Search Results (49,346)

This article describes a non-isolated boost DC–DC configuration that uses a two-winding coupled inductor (CI) together with two synchronous power switches to acquire ultra-high voltage conversion at relatively low duty cycles. The proposed structure combines a quadratic gain stage with the coupled inductor to realize a substantial output voltage boost. The overall conversion ratio can be flexibly adjusted through two independent design factors: the duty cycle of the switches and the turns ratio of the coupled inductor providing additional degrees of freedom for optimization. The main merits of the converter are its very high voltage gain (VG), reduced voltage stress (VS) on the active switches, continuous input current, common ground between input and output, soft-switching operation for diodes D₃ and D₄, and the possibility of using a synchronized gate-drive scheme. The paper thoroughly examines the operating intervals, steady-state behavior, design procedure, and efficiency performance, and also develops a dynamic model for control-oriented analysis. To highlight its strengths, the proposed topology is systematically compared with several existing high-gain converters. Finally, experimental outcomes obtained from a 400-W laboratory prototype operating at 50 kHz confirm the feasibility and effectiveness of the proposed converter in achieving high voltage gain, reduced device voltage stress, and high efficiency under practical operating conditions. Full article

The long-run sustainability of pay-as-you-go pension systems crucially depends on the dynamic balance between social-security contributions paid by the working population and benefits paid to retirees. In Italy, the National Social Security Institute (INPS) manages the core of the public system, whose financial equilibrium is increasingly challenged by demographic aging, labor market fragility, and macroeconomic shocks. In this paper, in line with the aims of the Special Issue “Signal Processing and Machine Learning in Real-Life Processes”, we reinterpret the Italian pension system as a complex stochastic signal-processing problem. Using the most recent data published in the Annuario Statistico Italiano 2024 highlighting by ISTAT—with a focus on Protection and Social Security—we construct a set of time series describing contributions, benefits, coverage ratios and pension amounts, both at the national and territorial level. On this basis, we compare classical time-series models and a recurrent neural network with Long Short-Term Memory (LSTM) architecture for multi-step forecasting of the main aggregates. The signal-processing perspective allows us to disentangle trend, cyclical and shock components, while machine learning provides flexible nonlinear forecasting tools capable of capturing structural breaks such as the COVID-19 crisis. Our empirical results suggest that (i) pension expenditure remains high and persistent as a share of GDP; (ii) the contribution coverage ratio improved in 2022 but remains below the pre-pandemic level; and (iii) regional heterogeneity in the per-capita pension deficit is substantial and stable over time, with persistent imbalances in Southern regions and Islands. Finally, we perform a scenario analysis combining LSTM-based forecasts with demographic and labor market hypotheses, and we quantify the impact of alternative policy measures on the future pension deficit signal. The proposed framework, which integrates permutation-based inference, signal decomposition and deep learning, provides a reproducible template for the real-time monitoring of pension sustainability using official open data. Full article

Background/Objectives: Carrier-based dry powder inhaler (DPI) formulations remain the predominant platform for respiratory drug delivery. However, integrated development frameworks that align upstream particle engineering with downstream manufacturing are underdeveloped. This study aimed to develop a comprehensive Quality-by-Design (QbD) strategy that systematically connects jet milling, formulation design, and blending scale-up for carrier-based DPI products containing micronized crystalline active pharmaceutical ingredient (API). Methods: Phenytoin was selected as a model API to investigate process–formulation–performance relationships. Jet milling parameters were optimized to generate three distinct API particle size distributions while monitoring solid-state integrity. A design of experiments (DoE) evaluated the impact of API particle size and lactose fines level on aerodynamic performance (fine particle fraction, FPF) and powder processability (flowability, compressibility). High-shear and low-shear blending techniques were compared, and a novel V-shell blending scale-up methodology was developed based on maintaining particle fall velocity and total strain across multiple scales (one-, two-, and eight-quart). Results: Optimized jet milling produced inhalation grade API particles with controlled amorphous content localized to high-energy processes. DoE analysis identified a design space in which API Dv90 of 2.9–4.5 µm and coarse lactose <96% maximized both aerosolization and blend flowability. Low-shear blending achieved superior lung delivery (FPF 62.6 ± 1.7%) compared with high-shear micing (50.1 ± 1.5%). The particle-velocity-based scale up strategy produced statistically equivalent FPF and ED across all scales (p < 0.01), with content uniformity (RSD ≤ 5%) and variability comparable to commercial DPIs. Conclusions: This integrated QbD framework demonstrates that the co-optimization of particle size engineering, formulation composition, and blending dynamics is essential for achieving robust and scalable DPI products. The approach offers a material-sparing, efficient pathway from API characterization through commercial scale manufacturing and is broadly applicable to respiratory drug development. Full article

Drought is expected to intensify under climate change, posing significant risks to Mediterranean agroecosystems. This study provides long-term projections of drought and wetness conditions for three representative Mediterranean regions—Eastern Mancha (Spain), Sidi Bouzid Governorate (Tunisia), and the Beqaa Valley (Lebanon)—to support climate-resilient planning. Future monthly precipitation (2020–2050) was dynamically downscaled using the Weather Research and Forecasting (WRF) model under the RCP4.5 scenario, and the Standardized Precipitation Index (SPI12) was subsequently applied to quantify drought severity at annual and monthly scales. By integrating dynamically downscaled WRF projections with pixel-based SPI analysis across three spatially distinct Mediterranean regions, the study provides a novel, spatially explicit and comparative framework for assessing future drought and wetness extremes in support of climate-resilient planning. The results reveal spatial variability and moderate temporal fluctuations across the three regions, reflected in differing timings and intensities of their driest and wettest hydrological years. Spain is projected to experience its driest hydrological year in 2046–2047, Tunisia in 2030–2031, and Lebanon in 2047–2048. The wettest years are projected to occur in 2045–2046 for Spain and Tunisia, and in 2028–2029 for Lebanon. Although extreme drought events are not widely anticipated, localised severe dry periods emerge in many parts of the study areas. while in Lebanon, these conditions also extend into the winter and spring. These findings underscore the need for spatially targeted adaptation rather than uniform regional measures. Identifying both driest and wettest projected years enhances preparedness, informs water-resource optimisation, and supports agricultural land-use planning, especially in areas with favourable future climatic conditions. Integrating drought projections into multi-hazard planning (i.e., drought and floods) frameworks can further strengthen territorial resilience in regions facing increasing climate-related extremes. Full article

A novel Lithium triflate-incorporated Solid Polymer Electrolyte (SPE) has been developed by using the optimized blend of Ghatti Gum (GG) and Xanthan Gum (XG) with a biodegradable synthetic polymer, Polyvinyl alcohol (PVA), ethylene glycol as a plasticizer, and formaldehyde as a cross-linker for energy storage applications. They are examined by X-ray diffraction, Fourier transform infrared spectroscopy, and electrochemical impedance analysis. The frequency-dependent conductivity adheres to Joshner’s universal power law, with the TF10 composition achieving the higher ionic conductivity of 2.73 × 10⁻⁵ S cm⁻¹. Temperature-dependent conductivity confirms Arrhenius-type behavior and shows a low activation energy of 0.15 eV that supports facile ion transport. The conduction process in TF10 follows the Correlated Barrier Hopping (CBH) model. Dielectric and modulus investigations indicate relaxation dynamics with the shorter relaxation time (6.45 × 10⁻⁶ s) from tangent loss spectra. From the SEM analysis, the uniform distribution and the porous nature of the electrode activated carbon are confirmed. A supercapacitor is assembled with TF10 displays electric double-layer capacitive features, delivering a specific capacitance of 7.1 Fg⁻¹ at 15 mVs⁻¹. Charge–discharge analysis reveals energy and power densities of 2.52 Wh kg⁻¹ and 2500 W kg⁻¹, respectively, for the supercapacitor. Full article

Barley grass is an emerging forage potentially helping relieve the lack of green forage for livestock, and its nutritive value is influenced by kinds of cultivation conditions. This study was conducted to investigate the effect of cultivation temperature (25 °C vs. 30 °C) and seed sterilization (0.2% NaClO) on the dynamic changes in nutrient component, fermentation potential and bacterial community of hydroponic barley grass. The results showed that starch content (56.67%) in the barley grass gradually declined and cell wall components, crude protein, and ash concentrations increased, with 26–35% dry matter loss by 10 days of cultivation, where a higher cultivation temperature (30 °C) resulted in a higher fiber concentration (NDF 29.82% vs. 19.44%; ADF 12.57% vs. 8.02%) and a lower starch content (19.69% vs. 32.05%) while seed sterilization treatment resulted in an opposite result along with an improved dry matter recovery (73.33% vs. 70.15%). Furthermore, seed sterilization increased in vitro rumen gas production (GP₄₈ 55.97 vs. 50.50 mL/0.2 g DM) of the resulting barley grass, and its fermentation potential by 10 days of cultivation was much lower than that by 8 days. Bacterial diversity analysis revealed that seed sterilization decreased the richness and diversity of bacterial community, and the abundance of taxa Methyloversatilis, Parabacteroides, Phascolarctobacterum, Lactococcus, Pseudomonas might account for the difference in nutrient component. It is suggested that optimizing cultivation conditions like temperature and sterilization could significantly improve nutrient value and dry matter recovery of hydroponic barley grass, and the production cycle of hydroponic barley grass is no better if more than 8 days, where the bacterial community plays an indispensable role. Full article

Background: The integration of advanced 3D scanning and additive manufacturing technologies in stroke rehabilitation offers promising advancements in the design and production of ankle-foot orthoses. These technological innovations are progressively recognized for their potential to provide more precise and customized orthotic solutions for individuals with stroke-related impairments. Objectives: The primary aim of this study was to biomechanically test and validate the effectiveness of custom ankle-foot orthoses produced through additive manufacturing technology using data captured by a novel photogrammetric scanning system. The customized orthosis was compared with a standard prefabricated orthosis to assess their relative effectiveness in improving gait dynamics and patient satisfaction in stroke rehabilitation. Methods: Participants with equinovarus deformity, a common consequence of stroke, were fitted with custom ankle-foot orthoses, alongside conventional prefabricated orthoses. The study utilized the Qualisys^® motion analysis system for comprehensive biomechanical gait analysis, and the QUEST questionnaire was employed to capture participant feedback on both types of orthoses. Detailed comparisons of gait dynamics were conducted using Statistical Parametric Mapping with each orthosis. Results: The study revealed notable kinematic and kinetic differences between the custom and prefabricated orthoses. The custom orthoses demonstrated superior performance in enhancing gait efficiency, symmetry, and safety. Patient feedback favored the customized orthoses over the prefabricated variants, with higher scores in comfort, fit, and overall effectiveness. Conclusions: This research underscores the effectiveness of custom orthoses produced through additive manufacturing technology for stroke rehabilitation. By offering a comprehensive evaluation of orthotic interventions and establishing a comparative framework, the study serves as a reference point for future research, advocating for a more personalized and evidence-based approach in orthotic design for improving the quality of life of stroke survivors. Full article

Background: Plasma fibrinogen (FIB) levels exhibit a significant elevation during the acute phase of ischemic stroke (IS), and their dynamic fluctuations serve as important biomarkers for stroke onset, disease progression, and long-term prognosis. Tong-Qiao-Huo-Xue Decoction (TQHXD) is highly effective in treating blood stasis syndromes affecting the head and face. Nevertheless, the association between TQHXD and FIB in the underlying mechanism of treating IS warrants further investigation. Methods: Proteomics analysis predicted the potential therapeutic targets of TQHXD for IS. An in vivo model of middle cerebral artery occlusion followed by reperfusion (MCAO/R) was created in mice. To explore the interaction between FIB and NLRP3, as well as to verify the particular healing outcomes of TQHXD. Results: An increased blood–brain barrier (BBB) permeability was observed after MCAO/R, accompanied by substantial accumulation of FIB in the brain. In vivo experiments demonstrated that FIB triggered the activation of the NLRP3 inflammasome in microglia. Proteomic analysis revealed a significant increase in FIB levels following model induction, which were markedly reduced after treatment with TQHXD; KEGG pathway enrichment analysis indicated that these changes were primarily associated with the NOD-like receptor signaling pathway. Laser speckle contrast imaging showed that TQHXD treatment significantly improved cerebral blood flow and attenuated brain injury in mice. Fluorescence imaging, ELISA, and Western blotting results collectively demonstrated that TQHXD effectively reduced FIB accumulation and suppressed NLRP3 inflammasome activation. MD and pull-down experiments further demonstrated a strong interaction strength between FIB and NLRP3. Conclusions: FIB accumulates in the ischemic penumbra following CIRI, while TQHXD can effectively down-regulate FIB expression and inhibit NLRP3 inflammasome activation to mitigate CIRI. These findings provide a novel theoretical foundation and treatment direction for stroke management in clinical settings. Full article

MADS-box transcription factors are key regulators of plant development and environmental responses. Here, we performed an integrated phylogenomic and expression analysis of the MADS-box gene family in Capsicum annuum, identifying 97 members that fall into 52 Type I and 45 Type II genes. Comparative phylogeny, exon–intron organization, conserved motifs, and chromosomal mapping allowed classification into 15 subfamilies. Gene duplication analysis revealed that segmental duplication has been a major driver of family expansion. Expression profiling across multiple tissues, together with promoter cis-element prediction and stress-responsive transcriptome data, demonstrated that Type II genes exhibit broad and dynamic expression patterns, particularly under ABA treatment and temperature stress. A key finding of this study is the complete absence of the Mβ lineage, a Type I subfamily typically associated with gametophyte and endosperm development in other angiosperms. No Mβ-like sequences were detected in the pepper genome, and Type I genes overall showed extremely low expression, suggesting that the Mβ lineage has undergone lineage-specific evolutionary loss and that its functions may be compensated by other Type I members or by expanded Type II regulatory modules. Together, this study provides the first evidence for the evolutionary disappearance of the Mβ subfamily in Capsicum and offers a comprehensive resource for dissecting the developmental and stress-responsive roles of MADS-box genes in pepper. Full article

Against the backdrop of global digitalization and green development, digital innovation ecosystems have emerged as key drivers for advancing regional green innovation cooperation and achieving sustainable development goals. This study constructs a theoretical analytical framework encompassing “Actor-Resource-Environment.” Utilizing panel data from 30 Chinese provinces spanning 2012–2022, it employs machine learning and dynamic QCA methods to dissect the dynamic causal relationship between digital innovation ecosystems and regional green innovation cooperation. Key findings include: (1) Green innovation cooperation networks are evolving from a “core-periphery structure” toward new characteristics of multi-centered mutual coupling and coordination. (2) Different machine learning models yield varying effects on how digital innovation ecosystems influence regional green innovation cooperation, with the XGBoost model demonstrating the strongest performance. (3) No single element within the digital innovation ecosystem can serve as a necessary condition for driving regional green innovation cooperation. (4) Three configuration patterns emerge for achieving high-level regional green innovation cooperation, with digital innovation funding, digital talent resources, and digitally inclusive financial environments consistently serving as core prerequisites. These findings deepen our understanding of the complex causal mechanisms involving multi-factor matching and linkage that influence regional green innovation cooperation, offering valuable insights for advancing high-quality regional green innovation development. The research findings reveal the complex configuration pathways through which multidimensional elements of the digital innovation ecosystem collectively drive regional green innovation cooperation. This provides practical governance pathways for breaking down regional barriers and building highly resilient green innovation cooperation networks. Full article

Collaborative projects under the Horizon Europe Framework Program of the European Union typically involve a large number of partners from multiple countries. Data-centric projects, among them, often require integration of disparate data source formats and collection methods, leading to complex data management architectures and policies. This article is an extended version of an article presented at the 1st International Conference on Big Data Analytics and Applications (BDAA’2025). It explores design decisions, organisational principles, and technological solutions to address these challenges by focusing on data integration of data sources and the hybridisation of data services. This experience was gathered while working on DiverSea, a project dedicated to the analysis of biodiversity dynamics along European coastlines—ranging from the Black Sea to the Mediterranean and the North Sea. While grounded in established technologies, the project’s takeaways offer valuable insights for environmental data projects across aquatic, terrestrial, and atmospheric domains. Full article

Background: Prostate cancer is a leading malignancy among males, and conventional chemotherapy is often limited by insufficient tumor selectivity and systemic toxicity. Prostate-specific membrane antigen (PSMA), which is highly expressed on prostate cancer cells, represents a promising target for precision drug delivery. In this study, we developed a folate-modified, PSMA-targeting nanoliposome loaded with docetaxel (DFL) to enhance tumor specificity and therapeutic efficacy. Methods: DFL was prepared using a thin-film hydration–sonication method and characterized through physicochemical analyses. Cellular uptake and cytotoxicity were evaluated in PSMA-high LNCaP cells, with PSMA knockdown used to assess target-dependent internalization. Antitumor efficacy was examined with a microfluidic system and LNCaP xenograft nude mice, and safety was evaluated by measuring hepatic and renal biomarkers and performing histopathological analysis of major organs. Results: DFL demonstrated favorable physicochemical properties and significantly enhanced cellular uptake and cytotoxicity in LNCaP cells relative to control formulations. PSMA knockdown markedly attenuated cellular sensitivity to DFL, confirming PSMA-dependent internalization. A 3D microfluidic perfusion platform further corroborated robust and selective DFL uptake under dynamic flow conditions, thereby strengthening the translational relevance of the targeting effect beyond static cultures. In vivo, DFL substantially inhibited tumor progression in LNCaP xenograft models, reducing both tumor volume and weight by more than 50%. TUNEL assays showed increased apoptosis, and immunohistochemistry revealed reduced Ki-67 expression with concomitant upregulation of Caspase-3. No significant alterations in hepatic or renal biomarkers were observed, and histopathological evaluation demonstrated no treatment-associated lesions in major organs. Conclusions: A folate-modified, PSMA-targeting docetaxel nanoliposome was successfully developed, demonstrating enhanced tumor-specific drug delivery and improved antitumor activity with favorable biocompatibility in preclinical models. DFL represents a promising nanomedicine strategy for the precision chemotherapy of prostate cancer. Full article

This review analyzes the transition from silicon to wide-bandgap (WBG) and ultrawide-bandgap (UWBG) semiconductor materials for power electronics, focusing on Silicon Carbide (SiC) and Gallium Nitride (GaN) technologies. Following a PRISMA-based systematic review methodology, we analyzed 94 peer-reviewed publications spanning device technology, converter architectures, and system applications. We employ a bottom-up approach, progressing from fundamental material properties through device architectures and converter topologies to system-level implications. We examine how intrinsic material properties enable operation at elevated temperatures, voltages, and frequencies while minimizing losses. Through analysis of Figures of Merit and system-level Key Performance Indicators, we quantify WBG benefits across automotive, industrial, renewable energy, and consumer electronics sectors, demonstrating 3–5× power density improvements and 20–40% cost reductions. The review presents emerging device technologies, including vertical GaN for medium-voltage applications and monolithic bidirectional switches (BDSs), enabling single-stage power conversion. We provide the first comprehensive topology-level comparison of emerging vertical GaN and monolithic bidirectional switches against established SiC solutions, identifying specific applications where each technology offers advantages. A comprehensive topology-by-topology comparison between SiC and GaN is provided, offering design guidelines for device selection. The review addresses practical constraints, including dynamic on-resistance degradation, threshold voltage instability, and electromagnetic interference challenges for both SiC and GaN. Finally, we examine emerging UWBG materials ($\beta$-Ga${}_2$O${}_3$, AlN, c-BN, Diamond) and their development status, manufacturing challenges, supply chain considerations, and commercialization prospects for ultra-high-voltage applications. Full article

Background: Sepsis is a life-threatening organ dysfunction that results from an exaggerated host immune response to disseminated infection. The relationship between lymphopenia and sepsis has been extensively studied, and in particular, sepsis-induced lymphopenia is gradually being recognized as an essential factor in the prognosis of sepsis. Notably, sepsis-induced lymphopenia has been associated with worse outcomes, including increased risk of secondary infections, multiple organ failure, and death. Few studies have directly compared the dynamic evolution of lymphocyte counts between different etiologies of sepsis or evaluated their prognostic value using serial measurements. This study aims to explore the temporal dynamics of lymphopenia, but also of neutrophil-to-lymphocyte (NLR) ratio in patients with severe systemic infections and to assess their relationship with in-hospital mortality. Methods: A prospective cohort of 95 adult patients was analyzed. Absolute lymphocyte counts (ALCs) and neutrophil-to-lymphocyte (NLR) ratio values were recorded on Days 1, 3, 5, and 7. Comparisons were made between different infectious etiologies and outcomes, and ROC analysis assessed predictive performance. Results and conclusions: Patients with viral sepsis (“COVID-19”) showed a significant and sustained decrease in lymphocyte counts (p < 0.001) and a progressive increase in NLR (p < 0.001), unlike patients with bacterial sepsis. In correlation with outcome, regardless of etiology, lymphocyte counts were significantly lower in non-survivors from Day 3 onward, while NLR was significantly higher on Day 7 (p = 0.002). Early NLR and ALC had limited predictive value, but longitudinal trends were associated with poor prognosis. Full article

Ag-Sn-S/Se semiconductors, particularly Ag₈SnS₆ and Ag₈SnSe₆, have emerged as promising thermoelectric (TE) materials due to their intrinsically low lattice thermal conductivity and favorable electronic transport properties. Owing to their direct and super-narrow bandgaps, these semiconductors also hold significant potential for photovoltaic (PV) applications, especially in near-infrared (NIR) energy harvesting and tandem architecture. This review provides a detailed analysis of the synthesis strategies, crystallographic evolution, phase transition mechanisms, and bandgap modulation in Ag-Sn-S/Se semiconductors. Particular focus is given to the structural adaptability of argyrodite-type compounds, where intrinsic cationic disorder and halogen-assisted anion substitution collectively enable the fine-tuning of electronic transport and lattice dynamics. TE performance is evaluated in terms of carrier mobility and thermal conductivity, highlighting a significant improvement in figure of merit. The review further explores the potential of Ag-Sn-S/Se semiconductors in energy conversion PVs, particularly as photoabsorber layers and counter electrode materials. Despite initial demonstrations, systematic studies on device integration remain limited, highlighting substantial opportunities for future research aimed at optimizing their optoelectronic interfaces and overall PV performance. This review ultimately discusses the potential of Ag-Sn-S/Se semiconductors, emphasizing their tunable properties as being key to next-generation PV and thermoelectric technologies. It highlights the current achievements and unresolved challenges, outlining strategic pathways for future research and device integration. Full article