Search Results (9,984)

Urbanization has emerged as one of the most significant global challenges and opportunities of the 21st century, driven by a complex interplay of dynamic processes. In Ethiopia, cities have undergone rapid expansion in recent decades, largely due to state-led economic reforms and infrastructure development. This study aims to investigate the spatiotemporal dynamics, driving forces, and future projections of urban expansion along the Ethio–Djibouti trade corridor, with a focus on Dire Dawa City in eastern Ethiopia. Landsat imagery from 1993, 2003, 2013, and 2023 was utilized to detect land use and land cover (LULC) changes and analyze urban growth patterns. Additionally, maps illustrating the city’s demographic, economic, and topographic characteristics were developed to identify the key driving factors behind land conversion and urban expansion. The spatial matrix and landscape expansion index were employed to examine the spatial patterns of urban growth. Furthermore, the study applied the Multi-Layer Perceptron–Markov Chain (MLP–MC) model to simulate future LULC changes and urban expansion. The results indicate that the built-up area in Dire Dawa has increased significantly over the past three decades, growing from 6.21 km² in 1993 to 21.54 km² in 2023. This urban growth is predominantly characterized by edge expansion, reflecting a pattern of unidirectional, unsustainable development that has consumed large areas of agricultural land. The analysis shows that socioeconomic development and population growth have had a greater influence on LULC conversion and urban expansion than physical factors. Based on these identified drivers, the study projected land conversion and simulated urban expansion for the years 2043 and 2064. The findings underscore the urgent need for context-sensitive urban growth strategies that harmonize local realities with national development policies and the Sustainable Development Goals. Full article

In this study, a new approach was developed for the estimation of optimum parameters (ODP), in terms of materials and design in livestock barns, and for optimal design. For this purpose, two thousand simulations were run using Monte Carlo (MC) techniques and Latin hypercube methods using the Energy Plus program on a 50-head closed dairy farm. In this study, the heat balance in the barn was adapted to Energy Plus using an innovative approach, using heat balance equations according to the ASHRAE Standard. First, data normality was determined using the Shapiro–Wilk (SW) and Kolmogorov–Smirnov (KS) tests. Data on thermal stress duration and energy consumption for dairy cattle welfare were estimated directly from the simulations, and sensitivity (SA) and uncertainty (UA) analyses were conducted. Furthermore, the statistical relationship between thermal comfort and energy consumption was determined using Pearson correlation. The predicted values obtained from the simulations were validated with barn values, and time-series overlay plots and histograms were generated. Furthermore, interpretations of the validation processes were made based on MBE, RSME, and R² statistical values. The study estimated an indoor thermal comfort temperature of 12 °C, and this value was taken into account in the innovatively developed simulations. The estimated optimum design parameters in the study resulted in energy reductions of 25% and 41% for walls and roofs, 48% and 19% for cooling and heating setpoint temperatures, 43% and 37% for window areas, and 75% and 40% for natural and mechanical ventilation, respectively. When the design parameters were evaluated holistically and analyzed in terms of average values, the new simulation model achieved approximately 50% energy savings. We believe that the newly developed approach will guide future planning for countries, the public, and private sectors to ensure animal welfare and reduce energy consumption. Full article

Background/Objectives: McCune–Albright syndrome (MAS) is a rare disease characterized by the triad of fibrous dysplasia (FD), café au lait skin macules, and hyperfunctioning endocrinopathies. Although there are many case reports of MAS, few have discussed long-term oral management. We describe the long-term follow-up of an MAS patient over 15 years. Case Presentation: A male patient aged 13 years and 7 months was referred to our department with a chief complaint of difficulty with toothbrushing. He was diagnosed with MAS at 9 years, and bisphosphonate therapy was started. We continued to review the patient periodically and extracted several primary teeth with no adverse effects such as the medication-related osteonecrosis of the jaw (MRONJ). We evaluated the changes in FD using facial photographs, and facial asymmetry worsened over time until the age of 19, when surgery was performed. Although improvement was observed after surgery, there was a tendency for recurrence up to the age of 25 years. Conclusions: Continuous dental support over 15 years has prevented oral disease and minimized the need for surgical procedures such as tooth extractions, which are factors in MRONJ. The worsening of FD on the left side caused facial asymmetry until the age of 25 years; however, the asymmetry may have stabilized with the development of FD on the right side and with age-related changes. It is important for dental professionals to provide MAS patients with appropriate oral health instruction and oral management, taking changes in FD into consideration. Full article

Geosynchronous satellite maneuver detection is critical for enhancing space situational awareness and inferring satellite intent. However, traditional methods often require high-quality orbital sequence data and heavily rely on hand-crafted features, limiting their effectiveness in complex real-world environments. While recent neural network-based approaches have shown promise, they are typically trained in scene or task-specific settings, resulting in limited generalization and adaptability. To address these challenges, we propose MC-MD, a pre-training framework that integrates Masked and Clustered learning strategies to improve the robustness and transferability of geosynchronous satellite Maneuver Detection. Specifically, we introduce a masked prediction module that applies both time- and frequency-domain masking to help the model capture temporal dynamics more effectively. Meanwhile, a cluster-based module guides the model to learn discriminative representations of different maneuver patterns through unsupervised clustering, mitigating the negative impact of distribution shifts across scenarios. By combining these two strategies, MC-MD captures diverse maneuver behaviors and enhances cross-scenario detection performance. Extensive experiments on both simulated and real-world datasets demonstrate that MCMD achieves significant performance gains over the strongest baseline, with improvements of 8.54% in Precision and 7.8% in F1-Score. Furthermore, reconstructed trajectories analysis shows that MC-MD more accurately aligns with the ground-truth maneuver sequence, highlighting its effectiveness in satellite maneuver detection tasks. Full article

Food packaging is an essential part of the food industry. Packaging materials are indispensable in ensuring product safety, enhancing consumer experience, and supporting sustainable practices. This review provides an update on the role of bio-based polymers, including polylactic acid (PLA), polyhydroxyalkanoates (PHAs), starch-based polymers, and cellulose-based polymers (cellulose acetate (CA), cellulose sulphate (CS), carboxymethyl cellulose (CMC), nanocellulose (NC), and methylcellulose (MC)) for food packaging applications. Properties as mechanical, barrier and antimicrobial, as well as their eco-friendly behavior, are also summarized. The advantages and disadvantages of using bio-based polymers in food packaging are discussed. Present review also addresses the challenges associated with their preparation and highlights the potential future prospects of bio-based polymers for packaging applications. Full article

Gestational diabetes mellitus (GDM) increases the risk of fetal overgrowth and macrosomia, yet the molecular mechanisms remain unclear. Emerging evidence implicates primate-specific placental microRNAs (miRNAs) from the C19MC cluster in modulating fetal growth via the insulin-like growth factor (IGF) axis. This study aimed to investigate the expression of circulating C19MC miRNAs in GDM pregnancies and their association with IGF axis biomarkers and birthweight outcomes. In this cross-sectional study, 158 pregnant women were stratified into normoglycemic pregnancies (n = 52), GDM with normal birthweight (n = 56), and GDM with large-for-gestational-age (LGA) newborns (n = 50). Plasma levels of 19 C19MC miRNAs and IGF-related proteins were measured. Associations between miRNAs, IGF axis components, and birthweight were analyzed using linear regression and correlation models adjusted for relevant covariates. Several miRNAs, including miR-516a-5p, miR-518d-3p, miR-521, and miR-525-3p, were differentially expressed in GDM, particularly in LGA cases. Strong correlations were observed, such as that of miR-516a-5p with IGFBP-5 (r = 0.705; p < 0.001). Inverse associations with birthweight were found for miR-519b-3p, miR-518d-5p, and miR-520a-5p. Circulating C19MC miRNAs are dysregulated in GDM and correlate with IGF signaling and fetal growth, supporting their potential as early biomarkers for macrosomia risk in GDM. Full article

Despite being considering as having infinite fatigue life, failures of motor crankshafts forged from DIN 34CrNiMo6 steels have been reported in Brazilian power plants. As such, the present work aims to discuss the failure of a crankshaft within this context, with the purpose of verifying whether the stresses developed in critical locations of the component were in accordance with the steel’s fatigue limits, as well as if the material exhibits an adequate resistance to crack propagation. Taking into consideration a set of critical-plane stress-based multiaxial fatigue criteria, namely Findley, Matake, McDiarmid and Susmel and Lazzarin, the fatigue behaviour of the material is analysed and discussed. Furthermore, $da/dN$ versus $\mathsf{\Delta }K$ experiments were carried out with the purpose of determining the DIN 34CrNiMo6 steel’s crack growth threshold $\mathsf{\Delta }{K}_{th}$ and comparing it to the $\mathsf{\Delta }{K}_{th}$ of three other commercially available steels (DIN 42CrMo4, SAE 4140 and SAE 4340). The selected multiaxial fatigue criteria indicated that the stresses developed throughout the component were not sufficient to drive the crankshaft to failure, thus indicating safety. On the other hand, the DIN 34CrNiMo6 steel presented the lowest $\mathsf{\Delta }{K}_{th}$ ($6.6\mathrm{M}\mathrm{P}\mathrm{a}{\mathrm{m}}^{1/2}$) among all the considered steels ($10.86$, $12.38$ and $7.22\mathrm{M}\mathrm{P}\mathrm{a}{\mathrm{m}}^{1/2}$ for the DIN 42CrMo4, SAE 4140 and SAE 4340, respectively), therefore being susceptible to shorter fatigue lives in comparison to the other materials. Full article

Due to the rapid advancements in coordinate measuring systems, data processing software, and additive manufacturing (AM) techniques, it has become possible to create copies of existing models through the reverse engineering (RE) process. However, the lack of precise estimates regarding the accuracy of the RE process—particularly at the measurement, reconstruction, and computer-aided design (CAD) modeling stages—poses significant challenges. Additionally, the assessment of dimensional and geometrical errors during the manufacturing stage using AM techniques limits the practical implementation of product replicas in the industry. This paper provides an estimation of the errors encountered in the RE process and the AM stage of various models. It includes examples of an electrical box, a lampshade for a standing lamp, a cover for a vacuum unit, and a battery cover. The geometry of these models was measured using a GOM Scan 1 (Carl Zeiss AG, Jena, Germany). Following the measurement process, data processing was performed, along with CAD modeling, which involved primitive detection, profile extraction, and auto-surface methods using Siemens NX 2406 software (Siemens Digital Industries, Plano, TX, USA). The models were produced using a Fortus 360-mc 3D printer (Stratasys, Eden Prairie, MN, USA) with ABS-M30 material. After fabrication, the models were scanned using a GOM Scan 1 scanner to identify any manufacturing errors. The research findings indicated that overall, 95% of the points representing reconstruction errors are within the maximum deviation range of ±0.6 mm to ±1 mm. The highest errors in CAD modeling were attributed to the auto-surfacing method, overall, 95% of the points are within the average range of ±0.9 mm. In contrast, the lowest errors occurred with the detect primitives method, averaging ±0.6 mm. Overall, 95% of the points representing the surface of a model made using the additive manufacturing technology fall within the deviation range ±0.2 mm on average. The findings provide crucial insights for designers utilizing RE and AM techniques in creating functional model replicas. Full article

Background: Interstitial lung disease (ILD) is a frequent and potentially progressive manifestation in patients with connective tissue diseases (CTDs). Accurate and reproducible quantification of parenchymal abnormalities on high-resolution computed tomography (HRCT) is essential for evaluating treatment response and monitoring disease progression, particularly in complex cases undergoing antifibrotic therapy. Artificial intelligence (AI)-based tools may improve consistency in visual assessment and assist less experienced radiologists in longitudinal follow-up. Methods: In this retrospective study, 48 patients with CTD-related ILD receiving antifibrotic treatment were included. Each patient underwent four HRCT scans, which were evaluated independently by two radiologists (one expert, one non-expert) using a semi-quantitative scoring system. Percentage estimates of lung involvement were assigned for four parenchymal patterns: hyperlucency, ground-glass opacity (GGO), reticulation, and honeycombing. AI-based analysis was performed using the Imbio Lung Texture Analysis platform, which generated continuous volumetric percentages for each pattern. Concordance between AI and human interpretation was assessed, along with mean absolute error (MAE) and inter-reader differences. Results: The AI-based system demonstrated high concordance with the expert radiologist, with an overall agreement of 81% across patterns. The MAE between AI and the expert ranged from 1.8% to 2.6%. In contrast, concordance between AI and the non-expert radiologist was significantly lower (60–70%), with higher MAE values (3.9% to 5.2%). McNemar’s and Wilcoxon tests confirmed that AI aligned more closely with the expert than the non-expert reader (p < 0.01). AI proved particularly effective in detecting subtle changes in parenchymal burden during follow-up, especially when visual interpretation was inconsistent. Conclusions: AI-driven quantitative imaging offers performance comparable to expert radiologists in assessing ILD patterns on HRCT and significantly outperforms less experienced readers. Its reproducibility and sensitivity to change support its role in standardizing follow-up evaluations and enhancing multidisciplinary decision-making in patients with CTD-related ILD, particularly in progressive fibrosing cases receiving antifibrotic therapy. Full article

Angelica sinensis radix (AS), the dried root of Angelica sinensis (Oliv.) Diels, is widely used in Chinese medicine and food products. However, after conducting market research, at least a quarter of AS on the market is commonly adulterated by Levisticum officinale W. D. J. Koch (LO), Angelica acutiloba (Sieb. et Zucc.) Kitagawa (AA), and Angelica gigas Nakai (AG), to varying degrees, which significantly affects its clinical efficacy and food safety. Therefore, there is a pressing need to establish safe and reliable methods for identifying illicit adulteration. In this study, the mass spectrometry (MS) information of AS, LO, AA, and AG was collected and converted into the data matrix for [t_R-m/z-I]. The top-n proprietary ions of AS, AG, AA, and LO were output as their molecular “matrix characteristics”. Test samples were also analyzed, transformed into data matrices, and their own matrix characteristics were matched sequentially. For matching credibility (MC) results, a significant difference was found between the MC of the four herbs compared to their own matrix characteristics, as well as between the MC of the four herbs compared with their non-self matrix characteristics. Research results showed that based on matrix characteristics, AS and its adulterations can be identified with a matching credibility (MC) ≥ 78.0%; 3% adulterations can also be identified, and two market-blind samples were identified as exhibiting adulterations. In addition, chemometrics analysis demonstrated that adulteration identification based on matrix characteristics is reasonable and reliable. The matrix characteristics of AS and its adulterants contribute to adulteration analysis. The identification method, based on matrix characteristics, is safe and reliable which is conducive to AS’s quality control and market supervision. Full article

Background: A number of viruses are oncogenic. These include the human papilloma virus (HPV), Epstein–Barr virus (EBV), Kaposi sarcoma human herpes virus 2/human herpes virus 8 (KSHHV/HHV8), hepatitis B virus, (HBV), hepatitis C virus (HCV), Merkel cell polyoma virus (McPyV), and the human T-cell leukemia virus type 1 (HTLV- 1). These viruses cause malignancies ranging from carcinomas, sarcomas, lymphomas, to leukemias. This review aims to study the effects and efficacy of vaccines against these viruses and the cancers they cause in their prevention and treatment. Methods: The literature in the past 30 years was searched employing Scopus and Google Scholar using the keywords “oncogenic viruses, HPV, EBV, KSHHV, HHV8, Polyoma virus, HTLV-1, COVID-19, carcinoma, sarcoma, lymphoma, leukemia, anti-virus vaccines”. Results: Prophylactic vaccines against the HPV and HBV are highly effective in preventing and reducing the incidence of uterine cervical and hepatocellular carcinomas. Prophylactic vaccines against other oncogenic viruses have been less successful, though efficacious in some experimental animals. Therapeutic vaccines are still mostly under evaluation and development. Conclusions: Identification of oncogenic viruses has rendered anti-viral vaccines conspicuous tools for preventing and treating cancers they cause. Many endeavors for the development of such vaccines have been met with limited success, apart from the very effective anti-HPV and anti-HBV vaccines in universal vaccination programs. With the development of new vaccine technologies, it is hoped that effective vaccines against other oncogenic viruses will be developed in the future. Full article

Identifying knowledge gaps and predictors of performance are proven ways to implement changes to a curriculum. This cross-sectional study investigates the subjective and objective competency of 52 medical students at McGill University in musculoskeletal (MSK) medicine, with a focus on orthopaedic surgery. We surveyed medical students to assess their confidence levels in orthopaedic surgery and their perceptions of its teaching. The students then completed a 25-question orthopaedics-focused exam as an objective assessment of their knowledge. Descriptive statistics were calculated, exam performance was compared across academic years, predictors of exam scores were analyzed, and student self-assessment accuracy was evaluated. Students reported lower confidence in orthopaedic surgery than in many other specialties, exam scores varied significantly across academic years (p = 0.007), and predicted exam performance was the only significant predictor of test score in multiple linear regression (R² = 0.313, p = 0.025). Calibration analysis revealed a substantial miscalibration, where students with higher predicted scores tended to overestimate their performance, while those with lower predictions tended to underestimate themselves (intercept = 27.2, slope = 0.54). A Bland–Altman plot demonstrated wide limits of agreement between predicted and actual scores (mean bias −1.2%, 95% LoA −35.0% to +32.6%). These findings highlight meaningful orthopaedic knowledge gaps and miscalibrated self-assessment, emphasizing the need for targeted, structured educational interventions in the MSK curriculum. Full article

Sand mining activities can significantly impact the microecology of rivers. Scientific studies are needed for the effective protection and restoration of river ecosystems impacted by sand mining activities. In this study, we used high-throughput sequencing technology to analyse the structure and function of sediment bacterial communities in three river habitats of the Jialing River Basin, namely, a natural river channel (no sand mining activities), a channel with continuous large-scale sand mining activities, and a channel in which sand mining had been terminated one year prior, as well as to analyse the main constraints leading to changes in sediment bacterial communities. The results revealed that the dominant bacteria in the different sand mining environments of the Jialing River were Proteobacteria, Chloroflexi, and Acidobacteria, and that total organic carbon (TOC), moisture content (MC) and total nitrogen (TN) were the main limiting factors affecting the structure of the bacterial community. In addition, large-scale sand mining activities caused significant changes (p < 0.05) in major secondary functions, such as energy metabolism, cofactor and vitamin metabolism, and translation. In summary, the persistence of large-scale sand mining activities led to heterogeneous changes in sediment bacterial community structure and function, which had an important impact on the stability of the ecosystem in the Jialing River Basin. Full article

Background/Objectives: Endovascular treatment has become the primary treatment for intracranial aneurysms, yet direct bypass surgery remains an option in selected cases where standard approaches fail. This study aims to evaluate the role, indications, and outcomes of bypass surgery for intracranial aneurysm management in the current endovascular era. Methods: A single-center retrospective analysis was conducted on consecutive cases who underwent direct intracranial bypass surgery for intracranial aneurysms between 2015 and 2024. Data on demographics, aneurysm characteristics, indications, bypass type, patency, and clinical outcomes (using the modified Rankin Scale) were collected. Results: Of the 101 bypasses performed between 2015 and 2025, 25 were used for complex aneurysm cases. Intracranial bypass was necessary in as many as 5% of all microsurgical aneurysm repairs in 2023 and 10% in 2024. Bypass surgery was indicated in young patients with complex aneurysms not amenable to endovascular therapy (45%) and in 20% of the cases for recanalized aneurysms after previous endovascular repair. Intraoperative and postoperative bypass patency was confirmed for all patients except one case due to ongoing malignant brain swelling after an ongoing infarction. At follow-up, 87% of patients, with both ruptured and unruptured aneurysms, had a good outcome (mRS ≤ 2), and all patients had a patent bypass. Permanent morbidity was observed in 5% and procedure-related mortality in 0%. Conclusions: While bypass surgery constitutes a minority of intracranial aneurysm treatment by volume, its role in intracranial aneurysm repair is crucial and relevant in response to the evolving complexity of aneurysms. Further refinement of techniques is necessary. Full article

Aims: Diabetes mellitus (DM) increases cardiovascular risk by inducing atherosclerotic plaque instability. StemBell therapy (i.e., adipose tissue-derived stem cells (ASCs) coupled to ultrasound-activated microbubbles) previously improved plaque stability in non-DM ApoE^−/− mice. Here, we investigated the effect of StemBell therapy on atherosclerotic plaque characteristics in a streptozotocin-induced DM mouse model. Methods: DM was induced in male C57BL/6 ApoE^−/− mice (n = 18) via intraperitoneal streptozotocin (STZ) injection (0.05 mg/g bodyweight) for 5 consecutive days. Eight weeks after the first STZ injection, the mice received either 5 × 10⁵ StemBells or vehicle intravenously. Due to unexpected mortality, the experiment was halted and restarted in week 9 with a final reduced dose of 1.25 × 10⁵ StemBells to avoid complications. The effect of StemBell therapy on plaque characteristics was determined 4 weeks post-treatment in five vehicle-treated and five StemBell-treated mice via (immuno)histochemical analyses. Furthermore, plasma monocyte subsets within 3 days pre- and 3 days post-treatment, and 3 weeks post-treatment, were studied via flow cytometry. Results: StemBell therapy did not significantly affect atherosclerotic plaque size or intra-plaque inflammation. StemBell-treated mice had less intra-plaque Ly6G+ neutrophils (0.4 ± 0.5%) and intra-plaque Mac3+ pan-macrophages (17.7 ± 3.4%), but more CD163+ anti-inflammatory M2 macrophages (p = 0.5) compared to vehicle-treated mice, although this was non-significant. Conclusions: StemBell therapy did not significantly affect atherosclerotic plaque size or intra-plaque inflammation in a streptozotocin-induced DM mouse model. Future research is essential to explore the potential and limitations of StemBell therapy in DM-related atherosclerosis. The higher mortality of StemBell therapy in diabetic mice compared to the previous non-diabetic mice also warrants further investigation. Full article