Search Results (10,656)

This study focuses on the high-precision microhole machining of 304 stainless steel and explores a backwater-assisted picosecond laser trepanning technique. The laser used is a 30 W green picosecond laser with a wavelength of 532 nm, a repetition rate of 1000 kHz, and a pulse width of less than 15 ps. Experiments were conducted under both water-based and non-water-based laser processing environments to systematically investigate the effects of laser power and scanning cycles on hole roundness, taper, and overall hole quality. The experimental results further confirm the advantages of the backwater-assisted technique in reducing slag accumulation, minimizing roundness variation, and improving hole uniformity. In addition, thermal effects during the machining process were analyzed, showing that the water-based environment effectively suppresses the expansion of the heat-affected zone and mitigates recast layer formation, thereby enhancing hole wall quality. Compared with conventional non-water-based methods, the backwater-assisted approach demonstrates superior processing stability, better hole morphology, and more efficient thermal management. This work provides a reliable technical route and theoretical foundation for precision microhole machining of stainless steel and exhibits strong potential for engineering applications. Full article

With the increasing penetration of photovoltaic systems in low-voltage distribution networks, new operational challenges arise for distribution system operators. This article focuses on a comprehensive analysis of the impact of single-phase and three-phase photovoltaic systems on voltage magnitude, voltage unbalance, and currents flowing through distribution lines. The steady-state operation was calculated using EA-PSM simulation software, and the assessment of the impact of photovoltaic systems on the network was carried out using the international standard EN 50160. Simulation results show that a high penetration of photovoltaic systems causes significant changes in the network’s voltage profile. The study also includes a proposal of measures aimed at mitigating the adverse effects of decentralized generation in photovoltaic systems on the distribution network. Among the most effective measures is the selection of an appropriate conductor cross-section for distribution lines. The results also indicate that, in terms of negative impact on the network, it is preferable to prioritize three-phase connection over single-phase connection, because for the same impact on the network, three-phase photovoltaic systems can inject several times more power into the network compared to single-phase systems. These and other findings may be beneficial, especially for distribution system operators in planning the operation and development of networks. Full article

This paper systematically explores the dynamic effects of foreign direct investment (FDI), foreign trade, technological innovation, and human capital across China’s 28 sub-industries. The results show that FDI and foreign trade significantly promote manufacturing output growth, while technological innovation and human capital have a more sensitive response to growth fluctuations in the short term. The Granger causality test shows that FDI, technological innovation, and human capital all have strong predictive power and can effectively predict the future trend of manufacturing output. The impulse response function and variance decomposition analysis further reveal the key role of these factors in promoting the manufacturing industry’s long-term sustainable development. Based on the above findings, this paper suggests that local government should continue to optimize the structure and quality of attracting foreign capital, increase the support for technology research and development and intelligent manufacturing, enhance the added value of export products, and strengthen human capital investment so as to promote China’s manufacturing industry’s high-quality and sustainable development and provide reference for other developing countries’ manufacturing development. Full article

Display-field communication (DFC) is an imperceptible screen-to-camera technology that embeds and recovers data from the frequency domain of an image frame. Conventional DFC requires a reference frame for each data frame to estimate the channel, a method that, while reliable, is not bandwidth-efficient. Similarly, iterative DFC requires the transmission of pilot symbols for channel estimation. In this paper, we propose an implicit DFC (iDFC) scheme that eliminates the need for reference frames by estimating them using the first-order statistics of the received image. The system employs discrete Fourier-transform-based subcarrier mapping and adds data directly to the frequency coefficients of the host image. At the receiver, statistical estimation enables blind channel equalization without sacrificing the data rate. The simulation results show that iDFC achieves an achievable data rate (ADR) of up to $1.52\times {10}^5$ bps, a significant enhancement of approximately 97% and 11% compared to conventional and iterative DFC schemes, respectively. Furthermore, the analysis reveals a critical trade-off between communication robustness and visual imperceptibility; allocating 70% of signal power to the image maintains high visual quality but results in a symbol error rate (SER) floor of $1.5\times {10}^{-1}$, whereas allocating only 10% improves the SER to below ${10}^{-2}$ at the cost of visible artifacts. The findings also identify QPSK as the optimal modulation order that maximizes the data rate, showing that higher-order schemes can be detrimental due to system impairments such as signal clipping. The proposed iDFC scheme presents a more efficient and robust solution for high-capacity DFC applications by balancing the competing demands of data throughput and visual fidelity. Full article

Accurate differentiation between Coilia brachygnathus and Coilia nasus is imperative for the effective management of fisheries, the conservation of aquatic ecosystems, and the mitigation of commercial fraud. Current morphological identification remains challenging due to their high morphological similarity—particularly for processed samples—while conventional molecular methods often lack the speed or specificity required for field applications or high-throughput screening. In this study, a novel integrated approach was developed and validated, combining TaqMan quantitative real-time PCR (qPCR). for precise genotyping of C. brachygnathus and C. nasus with Recombinase Polymerase Amplification coupled with Lateral Flow Dipstick (RPA-LFD) for rapid on-site screening. First, species-specific RPA-LFD assays were designed to target the mitochondrial COI gene sequence. This enabled visual detection within 10 min at 37 °C, with a sensitivity of 10² copies/μL, and required no complex equipment. A dual TaqMan MGB qPCR assay was further developed by validating stable differentiating SNPs (chr21:3798155, C/T) between C. brachygnathus and C. nasus, using FAM/VIC dual-labeled MGB probes. Results showed that this assay could distinguish the two species in a single tube: for C. brachygnathus, Ct values in the FAM channel were significantly earlier than those in the VIC channel (ΔCt ≥ 1), with a FAM detection limit of 125 copies/reaction; for C. nasus, only VIC channel amplification was observed, with a detection limit as low as 12.5 copies/reaction. Validation with 171 known tissue samples demonstrated 100% concordance with expected species identities. This integrated approach effectively combines the high accuracy and quantitative capacity of TaqMan qPCR for confirmatory laboratory genotyping with the speed, simplicity, and portability of RPA-LFD for initial field or point-of-need screening. This reliable, efficient, and user-friendly technique provides a powerful tool for resource management, biodiversity monitoring, and ensuring the authenticity of high-quality C. brachygnathus and C. nasus. Full article

The rapid growth of digital communication has intensified spam-related threats, including phishing and malware, which employ advanced evasion tactics. Traditional filtering methods struggle to keep pace, driving the need for sophisticated machine learning (ML) solutions. The effectiveness of ML models hinges on selecting high-quality input features, especially in high-dimensional datasets where irrelevant or redundant attributes impair performance and computational efficiency. Guided by principles of symmetry to achieve an optimal balance between model accuracy, complexity, and interpretability, this study proposes an Enhanced Hybrid Quantum-Inspired Firefly and Artificial Bee Colony (EHQ-FABC) algorithm for feature selection in spam detection. EHQ-FABC leverages the Firefly Algorithm’s local exploitation and the Artificial Bee Colony’s global exploration, augmented with quantum-inspired principles to maintain search space diversity and a symmetrical balance between exploration and exploitation. It eliminates redundant attributes while preserving predictive power. For interpretability, Shapley Additive Explanations (SHAPs) are employed to ensure symmetry in explanation, meaning features with equal contributions are assigned equal importance, providing a fair and consistent interpretation of the model’s decisions. Evaluated on the ISCX-URL2016 dataset, EHQ-FABC reduces features by over 76%, retaining only 17 of 72 features, while matching or outperforming filter, wrapper, embedded, and metaheuristic methods. Tested across ML classifiers like CatBoost, XGBoost, Random Forest, Extra Trees, Decision Tree, K-Nearest Neighbors, Logistic Regression, and Multi-Layer Perceptron, EHQ-FABC achieves a peak accuracy of 99.97% with CatBoost and robust results across tree ensembles, neural, and linear models. SHAP analysis highlights features like domain_token_count and NumberOfDotsinURL as key for spam detection, offering actionable insights for practitioners. EHQ-FABC provides a reliable, transparent, and efficient symmetry-aware solution, advancing both accuracy and explainability in spam detection. Full article

Thanks to the inherent advantages, including being green, broadband, and high security, visible light communication (VLC), as one powerful enabling technology for 6G and beyond the Internet of Things (IoT), has received ever-increasing discussion and attention. In order to improve the quality of VLC links and extend their coverage, various intelligent reflecting surfaces (IRSs) have been massively discussed and optimized into the VLC field. Apparently, the current research works are merely limited to the investigation of well-known Lambertian source-based, IRS-assisted VLC. Consequently, there is a lack of targeted analysis and evaluation of the diversity of beam configurations for light-emitting diodes (LEDs) and the potential non-Lambertian IRS-assisted VLC links. To fill the above research gap of this VLC branch, this article focuses on introducing the innovative LED non-Lambertian beams into typical IRS-assisted VLC systems to construct novel IRS-assisted non-Lambertian VLC links. The investigation results indicate that compared to the baseline Lambertian IRS-assisted VLC scheme, the proposed representative non-Lambertian IRS-assisted VLC schemes could provide up to 22.22 dB and 14.08 dB signal-to-noise ratio gains for side and corner receiver positions, respectively. Moreover, this article quantitatively evaluates the impact of the initial azimuth angle (i.e., beam azimuth orientation) of asymmetric non-Lambertian optical beams on the performance of IRS-assisted VLC and the relevant fundamental characteristics. Full article

High-speed laser cladding technology is an innovative process that reduces costs and enhances coating quality. In this study, CoCrMo wear-resistant coatings were fabricated on a 40Cr steel substrate using high-speed laser cladding technology and compared to CoCrMo coatings produced by traditional methods. The effects of both processes on the microstructure, nanoindentation characteristics, and wear behavior of CoCrMo coatings were examined. The results show that the phase compositions of both coatings include γ-Co solid solution and ε-Co solid solution. The high cooling rate of high-speed laser cladding significantly suppressed Mo precipitation, enhancing Mo solid solution strengthening. Additionally, the fine-grain strengthening effect induced by the high cooling rate contributed significantly to the coatings’ mechanical properties. The nano-hardness of the HS-CoCrMo coatings reached approximately 5.18 ± 0.23 GPa, 1.2 times higher than that of the N-CoCrMo coatings. Furthermore, the generalized hardness, H/E ratio, and H³/E² ratio of HS-CoCrMo coatings were improved. This increase in nano-hardness significantly boosted the wear resistance of HS-CoCrMo coatings, yielding an average friction coefficient of approximately 0.466, with wear volume and specific wear rate values of 6.55 × 10⁶ μm³ and 0.87 × 10⁻⁵ mm³/N·m, respectively, outperforming the N-CoCrMo coatings. The main wear mechanisms for the HS-CoCrMo coatings were abrasive wear, adhesive wear, and oxidative wear. In conclusion, high-speed laser cladding technology produces high-performance, wear-resistant coatings with high productivity, offering broader application prospects for the metallurgical and power industries, while effectively reducing production cycles and usage costs. Full article

The Atlantic blue crab (Callinectes sapidus) is an opportunistic invasive species in the Mediterranean that is negatively affecting biodiversity, fisheries, and tourism. In Italy, it is appreciated for its good meat quality, but the processing yield is low (21.87 ± 2.38%), generating a significant amount of by-products (72.45 ± 4.08%), which are underutilized. Valorizing this biomass is in line with circular economy principles and can improve both environmental and economic sustainability. This study aimed to valorize Atlantic blue crab by-products (BCBP), producing protein hydrolysates and assessing their in vitro bioactivities, in order to plan applications in animal food and related sectors. BCBP hydrolysates were obtained by enzymatic hydrolysis using Alcalase and Protamex enzymes. The treatment with Alcalase resulted in a higher degree of hydrolysis (DH = 23% in 205 min) compared to Protamex (DH = 14% in 175 min). Antioxidant activity of the hydrolisates was evaluated through DPPH, ABTS, reducing power and FRAP assays, as well as in vitro test in fibroblasts (HS-68). At 10 mg/mL, hydrolysates from both enzymes exhibited the maximum radical scavenging activity in DPPH and ABTS assays. In HS-68 cells, 0.5 mg/mL hydrolysates protected against H₂O₂-induced oxidative stress, showing a cell viability comparable to cells treated with 0.5 mM N-acetyl cysteine (NAC), as an antioxidant. Statistical analyses were performed using one-way ANOVA followed by Student–Newman–Keuls (SNK) or Games–Howell post hoc tests, with significance set at p < 0.05. Overall, both enzymes efficiently hydrolyzed BCBP proteins, generating hydrolysates with significant antioxidant activity and cytoprotective effects. These results demonstrate the potential to produce high-quality bioactive compounds from BCBPs, suitable for food, nutraceutical, and health applications. Scaling up this valorization process represents a viable strategy to improve sustainability and add economic value to the management of this invasive species, turning a problem in a resource. Full article

Patient-derived organoids (PDOs) have emerged as powerful tools in personalized medicine applicable to both non-malignant conditions and to cancer, where they are increasingly used for personalized drug screening and precision treatment strategies in part due to their ability to replicate tumor heterogeneity. They also serve as study model systems to understand disease mechanisms, pathways, and the impact of ex vivo exposures. We present a detailed step-by-step protocol for generating organoids from normal crypts, polyps, and tumors, including methods for tissue processing, crypt isolation, culture establishment, and the transition from basolateral to apical-out polarity for co-culture and exposure-based studies. The protocol also includes immunofluorescence staining procedures for cellular characterization and quality control measures. Our standardized approach successfully generates organoids from diverse colorectal tissues with high efficiency and reproducibility. This comprehensive guide addresses common technical challenges and provides troubleshooting strategies to improve success rates across different sample types. We believe that this resource will enhance reproducibility in organoid research and expand their utility in translational applications, particularly for personalized medicine approaches in colorectal cancer. Full article

Minimizing surface defects in perovskite films is crucial for suppressing non-radiative recombination and enhancing device performance. Herein, we propose the use of N-bromosuccinimide (NBS), a small molecule containing Lewis base carbonyl groups (C=O), to improve the quality of RbCsMAFA mixed-cation perovskite films. This surface treatment effectively reduces non-radiative charge-carrier recombination, in particular through the passivation of surface defects related to undercoordinated Pb²⁺ ions and halide vacancies, and significantly accelerates charge extraction from the perovskite into the Spiro-OMeTAD hole transporter. Consequently, NBS-treated PerSCs achieve a power conversion efficiency (PCE) of 18.24%, representing an 11% relative increase over the control device (16.48%). This enhancement is mainly attributed to a V_oc gain of up to 40 mV and modifications in the recombination dynamics. Supporting evidence from impedance spectroscopic analyses further confirms enhanced energy-level alignment and reduced interfacial losses, improved charge transport as well as prolonged charge lifetimes within the devices. This work provides a simple yet effective approach to reduce the non-radiative recombination losses towards more efficient and stable PerSCs. Full article

This study proposes a Personalized Deep Learning-Based Sleep Recommendation System Using Lifelog Data (PDSRS-LD). Traditional sleep research primarily relies on bio signals such as EEG and ECG recorded during sleep but often fails to sufficiently reflect the influence of daily activities on sleep quality. To address this limitation, we collect lifelog data such as stress levels, fatigue, and sleep satisfaction via wearable devices and use them to construct individual user profiles. Subsequently, real sleep data obtained from an AI-powered motion bed are incorporated for secondary training to enhance recommendation performance. PDSRS-LD considers comprehensive user data, including gender, age, and physical activity, to analyze the relationships among sleep quality, stress, and fatigue. Based on this analysis, the system provides personalized sleep improvement strategies. Experimental results demonstrate that the proposed system outperforms existing models in terms of F1 score and Average Precision (mAP). These results suggest that PDSRS-LD is effective for real-time, user-centric sleep management and holds significant potential for integration into future smart healthcare systems. Full article

The complex aquatic environment attenuates light transmission, thereby limiting the detection range of underwater laser systems. To address the challenges of limited operational distance and significant light energy attenuation, this study investigates optimized underwater lighting and imaging applications using a combined tricolor RGB (RED-GREEN-BLUE) white laser source. First, accounting for the attenuation characteristics of water, we propose a power-compensated white laser system based on transmission distance and underwater imaging theory. Second, underwater experiments are conducted utilizing both standard D65 white lasers and the proposed power-compensated white lasers, respectively. Finally, the theory is validated by assessing image quality metrics of the captured underwater imagery. The results demonstrate that a low-power (0.518 W) power-compensated white laser achieves a transmission distance of 5 m, meeting the requirements for a long-range, low-power imaging light source. Its capability for independent adjustment of the three-color power output fulfills the lighting demands for specific long-distance transmission scenarios. These findings confirm the advantages of power-compensated white lasers in long-range underwater detection and refine the characterization of white light for underwater illumination. Full article

Consumers increasingly seek clean-label meat products with improved nutrition and stability. We evaluated a collagen hydrolysate–cranberry mixture (CH-CR) as a functional additive in cooked sausages. Two formulations—control and CH-CR—were assessed for fatty acid profile; lipid and protein oxidation during storage; antioxidant capacity ferric-reducing antioxidant power (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, and half-maximal inhibitory concentration (IC50); amino acid composition; and instrumental color. Relative to the control, CH-CR produced a more favorable lipid profile: lower saturated fatty acids (SFAs) 23.9% vs. 28.0%, higher monounsaturated fatty acids (MUFAs) 53.2% vs. 49.3%, slightly higher polyunsaturated fatty acids (PUFAs) 23.3% vs. 22.7%, a higher PUFA/SFA ratio of 0.97 vs. 0.81, and a lower omega-6/omega-3 (n-6/n-3) ratio of 13.5 vs. 27.1, driven by higher alpha-linolenic acid (ALA) 1.6% vs. 0.8%, with trans fats <0.1%. Storage studies showed attenuated oxidation in CH-CR: lower peroxide value (PV) at day 10 8.1 ± 0.4 vs. 9.8 ± 0.5 meq/kg and lower thiobarbituric acid-reactive substances (TBARS) at day 6 0.042 ± 0.004 vs. 0.055 ± 0.006 mg MDA/kg and day 10 0.156 ± 0.016 vs. 0.590 ± 0.041 mg MDA/kg); the acid value at day 10 was similar. Antioxidant capacity increased with CH-CR FRAP 30.5 mg gallic acid equivalents (GAE)/g vs. not detected; DPPH inhibition was 29.88% vs. 10.23%; IC50 56.22 vs. 149.51 µg/mL. The amino acid profile reflected collagen incorporation—higher glycine+proline+hydroxyproline 2.37 vs. 1.38 g/100 g and a modest rise in indispensable amino acids (IAAs) 5.72 vs. 5.42 g/100 g, increasing the IAA/total amino acid (TAA) ratio to 0.411 vs. 0.380. CH-CR samples were lighter and retained redness better under light, with comparable overall color stability. Overall, CH-CR is a natural strategy to improve fatty acid quality and oxidative/color stability in sausages. Full article

With the increasing popularity of large language models (LLMs), retrieval-augmented generation (RAG) systems are gaining importance, enabling the use of internal company data to generate precise and relevant responses. The aim of this study was to develop a comprehensive methodology for measuring and optimizing RAG systems, focusing on analyzing the impact of key parameters such as chunk size, vector embedding models, and LLM selection on system effectiveness. Experiments were conducted on a RAG system using a large biographical dataset, stored in a Qdrant vector database, allowing for in-depth analysis in the context of long text data. The results indicated that optimizing RAG systems necessitates considering various factors, including LLM context window size, computational power, and processing costs. The selection of optimal parameters and LLM is a trade-off between response quality, computational cost, and hardware limitations. This study provides practical guidance for engineers and researchers working on improving RAG-based systems, enabling informed decisions regarding RAG system configuration in various business contexts. Full article