Search Results (1,466)

Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study presents a comprehensive comparative evaluation of two state-of-the-art deep learning families for the task of classifying diabetic retinopathy using retinal fundus images. Methods: The models were trained and tested in both binary and multi-class settings. The experimental design involved partitioning the data into training (70%), validation (20%), and testing (10%) sets. Model performance was assessed using standard metrics, including precision, sensitivity, specificity, F1-score, and the area under the receiver operating characteristic curve. Results: In binary classification, the ResNeXt101-64x4d model and RegNetY32GT model demonstrated outstanding performance, each achieving high sensitivity and precision. For multi-class classification, ResNeXt101-32x8d exhibited strong performance in early stages, while RegNetY16GT showed better balance across all stages, particularly in advanced diabetic retinopathy cases. To enhance transparency, SHapley Additive exPlanations were employed to visualize the pixel-level contributions for each model’s predictions. Conclusions: The findings suggest that while ResNeXt models are effective in detecting early signs, RegNet models offer more consistent performance in distinguishing between multiple stages of diabetic retinopathy severity. This dual approach combining quantitative evaluation and model interpretability supports the development of more robust and clinically trustworthy decision support systems for diabetic retinopathy screening. Full article

Cardiovascular disease (CVD) and dementia may share common pathogenic factors such as atherosclerosis and hyperlipoproteinemia. Dyslipidemia-induced oxidative stress contributes to dementia comorbidity in CVD. Abelmoschus esculentus (AE, okra) potentiates in alleviating hyperlipidemia and diabetes-related cognitive impairment. This study evaluated the effects of AE in hyperlipidemic ApoE^−/− mice treated with streptozotocin (50 mg/kg) and fed a high-fat diet (17% lard oil, 1.2% cholesterol). AE fractions F1 or F2 (0.65 mg/kg) were administered for 8 weeks. AE significantly reduced serum LDL-C, HDL-C, triglycerides, and glucose, improved cognitive and memory function, and protected hippocampal neurons. AE also lowered oxidative stress markers (8-hydroxy-2′-deoxyguanosine, 8-OHdG) and modulated neuronal nuclei (NeuN) and doublecortin (DCX) expression. In vitro, AE promoted neurite outgrowth and neuronal differentiation in retinoic acid (RA)-differentiated human SH-SY5Y cells under metabolic stress (glucose and palmitate), alongside the upregulation of heme oxygenase-1 (HO-1), Nuclear factor-erythroid 2-related factor 2 (Nrf2), and brain-derived neurotrophic factor (BDNF). These findings suggest AE may counter cognitive decline via oxidative stress regulation and the enhancement of neuronal differentiation. Full article

With the expansion of muskmelon cultivation, manual pollination is increasingly inadequate for sustaining industry development. Therefore, the development of automatic pollination robots holds significant importance in improving pollination efficiency and reducing labor dependency. Accurate flower detection and localization is a key technology for enabling automated pollination robots. In this study, the YOLO-MDL model was developed as an enhancement of YOLOv7 to achieve real-time detection and localization of muskmelon flowers. This approach adds a Coordinate Attention (CA) module to focus on relevant channel information and a Contextual Transformer (CoT) module to leverage contextual relationships among input tokens, enhancing the model’s visual representation. The pollination robot converts the 2D coordinates into 3D coordinates using a depth camera and conducts experiments on real-time detection and localization of muskmelon flowers in a greenhouse. The YOLO-MDL model was deployed in ROS to control a robotic arm for automatic pollination, verifying the accuracy of flower detection and measurement localization errors. The results indicate that the YOLO-MDL model enhances AP and F1 scores by 3.3% and 1.8%, respectively, compared to the original model. It achieves AP and F1 scores of 91.2% and 85.1%, demonstrating a clear advantage in accuracy over other models. In the localization experiments, smaller errors were revealed in all three directions. The RMSE values were 0.36 mm for the X-axis, 1.26 mm for the Y-axis, and 3.87 mm for the Z-axis. The YOLO-MDL model proposed in this study demonstrates strong performance in detecting and localizing muskmelon flowers. Based on this model, the robot can execute more precise automatic pollination and provide technical support for the future deployment of automatic pollination robots in muskmelon cultivation. Full article

Carbon deposits on the crown of engine pistons can markedly reduce combustion efficiency and shorten service life. Conventional cleaning techniques often fail to simultaneously ensure a high carbon removal efficiency and maintain optimal surface integrity. To enable efficient and precise carbon removal, this study proposes the application of hybrid laser cleaning—combining continuous-wave (CW) and pulsed lasers—to piston carbon deposit removal, and employs response surface methodology (RSM) for multi-objective process optimization. Using the N52B30 engine piston as the experimental substrate, this study systematically investigates the combined effects of key process parameters—including CW laser power, pulsed laser power, cleaning speed, and pulse repetition frequency—on surface roughness (Sa) and carbon residue rate (RC). Plackett–Burman design was employed to identify significant factors, the method of the steepest ascent was utilized to approximate the optimal region, and a quadratic regression model was constructed using Box–Behnken response surface methodology. The results reveal that the Y-direction cleaning speed and pulsed laser power exert the most pronounced influence on surface roughness (F-values of 112.58 and 34.85, respectively), whereas CW laser power has the strongest effect on the carbon residue rate (F-value of 57.74). The optimized process parameters are as follows: CW laser power set at 625.8 W, pulsed laser power at 250.08 W, Y-direction cleaning speed of 15.00 mm/s, and pulse repetition frequency of 31.54 kHz. Under these conditions, the surface roughness (Sa) is reduced to 0.947 μm, and the carbon residue rate (RC) is lowered to 3.67%, thereby satisfying the service performance requirements for engine pistons. This study offers technical insights into the precise control of the hybrid laser cleaning process and its practical application in engine maintenance and the remanufacturing of end-of-life components. Full article

Background/Objectives: Epilepsy is a brain condition that affects millions of people worldwide. Although there are many antiepileptic drugs with different mechanisms of action, many patients still fail to control their agonizing symptoms, a situation that highlights the need for more strategies to address this issue. In this in vitro study, we elucidated and characterized the alterations in intracellular Ca²⁺ levels in cell cultures where diazepam and repetitive transcranial magnetic stimulation were implemented, alone or in combination. Methods: Using the differentiated human-derived neuroblastoma cell line SH-SY5Y, we measured the alterations in intracellular Ca²⁺ levels under the impact of either low-frequency repetitive transcranial magnetic stimulation (1 Hz), diazepam (14 μM), or their combination. We used the Ca²⁺-sensitive fluorescent indicator Fluo-4 acetoxymethyl ester for calcium imaging, while neuronal excitation was achieved with 50 mM KCl. Results: The highest median fluorescence intensity increase (%ΔF/F = 24.80) was observed in control cell cultures, followed by rTMS cultures (%ΔF/F = 16.96) and diazepam cultures (%ΔF/F = 11.46). The lowest median fluorescence intensity value (%ΔF/F =−0.44) was observed when diazepam was used concomitantly with repetitive transcranial magnetic stimulation. Post hoc analysis assessed pairwise differences, showing statistically significant differentiation between the control group and all other groups. Additionally, statistically significant results were observed between repetitive transcranial magnetic stimulation or diazepam and their combination, but not between them. Conclusions: The combination of diazepam and repetitive transcranial magnetic stimulation resulted in the most significant reduction in intracellular Ca²⁺ levels, as indicated by the lowest fluorescence values compared with the control group. Individually, each treatment produced a notable but less pronounced effect. We conclude that both diazepam and low-frequency repetitive transcranial magnetic stimulation can control epileptiform activity in vitro, while their combination is the most effective treatment. Full article

Various SARS-CoV-2 remdesivir resistance-associated substitutions (RAS) have been reported, but a comprehensive comparison of their resistance levels is lacking. We identified novel RAS and performed head-to-head comparisons with known RAS in Vero E6 cells. A remdesivir escape polyclonal virus exhibited a 3.6-fold increase in remdesivir EC₅₀ and mutations throughout the genome, including substitutions in nsp12 (E796D) and nsp14 (A255S). However, in reverse-genetics infectious assays, viruses harboring both these substitutions exhibited only a slight decrease in remdesivir susceptibility (1.3-fold increase in EC₅₀). The nsp12-E796D substitution did not impair viral fitness (Vero E6 cells or Syrian hamsters) and was reported in a remdesivir-treated COVID-19 patient. In replication assays, a subgenomic replicon containing nsp12-E796D+nsp14-A255S led to a 16.1-fold increase in replication under remdesivir treatment. A comparison with known RAS showed that S759A, located in the active site of nsp12, conferred the highest remdesivir resistance (106.1-fold increase in replication). Nsp12-RAS V166A/L, V792I, E796D or C799F, all adjacent to the active site, caused intermediate resistance (2.0- to 11.5-fold), whereas N198S, D484Y, or E802D, located farther from the active site, showed no resistance (≤2.0-fold). In conclusion, our classification system, correlating replication under remdesivir treatment with RAS location in nsp12, shows that most nsp12-RAS cause moderate resistance. Full article

In this study, four types of fall detection systems for seniors living alone using x-y scatter and Doppler range images measured from frequency-modulated continuous wave (FMCW) millimeter-wave (mmWave) sensors were introduced. Despite advancements in fall detection, existing long short-term memory (LSTM)-based approaches often struggle with effectively distinguishing falls from similar activities of daily living (ADLs) due to their uniform treatment of all time steps, potentially overlooking critical motion cues. To address this limitation, an attention mechanism has been integrated. Data was collected from seven participants, resulting in a dataset of 669 samples, including 285 falls and 384 ADLs with walking, lying, inactivity, and sitting. Four LSTM-based architectures for fall detection were proposed and evaluated: Raw-LSTM, Raw-LSTM-Attention, HOG-LSTM, and HOG-LSTM-Attention. The histogram of oriented gradient (HOG) method was used for feature extraction, while LSTM networks captured temporal dependencies. The attention mechanism further enhanced model performance by focusing on relevant input features. The Raw-LSTM model processed raw mmWave radar images through LSTM layers and dense layers for classification. The Raw-LSTM-Attention model extended Raw-LSTM with an added self-attention mechanism within the traditional attention framework. The HOG-LSTM model included an additional preprocessing step upon the RAW-LSTM model where HOG features were extracted and classified using an SVM. The HOG-LSTM-Attention model built upon the HOG-LSTM model by incorporating a self-attention mechanism to enhance the model’s ability to accurately classify activities. Evaluation metrics such as Sensitivity, Precision, Accuracy, and F1-Score were used to compare four architectural models. The results showed that the HOG-LSTM-Attention model achieved the highest performance, with an Accuracy of 95.3% and an F1-Score of 95.5%. Optimal self-attention configuration was found at a 2:64 ratio of number of attention heads to channels for keys and queries. Full article

The rapid densification of wireless networks demands efficient evaluation of special functions underpinning system-level performance metrics. To facilitate research, we introduce a computational framework tailored for the zero-balanced Gauss hypergeometric function $\Psi (x,y)\triangleq {}_{2}F_1(1,x;1+x;-y)$, a fundamental mathematical kernel emerging in Signal-to-Interference-plus-Noise Ratio (SINR) coverage analysis of non-uniform cellular deployments. Specifically, we propose a novel Reciprocal-Argument Transformation Algorithm (RTA), derived rigorously from a Mellin–Barnes reciprocal-argument identity, achieving geometric convergence with $O\left(1/y\right)$. By integrating RTA with a Pfaff-series solver into a hybrid algorithm guided by a golden-ratio switching criterion, our approach ensures optimal efficiency and numerical stability. Comprehensive validation demonstrates that the hybrid algorithm reliably attains machine-precision accuracy ($\sim {10}^{-16}$) within 1 μs per evaluation, dramatically accelerating calculations in realistic scenarios from hours to fractions of a second. Consequently, our method significantly enhances the feasibility of tractable optimization in ultra-dense non-uniform cellular networks, bridging the computational gap in large-scale wireless performance modeling. Full article

Barcodes are ubiquitous in manufacturing and logistics, but defects can reduce decoding efficiency and disrupt the supply chain. Existing studies primarily focus on a single barcode type or rely on small-scale datasets, limiting generalizability. We propose Y8-LiBAR Net, a lightweight two-stage framework for multi-type barcode defect detection. In stage 1, a YOLOv8n backbone localizes 1D and 2D barcodes in real time. In stage 2, a dual-branch network integrating ResNet50 and ViT-B/16 via hierarchical attention performs three-class classification on cropped regions of interest (ROIs): intact, defective, and non-barcode. Experiments conducted on the public BarBeR dataset, covering planar/non-planar surfaces, varying illumination, and sensor noise, show that Y8-LiBARNet achieves a detection-stage mAP@0.5 = 0.984 (1D: 0.992; 2D: 0.977) with a peak F1 score of 0.970. Subsequent defect classification attains 0.925 accuracy, 0.925 recall, and a 0.919 F1 score. Compared with single-branch baselines, our framework improves overall accuracy by 1.8–3.4% and enhances defective barcode recall by 8.9%. A Cohen’s kappa of 0.920 indicates strong label consistency and model robustness. These results demonstrate that Y8-LiBARNet delivers high-precision real-time performance, providing a practical solution for industrial barcode quality inspection. Full article

Qingke (Hordeum vulgare L. var. nudum Hook. f.), a staple crop in the Tibetan Plateau, suffers from severe yield reduction under continuous cropping (by 38.67%), yet the underlying mechanisms remain unclear. This study systematically investigated the effects of 23-year continuous cropping (23y-CC) on the nutrient dynamics, carbohydrate metabolism, and enzymatic activities in Qingke leaves across five developmental stages (T1: seedling; T2: tillering; T3: jointing; T4: flowering; T5: filling). Compared to the control (first-year planting), 23y-CC significantly reduced leaf nitrogen (N), phosphorus (P), and potassium (K) contents by 60.94%, 47.96%, and 60.82%, respectively, at early growth stages. Key nitrogen-metabolizing enzymes, including glutamate synthase (GOGAT), glutamine synthase (GS), and nitrate reductase (NR), exhibited reduced activities under 23y-CC, indicating impaired nitrogen assimilation. Carbohydrate profiling revealed lower starch and glucose contents but higher sucrose accumulation in later stages (T4–T5) under 23y-CC, accompanied by the dysregulation of sucrose synthase (SS) and invertase activities. These findings elucidate how continuous cropping disrupts nutrient homeostasis and carbon allocation, ultimately compromising Qingke productivity. This study provides novel insights into agronomic strategies for mitigating continuous cropping obstacles in Qingke. Full article

Herpes simplex virus 2 (HSV-2) remains a significant cause of morbidity and mortality in immunocompromised individuals, despite the availability of effective antivirals. Infections caused by drug-resistant isolates are an emerging concern among these patients. Understanding evolutionary aspects of HSV-2 resistance is crucial for designing improved therapeutic strategies. Here, we characterized 11 HSV-2 isolates recovered from various body sites of a single immunocompromised patient suffering from a primary HSV-2 infection unresponsive to acyclovir and foscarnet. The isolates were analyzed phenotypically and genotypically (Sanger sequencing of viral thymidine kinase and DNA polymerase genes). Viral clone isolations, deep sequencing, viral growth kinetics, and dual infection competition assays were performed retrospectively to assess viral heterogeneity and fitness. Sanger sequencing identified mixed populations of DNA polymerase mutant variants. Viral clones were plaque-purified and genotyped, revealing 17 DNA polymerase mutations (K533E, A606V, C625R, R628C, A724V, S725G, S729N, I731F, Q732R, M789T/K, Y823C, V842M, R847C, F923L, T934A, and R964H) associated with acyclovir and foscarnet resistance. Deep-sequencing of the DNA polymerase detected drug-resistant variants ranging between 1 and 95%, although the first two isolates had a wild-type DNA polymerase. Some mutants showed reduced fitness, evidenced by (i) the frequency of variants identified by deep-sequencing not correlating with the proportion of mutants found by plaque-purification, (ii) loss of the variants upon passaging in cell culture, or (iii) reduced frequencies in competition assays. This study reveals the rapid evolution of heterogeneous drug-resistant HSV-2 populations under antiviral therapy, highlighting the need for alternative treatment options and resistance surveillance, especially in severe infections. Full article

Foeniculum vulgare Mill. (Apiaceae) is an aromatic medicinal plant known for its anti-inflammatory, antispasmodic, antiseptic, carminative, diuretic, and analgesic properties. This study aimed to investigate the effects of F. vulgare essential oil (FVEO; 25, 150, and 300 μL/L) on the cognitive performance and brain oxidative stress in a scopolamine (SCOP; 100 μM)-induced zebrafish model of cognitive impairment. Additionally, the pharmacokinetic properties and bioactivity profiles of the main FVEO constituents were predicted to be used in silico tools, including SwissADME, pkCSM, PASS online, and ADMETlab 2.0. Behavioral assays, novel tank diving test (NTT), Y-maze, and novel object recognition (NOR) test, were used to evaluate anxiety-like behavior, spatial memory, and recognition memory, respectively. Biochemical assessments of acetylcholinesterase (AChE) activity and oxidative stress biomarkers were also conducted. The results demonstrated that FVEO significantly improved cognitive performance in SCOP-treated zebrafish, normalized AChE activity, and reduced oxidative stress in the brain. These findings suggest the therapeutic potential of FVEO in ameliorating memory impairment and oxidative damage associated with neurodegenerative disorders such as Alzheimer’s disease (AD). Full article

This study examined the effect of build orientation on the surface finish of micro-optofludic (MoF) devices fabricated via a polydimethylsiloxane (PDMS)-based 3D-printing primary–secondary fabrication protocol, where an inkjet 3D-printing technique was implemented. The molds (i.e., primaries) for fabricating the MoF devices were 3D-printed in two orientations: along $XY$ (Dev-1) and across $YX$ (Dev-2) the printhead direction. Next, the surface finish was characterized using a profilometer to acquire the primary profile of the surface along the microchannel’s edge. The results indicated that the build orientation had a strong influence on the latter, since Dev-1 displayed a tall and narrow Gaussian distribution for a channel width of 398.43 ± 0.29 µm; Dev-2 presented a slightly lower value of 393.74 ± 1.67 µm, characterized by a flat and broader distribution, highlighting greater variability due to more disruptive, orthogonally oriented, and striated patterns. These results were also confirmed by hydrodynamically testing the two MoF devices with an air–water slug flow process. A large experimental study was conducted by analyzing the mean period trend in the slug flow with respect to the imposed flow rate and build orientation. Dev-1 showed greater sensitivity to flow rate changes, attributed to its smoother, more consistent microchannel geometry. The slightly narrower average channel width in Dev-2 contributed to increased flow velocity at the expense of having worse discrimination capability at different flow rates. This study is relevant for optimizing 3D-printing strategies for the fabrication of high-performance microfluidic devices, where precise flow control is essential for applications in biomedical engineering, chemical processing, and lab-on-a-chip systems. These findings highlight the effect of microchannel morphology in tuning a system’s sensitivity to flow rate modulation. Full article

Y₅F₃[AsO₃]₄ crystallizes needle-shaped in the tetragonal space group P4/ncc with the lattice parameters a = 1143.80(8) pm, c = 1078.41(7) pm and c/a = 0.9428 for Z = 4. The yttrium-fluoride substructure linked via secondary contacts forms a three-dimensional network $\begin{array}{c}3\\ \infty \end{array}${[Y₅F₃]¹²⁺} and the remaining part consists of ψ¹-tetrahedral [AsO₃]³⁻ units, which leave lone-pair channels along [001]. In contrast, platelet-shaped Y₅Cl₃[AsO₃]₄ crystals adopt the monoclinic space group C2/c with the lattice parameters a = 1860.56(9) pm, b = 536.27(3) pm, c = 1639.04(8) pm and β = 105.739(3)° for Z = 4. Condensation of [(Y1,2)O₈]¹³⁻ polyhedra via four common edges each leads to fluorite-like $\begin{array}{c}2\\ \infty \end{array}$ {[(Y1,2)O $\begin{array}{c}e\\ 8/2\end{array}$ ]⁵⁻} layers spreading out parallel to the (100) plane. Their three-dimensional linkage occurs via the (Y3)³⁺ cations with their Cl⁻ ligands on the one hand and the As³⁺ cations with their lone-pairs of electrons on the other, which also form within [AsO₃]³⁻ anions lone-pair channels along [010]. Both colorless compounds can be obtained by solid-state reactions from corresponding mixtures of the binaries (Y₂O₃, As₂O₃ and YX₃ with X = F and Cl) at elevated temperatures of 825 °C, most advantageously under halide-flux assistance (CsBr for Y₅F₃[AsO₃]₄ and ZnCl₂ for Y₅Cl₃[AsO₃]₄). By replacing a few percent of YX₃ with EuX₃ or TbX₃, Eu³⁺- or Tb³⁺-doped samples are accessible, which show red or green luminescence upon excitation with ultraviolet radiation. Full article

Background and Objectives: Conventional methods for removing cemented fixed prosthetic restorations (FPRs) are unreliable and lead to unsatisfactory outcomes. At their best, they allow the tooth to be saved at the expense of a laborious process that also wears down rotating tools and handpieces and occasionally results in abutment fractures. Restorations are nearly never reusable in any of these situations. Erbium-doped yttrium-aluminum-garnet (Er:YAG) and erbium-chromium yttrium-scandium-gallium-garnet (Er,Cr:YSGG) lasers casafely and effectively remove FPRs, according to scientific studiesre. This study sets out to examine the impact of Er:YAG laser radiation on the debonding of different ceramic restorations, comparing the behavior of various ceramic prosthetic restoration types under laser radiation action and evaluating the integrity of prosthetic restorations and dental surfaces exposed to laser radiation. Materials and Methods: The study included a total of 16 removed teeth, each prepared on opposite surfaces as abutments.y. Based on the previously defined groups, four types of ceramic restorations were included in the study: feldspathic (F), lithium disilicates (LD), layered zirconia (LZ), and monolithic zirconia (MZ). The thickness of the prosthetic restorations was measured at three points, and two different materials were used for cementation. The Er:YAG Fotona StarWalker MaQX laser was used to debond the ceramic FPR at a distance of 10 mm using an R14 sapphire tip with 275 mJ, 20 Hz, 5.5 W, with air cooling (setting 1 of 9) and water. After debonding, the debonded surface was visualized under electron microscopy. Results: A total of 23 ceramic FPRs were debonded, of which 12 were intact and the others fractured into two or three pieces. The electron microscopy images showed that debonding took place without causing any harm to the tooth structure. The various restoration types had the following success rates: 100% for the LZ and F groups, 87% for the LD group, and 0% for the MZ group. In terms of cement type, debonding ceramic FPRs cemented with RELYX was successful 75% of the time, compared to Variolink DC’s 69% success rate. Conclusions: In summary, the majority of ceramic prosthetic restorations can be successfully and conservatively debonded with Er:YAG radiation. Full article