Search Results (1,504)

The increasing prevalence of common cold viruses and bacteria in daily life has heightened interest in sterilization lamp technologies. Compared with traditional mercury-based ultraviolet (UV) lamps, modern UV lamps offer advantages including extended operational lifespan, high energy efficiency, compact form factor, and the absence of hazardous materials, rendering them both safer and environmentally sustainable. In particular, UV-C LED lamps, which emit at short wavelengths, are capable of disrupting the molecular structure of DNA or RNA in microbial cells, thereby inhibiting cellular replication and achieving effective disinfection and sterilization. Conventional UV-C LED sterilization lamp driver circuits frequently employ a two-stage architecture, which requires a large number of components, occupies substantial physical space, and exhibits reduced efficiency due to multiple stages of power conversion. To address these limitations, this paper proposes a UV-C LED sterilization lamp driver circuit for an AC voltage supply, employing boundary conduction mode (BCM) control with integrated power factor correction (PFC). The proposed single-stage, single-switch topology combines a buck PFC converter and a flyback converter while recovering transformer leakage energy to further improve efficiency. Compared with conventional two-stage designs, the proposed circuit reduces the number of power switches and components, thereby lowering manufacturing cost and enhancing overall energy conversion efficiency. The operating principles of the proposed driver circuit are analyzed, and a prototype is developed for a 110 V AC input with an output specification of 10.8 W (90 V/0.12 A). Experimental results demonstrate that the prototype achieves an efficiency exceeding 92%, a power factor of 0.91, an output voltage ripple of 1.298%, and an output current ripple of 4.44%. Full article

Additive manufacturing has promising potential for the development of 3D-printed protective structures such as stab-resistant body armor. However, no research to date has examined the impact of 3D printing parameters on the protective performance of such 3D-printed structures manufactured using fused filament fabrication technology. This study, therefore, investigates the effects of five key printing parameters: layer thickness, print speed, print temperature, infill density (Id), and layer width, on the mechanical and protective performance of 3D-printed polycarbonate (PC) armor. A Taguchi L₂₇ matrix was employed to systematically analyze these parameters, with toughness, stab penetration depth, and armor panel weight as the primary responses. ANOVA results, along with the Taguchi approach, demonstrated that Id was the most influential factor across all print parameters. This is because a higher Id led to denser structures, reduced voids and porosities, and enhanced energy absorption, significantly increasing toughness while reducing penetration depth. Morphological analysis supported the statistical findings regarding the role of Id on the performance of such structures. With optimized printing parameters, no penetration to the armor panels was recorded, outperforming the UK body armor standard of a maximum permitted knife penetration depth of 8 mm. Moreover, an artificial neural network (ANN) utilizing the 5-14-12-3 topology was created to predict the toughness, stab penetration depth, and armor panel weight of 3D-printed armors. The ANN model demonstrated better prediction performance for stab penetration depth compared to the Taguchi method, confirming the successful application of such an approach. These findings provide a critical foundation for the development of high-performance 3D-printed protective structures. Full article

This study explores the impact of symmetric and asymmetric channel power structures on green design decisions in supply chains, incorporating consumer environmental awareness (CEA). We develop a game-theoretic framework involving a manufacturer and a retailer under three distinct power configurations: manufacturer-led, retailer-led, and Nash game (symmetric power). The models examine how variations in power symmetry influence the manufacturer’s incentives to invest in green design, and their effects on pricing, demand, profit, and environmental performance. Our findings reveal that asymmetric power structures can significantly distort green design incentives. Specifically, green design does not always lead to higher prices or reduced environmental impact, depending on the interplay between power structure, investment cost, and CEA. Moreover, symmetric (Nash game) structures tend to improve overall supply chain performance when the green investment cost is high, while retailer-led structures are more effective under low-cost scenarios. Interestingly, unless green design significantly reduces per-unit environmental impact, the total environmental benefit may be offset by increased demand, highlighting the risk of a “green consumption trap”. Full article

This study presents a data-driven framework that integrates lean management and digital business process modelling to enhance sustainability in textile manufacturing. Conducted in a company producing industrial safety textiles from Peru, this research applies lean tools within a digital BPM structure supported by real-time data tracking. The integrated approach led to increased production efficiency (from 79% to 86%), reduced setup times, and improved operational agility. The digital infrastructure empowered operators and supported informed decision-making. This work contributes to Industrial Engineering, Business Administration, and MIS by offering a holistic model that bridges lean principles with Industry 4.0 technologies. The findings, though context-specific, provide actionable insights for manufacturers aiming for smart and sustainable operations. Future research should validate the proposed framework across diverse industrial contexts and assess its longitudinal impact on lean performance outcomes. Full article

Background: Digital light processing (DLP) is widely used in permanent dental restorations for its precision and efficiency, yet the effects of build orientation and post-washing time on resin properties remain unclear. This study aims to investigate the factors that impact the performance and biocompatibility of DLP-printed dental resins. Methods: Specimens were additively manufactured using permanent dental resin at 0°, 15°, and 90° orientations and post-washed for 90, 120, or 150 s. Evaluated properties included dimensional accuracy, hardness, flexural strength and modulus, degree of conversion, water sorption/solubility, and cytotoxicity. Results: Build orientation and post-washing time significantly affected dimensional accuracy, with thickness showing the least deviation. Flexural strength (p < 0.001) and modulus (p < 0.01) were highest at the 0° orientation. Post-washing for 90 s led to the greatest water absorption, while solubility remained unaffected. Cell viability increased with longer post-washing times, peaking at 150 s, with significant effects observed on days 5 and 7 (p < 0.05). Conclusions: Build orientation significantly affected dimensional accuracy and flexural strength, while post-washing time had minimal impact on physical properties. Notably, extended post-washing improved cell viability and reduced cytotoxicity, indicating its potential to enhance the clinical biocompatibility of DLP-fabricated dental resin. Full article

The convergence of nanotechnology with nuclear medicine has led to the development of theranostic nanoplatforms that combine targeted imaging and therapy within a single system. This review provides a critical and updated synthesis of the current state of nanoplatform-based theranostics, with a particular focus on their application in oncology. We explore multifunctional nanocarriers that integrate diagnostic radionuclides for SPECT/PET imaging with therapeutic radioisotopes (α-, β-, or Auger emitters), chemotherapeutics, and biological targeting ligands. We highlight advances in nanomaterial engineering—such as hybrid architectures, surface functionalization, and stimuli-responsive designs—that improve tumor targeting, biodistribution, and therapeutic outcomes. Emphasis is placed on translational challenges including pharmacokinetics, toxicity, regulatory pathways, and GMP-compliant manufacturing. The article closes with a forward-looking perspective on how theranostic nanoplatforms could reshape the future of personalized oncology through precision-targeted diagnostics and radiotherapy. Full article

The addition of sea buckthorn(Hippophae rhamnoides L.) fruits as well as their extracted juice or, even more interestingly, related by-products into chocolate results in manufacturing an innovative functional food rich in bioactive substances. Thirteen treatments derived from the factorial combination of three types of H. rhamnoides materials (total fruit powder; fruit by-product powder; and fruit juice) and four concentrations (10%, 15%, 20% and 25%), plus an untreated control, were compared in terms of texture, quality, colour, antioxidant, mineral and sensorial properties of white chocolate. The untreated control showed the highest values of most of the texture parameters, as well as of pH, dry matter, soluble solids and colour component ‘L’. The colour component ‘b’ was best influenced by the 10% by-product addition to chocolate, whereas mineral substances, ash and colour component ‘a’ augmented with the increasing concentration of added H. rhamnoides materials. Compared to the untreated control, protein and fat contents in chocolate decreased with the rising added concentration of sea buckthorn fruit juice but showed the opposite trend under the integration of the whole fruit and its by-products. The antioxidant compounds and activity increased from the untreated chocolate to the highest concentration of added sea buckthorn materials. The juice addition to the chocolate best affected vitamin C, total carotenoids, β-carotene and lycopene, whereas the whole fruit integration led to the top levels of flavonoids, polyphenols and antioxidant activity. Potassium and zinc contents decreased from the untreated control to the highest H. rhamnoides material addition, whereas opposite trends were shown by calcium, magnesium, sodium and phosphorus. The integration of H. rhamnoides fruit materials into chocolate presents a valuable strategy to produce innovative health beneficial functional food. Full article

Human activities have led to severe aquatic pollution and significant concerns about the ecological health of the Lianjiang River Basin (LRB). These concerns resulted in the implementation of comprehensive policies and treatments to improve the sediment and water quality. Herein, we explore the concentrations, sources, and degree of metal contamination in filtered water (FW), suspended solids (SSs), and surficial channel sediments (SCSs) in streams of the LRB. Calculated enrichment factors, an ecological risk index, and a principal component analysis were employed to understand the degree of elemental contamination, ecological risks, and their potential sources. Elements (e.g., Hg, Cd, Sn, Sb, Cu, and Mo) were mainly detected in FW, SSs, and SCSs in the Bergang, Hucheng, Xiashan, and Zhonggang rivers, and the mainstream of the LR. Four potential anthropogenic sources were identified, including electronic waste recycling (e.g., Cu, Sb, Pb, and Ni), mixed pollution (e.g., Se, Zn, Mn, and Mo), metal processing (e.g., Hg, Cr, Sn, and Cd), and battery manufacturing and recycling (e.g., Co, Ni, and Mn). Overall, Sn, Sb, Hg, Cu, and Cd were enriched by 37.5–79.2% and 34.8–91.3% at the SS and SCS sites, respectively. Mercury, Cd, Sn, Sb, Cu, and Mo posed the most risk both in the SSs and SCSs. Overall, the SS and SCS samples from the LRB remain severely contaminated with metals after recent environmental remediation. The implementation of pollution source control, sewage interception, and dredging operations should be further enhanced. Full article

The REPowerEU plan is aimed at a target of 35 bcm of biomethane annually by 2030, up from 4 bcm in 2023, requiring about EUR 37 billion in investment. Food waste is identified as a key feedstock, characterized by discrete homogeneity, although its availability may vary seasonally. In Italy, the Emilia-Romagna region generates approximately 450 kt/y of industrial waste from the food and beverage sector, primarily originating from meat processing (NACE 10.1), fruit and vegetable processing (NACE 10.3), and the manufacture of vegetable and animal oils and fats (NACE 10.4). Of this amount, food and beverage processing waste (EWC 02) accounts for about 302 kt from NACE 10 (food, year 2019) and 14 kt from NACE 11 (beverage, year 2019). This study provides a comprehensive screening of waste streams generated by the local food and beverage industry in Emilia-Romagna, evaluating the number of enterprises, their value added, and recorded waste production. The screening led to the identification of suitable streams for further valorization strategies: a total of ~93 kt/y was selected for the preliminary conceptual design of an integrated process combining anaerobic digestion with hydrothermal treatment, aimed at supporting national biomethane production targets while maximizing material recovery through hydrochar production. Preliminary estimations indicate that the proposed process may achieve a biochemical methane potential of approximately 0.23 Nm³/kg_VS, along with a hydrochar yield of about 130 kg/t_waste. Full article

The yellowing effect of camphorquinone (CQ) has led manufacturers to add alternative initiators into resin composites (RCs) to reduce the amount of CQ used. The aim of this study was to investigate the color change in commercial RCs with alternative photoinitiators besides CQ. Color change upon polymerization and aging in air and artificial saliva for up to 3 months was tested for seven commercial RCs (traditional and bulk-fill) with either CQ only or CQ and additional photoinitiators (CQ+). Color measurements were obtained with a spectrophotometer. Color change (ΔE) was calculated using the CIELab and CIEDE2000 formulae. ANOVA and a post hoc SNK test were conducted for statistical analysis. Upon polymerization, the ΔE of CQ+ was greater than that of CQ only, except in the case of dual-cure HyperFIL. The storage conditions did not affect the color change within 24 h for either air or artificial saliva, whereas they did have an influence on color stability when RCs were aged for 1 month and 3 months. The color changes in the RCs aged in artificial saliva were considered clinically acceptable for all RCs tested except HyperFIL. Additional photoinitiator systems tended to result in a greater color change upon polymerization but did not affect color change upon aging. During shade selection, especially when additional photoinitiators besides CQ are used, a guide reflecting the color after polymerization should be used. Full article

Background: Enamel surface roughness after bracket debonding is an important issue due to its impact on plaque accumulation and the potential development of carious lesions. This in vitro study aimed to assess enamel roughness after the removal of metallic and sapphire brackets and the effect of a remineralization treatment. Methods: Two hundred extracted human permanent teeth with healthy enamel were randomly distributed into two groups (n = 100) and bonded with either metallic or sapphire brackets using the same adhesive (3M™ Transbond™ XT (St. Paul, MN, USA), Minnesota Mining and Manufacturing Company, MN, USA). The enamel surface roughness was measured before bonding, after debonding, and after remineralization using SEM and a TR200 roughness (SaluTron GmbH, Frechen, Germany) tester. The parameter Ra was used to quantify the surface roughness. One-way ANOVA, the normality test, variance homogeneity, and the Bonferroni post hoc test were used to analyze the data. Results: Debonding significantly increased the enamel surface roughness in both groups. The sapphire bracket group presented significantly higher mean Ra values post debonding (4.14 ± 0.36 µm) compared to the metallic group (2.56 ± 0.52 µm). Remineralization led to a decrease in surface roughness in both groups, though not to baseline levels. The changes were statistically significant (p < 0.01), with a power of the test of 1.0. Conclusions: The bracket material significantly affects enamel surface roughness after orthodontic debonding. Sapphire brackets produced greater surface irregularities than metallic ones. Remineralization partially reduced roughness in both groups, with the final values in the metallic group being closer to baseline levels. Crucially, these values remained far above the clinical threshold for plaque retention, highlighting the need for improved debonding techniques. Full article

To address issues such as leading-edge and trailing-edge ablation and cracking of turbine blades during operation in an engine, this study integrates the characteristics of additive manufacturing technology and utilizes a comprehensive simulation and design platform for turbine-cooled blades to design three schemes of film cooling structures. Numerical simulations were employed to optimize the blade cooling configurations, resulting in a finalized cooling structure scheme, which was then subjected to experimental evaluation of its cooling performance. An experimental platform for turbine blade cooling effectiveness was established, capable of simulating actual engine operating parameters. Based on this platform, experimental studies were conducted to investigate the effects of key parameters—including pressure ratio(β), temperature ratio(K), and flow ratio(B) on the cooling effectiveness and the dimensionless temperature distribution on the blade surface. Experimental results show that within the studied operating conditions, the β has a greater impact on the cooling effectiveness of the blade compared to variations in B and K. When the β = 1.2, the cooling effectiveness of the blade surface is 0.130, and when β = 1.6, the effectiveness increases to 0.176, representing a 35.38% improvement. Within the tested range, variations in flow ratio resulted in a 19.12% increase in cooling effectiveness, while changes in temperature ratio led to a 26.62% improvement. Full article

The increasing adoption of additive manufacturing in applications requiring high strength, stiffness, and lightness has highlighted the need to outclass the classical design methodologies. As a matter of fact, traditional design approaches often fail to exploit additive manufacturing’s full potential. To address this need, this research presents an innovative design of a vertical tail for an unmanned aerial vehicle by integrating the generative design optimization strategy for additive manufacturing and engineered technopolymers reinforced with chopped carbon fiber. The proposed iterative method, combined with a high strength carbon fiber material, led to significant mass reductions, up to 71.2%, compared with a metallic design. Full article

Background: Severe class imbalance limits reliable tabular AI in manufacturing, finance, and healthcare. Methods: We built a modular pipeline comprising correlation-aware seriation; a hybrid convolutional neural network (CNN)–transformer–Bidirectional Long Short-Term Memory (BiLSTM) encoder; variational autoencoder (VAE)-based minority augmentation; and deep/tree ensemble heads (XGBoost and Support Vector Machine, SVM). We benchmarked the Synthetic Minority Oversampling Technique (SMOTE) and ADASYN under identical protocols. Focal loss and ensemble weights were tuned per dataset. The primary metric was the Area Under the Precision–Recall Curve (AUPRC), with receiver operating characteristic area under the curve (ROC AUC) as complementary. Synthetic-data fidelity was quantified by train-on-synthetic/test-on-real (TSTR) utility, two-sample discriminability (ROC AUC of a real-vs-synthetic classifier), and Maximum Mean Discrepancy (MMD²). Results: Across five datasets (SECOM, CREDIT, THYROID, APS, and UCI), augmentation was data-dependent: VAE led on APS (+3.66 pp AUPRC vs. SMOTE) and was competitive on CREDIT (+0.10 pp vs. None); the SMOTE dominated SECOM; no augmentation performed best for THYROID and UCI. Positional embedding (PE) with seriation helped when strong local correlations were present. Ensembles typically favored XGBoost while benefiting from the hybrid encoder. Efficiency profiling and a slim variant supported latency-sensitive use. Conclusions: A data-aware recipe emerged: prefer VAE when fidelity is high, the SMOTE on smoother minority manifolds, and no augmentation when baselines suffice; apply PE/seriation selectively and tune per dataset for robust, reproducible deployment. Full article

The growing complexity and scale of Cyber–Physical Systems (CPSs) have led to an increasing need for the holistic orchestration of multiple Digital Twins (DTs). Therefore, an extension to the UniTwin framework is introduced within this paper. UniTwin is a containerized, cloud-native DT framework. This extension enables the hierarchical aggregation of DTs across various abstraction levels. Traditional DT frameworks often lack mechanisms for dynamic composition at the level of entire systems. This is essential for modeling distributed systems in heterogeneous environments. UniTwin addresses this gap by grouping DTs into composite entities with an aggregation mechanism. The aggregation mechanism is demonstrated in a smart manufacturing case study, which covers the orchestration of a production line for personalized shopping cart chips. It uses modular DTs provided for each device within the production line. A System-Aggregated Digital Twin (S-ADT) is used to orchestrate the individual DTs, mapping the devices in the production line. Therefore, the production line adapts and reconfigures according to user-defined parameters. This validates the flexibility and practicality of the aggregation mechanism. This work contributes an aggregation mechanism for the UniTwin framework, paving the way for adaptable DTs for complex CPSs in domains like smart manufacturing, logistics, and infrastructure. Full article