Search Results (1,328)

Because of the relevance of Salmonella spp. in poultry, in 2016, the Brazilian Ministry of Agriculture, Livestock, and Supply updated its regulation for the control and monitoring of Salmonella in the poultry meat production chain. We herein present the results of the official monitoring of sampling cycles of carcasses performed by the Brazilian official veterinary inspection service (SIF) and the Center for Epidemiology, Statistics, and Public Health of the Veterinary School of the Federal University of Minas Gerais. Samples were collected in March–September 2017, during which 140 slaughterhouses slaughtered over three billion chickens. The establishments were classified according to the number of animals slaughtered per day, and cycles varied according to the size of the establishment. Sample weights were defined to increase the external validity of the data. Chicken carcasses were randomly sampled after chilling and dripping. A total of 1434 samples were analyzed in official laboratories using Vidas SLM and SPT systems, for positive samples were used the ISO 6579:2014. The estimated prevalence of Salmonella spp. in chicken carcasses was 17.88% (95% CI 14.34–22.05). Considering the representativeness of Brazilian chicken meat in the global market, constant evaluation and review of the program is necessary to reduce the prevalence of Salmonella. Full article

Silicon carbide (SiC), a wide-bandgap semiconductor, is renowned for its exceptional performance in power electronics and extreme-temperature environments. However, precision low-loss laser slicing of SiC is impeded by energy divergence and crack delamination induced by refractive-index-mismatch interfacial aberrations. This study presents an integrated laser slicing system based on a liquid crystal on silicon spatial light modulator (LCOS-SLM) to address aberration-induced focal elongation and energy inhomogeneity. Through dynamic modulation of the laser wavefront via an inverse ray-tracing algorithm, the system corrects spherical aberrations from refractive index mismatch, thus achieving precise energy concentration at wanted depths. A laser power attenuation model based on interface reflection and the Lambert–Beer law is established to calculate the required laser power at varying processing depths. Experimental results demonstrate that aberration correction reduces focal depth to approximately one-third (from 45 μm to 15 μm) and enhances energy concentration, eliminating multi-layer damage and increasing crack propagation length. Post-correction critical power measurements across depths are consistent with model predictions, with maximum error decreasing from >50% to 8.4%. Verification on a 6-inch N-type SiC ingot shows 90 μm damage thickness, confirming system feasibility for SiC laser slicing. The integrated aberration-correction approach provides a novel solution for high-precision SiC substrate processing. Full article

This research presents a novel methodology for lightweighting and cost reduction of components with high structural demands by integrating advanced design and manufacturing techniques. Specifically, it combines topology optimization (TO) with additive manufacturing (AM), also known as 3D printing. Unlike conventional approaches, the proposed method first determines the optimal geometry using an artificially stiff material, and only then evaluates real materials for structural and manufacturing feasibility. This design-first, material-second strategy enables broader material screening and maximizes weight reduction without compromising performance. The proposed workflow is applied to the design of a turbofan air intake—an aeronautical component operating under supersonic conditions—addressing both structural integrity and manufacturing feasibility. Three materials from distinct classes are assessed: two metallic alloys (aluminum alloy 6061 and titanium alloy, Ti6Al4V) and a high-performance polymer (polyetheretherketone, PEEK). This last option is preliminarily discarded after being analyzed for this specific application. Finite element (FE) simulations are used to evaluate the mechanical behavior of the optimized geometries, including bird-strike conditions. Among the evaluated manufacturing techniques, Selective Laser Melting (SLM) is identified as the most suitable for the metallic materials selected, providing an effective balance between performance, manufacturability, and aerospace compliance. This study illustrates the potential of TO–AM synergy as a sustainable and efficient design approach for next-generation aerospace components. Simulation results demonstrate a weight reduction of up to 71% while preserving critical functional regions and maintaining structural integrity in Al 6061 and Ti6Al4V cases, under the diverse loading conditions typical of real flight scenarios, while PEEK remains an attractive option for uses where mechanical demands are less stringent. Full article

Background: The release study is a standard tool for the development, evaluation, and control of dosage forms. In the case of traditional drug delivery systems, it is conducted in accordance with the established principles available in the European and American Pharmacopoeias or guidelines proposed by registration agencies. The problem is the study of modern carriers, not yet described in compendia, which require adjustments to traditionally used methods. Objectives: The present study focuses on developing an optimal method for testing the release of cyclosporine (Cs, 0.5–4%) incorporated in solid lipid microparticles (SLM) dispersions (10%) intended for administration in the form of eye drops. This is a multicompartment lipid carrier that provides prolonged release of the active substance. Methods: Three methods of testing the release were compared: the dialysis bag method, the horizontal cells technique, and a method without a membrane. Results: During the analyses, the proper membrane was selected and the effect of the lysozyme enzyme on the release profile was analyzed. The effect of the composition of the acceptor fluid on the obtained results was also assessed. In the model without a membrane, up to 60% of the Cs was released within 30 min due to the burst effect. In horizontal chambers, no formulation released more than 14% of the Cs over 96 h, while at the same time, 60–70% of the Cs was released from the dialysis bag. Conclusions: Based on the obtained results, the dialysis bag method was selected to study the release of Cs from SLM without the need to use multicomponent artificial tear fluid as an acceptor medium. Full article

Generative Adversarial Networks (GANs) using Long Short-Term Memory (LSTM) provide a computationally cheaper approach for text generation compared to large language models (LLMs). The low hardware barrier of training GANs poses a threat because it means more bad actors may use them to mass-produce prompt attack messages against LLM systems. Thus, to better understand the threat of GANs being used for prompt attack generation, we train two well-known GAN architectures, SeqGAN and RelGAN, on prompt attack messages. For each architecture, we evaluate generated prompt attack messages, comparing results with each other, with generated attacks from another computationally cheap approach, a 1-billion-parameter Llama 3.2 small language model (SLM), and with messages from the original dataset. This evaluation suggests that GAN architectures like SeqGAN and RelGAN have the potential to be used in conjunction with SLMs to readily generate malicious prompts that impose new threats against LLM-based systems such as chatbots. Analyzing the effectiveness of state-of-the-art defenses against prompt attacks, we also find that GAN-generated attacks can deceive most of these defenses with varying levels of success with the exception of Meta’s PromptGuard. Further, we suggest an improvement of prompt attack defenses based on the analysis of the language quality of the prompts, which we found to be the weakest point of GAN-generated messages. Full article

The study is motivated by the application of dry finish milling for post-build processing of additive Ti6Al4V blanks, since the use of neither lubricant nor coolants has been attracting increasing attention due to its environmental benefits, non-toxicity, and the elimination of the need for additional cleaning processes. For end mills, wear patterns were investigated upon finish milling of the SLM Ti6Al4V samples under various machining conditions (by varying the values of radial depth of cut and feed values at a constant level of axial depth of cut and cutting speed). When using all the applied milling modes, the identical tool wear mechanism was revealed. Built-up edges mainly developed on the leading surfaces, increasing the surface roughness on the SLM Ti6Al4V samples but protecting the cutting edges. However, abrasive wear was mainly characteristic of the flank surfaces that accelerated peeling of the protective coatings and increased wear of the end mills. The following milling parameters have been established as being close to rational ones: Vc = 60 m/min, Vf = 400 mm/min, a_p = 4 mm, and a_e = 0.4 mm. They affected the surface roughness of the SLM Ti6Al4V samples in the following way: max cutting thickness—8 μm; built-up edge at rake surface—50 ± 3 μm; max wear of flank surface—15 ± 1 μm; maximum adherence of workpiece. Mode III provided the maximum MRR value and negligible wear of the end mill, but its main disadvantage was the high average surface roughness on the SLM Ti6Al4V sample. Mode II was characterized by both the lowest average surface roughness and the lowest wear of the end mill, as well as an insufficient MRR value. Since these two modes differed only in their feed rates, their values should be optimized in the range from 200 to 400 mm/min. Full article

This study investigates the mechanical, tribological, and electrochemical behaviour of a novel precipitation-hardenable martensitic alloy produced by selective laser melting (SLM). The alloy was specifically engineered with an optimised composition, free from cobalt and molybdenum, and featuring reduced nickel content (7 wt.%) and 8 wt.% chromium. It has been developed as a cost-effective and sustainable alternative to conventional maraging steels, while maintaining high mechanical strength and a refined microstructure tailored to the steep thermal gradients inherent to the SLM process. Several ageing heat treatments were assessed to evaluate their influence on microstructure, hardness, tensile strength, retained austenite content, dislocation density, as well as wear behaviour (pin-on-disc test) and corrosion resistance (polarisation curves in 3.5%NaCl). The results indicate that ageing at 540 °C for 2 h offers an optimal combination of hardness (550–560 HV), tensile strength (~1700 MPa), microstructural stability, and wear resistance, with a 90% improvement compared to the as-built condition. In contrast, ageing at 600 °C for 1 h enhances ductility and corrosion resistance (Rp = 462.2 kΩ; Ecorr = –111.8 mV), at the expense of a higher fraction of reverted austenite (~34%) and reduced hardness (450 HV). This study demonstrates that the mechanical, surface, and electrochemical performance of this novel SLM-produced alloy can be effectively tailored through controlled thermal treatments, offering promising opportunities for demanding applications requiring a customised balance of strength, durability, and corrosion behaviour. Full article

This narrative review explores the role of additive manufacturing (AM) technologies in the production of dental implants, focusing on materials and key AM methods. The study discusses several materials used in implant fabrication, including porous titanium, trabecular tantalum, zirconium dioxide, polymers, and composite materials. These materials are evaluated for their mechanical properties, biocompatibility, and suitability for AM processes. Additionally, the review examines the main AM technologies used in dental implant production, such as selective laser melting (SLM), electron beam melting (EBM), stereolithography (SLA), selective laser sintering (SLS), and direct metal laser sintering (DMLS). These technologies are compared based on their accuracy, material limitations, customization potential, and applicability in dental practice. The final section presents a data source analysis of the Web of Science and Scopus databases, based on keyword searches. The analysis evaluates the research trends using three criteria: publication category, document type, and year of publication. This provides an insight into the evolution and current trends in the field of additive manufacturing for dental implants. The findings highlight the growing importance of AM technologies in producing customized and efficient dental implants. Full article

This study dives into what drives people to use AR filters in the catering industry, focusing on the Hong Kong market. The main idea is to determine how “perceived value” shapes users’ intentions to engage with these filters. To do this, the research combines concepts from two popular models—the extended Technology Acceptance Model (TAM) and the Satisfaction–Loyalty Model (SLM)—to understand what influences perceived value. The survey data were then analyzed with Structural Equation Modeling (SEM) to see how perceived usefulness, enjoyment, satisfaction, and value connect to users’ intentions. The results showed that “perceived value” is a big deal—the main factor driving whether people want to use AR filters. Things like how useful or enjoyable the filters are and how satisfied users feel all play a role in shaping this perceived value. These findings are gold for marketing teams and AR developers, especially in the catering world. Combining TAM and the Satisfaction–Loyalty Model offers a fresh perspective on how AR technology influences consumer behavior. On top of that, it gives practical advice for businesses looking to make the most of AR filters in their marketing and customer experience strategies. Full article

The research presented in this paper is based on the need for personalized medical implants, whose serial production is impossible, so the need for production process adjustments is inevitable. Conventional production technologies usually set geometrical limitations and generate a lot of waste material, which leads to great expenses, especially when the material used for production is an expensive Ti alloy. Additive technologies offer the possibility to produce a product almost without waste material and geometrical limitations. Nevertheless, the methods developed for additive production using metal powder are not significantly used in biomedicine because there is insufficient data published regarding the properties of additively produced parts, especially from the fatigue and fracture standpoint. The aim of this research is the experimental determination of fracture mechanics properties of additively produced parts and their comparison with the properties of parts produced by conventional technologies. Drawing is the first production process in the comparison, and the second one is selective laser melting (SLM). The Ti-alloy Ti-6Al-7Nb, used for medical implants, was selected for this research. Experimental testing was performed in order to determine ΔK_th fracture mechanics parameters and resistance curves according to ASTM E1820. Test specimen dimensioning and the experiments were carried out according to the respective standards. For the drawn test specimen, the value obtained was ΔK_th = 3.84 MPam^0.5, and the fracture toughness was K_c = 84 MPam^0.5, while for SLM produced test specimens the values were ΔK_th = 4.53 MPam^0.5, and K_c = 21.9 MPam^0.5. Full article

A Cu-11.85Al-3.2Mn-0.1Ti shape memory alloy (SMA) with excellent superelasticity and shape memory effect was successfully fabricated via selective laser melting (SLM). Increasing the energy density enhanced grain refinement, achieving a 90% refinement rate compared to cast alloy, with an average width of ~0.15 µm. Refined martensite lowered transformation temperatures and increased thermal hysteresis. Nanoscale Cu₂TiAl phases precipitated densely within the matrix, forming a dual strengthening network combining precipitation hardening and dislocation hardening. This mechanism yielded a room-temperature tensile strength of 829.07 MPa, with 6.38% fracture strain. At 200 °C, strength increased to 883.68 MPa, with 12.26% strain. The maximum tensile strength represents a nearly 30% improvement on existing laser-melted quaternary Cu-based SMAs. Full article

Selective laser melting (SLM) offers a novel approach for manufacturing intricate structures, broadening the application of titanium alloy parts in the aerospace industry. After the build period, heat treatments of annealing (AT) and hot isostatic pressing (HIP) are often implemented, but a comparison of their mechanical performances based on the specimen orientation is still lacking. In this study, horizontally and vertically built Ti6Al4V SLM specimens that underwent the aforementioned treatments, together with their microstructural and defect characteristics, were, respectively, investigated using metallography and X-ray imaging. The mechanical properties and failure mechanism, via fracture analysis, were obtained. The critical factors influencing the mechanical properties and the correlation of the fatigue lives and failure origins were also estimated. The results demonstrate that the mechanical performances were determined by the α-phase morphology and defects, which included micropores and fewer large lack-of-fusion defects. Following the coarsening of the α phase, the strength decreased while the plasticity remained stable. With the discrepancy in the defect occurrence, anisotropy and scatter of the mechanical performances were introduced, which was significantly alleviated with HIP treatment. The fatigue failure origins were governed by defects and the α colony, which was composed of parallel α phases. Approximately linear relationships correlating fatigue lives with the X-parameter and maximum stress amplitude were, respectively, established in the AT and HIP states. The results provide an understanding of the technological significance of the evaluation of mechanical properties. Full article

Text2Cypher is a text-to-text task that converts natural language questions into Cypher queries. Recent research by Neo4j on Text2Cypher demonstrates that fine-tuning a baseline language model (a pretrained and instruction-tuned generative model) using a comprehensive Text2Cypher dataset can effectively enhance query generation performance. However, the improvement is still insufficient for effectively learning the syntax and semantics of complex natural texts, particularly when applied to unseen Cypher schema structures across diverse domains during training. To address this challenge, we propose a novel refinement training method based on baseline language models, employing reinforcement learning with Group Relative Policy Optimization (GRPO). This method leverages extracted semantic information, such as key-value properties and triple relationships from input texts during the training process. Experimental results of the proposed refinement training method applied to a small-scale baseline language model (SLM) like Qwen2.5-3B-Instruct demonstrate that it achieves competitive execution accuracy scores on unseen schemas across various domains. Furthermore, the proposed method significantly outperforms most baseline LMs with larger parameter sizes in terms of Google-BLEU and execution accuracy scores over Neo4j’s comprehensive Text2Cypher dataset, with the exception of colossal LLMs such as GPT4o, GPT4o-mini, and Gemini. Full article

Small Language Models (SLMs) have emerged as a critical area of study within natural language processing, attracting growing attention from both academia and industry. This systematic literature review provides a comprehensive and reproducible analysis of recent developments and advancements in SLMs post-2023. Drawing on 70 English-language studies published between January 2023 and January 2025, identified through Scopus, IEEE Xplore, Web of Science, and ACM Digital Library, and focusing primarily on SLMs (including those with up to 7 billion parameters), this review offers a structured overview of the current state of the art and potential future directions. Designed as a resource for researchers seeking an in-depth global synthesis, the review examines key dimensions such as publication trends, visual data representations, contributing institutions, and the availability of public datasets. It highlights prevailing research challenges and outlines proposed solutions, with a particular focus on widely adopted model architectures, as well as common compression and optimization techniques. This study also evaluates the criteria used to assess the effectiveness of SLMs and discusses emerging de facto standards for industry. The curated data and insights aim to support and inform ongoing and future research in this rapidly evolving field. Full article

In this study, the influence of annealing on the phase evolution and mechanical properties of the Fe₆₂Ni₁₈P₁₃C₇ (at.%) alloy was investigated. Ribbons produced via melt-spinning were annealed at various temperatures, and their structural transformations and hardness were evaluated. The alloy exhibited a narrow supercooled liquid region (ΔT_x ≈ 22 °C), confirming its low glass-forming ability (GFA). Primary crystallization began at approximately 380 °C with the formation of α-(Fe,Ni) and Fe₂NiP, followed by the emergence of γ-(Fe,Ni) phase at higher temperatures. A significant increase in hardness was observed after annealing up to 415 °C, primarily due to nanocrystallization and phosphide precipitation. Further heating resulted in a hardness plateau, followed by a noticeable decline. Additionally, samples were produced via selective laser melting (SLM). The microstructure of the SLM-processed material revealed extensive cracking and the coexistence of phosphorus-rich regions corresponding to Fe₂NiP and iron-rich regions associated with γ-(Fe,Ni). Full article