Search Results (96)

Background: Salmonella is a bacterium that causes foodborne infections. This study characterized two strains isolated from cheese and beef in Brazil using whole-genome sequencing (WGS). Objectives: We evaluated their antimicrobial resistance profiles, virulence factors, plasmid content, serotypes and phylogenetic relationships. Methods: DNA was extracted and sequenced on the NovaSeq 6000 platform; the pangenome was assembled using the Roary tool; and the phylogenetic tree was constructed via IQ-TREE. Results and Discussion: For contextualization and comparison, 3493 Salmonella genomes of Brazilian origin from NCBI were analyzed. In our isolates, both strains carried the aac(6′)-Iaa_1 gene, while only Schwarzengrund harbored the qnrB19_1 gene and the Col440I_1 plasmid. Cerro presented the islands SPI-1, SPI-2, SPI-3, SPI-4, SPI-5 and SPI-9, while Schwarzengrund also possessed SPI-13 and SPI-14. Upon comparison with other Brazilian genomes, we observed that Cerro and Schwarzengrund represented only 0.40% and 2.03% of the national database, respectively. Furthermore, they revealed that Schwarzengrund presented higher levels of antimicrobial resistance, a finding supported by the higher frequency of plasmids in this serovar. Furthermore, national data corroborated our findings that SPI-13 and SPI-14 were absent in Cerro. A virulence analysis revealed distinct profiles: the cdtB and pltABC genes were present in the Schwarzengrund isolates, while the sseK and tldE1 family genes were exclusive to Cerro. The results indicated that the sequenced strains have pathogenic potential but exhibit low levels of antimicrobial resistance compared to national data. The greater diversity of SPIs in Schwarzengrund explains their prevalence and higher virulence potential. Conclusions: Finally, the serovars exhibit distinct virulence profiles, which results in different clinical outcomes. Full article

Interventional radiology offers minimally invasive procedures guided by real-time imaging, reducing surgical risks and enhancing patient recovery. While beneficial to patients, these advancements increase occupational hazards for physicians due to chronic exposure to ionizing radiation. This exposure raises health risks like radiation-induced cataracts, cardiovascular disease, and cancer. Despite regulations like the European Council Directive 2013/59/EURATOM, which sets limits on whole-body and eye lens doses, no dose limits exist for the brain and meninges, since the brain has traditionally been considered a radioresistant organ. Recent studies, however, have highlighted radiation-induced brain damage, suggesting that meningeal exposure in interventional radiology may be underestimated. This study evaluates the entrance air Cumulative mean annual entrance air kerma to the skullull during interventional radiology procedures, using thermoluminescent dosimeters and controlled exposure simulations. Data were collected by varying the exposure time and analyzing the contribution to the entrance air kerma on each side of the head. The results indicate that, considering the attenuation of the cranial bone, the absorbed dose to the brain, obtained by averaging the head entrance air kerma for the right, front, and left sides of the operator’s head, could represent 0.81% to 2.18% of the annual regulatory limit in Italy of 20 mSv for the average annual effective dose of exposed workers (LD 101/2020). These results provide an assessment of brain exposure, highlighting the relatively low but non-negligible contribution of brain irradiation to the overall occupational dose constraint. Additionally, a correlation between entrance air kerma and the Kerma-Area Product was observed, providing a potential method for improved dose estimation and enhanced radiation safety for interventional radiologists. Full article

Autonomous vehicles are one of the key components of smart mobility that leverage innovative technology to navigate and operate safely in urban environments. Traffic light detection systems, as a key part of autonomous vehicles, play a key role in navigation during challenging traffic scenarios. Nighttime driving poses significant challenges for autonomous vehicle navigation, particularly in regard to the accuracy of traffic lights detection (TLD) systems. Existing TLD methodologies frequently encounter difficulties under low-light conditions due to factors such as variable illumination, occlusion, and the presence of distracting light sources. Moreover, most of the recent works only focused on daytime scenarios, often overlooking the significantly increased risk and complexity associated with nighttime driving. To address these critical issues, this paper introduces a novel approach for nighttime traffic light detection using the LNT-YOLO model, which is based on the YOLOv7-tiny framework. LNT-YOLO incorporates enhancements specifically designed to improve the detection of small and poorly illuminated traffic signals. Low-level feature information is utilized to extract the small-object features that have been missing because of the structure of the pyramid structure in the YOLOv7-tiny neck component. A novel SEAM attention module is proposed to refine the features that represent both the spatial and channel information by leveraging the features from the Simple Attention Module (SimAM) and Efficient Channel Attention (ECA) mechanism. The HSM-EIoU loss function is also proposed to accurately detect a small traffic light by amplifying the loss for hard-sample objects. In response to the limited availability of datasets for nighttime traffic light detection, this paper also presents the TN-TLD dataset. This newly curated dataset comprises carefully annotated images from real-world nighttime driving scenarios, featuring both circular and arrow traffic signals. Experimental results demonstrate that the proposed model achieves high accuracy in recognizing traffic lights in the TN-TLD dataset and in the publicly available LISA dataset. The LNT-YOLO model outperforms the original YOLOv7-tiny model and other state-of-the-art object detection models in mAP performance by 13.7% to 26.2% on the TN-TLD dataset and by 9.5% to 24.5% on the LISA dataset. These results underscore the model’s feasibility and robustness compared to other state-of-the-art object detection models. The source code and dataset will be available through the GitHub repository. Full article

Tuned Liquid Dampers (TLDs) are dissipative devices that mitigate vibrations through the out-of-phase movement of a fluid, typically water, inside a container relative to a main structure. Water’s low density and viscosity have led to modifications to enhance their effectiveness. Fluid properties, such as density or viscosity, significantly impact their performance by altering mass and damping, respectively. When magnetorheological fluids are employed, magnetic fields can modify the fluid viscosity, affecting the damping. This study experimentally examines the effect of a magnetic field and ambient parameters on the viscosity of different low-cost, custom-prepared magnetic fluids. A tube filled with magnetic liquids into which diverse non-magnetic spheres are dropped was employed, considering on- and off-states of the magnetic field generated by a pair of Helmholtz coils. The impact on the fluid viscosity variation of different measured variables was statistically analyzed. It was found that in all cases, the variations in ambient temperature and relative humidity had no effect on the results. While the magnetic field had a large effect on the viscosity of the magnetic fluid, for the sunflower oil-based fluids, the spheres used or the concentration of iron filings had a greater effect on the viscosity than the presence of the magnetic field. Full article

In vivo dosimetry (IVD) is a vital component of modern radiotherapy, ensuring accurate and safe delivery of radiation doses to patients by measuring dose parameters during treatment. This paper provides a comprehensive overview of IVD, covering its fundamental principles, historical development, and the technologies used in clinical practice. Key techniques, including thermoluminescent dosimeters (TLDs), optically stimulated luminescent dosimeters (OSLDs), diodes, metal-oxide-semiconductor field-effect transistors (MOSFETs), and electronic portal imaging devices (EPIDs), are discussed, highlighting their clinical applications, advantages, and limitations. The role of IVD in external beam radiotherapy, brachytherapy, and pediatric treatments is emphasized, particularly its contributions to quality assurance, treatment validation, and error mitigation. Challenges such as measurement uncertainties, technical constraints, and integration into clinical workflows are explored, along with potential solutions and emerging innovations. The paper also addresses future perspectives, including advancements in artificial intelligence, adaptive radiotherapy, and personalized dosimetry systems. This entry underscores the critical role of IVD in enhancing the precision and reliability of radiotherapy, advocating for ongoing research and technological development. Full article

Background/Objectives: Phenylketonuria (PKU) is a rare inherited metabolic disorder caused by phenylalanine hydroxylase deficiency, resulting in highly elevated blood phenylalanine (Phe) concentrations, leading to neurotoxic effects. Despite advancements in treatment, adult patients with PKU may experience impairments in executive functions (EFs). This study investigates the influence of metabolic control across different life stages on EFs and sociodemographic outcomes in adult PKU. Methods: We conducted a monocentric study with 36 early-diagnosed and treated PKU patients (mean age: 34.8 years). EFs were assessed using the Test Battery for Attentional Performance (TAP) and the Tower of London (TL-D). Metabolic data were extracted from medical records, focusing on childhood and adulthood metabolic control, including Phe fluctuations. Sociodemographic data were collected via questionnaires. Statistical analyses explored relationships between EFs, metabolic control, and sociodemographic data. Results: EFs in the cohort were within the lower average range. Significant negative correlations could be observed between EF performance and dried blood Phe concentrations during childhood (ages 0–10 years) as well as current Phe concentrations and Phe variation. Elevated childhood Phe concentrations were associated with lower educational attainment. Sociodemographic characteristics, such as employment status and living arrangements, aligned with those of the general population. Conclusions: Optimal cognitive development in PKU requires good metabolic control, particularly in early childhood. In adulthood, while dietary restrictions may be relaxed, maintaining low and stable Phe concentrations is crucial for EFs. Consistent monitoring and tailored therapeutic approaches throughout life seem essential for optimizing metabolic and neurocognitive outcome in PKU. Full article

Background: Digital tomosynthesis (DTS) is an advanced imaging modality that enhances diagnostic accuracy by offering three-dimensional visualization from two-dimensional projections, which is particularly beneficial in breast and lung imaging. However, this increased imaging capability raises concerns about patient exposure to ionizing radiation. Methods: This study explores the energy and angular dependence of thermoluminescent dosimeters (TLDs), specifically TLD100H, to improve the accuracy of organ dose assessment during DTS. Using a comprehensive experimental approach, organ doses were measured in both DTS and traditional RX modes. Results: The results showed lung doses of approximately 3.21 mGy for the left lung and 3.32 mGy for the right lung during DTS, aligning with the existing literature. In contrast, the RX mode yielded significantly lower lung doses of 0.33 mGy. The heart dose during DTS was measured at 2.81 mGy, corroborating findings from similar studies. Conclusions: These results reinforce the reliability of TLD100H dosimetry in assessing radiation exposure and highlight the need for optimizing imaging protocols to minimize doses. Overall, this study contributes to the ongoing dialogue on enhancing patient safety in diagnostic imaging and advocates for collaboration among medical physicists, radiologists, and technologists to establish best practices. Full article

Background/Objectives: Endogenous oscillations reflect the spontaneous activity of brain networks involved in cognitive processes. In adults, endogenous activity across different bands correlates with, and can even predict, language and speech perception processing. However, it remains unclear how this activity develops in children with typical and atypical development. Methods: We investigated differences in resting-state EEG between preschoolers with developmental language disorder (DLD), their age-matched controls with typical language development (TLD), and a group of adults. Results: We observed significantly lower oscillatory power in adults than in children (p < 0.001 for all frequency bands), but no differences between the groups of children in power or hemispheric lateralisation, suggesting that oscillatory activity reflects differences in age, but not in language development. The only measure that differed between the children’s groups was theta/alpha band ratio (p = 0.004), which was significantly smaller in TLD than in DLD children, although this was an incidental finding. Behavioural results also did not fully align with previous research, as TLD children performed better in the filtered speech test (p = 0.01), but not in the speech-in-babble one, and behavioural test scores did not correlate with high-frequency oscillations, lateralisation indices, or band ratio measures. Conclusions: We discuss the suitability of these resting-state EEG measures to capture group-level differences between TLD/DLD preschoolers and the relevance of our findings for future studies investigating neural markers of typical and atypical language development. Full article

Energy performance improvements in existing homes play a substantial role in the achievement of the UK’s net-zero emissions target. However, retrofitting dwellings remains a particularly challenging task in the UK, where traditional dwellings make up a large part of the building repository. Traditional dwellings’ contribution to decarbonization has not yet been fully realized due to the risks imposed to the thermo-hygrometric balance of their constructions and to their heritage value. These tend to hinder the “fabric-first” approach for the retrofit of such dwellings, where active measures are often prioritized. The aim of this research is to propose a systemic approach to intervene in Traditional Listed Dwellings (TLDs) to improve their energy performance by means of passive retrofit measures and to shape a more future-proof heritage. A mixed methodology was developed that utilizes 19th C TLD case studies (CSs) in South-East England and dynamic energy simulation (DES) to investigate their current energy performance and possible improvements using responsible, safe and effective energy retrofit scenarios. Providing an overview of the methodology adopted in this research, this paper presents the main results of this study. This paper highlights the savings associated with the best-performing combinations of retrofit measures and the areas of intervention where the highest energy and carbon savings can be achieved. Full article

This paper presents a novel Q-value-based formability assessment for optimizing deep drawing processes. The Q-value, derived from thinning limit diagrams (TLDs), uses offset thinning and wrinkling limit curves to define severity levels. It is calculated by summing the product of Pascal’s triangle weighting factors and normalized element counts within each severity level. The effectiveness of this Q-value assessment was demonstrated using experimentally validated finite element analysis (FEA) to optimize blank size, tool geometry, and drawbead design (male bead height and contra-bead radius) for a deep-drawn AA5754-O automotive fuel tank. Validation of FEA results with experimental thickness measurements showed that the Barlat and Lian 1989 yield criterion provided higher accuracy than Hill’s 1948 model. An optimal condition, determined using the Q-value, consists of a 430 mm × 525 mm blank formed by a redesigned tool cooperated with optimized semi-circular drawbead geometries, achieving experimental significant formability improvements by minimizing wrinkling and thinning. During optimization, this study revealed a significant interaction between blank width and length, which influenced formability. Side-wall wrinkles were attributed to insufficient tool support for the blank during forming and were relieved through tool redesign. Furthermore, increasing the male drawbead height effectively reduced wrinkling but led to increased thinning, whereas increasing the contra-bead radius had the opposite effect. Full article

For the first time, thermally stimulated luminescence spectra in the region of high-temperature peaks (up to 770 K) have been measured in NaCl:Li and KCl:Na single crystals (with impurity cations of small ionic radii) exposed to isodose irradiation by X-rays irradiated uniformly. Comparative analysis of these spectra with the spectra of X-ray and tunnel luminescence of the same crystals showed that the luminescence associated with exciton-like formations near impurity cations dominates in all three cases. The formation mechanisms of such bound excitons during a thermal dissociation of complex radiation defects are considered. Integral light sums of high-temperature TSL in NaCl:Li and KCl:Na crystals are significantly higher than that of a standard LiF:Mg, Ti dosimetric crystal (a TLD-100 luminescent dosimeter). Full article

Real-world data on HIV drug resistance (HIVDR) after transitioning to tenofovir disoproxil fumarate/lamivudine/dolutegravir (TLD) are limited. We assessed HIVDR rates and patterns in clients with virological failure (VF) after switching from an NNRTI-based regimen to TLD. A cross-sectional study was conducted in Gaza, Mozambique (August 2021–February 2022), including adults on first-line ART for ≥12 months who transitioned to TLD and had unsuppressed viral load (VL) ≥ 1000 copies/mL six months post-transition. After three adherence counseling sessions, participants with VF underwent genotyping for drug resistance mutations (DRMs) using the Stanford HIVdb Program. Of 717 participants (median age 39.2 years, 70.7% female), 217 (30.2%) had VF, 193 (88.9%) underwent genotyping, with 183 (94.8%) successfully genotyped. Intermediate–high dolutegravir (DTG) resistance was found in 19.6% (36/183). Unsuppressed VL before DTG transition was independently associated with VF (aOR: 2.14). Resistance patterns included 33.3% (12/36; 95% CI: 14.6–46.3) to all three TLD drugs, 55.6% (20/36; 95% CI: 39.3–71.9) to DTG and 3TC, and 11% (4/36; 95% CI: 0.8–21.3) to DTG only. Major drug resistance mutations to DTG included G118R (9.3%), R263K (6.6%), and Q148H/R/K (4.4%). This study highlights the need to consider virologic status before transitioning PLHIV to TLD and suggests that adherence counseling may not prevent resistance in those with unknown or prior VF. Full article

Background: Children with a developmental language disorder (DLD) frequently experience deficits in cognitive skills such as working memory (WM) and sustained attention (SA), which are closely related to language development. Yet, these cognitive deficits remain underexplored in early childhood, particularly during the preschool years. Objective: This study explores WM and SA in Chilean preschoolers with a DLD compared to their typically developing (TD) peers, using the nonverbal tasks “Torpo the Clumsy Mole” for WM and the Continuous Performance Task (CPT) “Duno and the Worms” for SA, both from the Child Neuropsychological Evaluation Test (TENI in Spanish). Method: Thirty DLD and 30 TLD peers (aged 4 to 4 years 11 months) participated. Accuracy and reaction times in both tasks were assessed. Results: The children with a DLD demonstrated significant deficits in working memory accuracy and poorer sustained attention accuracy despite exhibiting shorter reaction times in the sustained attention task compared to TLD children. Conclusions: The findings highlight the multifaceted nature of a DLD, particularly in relation to cognitive dimensions beyond language, such as working memory and sustained attention. Early identification of these differences emphasizes the important role of executive functions in DLDs. Full article

Today, various systems are used to reduce vibrations in civil engineering structures. Among these systems, tuned liquid dampers are the preferred passive systems due to their ability to be designed in different geometries, their low cost, their ease of installation, and their low maintenance costs. This study examines the effectiveness of tuned liquid dampers (TLD) and tuned liquid column dampers (TLCD) under identical geometric conditions and harmonic ground motion to assess which is more efficient in controlling the behavior of a three-storey steel shear frame model equipped with these systems. A small-scale, three-storey shear frame model placed on a uniaxial shaking table was subjected to harmonic motion with a 5 mm amplitude, 1.4 Hz frequency, and 10 cycles. The chosen frequency aligns with the resonance frequency of the undamped building model’s first mode. Both TLD and TLCD tanks, positioned atop the structure, share a geometry of 30 cm in length and 10 cm in width, with variable liquid heights of 5, 10, 15, and 20 cm. Mounting TLD and TLCD models with four different liquid heights on the undamped model resulted in nine distinct setups. In this designed scenario, the TLDs and TLCDs on the undamped shear frame were compared according to liquid heights at rest. To identify the best-performing system based on liquid height, response displacement–frequency graphs were generated for all models within a frequency range of 0.5–2.5 Hz, and damping ratios were calculated using the half-power bandwidth method. Additionally, harmonic ground motion experiments at the resonance frequency compared both acceleration and displacement values over time for damped and undamped models. Peak acceleration and displacement values on each floor were also analyzed. The results highlight which system proves more effective based on damping ratio, acceleration, and displacement values under equivalent conditions. Full article

This research reviews a novel artificial intelligence (AI)-based application called TLDetect, which filters and classifies anomalous glow curves (GCs) of thermoluminescent dosimeters (TLDs). Until recently, GC review and correction in the lab were performed using an old in-house software, which uses the Microsoft Access database and allows the laboratory technician to manually review and correct almost all GCs without any filtering. The newly developed application TLDetect uses a modern SQL database and filters out only the necessary GCs for technician review. TLDetect first uses an artificial neural network (ANN) model to filter out all regular GCs. Afterwards, it automatically classifies the rest of the GCs into five different anomaly classes. These five classes are defined by the typical patterns of GCs, i.e., high noise at either low or high temperature channels, untypical GC width (either wide or narrow), shifted GCs whether to the low or to the high temperatures, spikes, and a last class that contains all other unclassified anomalies. By this automatic filtering and classification, the algorithm substantially reduces the amount of the technician’s time spent reviewing the GCs and makes the external dosimetry laboratory dose assessment process more repeatable, more accurate, and faster. Moreover, a database of the class anomalies distribution over time of GCs is saved along with all their relevant statistics, which can later assist with preliminary diagnosis of TLD reader hardware issues. Full article