Search Results (2,645)

To address the issues of information leakage risks faced by the base station (BS) when communicating with multiple users in an integrated sensing and communication (ISAC) system, as well as the blockage of the direct link between the BS and the target to be detected, which limits sensing functionality, this paper introduces the active intelligent reflecting surface (IRS) into the ISAC system. By creating a virtual line-of-sight (LoS) path, signal blockage is effectively mitigated, while the active IRS enhances the incident signal strength and adjusts the reflection phase shifts, thereby improving the reliability and security of communication. This paper proposes a joint optimization scheme for the active IRS-assisted ISAC system, which jointly designs the BS beamforming and the IRS reflection coefficient matrix. A non-convex optimization problem is formulated with the objective of maximizing the radar output signal-to-noise ratio (SNR) subject to communication performance constraints. To solve this problem, this paper employs an iterative algorithm based on alternating optimization (AO), fractional programming (FP), and semidefinite relaxation (SDR). Simulation results demonstrate that the proposed scheme significantly outperforms the benchmark schemes without IRS assistance and with passive IRS assistance in terms of enhancing the sensing performance of the ISAC system. Full article

Thermal processing of biomass can induce chemical transformations that lead to the formation of fluorescent carbonaceous products. In this study, six β-glucan-rich medicinal mushrooms, Ganoderma lucidum, Cordyceps sinensis, Inonotus obliquus, Lentinula edodes, Grifola frondosa, and Hericium erinaceus, were subjected to mild pyrolytic treatment (200 °C for 3 h) to investigate the formation of water-soluble fluorescent fractions. Physicochemical characterization of aqueous extracts was performed using high-performance liquid chromatography size-exclusion chromatography (HPLC-SEC), fluorescence emission spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and β-glucan quantification. Fluorescence emission spectra revealed species-dependent differences in emission intensity, with the most pronounced signals observed for G. lucidum and C. sinensis. HPLC-SEC analysis showed only minor changes in molecular weight distribution after thermal treatment, suggesting limited polymer degradation. FTIR spectra indicated moderate structural modifications consistent with partial carbonization and chemical rearrangement within the mushroom matrices. Despite the mild processing conditions, measurable increases in fluorescence intensity were observed in several species, indicating the formation of fluorescent carbon-rich molecular structures. These findings demonstrate that moderate thermal treatment of β-glucan-rich fungal biomass can generate water-soluble fluorescent carbonaceous fractions without extensive breakdown of the original polysaccharide matrix. The results provide new insights into thermally induced photophysical changes in medicinal mushrooms and contribute to understanding the formation of fluorescent carbonaceous products from natural biomaterials. Full article

Purchasing portfolio models, particularly the Kraljic matrix, are widely used to support sourcing decisions under supply risk. Yet, they are often criticized for relying on subjective assessments and focusing mainly on upstream uncertainty while neglecting downstream demand volatility. This study develops a quantitatively grounded purchasing portfolio framework that integrates demand volatility and lead-time volatility into a unified measure of supply risk to support more sustainable sourcing decisions. Using transactional data for 876 stock-keeping units (SKUs) from a pharmaceutical distribution company, demand and lead-time volatility are measured through coefficients of variation and combined using an adjusted multifactor model that accounts for their interdependence. Financial importance is measured objectively through gross profit and classified according to the 80–20 Pareto principle. These metrics are incorporated into a revised purchasing portfolio matrix that classifies items into strategic, leverage, bottleneck, and routine categories. The findings reveal substantial variation in combined volatility across SKUs and show that incorporating demand uncertainty significantly changes portfolio positioning compared with traditional approaches. By linking purchasing and marketing perspectives, the proposed model reduces subjectivity, improves risk visibility, and supports sustainable sourcing and inventory decisions in volatile environments. Full article

Cultural ecosystem services (CES) provide non-material benefits that support human well-being and motivate ecosystem conservation, yet their subjectivity and spatial ambiguity complicate quantitative assessment and management. Taking the Changbai Mountain tourism area as a case, we adopted the ecosystem service matrix method to assess the CES supply score based on the natural system and human system. The service coverage density was obtained through accessibility, thereby quantifying the available supply index for each tourist source area. In addition, we quantified CES demand using a questionnaire survey. Demand for 10 CES types was measured via preference ranking and integrated with the entropy weight method; statistical analysis and GIS mapping were used to examine spatial patterns and influencing factors. Results show that: (1) The overall CES demand in the Changbai Mountain tourism area exhibits clear spatial differentiation, with higher demand in the central and eastern regions and lower demand in the northwest. High-demand areas are mainly concentrated in cities relatively close to the Changbai Mountain tourism area. (2) Among individual CES, recreation (r = 6.58), natural landscapes (r = 6.35), and aesthetic value (r = 6.19) receive the highest demand, and demand structure is significantly associated with occupation, education level, consumption level, and spatial distance. The results indicate that cultural services dominated by knowledge-based services are significantly positively correlated with educational level (r = 0.549, p < 0.001). (3) CES supply capacity shows strong seasonal fluctuations, and is frequently overloaded during peak seasons, leading to prominent supply–demand conflicts; with the exception of Shenyang, Dalian, Jilin and Anshan, the other 17 cities exhibit supply–demand imbalance. By integrating multiple CES types and multiple drivers, this study reveals spatial matching patterns of CES supply and demand in a complex mountain ecotourism region and provides evidence to support ecotourism management, service capacity improvement, and sustainable development. Full article

Milkfish (Chanos chanos), a widely consumed fish in the Philippines, is highly perishable, and conventional freshness assessments based on physical and olfactory inspection are often subjective and unreliable. To address this, we introduce an electronic nose system for the accurate classification of milkfish freshness based on spoilage-related gas emissions, namely methane, ammonia, hydrogen sulfide, and trimethylamine. The system integrates the MQ-series sensors and Taguchi gas sensor with Arduino Nano and Raspberry Pi 5 for data acquisition and signal processing. The k-nearest neighbor algorithm was used for classification, and its performance was evaluated using a confusion matrix. The data was gathered from 100 samples, consisting of 50 fresh and 50 spoiled fish. The evaluation demonstrated a peak classification accuracy of 92% for k-values between 1 and 15, confirming the system’s reliability. These findings indicate the system’s potential as a practical, low-cost, and efficient tool for enhancing consumer safety and quality assurance in the fish supply chain. Full article

This paper presents a systematic methodology for time-domain modeling of three-phase power transformers aimed at electromagnetic transient analysis in shipboard and embedded electrical systems. Accurate modeling of transformers in such environments is critical, as naval power systems are subject to strict electromagnetic compatibility (EMC) requirements and are particularly susceptible to fast transients caused by switching operations, fault events, and nonlinear loads operating in confined and isolated grids. The proposed approach combines the Vector Fitting (VF) algorithm with Clarke modal decomposition to obtain stable, passive, and causal rational approximations of the frequency-dependent admittance matrix over a wide frequency range. The admittance matrix is first identified from frequency-domain measurements or simulations, capturing the transformer’s terminal behavior across multiple frequency sub-bands. Clarke’s transformation is then applied to decouple the three-phase system into independent modal components—namely the zero-sequence and positive-sequence modes, reducing the original multi-phase problem to a set of independent single-phase systems. This modal decoupling significantly improves computational efficiency without sacrificing accuracy, as each mode can be fitted and simulated independently. Full article

The increasing demand for high-quality grapes necessitates rapid and objective quality assessment methods to overcome the limitations of traditional subjective and destructive techniques. This study investigated the feasibility of using hyperspectral imaging combined with machine learning for non-destructive quality evaluation of fresh grapes. Hyperspectral data were acquired from four table grape varieties (“Rose”, “Yongyou”, “Xiahei”, and “Jumbo”), and their Soluble Solids Content (SSC) was measured, which varied significantly among varieties. We extracted texture features using the Gray-Level Co-occurrence Matrix (GLCM) from images at key wavelengths, which were a combination of those selected by the Successive Projections Algorithm (SPA) and sensitive wavelengths. Comparative models for variety classification (qualitative) and SSC prediction (quantitative) were built using Extreme Learning Machine (ELM), Convolutional Neural Network (CNN), and Partial Least Squares (PLS) with full-range spectra and texture features as inputs. The results showed that the ELM model using full-range spectra was superior for both tasks, achieving a classification accuracy of 97.56% and, for SSC prediction, an $R_p^2$ of 0.75 and an RMSEP of 0.81. Notably, CNN models also showed considerable robustness. Our findings confirm that combining hyperspectral imaging with machine learning is a viable strategy for fresh grape quality assessment. Full article

In a previous study, we demonstrated that a novel surface treatment applied to laser-melted Ti6Al4V substrates supports osteoblast-like cell adhesion, proliferation, and the activation of early osteogenic pathways. Building on these preliminary findings, the present work aimed to further investigate the ability of the same surface to promote extracellular matrix (ECM) deposition, organization, and osteogenic maturation, which are critical events for the establishment of a stable bone–implant interface in subperiosteal dental implants. Human osteoblast-like MG-63 cells were cultured on Ti6Al4V discs subjected to different surface treatments, including a proprietary surface modification (ATcs) specifically designed for subperiosteal applications. ECM formation and maturation were evaluated through scanning electron microscopy coupled with energy-dispersive spectroscopy, immunofluorescence, and semiquantitative analyses of osteogenic markers type I collagen (COL1A1), secreted protein acidic and rich in cysteine (SPARC), and dentin matrix protein 1 (DMP1) through Western blotting. The results showed that, while all tested surfaces supported cell adhesion, the ATcs surface promoted a distinct osteogenic profile characterized by enhanced DMP1 expression, organized collagen deposition, and the formation of calcium–phosphate–rich mineralized structures. Compared to surfaces that primarily stimulated cell proliferation or early matrix production, ATcs appeared to favour progression toward late-stage osteogenic maturation and matrix mineralization. Taken together, these findings extend our previous observations and indicate that this novel surface treatment not only supports osteoblast viability and early differentiation but also promotes extracellular matrix maturation, a key prerequisite for effective osseointegration. Although further in vivo studies are required, the present data provide additional biological rationale for the use of ATcs-treated Ti6Al4V surfaces in next-generation custom-made subperiosteal implant designs. Full article

Diet plays a fundamental role in maintaining human health, which has intensified scientific interest in bioactive food constituents and contributed to the development of functional foods. Polyphenols, one of the most important groups of plant secondary metabolites, are valued for their strong antioxidant properties and potential health benefits. Species belonging to the Rosaceae family, including Rosa, Crataegus, and Pyracantha, are recognized as promising sources of phenolic compounds, although their chemical profiles and antioxidant potential remain insufficiently characterized. The aim of this study was to quantitatively assess selected phenolic compounds in extracts obtained from ripe fruits of selected Rosaceae species and cultivars. The extracts were prepared using ultrasound-assisted solvent extraction, pressurized liquid extraction, and matrix solid-phase dispersion. The resulting samples were subsequently subjected to comprehensive analyses of their chemical composition and antioxidant capacity. These extraction techniques differ substantially in their operational principles and process parameters; notably, ultrasound-assisted solvent extraction and pressurized liquid extraction require more complex and tightly controlled conditions, whereas matrix solid-phase dispersion constitutes a comparatively simpler and less parameter-dependent approach. The results revealed distinct phenolic profiles among the examined species and confirmed the presence of compounds exhibiting strong antioxidant activity. Collectively, these findings broaden current knowledge of the phytochemical diversity present in Rosaceae fruits and underscore their potential as natural sources of bioactive constituents relevant to the development and formulation of functional food products. Full article

Fibromyalgia (FM) is a complex chronic syndrome marked by widespread musculoskeletal pain, neurocognitive dysfunction (“fibro-fog”), and autonomic disturbances. Clinical management remains challenging due to subjective symptom reporting and the lack of definitive diagnostics. Emerging evidence points to a multifactorial origin involving central sensitization, neuroendocrine imbalance, and systemic immune-inflammatory alterations. A wide array of candidate biomarkers has been reported in FM, encompassing neurotransmitters (serotonin, norepinephrine), excitatory and inhibitory amino acids, metabolic and glycolytic enzymes, stress-related proteins, autoantibodies, oxidative stress markers and pro-inflammatory cytokines. This molecular heterogeneity reflects the systemic and multidimensional nature of FM. However, most of these biomarkers have been primarily investigated in serum or plasma, where analytical validation and reference ranges are more established. In contrast, the exploration of salivary biomarkers—although highly attractive due to its non-invasive, stress-free, and repeatable collection—remains comparatively limited. Saliva contains a reduced concentration range of many systemic markers and is strongly influenced by circadian rhythms, stress, flow rate, and oral health conditions. While promising candidates such as α-amylase, cortisol, calgranulins, and selected metabolic enzymes have shown potential in saliva, many proposed FM-related biomarkers lack full analytical validation, standardized protocols, and clinically defined reference intervals in this matrix. In this context, non-invasive electrochemical biosensors represent a transformative technological approach. Advanced electrode architectures incorporating nucleic acid probes, redox reporters, and nanostructured materials offer high sensitivity in low-volume and low-concentration biofluids such as saliva. The integration of multiplexed biomarker panels into portable platforms could enable real-time, longitudinal monitoring of FM pathophysiology, supporting phenotype stratification, personalized therapeutic adjustment, and objective disease activity tracking. Full article

Background/Objectives: Soy flour has been proposed as a functional ingredient to improve the protein and fiber content of foods; however, its metabolic and sensory effects, particularly in individuals at elevated risk for metabolic disease, remain insufficiently characterized. This randomized, repeated-measures study examined whether substituting refined wheat or corn flour with soy flour influences postprandial glucose and insulin plasma concentrations, appetite ratings, and product acceptability in adults with overweight or obesity. Methods: Participants (N = 17) attended at least three separate visits during which they consumed, in random order, a food matrix with 0% (control), 10%, or 30% soy flour substitution. Food matrices included breads (n = 10), tortillas (n = 10), and arepas (n = 8); some participants completed more than one matrix. Postprandial plasma glucose and insulin concentrations were measured at baseline and at 15, 30, 60, 90, and 120 min post-ingestion. Subjective hunger, satiety, and product liking were assessed using a 10 cm visual analog scale. Results: Compared with the control condition, substituting 30% of refined flour with soy flour significantly reduced the area under the concentration–time curve for postprandial glucose for breads (p = 0.03) and arepas (p = 0.04), and reduced plasma glucose concentrations at 90–120 min for tortillas (p = 0.0009). In contrast, postprandial insulin concentrations and subjective hunger and satiety ratings did not differ across substitution levels or food matrices (all p > 0.05). Importantly, even 30% soy flour substitution maintained product liking. Conclusions: Incorporating up to 30% soy flour may improve postprandial glycemic responses without compromising overall liking, supporting its potential as a practical food reformulation strategy to improve metabolic health in populations at increased risk of metabolic disease. Full article

The load characteristics of the helicopter tail rotor system are critical to flight safety and handling performance, and flight testing remains the most direct and reliable means to obtain authentic load data. In this paper, the well-established Wheatstone bridge strain measurement method is adopted to carry out accurate load testing on the helicopter tail rotor system. The tail rotor assembly mainly consists of the tail rotor shaft, pitch link, and tail rotor blades, which undertake different load transfer tasks during flight. Under actual operating conditions, the tail rotor shaft bears significant axial tension as well as combined lateral and vertical bending moments; the pitch link is primarily subjected to alternating axial tension and compression; and the tail rotor blades withstand complex loads including flapping bending, lagwise bending, and torsional moments. According to the distinct stress characteristics and force transmission paths of each component, targeted flight test maneuvers are reasonably designed. These maneuvers include steady-level flight at low, medium, and high speeds, zigzag climbing flight, near-ground side-rear flight, as well as deceleration-to-sprint and obstacle slope maneuvers specified in ADS-33E. Key flight parameters are selected for in-depth analysis to reveal the load distribution and dynamic variation patterns of the tail rotor under typical operating conditions. On this basis, a helicopter load risk test point matrix is established to identify high-risk working conditions and key monitoring positions. This study provides a solid theoretical and data foundation for subsequent flight test monitoring and structural strength verification. It effectively reduces flight test risks, improves monitoring efficiency and accuracy, and helps cut down the human, material, and financial costs associated with flight test monitoring. The research results can also provide important references for the design optimization and safety evaluation of helicopter tail rotor systems. Full article

Exosomes (EXs) mediate intercellular communication in the tissue microenvironment. We previously demonstrated that endothelial progenitor cell-derived exosomes (EPC-EXs) from exercised mice protect neurons and cerebral endothelial cells from hypoxia- and hypertension- induced injury ex vivo, suggesting their therapeutic potential in hypertensive ischemic injury. Here, we investigated whether exercise-conditioned EPC-EXs (ET-EPC-EXs) confer protection against acute ischemic injury. Hypertensive transgenic mice were divided into donor and recipient groups. Donor mice underwent treadmill exercise to generate ET-EPC-EXs. Recipient mice was subjected to middle cerebral artery occlusion and received ET-EPC-EXs via tail vein injection (2 × 10⁸/100 μL saline) two hours after stroke onset. Cerebral blood flow (CBF) was assessed, and brains were collected on day two for histological and molecular analyses. Our data showed that ET-EPC-EXs were robustly taken up by cerebral cells, predominantly in the penumbra in the ipsilateral hemisphere. ET-EPC-EXs reduced cell death and microglia activation and restored tight-junction proteins. Moreover, ET-EPC-EX treatment preserved CBF and improved sensorimotor function on day two post-stroke. Mechanistically, ET-EPC-EXs suppressed p38 activation, accompanied by reduced matrix metalloproteinase-3 and cytochrome c levels in the ipsilateral brain. Collectively, these findings demonstrate that EPC-EXs from exercise mice improve sensorimotor functions and confer protection in hypertensive ischemic brain injury, likely through attenuation of neuroinflammation and preservation of vascular integrity via modulation of the p38 signaling. Full article

Biometric systems are widely used in security and forensic applications. Conventionally, contact-based footprint scanners require physical contact, which presents significant limitations. These devices raise hygiene concerns and are impractical in field identification conditions, such as forensic investigations or disaster victim identification, where quick and non-invasive methods are essential. To address these challenges, a contactless footprint acquisition and identification system was developed using image processing techniques and a Convolutional Neural Network (CNN) based on the Visual Geometry Group–16 layer architecture. The system employs a Raspberry Pi 4, a Logitech C922 camera, and a ring light to capture footprints without direct surface contact. Captured images are processed with Contrast Limited Adaptive Histogram Equalization (CLAHE) to improve contrast and mean thresholding to generate binary images for clearer feature extraction. System performance was evaluated using a multiclass confusion matrix. The CNN correctly classified 158 of 160 test images, achieving an accuracy of 98.75%. This result demonstrates higher accuracy than earlier studies that used older CNN models, such as Alex Krizhevsky’s Network and LeCun’s Network-5, which performed with fewer subjects and lower accuracy rates. The developed system shows potential for biometric security, forensic investigations, and disaster response, where contactless and reliable identification is required. Future research can expand the dataset with more diverse footprints, test performance under varied conditions, and extend the approach to other contactless biometrics such as palmprints or ears. Full article

The paper presents SFPD, the new open algorithm developed by the University of Padova (PD in the acronym) for computing the steady-state regime due to any number of simultaneous faults (SF at the beginning of the acronym) both short circuits and open conductors. The algorithm does not have simplified hypotheses, since it benefits from the pre-fault regime based on PFPD_MCA (power flow by University of Padova with multiconductor cell analysis), a multiconductor power flow (developed and published by the first author) which takes into account both the active conductors (i.e., the phases subjected to the impressed voltages) and the passive conductors (i.e., the interfered metallic conductors, namely earth wires of overhead lines, metallic screens and armors of land and submarine cables, enclosures of gas insulated lines, return and earth wires of 2 × 25 kV AC high-speed railway supply system, etc.). Different types of faults are considered, and where they occur (also along the lines), by means of a suitable admittance matrix in phase frame of reference and embedded inside the overall network bus admittance matrix. Some comparisons with simplified approaches are presented in order to demonstrate the power of the method. Eventually, application to the real Italian network is comprehensively shown. Full article