Both enthalpy- and entropy-controlled enantioseparation were also observed in several cases; however, temperature-dependent elution order reversal was not. The hysteresis of retention and selectivity was further investigated on amylose-type columns in methanol–2-propanol and methanol–ethanol eluent mixtures. The phenomenon was observed on all amylose columns regardless of the eluent mixtures employed. Hystereticity ratios were calculated and used to compare the hysteresis behaviors of different systems. Multivariate statistical analysis revealed that Chiralpak AS exhibited the most distinct enantioselective behavior among the tested columns, likely due to the absence of a direct connection between the carbamate moiety and the aromatic substituent. The present study aided in understanding the mechanisms leading to enantiomer recognition, which is crucial for developing new chiral stationary phases and chiral HPLC method development in general. Full article

Energy security is a global and strategic issue that is vital to national economic and social development. The conflict between Russia and Ukraine has profoundly changed the world’s energy trade structure and brought great challenges to global energy security, especially to the European Union (EU). Under this background, this study tries to construct a conceptual framework for energy security from trade and selects the EU as a case to analyze its energy security evolution at both the regional and national scales. The findings of this paper are as follows. (1) In the context of energy transition, oil and gas remain pivotal components due to their longstanding historical presence. However, they are also the most susceptible elements within the EU’s energy system. (2) The level of oil security within the EU is higher than that of natural gas. The level of oil security in member countries varies considerably, with significant geographic disparities. Aside from the exception of the Netherlands and Denmark, the majority of member countries exhibit a consistently low level of natural gas security. (3) From 1991 to 2021, the EU’s energy security pattern underwent significant changes, exhibiting a general downward trend due to the increased utilization of natural gas. In light of the aforementioned research outcomes, this paper seeks to offer policy recommendations for the enhancement of the EU’s energy security. Full article

This paper presents a method of evaluating energy and environmental factors before and after chilled water production system retrofitting at an industrial facility. A general algorithm was used for the analysis of chilled water system retrofitting at a pharmaceutics factory. Two retrofitting variants based on dual-stage absorption chillers supplied from an existing gas-fueled co-generation plant were identified. The proposed variants, i.e., tri-generation systems, were compared with the basic variant, which relied on electric compression water chillers. An evaluation of the variants was performed on the basis of two criteria: annual primary energy consumption and annual carbon dioxide emission. Variant 2, i.e., with a 1650 kW dual-stage absorption water chiller supplied from an existing gas fueled co-generation plant, was chosen as the optimal variant. It achieved a 370 MWh annual primary energy consumption reduction and a 1140 Mg annual carbon dioxide emission reduction. It was found that increasing the co-generation ratio for the CHP plant powering the pharmaceutical factory resulted in lower consumption of primary energy in variants in which the cooling energy supply system was retrofitted based on absorption water chillers. The threshold values of the co-generation ratio were e = 0.37 for Variant 1 and e = 0.34 for Variant 2. A literature survey revealed that there is limited interest in the application of such a solution in industrial plants. The performed analysis showed that the evaluated systems may nonetheless be an attractive option for pharmaceutics factories, leading to the reduction of primary energy consumption and carbon dioxide emissions, thereby making more electrical power available for core production. The lessons learned during our analysis could be easily transferred to other industrial facilities requiring chilled water production systems. Full article

The detection of zinc ions plays an essential role in protecting public health and maintaining ecological balance. However, traditional fluorescent probes for Zn²⁺ are limited in their specificity, especially under complex environments, due to their single-mode optical signal and inadequate recognization capacities. Herein we report a dual-mode supramolecular sensing system constructed from a unique three-component assembly involving a terpyridine platinum (II) complex, oxalate, and Zn²⁺, enabling highly specific detection performance for Zn²⁺. The supramolecular sensing system exhibits excellent selectivity among various interfering substances, accompanied by ultra-low detection limit (0.199 μM) and fast response (<3 s). The high recognization capacity comes from tri-component-based supramolecular assembly, while the dual-mode response arises from the generation of intermelcular Pt-Pt and π-π interactions, which yields absorption and emission originating from low-energy metal–metal-to-ligand charge transfer (MMLCT) transitions. This work marks a pioneering demonstration for highly specific detection of Zn²⁺ and inspires an alternative strategy for designing cation probes. Full article

Biofouling, the undesirable deposition of microorganisms on surfaces, is ubiquitous in aqueous systems. This is no different for systems running with water-miscible metalworking fluids (MWFs), which additionally contain many organic chemicals that create favorable conditions for growth and metabolism. Biofilm formation is thus inevitable, as there is no shortage of wetted surfaces in metalworking systems. MWF manufacturers tried in vain to offer resistance by using biocides and biostatic compounds as ingredients in concentrates and as tank-side additives. We report here that such elements, alone or as components of MWFs, did not prevent biofilm formation and had negligible effects on pre-established laboratory biofilms. Moreover, biofilms in metalworking systems are interwoven with residues, sediments, and metal swarfs generated during machining. Again, co-incubation of such “real” biofilms with MWFs had no significant effect on population size—but on population composition! The implications of this finding are unclear but could provide a starting point for the treatment of biofouling, as biofilm population structure might be of importance. Finally, we show that bacteria gain function in biofilms and that they were able to degrade a toxic amine in MWFs, which the same bacteria were unable to do in planktonic form. Full article

The replication machinery of SARS-CoV-2 is a primary target for therapeutic intervention, and has led to significant progress in antiviral medication discovery. This review consolidates contemporary molecular insights into viral replication and rigorously assesses treatment methods at different phases of viruses’ clinical development. Direct-acting antivirals, such as nucleoside analogs (e.g., remdesivir, molnupiravir) and protease inhibitors (e.g., nirmatrelvir), have shown clinical effectiveness in diminishing morbidity and hospitalization rates. Simultaneously, host-targeted medicines like baricitinib, camostat, and brequinar leverage critical host–virus interactions, providing additional pathways to reduce viral replication while possibly minimizing the development of resistance. Notwithstanding these advancements, constraints in distribution methods, antiviral longevity, and the risk of mutational evasion demand novel strategies. Promising investigational approaches encompass CRISPR-mediated RNA degradation systems, inhalable siRNA-nanoparticle conjugates, and molecular glue degraders that target host and viral proteins. Furthermore, next-generation treatments aimed at underutilized enzyme domains (e.g., NiRAN, ExoN) and host chaperone systems (e.g., TRiC complex) signify a transformative approach in antiviral targeting. The integration of high-throughput phenotypic screening, AI-driven medication repurposing, and systems virology is transforming the antiviral discovery field. An ongoing interdisciplinary endeavor is necessary to convert these findings into versatile, resistance-resistant antiviral strategies that are applicable beyond the present pandemic and in future coronavirus epidemics. Full article

The present study evaluates the viability of fabricating unmanned aerial vehicle (UAV) propellers using fused filament fabrication (FFF), with an emphasis on low-cost, desktop-scale production. The study’s backdrop is the recent adoption of UAVs and advancements in additive manufacturing. While the scope targets accessibility for individual and small-scale users, the results have broader implications for scalable UAV propulsion systems. The research was conducted within an experimental UAV development framework aimed at optimizing propeller performance through strategic material selection, geometrical design optimization, and additive manufacturing processes. Six propeller variants were manufactured using widely available thermoplastic polymers, including polyethylene terephthalate glycol-modified (PETG) and thermoplastic polyurethane (TPU), as well as photopolymer-based propellers fabricated using vat photopolymerization, also known as digital light processing (DLP). Mechanical and aerodynamic characterizations were performed to assess the structural integrity, flexibility, and performance of each material under dynamic conditions. Two blade configurations, a toroidal propeller with anticipated aerodynamic advantages and a conventional tri-blade propeller (Gemfan 51466-3)—were comparatively analyzed. The primary contribution of this work is the systematic evaluation of performance metrics such as thrust generation, acoustic signature, mechanical strength, and thermal stress imposed on the electrical motor, thereby establishing a benchmark for polymer-based propeller fabrication via additive manufacturing. The findings underscore the potential of polymeric materials and layer-based manufacturing techniques in advancing the design and production of UAV propulsion components. Full article

As the world’s population grows and energy demand increases, there is a need to switch from fossil fuels to renewable energy. In order to preserve the environment and meet these growing demands, especially for cooling applications, trigeneration systems could be the answer. The aim of this work is to provide a structured overview of the current state of the art in the field of trigeneration (CCHP) systems. Firstly, these systems and their applications are presented. An overview of the different indicators used to describe the performance of these systems is given. A comparison between CCHP (combined cooling, heat, and power) systems is made. Finally, improvements and other concepts found in the literature are presented. This review will later serve as a basis for the exergo-economic optimization of a low-temperature CCHP system based on renewable energy sources. Therefore, more attention is given to the technologies used for such systems. Full article

Background: Investment decisions in stocks are one of the most complex tasks due to the uncertainty of which stocks will increase or decrease in their values. A diversified portfolio statistically reduces the risk; however, stock choice still substantially influences the profitability. Methods: This work proposes a methodology to automate investment decision recommendations with clear explanations. It utilizes generative AI, guided by prompt engineering, to interpret price predictions derived from neural networks. The methodology also includes the Artificial Intelligence Trust, Risk, and Security Management (AI TRiSM) model to provide robust security recommendations for the system. The proposed system provides long-term investment recommendations based on the financial fundamentals of companies, such as the price-to-earnings ratio (PER) and the net margin of profits over the total revenue. The proposed explainable artificial intelligence (XAI) system uses DeepSeek for describing recommendations and suggested companies, as well as several charts based on Shapley additive explanation (SHAP) values and local-interpretable model-agnostic explanations (LIMEs) for showing feature importance. Results: In the experiments, we compared the profitability of the proposed portfolios, ranging from 8 to 28 stock values, with the maximum expected price increases for 4 years in the NASDAQ-100 and S&P-500, where both bull and bear markets were, respectively, considered before and after the custom duties increases in international trade by the USA in April 2025. The proposed system achieved an average profitability of 56.62% while considering 120 different portfolio recommendations. Conclusions: A t-Student test confirmed that the difference in profitability compared to the index was statistically significant. A user study revealed that the participants agreed that the portfolio explanations were useful for trusting the system, with an average score of 6.14 in a 7-point Likert scale. Full article

Most bioplastics are based on polysaccharides, which are either synthesized from a variously sourced monomer or extracted from some biomass waste. In many cases, some lignocellulosic fibers are then added to the obtained bioplastics to form biocomposites and extend their range of applications beyond packaging films and generically easily biodegradable materials. Plant-extracted tannins, which, as such, might also be building blocks for bioplastics, do nonetheless represent a useful complement in their production when added to polysaccharide-based plastics and biocomposites, since they offer other functions, such as bioadhesion, coloration, and biocidal effect. The variety of species used for tannin extraction and condensation is becoming very wide and is also connected with the local availability of amounts of bio-waste from other productions, such as from the food system. This work tries to summarize the evolution and recent developments in tannin extraction and their increasing centrality in the production of polysaccharide-based plastics, adhesives, and natural fiber composites. Full article

This paper examines farmers’ perceptions about organic certification procedures by focusing on the complexity and effectiveness of the procedures required. Also, this paper tries to shed some light on the challenges faced by farmers in implementing the certification specifications and looks for ways to improve the process. Overall, investigating farmers’ perceptions of the organic certification standards is an important step toward promoting and improving organic agriculture, as it helps to tailor the certification system to better meet farmers’ needs and concerns. The conducted analysis first provides some valuable insights into the general knowledge of farmers’ motivations and preferences for adopting organic farming. The analysis revealed the influence of concurrent agricultural activities (conventional and organic) on the perceptions and preferences of farmers. Thus, this study highlights the differences between organic and conventional growers regarding compliance issues and perceptions of specifications, adding depth and practical significance to this study. Overall, the research constitutes an important contribution to the understanding of organic agriculture, deepening the general knowledge of farmers’ motivations and preferences in this field. Full article

Control engineering plays an indispensable role in enhancing safety, improving comfort, and reducing fuel consumption and emissions for various industries, for which system identification, control, and optimization are primary topics. Alternatively, artificial intelligence (AI) is a leading, multi-disciplinary technology, which tries to incorporate human learning and reasoning into machines or systems. AI exploits data to improve accuracy, efficiency, and intelligence, which is beneficial, especially in complex and challenging cases. The rapid progress of AI facilitates major changes in control engineering and is helping advance the next generation of system identification, control, and optimization methods. In this study, we review the developments, key technologies, and recent advancements of AI-based system identification, control, and optimization methods, as well as present potential future research directions. Full article

This paper explores how generative AI can enhance the modelling and optimization of maintenance policies by incorporating real-time problem-solving techniques into structured maintenance frameworks. Maintenance policies, evolving from simple calendar-dependent or age-dependent preventive maintenance strategies to more complex approaches involving partial system replacement, minimal repairs, or imperfect maintenance, have traditionally been optimized based on minimizing costs, maximizing reliability, and ensuring operational continuity. In this work, we leverage AI models to simulate and analyze the implementation and overlap of different maintenance strategies to an industrial asset, including the combined use of different preventive (total and partial replacement) and corrective actions (minimal repair and normal repairs), with perfect or imperfect maintenance results. Integrating generative AI with well-established maintenance policies and optimization criteria, this paper tries to demonstrate how AI-assisted tools can model maintenance scenarios dynamically, learning from predefined strategies and improving decision-making in real-time. Python-based simulations are employed to validate the approach, showcasing the benefits of using AI to enhance the flexibility and efficiency of maintenance policies. The results highlight the potential for AI to revolutionize maintenance optimization, particularly in single-unit systems, and lay the groundwork for future studies in multi-unit systems. Full article

The energy crisis has highlighted the need for a significant change in Kosovo’s lignite-based electrical energy system, particularly greater investments in renewable energy sources. These sources would provide greater price stability, centralized accessibility, and relatively affordable investment costs. This research tries to analyze the basic attitudes behind the behavior of the students from the agricultural faculty in Kosovo in order to acquire a better understanding of their preferences for renewable energy source purchases, using the Best–Worst Scaling (BWS) method and cluster analysis. Students’ perspectives on renewable energy show strong environmental and price conscientiousness in BWS methods (first and second rank), while the rate of eco-skeptic students reaches only 23% in the cluster analysis, which is a very promising sign of the younger generation’s growing dedication to sustainability. Students, as future decision-makers, can play a critical role in making the transition to a more sustainable and resilient agricultural system. Green transition in Kosovo can be reached by combining the importance of dissemination and marketing tools with the pressing demand for renewable energy solutions, which might be interesting not only for Kosovo, but (considering the expectable enlargement) also for the EU. Full article

The periodical distribution of N and C atoms in carbon nitride (CN) not only results in localized electrons in each tri-s-triazine unit, but oxidation and reduction sites are in close contact spatially, resulting in severe carrier recombination. Herein, the hydrothermal method was first employed to synthesize carbon nitride (HCN), and then picolinamide (Pic) molecules were introduced at the edge of the carbon nitride so that the photo-generated electrons of the whole structure of the carbon nitride system were transferred from the center to the edge, which effectively promoted the separation of photo-generated carriers and inhibited the recombination of carriers in the structure. The introduced picolinamide not only changed the π-conjugated structure of the entire system but also acted as an electron-withdrawing group to promote charge transfer. The photocatalytic hydrogen evolution rate (HER) of the optimized HCN-Pic-1:1 sample could reach 918.03 μmolg⁻¹ h⁻¹, which was 11.8 times higher than that of the HCN, and the performance also improved. Full article