Organic room temperature phosphorescent (ORTP) materials with stimuli-responsive, multicomponent emissive behaviour are extremely desirable for various applications. The derivative of cyclic triimidazole (TT) functionalized with an ethynyl group, TT-CCH, is isolated and investigated. The compound possesses crystallization-enhanced emission (CEE) comprising dual fluorescence and dual phosphorescence of both molecular and supramolecular origin with aggregation-induced components highly sensitive to grinding. The mechanisms involved in the emissions have been disclosed thanks to combined structural, spectroscopic and computational investigations. In particular, strong CH⋯N hydrogen bonds are deemed responsible, for the first time in the TT family, together with frequently observed π⋯π stacking interactions, for the aggregated fluorescence and phosphorescence. Full article

Currently, the visual detection of a target’s shock flow field through background schlieren technology is a novel detection system. However, there are very few studies on the long-distance background schlieren imaging mechanism and its application in system design in the field of target detection. This paper proposes a design optimization method for space-based BOS detection system metrics. By establishing sensitivity evaluation models and image signal-to-noise ratio evaluation models for BOS detection systems, the influence of the different flight parameters and key parameters of BOS systems (detection spectral bands and spatial resolution) on target detection efficiency is explored. Furthermore, an optimization method based on the image signal-to-noise ratio of the BOS system and the overall metrics for specific scenarios are provided. The simulation results demonstrate that under satellite background images and speckle background images, the system metrics can detect and identify the schlieren of high-speed targets, with better applicability to disordered and complex real background images. This research contributes to advancing the development of high-speed target detection technology based on BOS. Full article

The interaction of heparin with antithrombin (AT) involves a specific sequence corresponding to the pentasaccharide GlcNAc/NS6S-GlcA-GlcNS3S6S-IdoA2S-GlcNS6S (AGA*IA). Recent studies have revealed that two AGA*IA-containing hexasaccharides, which differ in the sulfation degree of the iduronic acid unit, exhibit similar binding to AT, albeit with different affinities. However, the lack of experimental data concerning the molecular contacts between these ligands and the amino acids within the protein-binding site prevents a detailed description of the complexes. Differential epitope mapping (DEEP)-STD NMR, in combination with MD simulations, enables the experimental observation and comparison of two heparin pentasaccharides interacting with AT, revealing slightly different bound orientations and distinct affinities of both glycans for AT. We demonstrate the effectiveness of the differential solvent DEEP-STD NMR approach in determining the presence of polar residues in the recognition sites of glycosaminoglycan-binding proteins. Full article

Background: Recent studies have investigated the effects of exercise on the functional capacity of older adults; training with a balance exercise assist robot (BEAR) effectively improves posture. This study compared the clinical safety and efficacy of training using BEAR video games to conventional resistance training in older adults with cardiovascular disease (CVD). Methods: Ninety patients (mean age: 78 years) hospitalized due to worsening CVD were randomized to cardiac rehabilitation (CR) Group R (conventional resistance training) or Group B (training using BEAR). After appropriate therapy, patients underwent laboratory testing and functional evaluation using the timed up-and-go test (TUG), short physical performance battery (SPPB), and functional independence measure (FIM) just before discharge and 4 months after CR. The rates of CVD readmission, cardiac death, and fall-related fractures were monitored. Results: BEAR had no adverse effects during exercise. At 4 months, TUG and SPPB improved significantly in both groups, with no significant difference between them. FIM motor and the Geriatric Nutritional Risk Index were significantly improved in Group B versus Group R. There was no significant difference in cardiac events and fall-related fractures between the two groups. Conclusion: CR with BEAR is safe and comparable to conventional resistance training for improving balance in older adults with CVD. Full article

The selection of multiple contingency scenarios is a key task to perform resilience-oriented long-term planning analyses. However, the identification of relevant multiple contingencies may easily lead to combinatorial explosion issues, even for relatively small systems. This paper proposes an effective methodology for the identification of relevant multiple contingencies and their probabilities, suitable for the long-term resilience analysis of large power systems. The methodology is composed of two main pillars: (1) the clustering of lines that are more likely to fail together, to reduce the computational complexity of the analysis exploiting historical weather data and (2) the probability-based identification of multiple contingencies within each cluster, where the contingency probability is computed applying the copula theory. Tests performed on a portion of the Italian EHV transmission system confirm the validity of the clustering results compared against historical failure events. Moreover, the copula-based algorithm for contingency probability estimation passes the tests carried out on relatively large clusters with very low error tolerance. The method successfully pinpoints critical multiple contingency scenarios and their likelihoods, making it valuable for assessing power system resilience over long-term horizons in support of resilience-oriented planning activities. Full article

Tellurium exhibits exceptional intrinsic electronic properties. However, investigations into the modulation of tellurium’s electronic properties through physical modification are notably scarce. Here, we present a comprehensive study focused on the evolution of the electronic properties of tellurium crystal flakes under plasma irradiation treatment by employing conductive atomic force microscopy and Raman spectroscopy. The plasma-treated tellurium experienced a process of defect generation through lattice breaking. Prior to the degradation of electronic transport performance due to plasma irradiation treatment, we made a remarkable observation: in the low-energy region of hydrogen plasma-treated tellurium, a notable enhancement in conductivity was unexpectedly detected. The mechanism underlying this enhancement in electronic transport performance was thoroughly elucidated by comparing it with the electronic structure induced by argon plasma irradiation. This study not only fundamentally uncovers the effects of plasma irradiation on tellurium crystal flakes but also unearths an unprecedented trend of enhanced electronic transport performance at low irradiation energies when utilizing hydrogen plasma. This abnormal trend bears significant implications for guiding the prospective application of tellurium-based 2D materials in the realm of electronic devices. Full article

Based on the previous work conducted by Fujii et al., NdBaInO₄ compounds present modest oxide-ion conductivities. Therefore, it has been an attractive system of significant interest. In this study, we attempted to partially substitute Ca for Nd and the total electrical conductivity was successfully improved due to the generation of oxygen vacancies. The synthesis, crystal structure, density, surface topography, and electrical properties of NdBaInO₄ and Ca-doped NdBaInO₄ have been studied, respectively. NdBaInO₄ and 10% and 20% molar fractions of Ca-doped NdBaInO₄ were synthesized through solid-state reactions. The crystal structure of them was obtained from Le Bail refinement of the XRD pattern, giving the result of the monoclinic structure, which belongs to P2₁/c space group. The highest total electrical conductivity of 4.91 × 10⁻³ S cm⁻¹ was obtained in the Nd_0.9Ca_0.1BaInO_3.95 sample at a temperature of 760 °C in the dry atmosphere and the activation energy was reduced from 0.68 eV to 0.58 eV when the temperature was above 464 °C (737 K) after doping the NdBaInO₄ with a 0.1 molar fraction of Ca²⁺. Moreover, the total conductivity of Nd_0.9Ca_0.1BaInO_3.95 in the wet atmosphere at moderate temperature was relatively higher than that in the dry atmosphere, which suggests that potential proton conduction may exist in wet atmospheres. In addition, the oxygen diffusion coefficients of Nd_0.9Ca_0.1BaInO_3.95 (D* = 1.82 × 10⁻⁸ cm²/s, 850 °C) was about two times higher than that of Nd_0.8Ca_0.2BaInO_3.90 (D* = 7.95 × 10⁻⁹ cm²/s, 850 °C) and was increased significantly by two orders of magnitude when compared with the oxygen diffusion coefficient of the undoped NdBaInO₄ (D* = 8.25 × 10⁻¹¹ cm²/s, 850 °C). Full article

Terpenoid alkaloids are recognized as a class of compounds with limited numbers but potent biological activities, primarily derived from plants, with a minor proportion originating from animals and microorganisms. These alkaloids are synthesized from the same prenyl unit that forms the terpene skeleton, with the nitrogen atom introduced through β-aminoethanol, ethylamine, or methylamine, leading to a range of complex and diverse structures. Based on their skeleton type, they can be categorized into monoterpenes, sesquiterpenes, diterpenes, and triterpene alkaloids. To date, 289 natural terpenoid alkaloids, excluding triterpene alkaloids, have been identified in studies published between 2019 and 2024. These compounds demonstrate a spectrum of biological activities, including anti-inflammatory, antitumor, antibacterial, analgesic, and cardioprotective effects, making them promising candidates for further development. This review provides an overview of the sources, chemical structures, and biological activities of natural terpenoid alkaloids, serving as a reference for future research and applications in this area. Full article

The development of analytical procedures, in line with the recent regulatory requirements ICH Q2 (R2) and ICH Q14, is progressing, and it must be able to manage the entire life cycle of the methodology. This is also applicable to and especially challenging for combinations of drug substances and dosage form. A reliable and efficient, stability-indicating, MS-compatible, reverse-phase ultra-performance liquid chromatographic (UPLC^®) method was developed for the determination of carvedilol and felodipine in a combination oral dosage form. The development of the method, performed using analytical quality by design (AQbD) principles, was in line with the future regulatory requirements. Furthermore, the fixed-dose combination dosage forms are a clear solution to the polypharmacy phenomenon in the elderly population. The main factors evaluated were the mobile phase buffer, organic modifier, column, flow, and column temperature. The optimum conditions were achieved with a Waters Acquity HSS T3 (100 × 2.1 mm i.d., 1.8 µm) column at 38 °C, using ammonium acetate buffer (5 mM, pH 4.5) (Solution A) and MeOH (Solution B) as mobile phases in gradient elution (t = 0 min, 10% B; t = 1.5 min, 10% B; t = 12.0 min, 90% B; t = 13.0 min, 10% B; t = 15.5 min, 10% B) at a flow rate of 0.2 mL/min and UV Detection of 240 and 362 nm for carvedilol (CAV) and felodipine (FLP), respectively. The linearity was demonstrated over concentration ranges of 30–650 µg/mL (R² = 0.9984) (CAV) and 32–260 µg/mL (R² = 0.9996) (FLP). Forced degradation studies were performed by subjecting the samples to hydrolytic (acid and base), oxidative, and thermal stress conditions. Standard solution stability was also performed. The proposed validated method was successfully used for the quantitative analysis of bulk, stability, and fixed-dose combination dosage form samples of the desired drug product. Using the AQbD principles, it is possible to generate methodologies with improved knowledge, leading to high-quality data, lower operation costs, and minimum regulatory risk. Furthermore, this work paves the way for providing a platform of robust analytical methods for the simultaneous quantification of innovative on-demand new dose combinations. Full article

Background and Objectives: Early discharge after childbirth has led to a rise in neonatal readmission, thereby becoming a major concern in recent decades. Our research aimed to identify the risk factors and incidence of neonatal readmission and explore preventive measures. Materials and Methods: Our study at the Clinical Hospital of Pediatrics in Ploiești, Romania, included 108 neonates admitted during the neonatal period. Results: This accounted for 2.06% of all admissions (5226). The most prevalent cases were malnutrition (25%), fever (20.3%), and bronchiolitis (17.5%). Diarrhea and infectious gastroenteritis were also observed (14.8%), along with acute rhinoconjunctivitis (9.2%) and late-onset sepsis (3.7%). No deaths were recorded. The most significant characteristics identified were number of children (p < 0.001) and age at maternity discharge (p < 0.001). By following the prevention rules, malnutrition, feeding errors, and infections can be avoided. This includes practicing proper hand hygiene for both mothers and medical staff, as well as educating and demonstrating to mothers the benefits of breastfeeding. In addition, all newborns discharged from the maternity ward would benefit from follow-up at 7–10 days of life. Conclusions: Our results confirm the effectiveness of a multidisciplinary team and endorse the promotion of breastfeeding. Implementing quality control measures and regularly evaluating the surveillance program will help improve its effectiveness. Full article

Electrochemical biosensors include a recognition component and an electronic transducer, which detect the body fluids with a high degree of accuracy. More importantly, they generate timely readings of the related physiological parameters, and they are suitable for integration into portable, wearable and implantable devices that are significant relative to point-of-care diagnostics scenarios. As an example, the personal glucose meter fundamentally improves the management of diabetes in the comfort of the patients’ homes. This review paper analyzes the principles of electrochemical biosensing and the structural features of electrochemical biosensors relative to the implementation of health monitoring and disease diagnostics strategies. The analysis particularly considers the integration of the biosensors into wearable, portable, and implantable systems. The fundamental aim of this paper is to present and critically evaluate the identified significant developments in the scope of electrochemical biosensing for preventive and customized point-of-care diagnostic devices. The paper also approaches the most important engineering challenges that should be addressed in order to improve the sensing accuracy, and enable multiplexing and one-step processes, which mediate the integration of electrochemical biosensing devices into digital healthcare scenarios. Full article

Accurately calculating the annual yield of floating PV (FPV) systems necessitates incorporating appropriate FPV-specific heat loss coefficients into the calculation, including both wind-dependent and wind-independent factors. The thermal behavior of several FPV systems has been investigated within this study, through the analysis of heat loss coefficients across various system sizes and configurations. Over a one-year period, data were collected from two measurement sites with three distinct systems: two ~50 kWp demonstrator-scale setups of Solarisfloat (azimuthal tracking) and Solar Float (East-West orientation) and a 2 MWp commercial-scale East–West system by Groenleven. The Solarisfloat demonstrator revealed a wind-dependent heat loss coefficient of 3.2 m³/Ks. In comparison, the Solar Float demonstrator system displayed elevated wind-dependent heat loss coefficients, measuring 4.0 W/m³Ks for the east-facing module and 5.1 W/m³Ks for the west-facing module. The Groenleven system, which shares design similarities with Solar Float, showed lower wind-dependent heat loss coefficients of 2.7 W/m³Ks for the east-facing module and 2.8 W/m³Ks for the west-facing module. A notable discrepancy in the wind-dependent coefficients, particularly evident under a north wind direction, indicates a more efficient convective cooling effect by the wind on the demonstrator scale system of Solar Float. This could possibly be attributed to improved wind flow beneath its PV modules, setting it apart from the Groenleven system. Additionally, a thermal model founded on a ‘balance-of-energy’ methodology, integrating water temperature as a variable was introduced. The heat loss coefficient, dependent on the surface water temperature, fluctuated around zero, depending on whether the water temperature surpassed or fell below the ambient air temperature. It can be concluded that it is not of added value to introduce this floating specific heat loss coefficient parameter, as this parameter can be integrated in the wind speed independent U_c parameter. Full article

Trajectory planning plays a crucial role in achieving unmanned excavator operations. The quality of trajectory planning results heavily relies on the level of rules extracted from objects such as scenes and optimization objectives, using traditional theoretical methods. To address this issue, this study focuses on professional operators and employs machine learning methods for job trajectory planning, thereby obtaining planned trajectories which exhibit excellent characteristics similar to those of professional operators. Under typical working conditions, data collection and analysis are conducted on the job trajectories of professional operators, with key points being extracted. Machine learning is then utilized to train models under different parameters in order to obtain the optimal model. To ensure sufficient samples for machine learning training, the bootstrap method is employed to adequately expand the sample size. Compared with the traditional spline curve method, the trajectories generated by machine learning models reduce the maximum speeds of excavator boom arm, dipper stick, bucket, and swing joint by 8.64 deg/s, 10.24 deg/s, 18.33 deg/s, and 1.6 deg/s, respectively; moreover, the error does not exceed 2.99 deg when compared with curves drawn by professional operators; and, finally, the trajectories generated by this model are continuously differentiable without position or velocity discontinuities, and their overall performance surpasses that of those generated by the traditional spline curve method. This paper proposes a trajectory generation method that combines excellent operators with machine learning and establishes a machine learning-based trajectory-planning model that eliminates the need for manually establishing complex rules. It is applicable to motion path planning in various working conditions of unmanned excavators. Full article

The gut microbiota and its related metabolites differ between inflammatory bowel disease (IBD) patients and healthy controls. In this study, we compared faecal volatile organic compound (VOC) patterns of paediatric IBD patients and controls with gastrointestinal symptoms (CGIs). Additionally, we aimed to assess if baseline VOC profiles could predict treatment response in paediatric IBD patients. We collected faecal samples from a cohort of de novo therapy-naïve paediatric IBD patients and CGIs. VOCs were analysed using gas chromatography–ion mobility spectrometry (GC-IMS). Response was defined as a combination of clinical response based on disease activity scores, without requiring treatment escalation. We included 109 paediatric IBD patients and 75 CGIs, aged 4 to 17 years. Faecal VOC profiles of paediatric IBD patients were distinguishable from those of CGIs (AUC ± 95% CI, p-values: 0.71 (0.64–0.79), <0.001). This discrimination was observed in both Crohn’s disease (CD) (0.75 (0.67–0.84), <0.001) and ulcerative colitis (UC) (0.67 (0.56–0.78), 0.01) patients. VOC profiles between CD and UC patients were not distinguishable (0.57 (0.45–0.69), 0.87). Baseline VOC profiles of responders did not differ from non-responders (0.70 (0.58–0.83), 0.1). In conclusion, faecal VOC profiles of paediatric IBD patients differ significantly from those of CGIs. Full article

Guided by entering the deep sea and achieving deep marine development in marine construction, the factors hindering marine construction cannot be ignored. Strong ocean winds have a devastating impact on tasks such as ship navigation, carrier aircraft take-off and landing, naval operations and military exercises, and affect the planning of sea routes and the development of the long-distance sea. This paper uses ERA5 wind field data and key climate indices to conduct a systematic analysis of catastrophic winds in the global ocean using methods such as climate statistical analysis, the Theil–Sen trend method, Pearson correlation and contribution rate calculation. It points out the spatiotemporal distribution, variation trend, climate index correlation and contribution rate characteristics of strong winds occurrence (SWO) and hopes that the results of this study can serve as a guide for maritime route planning and provide technical assistance and decision-making support for marine development and other needs. The results show the following: The high global SWO occurs in the Southern Ocean, the North Atlantic, the North Pacific, near Taiwan, China, the Arabian Sea and other locations, with the strongest SWO in summer. The growth trend of SWO in the Southern Ocean is strongest, with decreasing regions near the Arabian Sea and the Bay of Bengal, and the growth trend is reflected in all four seasons. The climate indices with the strongest correlation and highest contribution to the global SWO are AAO (Antarctic Oscillation) and EP–NP (East Pacific–North Pacific pattern) with a correlation between −0.5 and 0.5 and a contribution rate of up to −50%~50%. Full article

Mechanical failures in the operating stacks of solid oxide fuel cells (SOFCs) are frequently related to thermal stresses generated by a temperature gradient and its variation. In this study, a computational fluid dynamics (CFD) model is developed and further applied in full-size SOFC stacks, which are fully coupled and implemented for analysis of heat flow electrochemical phenomena, aiming to predict thermal stress distribution. The primary object of the present investigation is to explore features and characteristics of the thermal stress influenced by electrochemical reactions and various transport processes within the stacks. It is revealed that the volume ratio of the higher thermal stress region differs nearly 30% for different stack flow configurations; the highest probability of potential failure appears in the cell cathodes; the more cells applied in the stack, the greater the difference in the predicted temperature/thermal stress between the cells; the counter-flow stack performs the best in terms of output power, but the predicted thermal stress is also higher; the cross-flow stack exhibits the lowest thermal stress and a lower output power; and although the temperature and thermal stress distributions are similar, the differences between the unit cells are bigger in the longer stacks than those predicted for shorter stacks. The findings from this study may provide a useful guide for assessing the thermal behavior and impact on SOFC performance. Full article

Utilizing hydrogen as a viable substitute for fossil fuels requires the exploration of hydrogen storage materials with high capacity, high quality, and effective reversibility at room temperature. In this study, the stability and capacity for hydrogen storage in the Sc-modified C₃N₄ nanotube are thoroughly examined through the application of density functional theory (DFT). Our finding indicates that a strong coupling between the Sc-3d orbitals and N-2p orbitals stabilizes the Sc-modified C₃N₄ nanotube at a high temperature (500 K), and the high migration barrier (5.10 eV) between adjacent Sc atoms prevents the creation of metal clusters. Particularly, it has been found that each Sc-modified C₃N₄ nanotube is capable of adsorbing up to nine H₂ molecules, and the gravimetric hydrogen storage density is calculated to be 7.29 wt%. It reveals an average adsorption energy of −0.20 eV, with an estimated average desorption temperature of 258 K. This shows that a Sc-modified C₃N₄ nanotube can store hydrogen at low temperatures and harness it at room temperature, which will reduce energy consumption and protect the system from high desorption temperatures. Moreover, charge donation and reverse transfer from the Sc-3d orbital to the H-1s orbital suggest the presence of the Kubas effect between the Sc-modified C₃N₄ nanotube and H₂ molecules. We draw the conclusion that a Sc-modified C₃N₄ nanotube exhibits exceptional potential as a stable and efficient hydrogen storage substrate. Full article

Background: Artificial intelligence (AI) algorithms can be applied in breast cancer risk prediction and prevention by using patient history, scans, imaging information, and analysis of specific genes for cancer classification to reduce overdiagnosis and overtreatment. This scoping review aimed to identify the barriers encountered in applying innovative AI techniques and models in developing breast cancer risk prediction scores and promoting screening behaviors among adult females. Findings may inform and guide future global recommendations for AI application in breast cancer prevention and care for female populations. Methods: The PRISMA-SCR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) was used as a reference checklist throughout this study. The Arksey and O’Malley methodology was used as a framework to guide this review. The framework methodology consisted of five steps: (1) Identify research questions; (2) Search for relevant studies; (3) Selection of studies relevant to the research questions; (4) Chart the data; (5) Collate, summarize, and report the results. Results: In the field of breast cancer risk detection and prevention, the following AI techniques and models have been applied: Machine and Deep Learning Model (ML-DL model) (n = 1), Academic Algorithms (n = 2), Breast Cancer Surveillance Consortium (BCSC), Clinical 5-Year Risk Prediction Model (n = 2), deep-learning computer vision AI algorithms (n = 2), AI-based thermal imaging solution (Thermalytix) (n = 1), RealRisks (n = 2), Breast Cancer Risk NAVIgation (n = 1), MammoRisk (ML-Based Tool) (n = 1), Various MLModels (n = 1), and various machine/deep learning, decision aids, and commercial algorithms (n = 7). In the 11 included studies, a total of 39 barriers to AI applications in breast cancer risk prediction and screening efforts were identified. The most common barriers in the application of innovative AI tools for breast cancer prediction and improved screening rates included lack of external validity and limited generalizability (n = 6), as AI was used in studies with either a small sample size or datasets with missing data. Many studies (n = 5) also encountered selection bias due to exclusion of certain populations based on characteristics such as race/ethnicity, family history, or past medical history. Several recommendations for future research should be considered. AI models need to include a broader spectrum and more complete predictive variables for risk assessment. Investigating long-term outcomes with improved follow-up periods is critical to assess the impacts of AI on clinical decisions beyond just the immediate outcomes. Utilizing AI to improve communication strategies at both a local and organizational level can assist in informed decision-making and compliance, especially in populations with limited literacy levels. Conclusions: The use of AI in patient education and as an adjunctive tool for providers is still early in its incorporation, and future research should explore the implementation of AI-driven resources to enhance understanding and decision-making regarding breast cancer screening, especially in vulnerable populations with limited literacy. Full article

Objective: Non-alcoholic fatty liver disease (NAFLD) is strongly associated with hyperlipidemia, which is closely related to high levels of sugar and fat. β-sitosterol is a natural product with significant hypolipidemic and cholesterol-lowering effects. However, the underlying mechanism of its action on aquatic products is not completely understood. Methods: A high-fat diet (HFD)-induced NAFLD zebrafish model was successfully established, and the anti-hyperlipidemic effect and potential mechanism of β-sitosterol were studied using oil red O staining, filipin staining, and lipid metabolomics. Results: β-sitosterol significantly reduced the accumulation of triglyceride, glucose, and cholesterol in the zebrafish model. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that differential lipid molecules in β-sitosterol mainly regulated the lipid metabolism and signal transduction function of the zebrafish model. β-sitosterol mainly affected steroid biosynthesis and steroid hormone biosynthesis in the zebrafish model. Compared with the HFD group, the addition of 500 mg/100 g of β-sitosterol significantly inhibited the expression of Ppar-γ and Rxr-α in the zebrafish model by at least 50% and 25%, respectively. Conclusions: β-sitosterol can reduce lipid accumulation in the zebrafish model of NAFLD by regulating lipid metabolism and signal transduction and inhibiting adipogenesis and lipid storage. Full article

Mesoporous/hierarchical zeolites (HZs) are a relatively new group of materials, and interest in their application in catalysis is continuously growing. This paper presents recent achievements in the application of mesoporous zeolites in catalytic reactions of nitrogen pollutant conversion. The analysis presented includes processes such as selective catalytic reduction of NO_x with ammonia (NH₃-SCR, DeNO_x), selective catalytic oxidation of ammonia (NH₃-SCO, AMO_x), and catalytic decomposition of N₂O. Different zeolite topologies and methods of their modification focused on mesoporosity generation (e.g., desilication, dealumination, steaming, self-assembly techniques, and application of hard and soft templates) are reviewed and compared with respect to catalytic processes. Special attention is paid to the role of porous structure and acidity, as well as the form of deposited transition metals, in the catalytic activation of modified zeolites in the elimination of nitrogen pollutants from flue gases. Full article

With the advancement of distributed power generation technology and the deepening of the low-carbon transformation of energy structure, a high proportion of renewable energy has become an inevitable trend in future energy systems, especially for microgrids. However, the volatility and uncertainty associated with renewable energy pose significant challenges to the secure and stable operation of power systems, necessitating the exploration of the flexible regulation of resources. Energy storage, as a crucial flexible resource characterized by technological diversity and a variety of regulation capabilities, has been extensively studied and applied. Nonetheless, the high investment costs and limited returns of energy storage technology, coupled with the ambiguous utility in different scenarios under the current electricity market’s framework, complicate its broader application. To thoroughly analyze the utility of energy storage in facilitating flexible adjustments in microgrids, this study developed a composite weight-TODIM (an acronym in Portuguese for interactive and multi-criteria decision making) model for assessing the utility of energy storage that incorporates heterogeneity in the risk preferences. This model enabled a comparative analysis of the utility of energy storage technology across multiple scenarios, taking the risk preferences of decision-makers into account, thereby providing strategic insights for the application of multi-temporal energy storage in microgrids. The feasibility and effectiveness of the model were validated through a case study analysis. Full article

Monitoring horizontal displacements, such as landslides and tectonic movements, holds great importance and high-cost geodetic GNSS equipment stands as a crucial tool for the precise determination of these displacements. As the utilization of low-cost GNSS systems continues to rise, there is a burgeoning interest in evaluating their efficacy in measuring such displacements. This evaluation is particularly vital as it explores the potential of these systems as alternatives to high-cost geodetic GNSS systems in similar applications, thereby contributing to their widespread adoption. In this study, we delve into the assessment of the potential of the dual-frequency U-Blox Zed-F9P GNSS system in conjunction with a calibrated survey antenna (AS-ANT2BCAL) for determining horizontal displacements. To simulate real-world scenarios, the Zeiss BRT 006 basis-reduktionstachymeter was employed as a simulation device, enabling the creation of horizontal displacements across nine different magnitudes, ranging from 2 mm to 50 mm in increments of 2, 4, 6, 8, 10, 20, 30, 40, and 50 mm. The accuracies of these simulated displacements were tested through low-cost GNSS observations conducted over a 24 h period in open-sky conditions. Additionally, variations in observation intervals, including 3, 6, 8, and 12 h intervals, were investigated, alongside the utilization of the relative positioning method. Throughout the testing phase, GNSS data were processed using the GAMIT/GLOBK GNSS (v10.7) software, renowned for its accuracy and reliability in geodetic applications. The insightful findings gleaned from these extensive tests shed light on the system’s capabilities, revealing crucial information regarding its minimum detectable displacements. Specifically, the results indicate that the minimum detectable displacements with the 3-sigma rule stand at 22.8 mm, 11.7 mm, 8.7 mm, and 4.8 mm for 3 h, 6 h, 8 h, and 12 h GNSS observations, respectively. Such findings are instrumental in comprehending the system’s performance under varying conditions, thereby informing decision-making processes and facilitating the adoption of suitable GNSS solutions for horizontal displacement monitoring tasks. Full article