Search Results (422,914)

Quantum machine learning (QML) has emerged as a promising approach for enhancing image classification by exploiting quantum computational principles such as superposition and entanglement. However, practical applications on complex datasets like CIFAR-100 remain limited due to the low expressivity of shallow circuits and challenges in circuit optimization. In this study, we propose HQCNN–REGA—a novel hybrid quantum–classical convolutional neural network architecture that integrates data re-uploading and genetic algorithm optimization for improved performance. The data re-uploading mechanism allows classical inputs to be encoded multiple times into quantum states, enhancing the model’s capacity to learn complex visual features. In parallel, a genetic algorithm is employed to evolve the quantum circuit architecture by optimizing gate sequences, entanglement patterns, and layer configurations. This combination enables automatic discovery of efficient parameterized quantum circuits without manual tuning. Experiments on the MNIST and CIFAR-100 datasets demonstrate state-of-the-art performance for quantum models, with HQCNN–REGA outperforming existing quantum neural networks and approaching the accuracy of advanced classical architectures. In particular, we compare our model with classical convolutional baselines such as ResNet-18 to validate its effectiveness in real-world image classification tasks. Our results demonstrate the feasibility of scalable, high-performing quantum–classical systems and offer a viable path toward practical deployment of QML in computer vision applications, especially on noisy intermediate-scale quantum (NISQ) hardware. Full article

The textile industry’s reliance on synthetic dyes contributes significantly to pollution, highlighting the need for sustainable alternatives like biopigments. This study investigates the production and application of the biopigment prodigiosin, which was produced by Pseudomonas putida with a yield of 1.85 g/L. Prodigiosin was prepared under acidic, neutral, and alkaline conditions, resulting in varying protonation states that influenced its affinity for cotton and polyester fibers. Three surfactants (anionic, cationic, non-ionic) were tested, with non-ionic Tween 80 yielding a promising color strength (above 4) and fastness results with neutral prodigiosin at 1.3 g/L. Cotton and polyester demonstrated good washing (color difference up to 14 for cotton, 5 for polyester) and light fastness (up to 15 for cotton, 16 for polyester). Cellulose acetate, used in the conventional printing process as a thickener, produced superior color properties compared to commercial thickeners. Neutral prodigiosin achieved higher color strength, and cotton fabrics displayed halochromic properties, distinguishing them from polyester, which showed excellent fastness. Prodigiosin-printed samples also exhibited strong antimicrobial activity against Pseudomonas aeruginosa and retained halochromic properties over 10 pH cycles. These findings suggest prodigiosin as a sustainable dye alternative and pH sensor, with potential applications in biomedical materials, such as antimicrobial and pH-responsive wound dressings. Full article

Environmental noise is inevitable during seismic data acquisition, with major sources including heavy machinery, rivers, wind, and other environmental factors. During field data acquisition, it is important to assess the impact of environmental noise and evaluate data quality. In subsequent seismic data processing, these noise components also need to be eliminated. Accurate identification of noise traces facilitates rapid quality control (QC) during fieldwork and provides a reliable basis for targeted noise attenuation. Conventional environmental noise identification primarily relies on amplitude differences. However, in seismic data, high-amplitude signals are not necessarily caused by environmental noise. For example, surface waves or traces near the shot point may also exhibit high amplitudes. Therefore, relying solely on amplitude-based criteria has certain limitations. To improve noise identification accuracy, we use the Mel-spectrogram to extract features from seismic data and construct the dataset. Compared to raw time-series signals, the Mel-spectrogram more clearly reveals energy variations and frequency differences, helping to identify noise traces more accurately. We then employ a Vision Transformer (ViT) network to train a model for identifying noise in seismic data. Tests on synthetic and field data show that the proposed method performs well in identifying noise. Moreover, a denoising case based on synthetic data further confirms its general applicability, making it a promising tool in seismic data QC and processing workflows. Full article

Spruce wood is a natural polymeric material, consisting of cellulose, lignin, hemicelluloses and other secondary components, which gives it a unique chemical footprint and architecture. Varnishes are used in musical instruments to protect the wood against humidity variations, wood being a hygroscopic material, but also to protect the wood from dirt. The varnishes used both to protect the wood from resonance and to ensure a special aesthetic appearance are either polymeric varnishes (nitrocellulose, oil-based) or volatile solvents (spirit). In this study, the color changes, the surface morphology and the chemical spectrum produced by three types of varnishes, applied in 5, 10 and 15 layers, on resonance spruce plates were analyzed. The results revealed significant changes in the color parameters: the lightness decreased by approximately 17% after the first layer, by 50% after 5 layers, by 65% after 10 layers and by 70% after 15 layers. The color parameters are most influenced by the anatomical quality of spruce wood (annual ring width and earlywood/latewood ratio) in the case of oil-based varnishes and least influenced in the case of nitrocellulose varnishes. The chemical fingerprint was determined by FTIR spectrum analysis, which revealed that the most pronounced absorptions were the double band 2926–2858 cm⁻¹, corresponding to aliphatic methylene and methyl groups (asymmetric and symmetrical C-H stretch), and the bands at 1724 cm⁻¹ (oil-based varnish), 1722 cm⁻¹ (nitrocellulose varnish) and 1708 cm⁻¹ (spirit varnish), all assigned to non-conjugated carbonyl groups in either carboxylic acids, esters aldehydes or ketones. The novelty of the study lies in the comparative analysis of three types of varnishes used in the musical instrument industry, applied to samples of spruce resonance wood with different macroscopic characteristics in three different layer thicknesses. Full article

To enable the practical application of passive back-support exoskeletons employing pneumatic artificial muscles (PAMs) in tasks such as agricultural work, we evaluated their assistive effectiveness in a half-squatting posture with a staggered stance. In this context, assistive force profiles were adjusted according to body posture to achieve more effective support. The targeted assistive force profile was designed to be continuously active from the standing to the half-squatting position, with minimal variation across this range. The assistive force profile was developed based on a PAM contractile force model and implemented using a cam mechanism. The effectiveness of assistance was assessed by measuring body flexion angles and erector spinae muscle activity during lifting and carrying tasks. The results showed that the assistive effect was greater on the side with the forward leg. Compared to the condition without exoskeleton assistance, the conventional pulley-based system reduced muscle activity by approximately 20% whereas the cam-based system achieved a reduction of approximately 30%. Full article

Cystic echinococcosis is a zoonosis caused by the cestode Echinococcus granulosus sensu stricto. Population genetic studies and phylogeographic patterns are essential to understanding the transmission dynamics of this parasite under varying environmental conditions. In this study, the genetic diversity of E. granulosus s.s. was evaluated using 46 hydatid cyst samples obtained from sheep, goats, cattle, and humans across three regions of Chile: Coquimbo, La Araucanía, and Magallanes. Mitochondrial cox1 gene sequences were analyzed and compared with reference sequences reported from South America, Europe, Africa, Asia, and Oceania. In Chile, the EG01 haplotype was the predominant haplotype. A total of four haplotypes were identified, with low haplotype diversity (Hd = 0.461 ± 0.00637) and low nucleotide diversity (π = 0.00181 ± 0.00036). The haplotype network displayed a star-like configuration, with the EG01 genotype at the center, suggesting a potentially ancestral or widely distributed lineage. In Coquimbo (Tajima’s D = −0.93302, p = 0.061; Fu’s Fs = −0.003, p = 0.502) and Magallanes (Tajima’s D = −0.17406, p = 0.386; Fu’s Fs = −0.121, p = 0.414), both neutrality tests were non-significant, indicating no strong evidence for recent population expansion or selection. Star-like haplotype network patterns were also observed in populations from Europe, the Middle East, Asia, Africa, and Oceania, with the EG01 genotype occupying the central position. The population genetic structure of Echinococcus granulosus s.s. in Chile demonstrates considerable complexity, with EG01 as the predominant haplotype. Further comprehensive studies are required to assess the intraspecific genetic variability of E. granulosus s.s. throughout Chile and to determine whether this variability influences the key biological traits of the parasite. This structure may prove even more complex when longer fragments are analyzed, which could allow for the detection of finer-scale microdiversity among isolates from different hosts. We recommended that future cystic echinococcosis control programs take into account the genetic variability of E. granulosus s.s. strains circulating in each endemic region, to better understand their epidemiological, immunological, and possibly pathological differences. Full article

This research considers a preliminary comparative technical evaluation of two micro-gas turbine (MGT) systems in combined heat and power (CHP) mode (100 kWe), aimed at supplying heat to a residential community of 15 average-sized buildings located in Central Europe over a year. Two systems were modelled in Ebsilon 15 software: a natural gas case (benchmark) and an ammonia-fueled case, both based on the same on-design parameters. Off-design simulations evaluated performance over variable ambient temperatures and loads. Idealized, unrecuperated cycles were adopted to isolate the thermodynamic impact of the fuel switch under complete combustion assumption. Under these assumptions, the study shows that the ammonia system produces more electrical energy and less excess heat, yielding marginally higher electrical efficiency and EUF (26.05% and 77.63%) than the natural gas system (24.59% and 77.55%), highlighting ammonia’s utilization potential in such a context. Future research should target validating ammonia combustion and emission profiles across the turbine load range, and updating the thermodynamic model with a recuperator and SCR accounting for realistic pressure losses. Full article

Nanofertilizers (NFs) and engineered nanoparticles (NPs) are increasingly used in agriculture, yet their environmental safety remains poorly understood. This study evaluated the comparative phytotoxicity of zinc oxide (ZnO), titanium dioxide (TiO₂), and clinoptilolite nanoparticles, three commercial nanofertilizers, and potassium dichromate (K₂Cr₂O₇) using Lactuca sativa seeds under adapted OECD-208 protocol conditions. Seeds were exposed to varying concentrations of each xenobiotic material (0.5–3% for NFs; 10–50% for NPs), with systematic assessment of seedling survival, root and hypocotyl length, dry biomass, germination index (GI), and median effective concentration (EC₅₀) values. Nanofertilizers demonstrated significantly greater phytotoxicity than engineered nanoparticles despite lower application concentrations. The toxicity ranking was established as NF1 > NF3 > NF2 > NM2 > NM1 > NM3, with NF1 being most toxic (EC₅₀ = 1.2%). Nanofertilizers caused 45–78% reductions in root length and 30–65% decreases in dry biomass compared with controls. GI values dropped to ≤70% in NF1 and NF3 treatments, indicating concentration-dependent growth inhibition. While nanofertilizers offer agricultural benefits, their elevated phytotoxicity compared with conventional nanoparticles necessitates rigorous pre-application safety assessment. These findings emphasize the critical need for standardized evaluation protocols incorporating both physiological and ecotoxicological endpoints to ensure safe xenobiotic nanomaterial deployment in agricultural systems. Full article

Due to the effect of room acoustics on musical interpretation, a musician’s rehearsal may be greatly enhanced by leveraging virtual and augmented reality technology. This paper presents a preliminary study on a rehearsal tool designed for musicians, enabling practice in a virtual acoustic environment with audience-positioned playback. Fourteen participants, both professional and non-professional musicians, were recruited to practice with the rehearsal tool prior to performing in an unfamiliar venue. Throughout the rehearsal, the subjects either played in a virtual environment that matched the acoustics of the performance venue or one that was acoustically different. A control group rehearsed in an acoustically dry room with no virtual acoustic environment. The tool’s effectiveness was evaluated with two 16-item questionnaires that assessed quality, usefulness, satisfaction with the rehearsal, and aspects of the performance. Findings indicate that rehearsing in a virtual acoustic environment that matches the performance venue improves acoustic awareness during the performance and enhances ease and comfort on stage compared to practising in a different environment. These results support the integration of virtual acoustics in rehearsal tools to help musicians better adapt their performance to concert settings. Full article

Gastric-type cervical adenocarcinoma (GCA) is a rare and aggressive subtype of cervical adenocarcinoma. Despite its clinical significance, its molecular carcinogenesis and therapeutic targets remain poorly understood. This study aimed to compare the clinicopathological, immunohistochemical, and molecular profiles of GCA and usual-type cervical adenocarcinoma (UCA), exploring prognostic and therapeutic biomarkers in a Japanese population. A total of 110 cervical adenocarcinoma cases, including 16 GCA and 94 UCA cases, were retrospectively analyzed for clinicopathological features, and a panel of immunohistochemical markers was assessed. Sanger sequences were performed for the KRAS, PIK3CA, and BRAF genes, and survival and clinicopathological correlations were assessed using Kaplan–Meier and Cox regression analyses. GCA was significantly associated with more aggressive features than UCA, including lymph node involvement, advanced FIGO stages, increasing recurrence rate, and poor survival status. High ARID1B expression was observed in a subset of GCA cases and correlated with worse progression-free and overall survival. Additionally, PD-L1 expression was more frequent in GCA than UCA and was associated with unfavorable prognostic factors. Conversely, UCA cases showed strong p16 expression, supporting their HPV-driven pathogenesis. Molecular profiling revealed KRAS and PIK3CA mutations in both subtypes, while BRAF mutations were identified exclusively in GCA. These findings reveal distinct clinical and molecular profiles for both tumor types and underscore ARID1B and PD-L1 as predictive prognostic and therapeutic biomarkers in GCA, implicating the use of subtype-specific treatment strategies. Full article

To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to solve two core tasks: one is binary classification of pixel-level cracks, and the other is multi-category assessment of damage state based on crack morphology. Using three-channel RGB images as input, a dual-path collaborative training framework based on U-Net encoder–decoder architecture is constructed, and a binary segmentation mask of the same size is output to achieve the accurate segmentation of cracks at the pixel level. By constructing a dual-path collaborative training framework and employing a dynamic pseudo-label refinement mechanism, the model achieves an F1-score of 0.883 using only 50% labeled data—a mere 1.3% decrease compared to the fully supervised benchmark DeepCrack (F1 = 0.896)—while reducing manual annotation costs by over 60%. Furthermore, a quantitative correlation model between crack fractal characteristics and structural damage severity is established by combining a U-Net segmentation network with the differential box-counting algorithm. The experimental results demonstrate that under a cyclic loading of 147.6–221.4 kN, the fractal dimension monotonically increases from 1.073 (moderate damage) to 1.189 (failure), with 100% accuracy in damage state identification, closely aligning with the degradation trend of macroscopic mechanical properties. In complex crack scenarios, the model attains a recall rate (Re = 0.882), surpassing U-Net by 13.9%, with significantly enhanced edge reconstruction precision. Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance. Full article

This paper proposes a novel dual-functional radar-communication (DFRC) framework that integrates unmanned aerial vehicle (UAV) communications into an integrated sensing and communication (ISAC) system, termed the ISAC-UAV architecture. In this system, the UAV’s mobility is leveraged to simultaneously serve multiple single-antenna uplink users (UEs) and perform radar-based sensing tasks. A key challenge stems from the target position uncertainty due to movement, which impairs matched filtering and beamforming, thereby degrading both uplink reception and sensing performance. Moreover, UAV energy consumption associated with mobility must be considered to ensure energy-efficient operation. We aim to jointly maximize radar sensing accuracy and minimize UAV movement energy over multiple time steps, while maintaining reliable uplink communications. To address this multi-objective optimization, we propose a deep reinforcement learning (DRL) framework based on a long short-term memory (LSTM)-enhanced deep deterministic policy gradient (DDPG) network. By leveraging historical target trajectory data, the model improves prediction of target positions, enhancing sensing accuracy. The proposed DRL-based approach enables joint optimization of UAV trajectory and uplink power control over time. Extensive simulations validate that our method significantly improves communication quality and sensing performance, while ensuring energy-efficient UAV operation. Comparative results further confirm the model’s adaptability and robustness in dynamic environments, outperforming existing UAV trajectory planning and resource allocation benchmarks. Full article

Aims: Sinus tachycardia after heart transplantation (HTX) due to cardiac graft denervation is associated with reduced post-transplant survival and requires adequate treatment. We analyzed the long-term effects of heart rate control with ivabradine or metoprolol succinate in HTX recipients. Methods: This observational retrospective single-center study analyzed the ten-year results of 110 patients receiving ivabradine (n = 54) or metoprolol succinate (n = 56) after HTX. Analysis included comparison of demographics, medications, heart rates, blood pressure values, echocardiographic features, cardiac catheterization data, cardiac biomarkers, and post-transplant survival including causes of death. Results: Both groups showed no significant differences concerning demographics or medications (except for ivabradine and metoprolol succinate). At 10-year follow-up, HTX recipients with ivabradine showed a significantly lower heart rate (72.7 ± 8.5 bpm) compared to baseline (88.8 ± 7.6 bpm; p < 0.001) and to metoprolol succinate (80.1 ± 8.1 bpm; p < 0.001), a significantly lower NT-proBNP level (588.4 ± 461.4 pg/mL) compared to baseline (3849.7 ± 1960.0 pg/mL; p < 0.001) and to metoprolol succinate (1229.0 ± 1098.6 pg/mL; p = 0.005), a significantly lower overall mortality (20.4% versus 46.4%; p = 0.004), and mortality due to graft failure (1.9% versus 21.4%; p = 0.001). Multivariate analysis showed a significantly decreased risk of death within 10 years after HTX in patients with post-transplant use of ivabradine (HR 0.374, CI 0.182–0.770; p = 0.008). Conclusions: In this single-center trial, patients with ivabradine revealed a significantly more pronounced heart rate reduction, a lower NT-proBNP level, and a superior 10-year survival after HTX. Full article

Background/Objectives: Conventional ketogenic diets, although effective for weight loss, often contain high total and saturated fat intake, which leads to increased low-density lipoprotein cholesterol (LDL-C). Thus, the Healthy Ketogenic Diet (HKD) was developed to address these concerns. It emphasizes calorie restriction, limiting net carbohydrate intake to 50 g per day, prioritizing unsaturated fats, and reducing saturated fat intake. However, adherence to the HKD remains a challenge in urban, time-constrained environments. Therefore, this pilot randomized controlled trial aimed to investigate the effects of Healthy Ketogenic Diet Ready-To-Eat (HKD-RTE) meals (provided for the first month only) versus HKD alone on weight loss and metabolic parameters among overweight adults. Methods: Multi-ethnic Asian adults (n = 50) with a body mass index (BMI) ≥ 27.5 kg/m² were randomized into the HKD-RTE group (n = 24) and the HKD group (n = 26). Both groups followed the HKD for six months, with the HKD-RTE group receiving HKD-RTE meals during the first month. Five in-person workshops and mobile health coaching through the Nutritionist Buddy Keto app helped to facilitate dietary adherence. The primary outcome was the change in body weight at 6 months. Linear regression was performed on the change from baseline for each continuous outcome, adjusting for demographics and relevant covariates. Logistic regression was performed on binary weight loss ≥5%, adjusting for demographics and relevant covariates. Results: In the HKD group, participants’ adherence to the 50 g net carbohydrate target was 15 days, while that in the HKD-RTE group was 19 days over a period of 30 days. Participants’ adherence to calorie targets was 21 days in the HKD group and 23 days in the HKD-RTE. The average compliance with the HKD-RTE meals provided in the HKD-RTE group was 55%. The HKD-RTE group experienced a greater percentage weight loss at 1 month (−4.8 ± 3.0% vs. −1.8 ± 6.2%), although this was not statistically significant. This trend continued up to 6 months, with the HKD-RTE group showing a greater percentage weight reduction (−8.6 ± 6.8% vs. −3.9 ± 8.6%; p = 0.092). At 6 months, the HKD-RTE group had a greater reduction in total cholesterol (−0.54 ± 0.76 mmol/L vs. −0.05 ± 0.56 mmol/L; p = 0.283) and LDL-C (−0.43 ± 0.67 mmol/L vs. −0.03 ± 0.52 mmol/L; p = 0.374) compared to the HKD group. Additionally, the HKD-RTE group exhibited greater reductions in systolic blood pressure (−8.3 ± 9.7 mmHg vs. −5.3 ± 11.0 mmHg), diastolic blood pressure (−7.7 ± 8.8 mmHg vs. −2.0 ± 7.0 mmHg), and HbA1c (−0.3 ± 0.5% vs. −0.1 ± 0.4%) than the HKD group (not statistically significant for any). Conclusions: Both HKD-RTE and HKD led to weight loss and improved metabolic profiles. The HKD-RTE group tended to show more favorable outcomes. Short-term HKD-RTE meal provision may enhance initial weight loss, with sustained long-term effects. Full article

Background: Diabetes mellitus is associated with worse outcomes after cardiac arrest. Hyperglycemia, diabetes treatments and other long-term sequalae may contribute to this association. We sought to determine the acute effect of diabetes on the return of spontaneous circulation (ROSC) and post-arrest cardiac function in a rat cardiac arrest model. Methods: Eighteen male Wistar rats were utilized, and 12 underwent the induction of type II diabetes for 10 weeks through a high-fat diet and the injection of streptozotocin. The carotid artery flow and femoral arterial pressure were measured. Seven minutes of asphyxial cardiac arrest was induced. An external cardiac compression was performed via an automated piston. Post-ROSC, epinephrine was titrated to a mean arterial pressure (MAP) of 70 mmHg. Data was analyzed using the Mann–Whitney test. The significance was set at p ≤ 0.05. Results: The rate of the ROSC was significantly lower in animals with diabetes, 50% compared to 100% in non-diabetics. Additionally, it took significantly longer to achieve the ROSC in diabetics, p = 0.034. In animals who survived, the cardiac function was reduced, as indicated by an increased epinephrine requirement, p = 0.041, and a decreased cardiac output at the end of the experiment, p = 0.017. The lactate, venous and arterial pressures, heart rate and carotid flow did not differ between groups at 2 h. Conclusions: Diabetes negatively affects the survival from cardiac arrest. Here, the critical difference was the rate of the conversion to a life-sustaining rhythm and the achievement of the ROSC. The post-ROSC cardiac function was depressed in diabetic animals. Interventions targeted at improving defibrillation success may be important in diabetics. Full article