Search Results (33)

Background/Objectives: Ventricular enlargement is a common finding on non-contrast computed tomography (CT) in acute neurological presentations, occurring in hydrocephalus, stroke, and traumatic brain injury. This study evaluated whether routinely available CT-based ventricular morphometric parameters can distinguish hydrocephalus from stroke and traumatic brain injury using initial imaging examinations. Methods: This retrospective observational study included 186 adults (68 with hydrocephalus, 64 with stroke, and 54 with TBI) who underwent index non-contrast cranial CT. Quantitative ventricular parameters included Evans index and third ventricle width, alongside temporal horn dilation and periventricular edema. Multivariable logistic regression models were developed to assess diagnostic performance. A primary morphometric model and a distortion-controlled model incorporating midline shift, mass lesions, and hemorrhage burden were analyzed. Discrimination was evaluated using receiver operating characteristic (ROC) curves. Results: Patients with hydrocephalus showed significantly greater ventricular enlargement, with higher Evans index and third ventricle width compared with stroke and traumatic brain injury groups. The primary model demonstrated moderate discrimination (AUC 0.71). After adjustment for intracranial distortion variables, model performance improved substantially (AUC 0.91), with balanced sensitivity and specificity at optimized thresholds. Evans index and third ventricle width were the strongest independent predictors. Conclusions: CT-derived ventricular morphometrics provide a practical and reproducible approach for differentiating hydrocephalus from stroke and traumatic brain injury on first-presentation CT, supporting objective interpretation in routine neuroimaging practice. Full article

The Nd:GYSAG crystal enables multi-wavelength near-infrared laser output, with adjustable wavelengths tailored for specific application requirements, making it highly valuable for space-borne water vapor detection. This study reports, for the first time, the side-pumping characteristics and electro-optical Q-switching performance of this crystal. Using Ø3 × 73 mm and Ø4 × 73 mm crystal rods doped with 1.21 at.% Nd:GYSAG (chemical formula Nd_0.033Gd_0.93Y_1.79Sc_0.70Al_4.54O_11.99), 1060.4 nm laser output was achieved under 808 nm laser diode (LD) side-pumping at a repetition rate of 100 Hz and a pump pulse width of 250 μs. The experimental results show that the Ø4 × 73 mm rod had a higher laser threshold but exhibited significantly superior slope efficiency and maximum output power compared to the Ø3 × 73 mm rod. Using a flat–flat resonator, optimal laser performance was obtained with an output coupler transmission of 35%, yielding a slope efficiency of 37.2%. A maximum output energy of 179.4 mJ was achieved at a pump energy of 646 mJ. Thermal lensing effects were compensated using a flat–convex cavity, leading to improved laser performance and beam quality. Electro-optical Q-switching experiments were conducted using a KD*P crystal. A comparison between voltage-applied and voltage-removed Q-switching techniques revealed superior performance for the voltage-applied method. High-performance laser output was realized, achieving a maximum pulse energy of 59.6 mJ, a pulse width of 14.93 ns, and a peak power of 3.99 MW. This study provides an important foundation for the development of near-infrared laser devices based on Nd:GYSAG. Full article

Soil salinity in wheat represents a severe threat to global productivity, requiring a deep understanding of physiological adaptation mechanisms to ensure food security in the context of continuous agricultural land degradation. The study aim was to assess the impact of a salinity gradient (0–75 mM NaCl) on the dynamics of stomatal opening and chlorophyll content of the varieties Glosa, Taisa, Boema and Granny. The methodology integrated four joint classes, of which two were from detailed physiological parameters, stomatal features and chlorophyll content, and two morphological characteristics, growth visual indices and biomass allocation. All data was corroborated into an original hierarchical synthesis model presented in a multi-layered sunburst plot. The most relevant results indicate that the concentration of 45 mM NaCl represents the osmotic adjustment threshold, where the active accumulation of ions decreases the internal osmotic potential, facilitating an influx of water that maximizes guard cell turgor and, implicitly, stomatal width. Maximal physiological parameters and biomass ranked the variety Granny first, followed by Taisa. Despite stomatal increases, Boema ranked third and Glosa showed overall decreased development and the lowest plant biomass. These findings validate the use of interconnected effects analysis as a screening tool for identifying the salinity responses of wheat varieties. Full article

Lateral passing distance (LPD) when motor vehicles overtake cyclists is a key safety metric, yet infrastructure-aware evidence remains limited. This study analyses 11,399 overtaking measurements from Austria’s OpenBikeSensor (OBS) project, spatially linked to the national road graph (GIP), with urban and rural networks examined separately. LPD was treated as a continuous dependent variable, and bivariate relationships were tested using nonparametric methods: Spearman’s rho/Kendall’s tau for metric predictors (speed limit, lane width, number of lanes) and Kruskal–Wallis tests with Dunn–Holm post hoc adjustments for categorical factors (Functional Road Class, Road Configuration, Infrastructure Type). Effect sizes and confidence intervals supported substantive interpretation. LPD was higher in rural than urban contexts, with compliance to Austria’s 2023 legal thresholds averaging 40% in cities (≥1.5 m) and 19% in rural areas (≥2.0 m). Positive correlations were found between LPD and lane width, speed limit, and functional class. The findings highlight infrastructure-sensitive patterns in sensor-generated LPD and emphasise the importance of clear cyclist allocation or physical separation, especially where high speeds or spatial constraints increase close-passing risk. Full article

To address the challenges of small target detection in UAV aerial images—such as difficulty in feature extraction, complex background interference, high miss rates, and stringent real-time requirements—this paper proposes an innovative model series named SRTSOD-YOLO, based on YOLO11. The backbone network incorporates a Multi-scale Feature Complementary Aggregation Module (MFCAM), designed to mitigate the loss of small target information as network depth increases. By integrating channel and spatial attention mechanisms with multi-scale convolutional feature extraction, MFCAM effectively locates small objects in the image. Furthermore, we introduce a novel neck architecture termed Gated Activation Convolutional Fusion Pyramid Network (GAC-FPN). This module enhances multi-scale feature fusion by emphasizing salient features while suppressing irrelevant background information. GAC-FPN employs three key strategies: adding a detection head with a small receptive field while removing the original largest one, leveraging large-scale features more effectively, and incorporating gated activation convolutional modules. To tackle the issue of positive-negative sample imbalance, we replace the conventional binary cross-entropy loss with an adaptive threshold focal loss in the detection head, accelerating network convergence. Additionally, to accommodate diverse application scenarios, we develop multiple versions of SRTSOD-YOLO by adjusting the width and depth of the network modules: a nano version (SRTSOD-YOLO-n), small (SRTSOD-YOLO-s), medium (SRTSOD-YOLO-m), and large (SRTSOD-YOLO-l). Experimental results on the VisDrone2019 and UAVDT datasets demonstrate that SRTSOD-YOLO-n improves the mAP@0.5 by 3.1% and 1.2% compared to YOLO11n, while SRTSOD-YOLO-l achieves gains of 7.9% and 3.3% over YOLO11l, respectively. Compared to other state-of-the-art methods, SRTSOD-YOLO-l attains the highest detection accuracy while maintaining real-time performance, underscoring the superiority of the proposed approach. Full article

Background: The hemoglobin-to-red-cell distribution width ratio has emerged as a novel prognostic marker in various clinical settings. However, its association with total bone mineral density in adolescents remains inadequately explored. Methods: This cross-sectional study was based on data from the 2011–2018 National Health and Nutrition Examination Survey, including adolescents aged 12–19 years with complete data on hemoglobin, red cell distribution width, and total bone mineral density. Weighted multivariable linear regression models and generalized additive models were used to evaluate the association between hemoglobin-to-red-cell distribution width and total bone mineral density. A two-piecewise linear regression model was applied to assess potential threshold effects, with log-likelihood ratio tests used to determine the significance of inflection points. Subgroup and interaction analyses were further conducted to examine whether age, sex, race, and milk product consumption modified this association. Results: A total of 3789 adolescents were included. Participants in the highest hemoglobin-to-red-blood-cell distribution width ratio quartile had significantly higher hemoglobin levels, lower red blood cell distribution width, greater total bone mineral density, higher total calcium and blood urea nitrogen levels, and lower body mass index, high-density lipoprotein cholesterol, and serum 25OHD levels compared to lower quartiles. The hemoglobin-to-red-blood-cell distribution width ratio was positively associated with total bone mineral density (fully adjusted β = 0.078, 95% CI: 0.053, 0.104, p < 0.0001). A two-piecewise linear regression model identified an inflection point at the hemoglobin-to-red-cell distribution width ratio = 1.055; the positive association became stronger above this threshold (β = 0.143 vs. β = 0.039 below the threshold, p = 0.003 for nonlinearity). Subgroup analysis revealed significant gender interactions (p < 0.0001). A higher HRR was significantly associated with greater total BMD in males (β = 0.130, 95% CI: 0.089–0.171, p < 0.0001), whereas no significant association was observed in females (β = −0.009, 95% CI: −0.043–0.025, p = 0.604). Positive associations were also observed among participants aged 12–15 years, non-Hispanic Whites, non-Hispanic Blacks, other Hispanics, Mexican Americans, and frequent milk consumers. Conclusions: Our results indicate that the hemoglobin-to-red-cell distribution width ratio shows a potential association with bone mineral density in male adolescents, which may offer supportive value for bone health assessment but requires further validation. Full article

Each layer of the constructed asphalt pavement is evaluated by measuring its quality indicators, as specified in the construction regulations ĮT ASFALTAS 08, and comparing the obtained values with the corresponding design or threshold values. Due to inherent variability in material properties and systematic or random errors during the production, transport, and installation of the asphalt mixture, the quality indicators of the asphalt layers often deviate from their optimal values. When deviations exceed permissible deviations (PD) or limit values (LV), monetary deductions (MDs) are applied. This study presents normalised values and variation dynamics for 10 quality indicators of the asphalt layer subject to MDs in Lithuania. Using the expertise of 71 road construction professionals and multi-criteria decision-making (MCDM) methods, the influence of these deviations on road quality was assessed. The experts ranked all indicators using percentage weights and the Analytic Hierarchy Process (AHP) method. Expert consensus was verified using concordance coefficients and consistency ratios. After eight statistical outliers were excluded, adjusted weights were calculated based on responses from 63 experts. The proposed method, termed CIBRO (Criteria Importance But Rejected Outliers), enables the objective prioritisation of asphalt quality indicators. The CIBRO method enhances expert concordance and results reliability by aligning criterion ranks with the normal distribution, complementing the Kendall rank correlation approach. The findings highlight that insufficient compaction, inadequate layer thickness, and binder content deviations are the most influential factors that affect layer quality. In contrast, deviations in pavement width, friction coefficient, and surface evenness (measured with a 3 m straight edge) were found to have a lesser impact. The CIBRO method offers a robust approach to assessing the importance of the quality of the asphalt layer, supporting improvements in construction standards and pavement assessment systems. Full article

This study, in response to the optimization needs of fall risks for the elderly in the context of cultural and tourism integration in Hebei Province, China, established a quantitative correlation system between ten gait parameters and ten types of spatial risk factors. By collecting gait data (Qualisys infrared motion capture system, sampling rate 200 Hz) and spatial parameters from 30 elderly subjects (with mild, moderate, and severe functional impairments), a multi-level regression model was established. This study revealed that step frequency, step width, and step length were nonlinearly associated with corridor length, door opening width, and step depth (R² = 0.53–0.68). Step speed, ankle dorsiflexion, and foot pressure were key predictive factors (OR = 0.04–8.58, p < 0.001), driving the optimization of core spatial factors such as threshold height, handrail density, and friction coefficient. Step length, cycle, knee angle, and lumbar moment, respectively, affected bed height (45–60 cm), switch height (1.2–1.4 m), stair riser height (≤35 mm), and sink height adjustment range (0.7–0.9 m). The prediction accuracy of the ten optimized values reached 86.7% (95% CI: 82.1–90.3%), with Hosmer–Lemeshow goodness-of-fit x² = 7.32 (p = 0.412) and ROC curve AUC = 0.912. Empirical evidence shows that the graded optimization scheme reduced the fall risk by 42–85%, and the estimated fall incidence rate decreased by 67% after the renovation. The study of the “abnormal gait—spatial threshold—graded optimization” quantitative residential layout optimization provides a systematic solution for the data-quantified model of elderly-friendly residential renovations. Full article

In this work, we report the formation of multiple mode-locking states in an Erbium/Ytterbium co-doped fiber laser, such as domain-wall (DW) dark pulses, high-order dark harmonic pulses, dissipative soliton resonance (DSR) pulses, and dual-wavelength h-shaped pulses. By increasing the pump power and adjusting the quarter-wave retarder (QWR) plates, we experimentally achieve 310th-order harmonic dark pulses. DSR pulses emerge at a pump power of 1.01 W and remain stable up to 9.07 W, reaching a maximum pulse width of 676 ns and a pulse energy of 1.608 µJ, while Dual-wavelength h-shaped pulses have a threshold of 1.42 W and maintain stability up to 9.07 W. Using a monochromator, we confirm that these h-shaped pulses result from the superposition of a soliton-like pulse and a DSR-like pulse, emitting at different wavelengths but locked in time. The fundamental repetition rate for dark pulsing, DSR, and h-shaped pulses is 321.34 kHz. This study provides new insights into complex pulse dynamics in fiber lasers and demonstrates the versatile emission regimes achievable through precise pump and polarization control. Full article

In pipeline all-position welding processes, laser scanning provides critical geometric data of width-changing bevel morphology for welding torch swing control, yet conventional second-order derivative zero methods often yield pseudo-inflection points in practical applications. To address this, a third-order derivative weighted average threshold algorithm was developed, integrating image denoising, enhancement, and segmentation pre-processing with cubic spline fitting for precise bevel contour reconstruction. Bevel pixel points were captured by the laser sensor as inputs through the extracted second-order derivative eigenvalues to derive third-order derivative features, applying weighted threshold discrimination to accurately identify inflection points. Dual-angle sensors were implemented to synchronize laser-detected bevel geometry with real-time torch swing adjustments. Experimental results demonstrate that the system achieves a steady-state error of only 1.645% at the maximum swing width, a dynamic response time below 50 ms, and torch center trajectory tracking errors strictly constrained within ±0.1 mm. Compared to conventional methods, the proposed algorithm improves dynamic performance by 20.6% and exhibits unique adaptability to narrow-gap V-grooves. The results of these studies confirmed the ability of the method to provide real-time, accurate control for variable-width weld tracking, forming a swing-width adaptive control system. Full article

The special band structure of bilayer MoS₂ makes it show strong nonlinear optical characteristics in the visible band, which provides a new way to develop visible nonlinear devices. In this paper, we present a theoretical analysis of the optical bistability (OB) in a silver–Bragg reflector structure by embedding bilayer MoS₂ at the visible band. The nonlinear OB phenomenon is achieved due to the nonlinear conductivity of the bilayer MoS₂ and the excitation of the optical Tamm state at the interface between the silver and the Bragg reflector. It is found that the hysteresis behavior and the threshold width of the OB can be effectively tuned by varying the incident light wavelength. In addition, the optical bistable behavior of the structure can be adjusted by varying the position of the MoS₂ inset in the defect layer, the incident angle, and the structural parameters of the spacer layer. We believe the above results can provide a new paradigm for the construction of controllable bistable devices. Full article

This study conducted a classification analysis of hydrometeor types during a typical stratiform mixed cloud precipitation event in the rainy season using data from the Liupan Mountains micro rain radar power spectra. The primary research findings are as follows: (1) Utilizing the RaProM method synthesizes the information of particle falling velocity, equivalent radar reflection coefficient, particle scale characteristics at different stages, and the location of the bright zone in the zero-degree layer to classify hydrometeors during this precipitation process, and the results show that drizzle and raindrop distribution time periods do not match with the raindrop spectra and rain intensities observed by the DSG5 ground-based precipitation gauge. (2) Sensitivity experiments conducted on the RaProM method revealed that after modifying the discrimination thresholds for drizzle and raindrops, the distributions of drizzle and raindrops were more aligned with ground-based raindrop spectrum observations. Furthermore, these adjustments also showed better consistency with the radar reflectivity factor, Doppler velocity, and velocity spectrum width thresholds used by existing millimeter-wave cloud radars to discriminate between drizzle and raindrops. (3) Various kinds of hydrometeors show different vertical distribution characteristics in three precipitation stages: weak, strong, and weak. In the two weak precipitation stages, hydrometeors mainly existed in the form of snowflakes at altitudes above the zero-degree layer and in the form of drizzle at altitudes below the zero-degree layer. The vertical distribution disparity of hydrometeors between the mountain peak and base sites demonstrates that terrain significantly influences hydrometeors during the precipitation process. Full article

In extremely cold environments, when battery electric vehicles (BEVs) are navigating urban roads at low speeds, the limited heating capacity of the on-board heat pump system and positive temperature coefficient (PTC) device can lead to an inevitable decline in battery temperature, potentially falling below its permissible operating range. This situation can subsequently result in vehicle malfunctions and, in severe cases, traffic accidents. Henceforth, a novel battery self-heating method during driving is proposed to maintain battery temperature. This approach is ingeniously embedded within the heating mechanism within the motor driving system without any necessity to alter or modify the existing driving circuitry. In the meantime, the battery voltage can be regulated to prevent it from surpassing the limit, thereby ensuring the battery’s safety. This method introduces the dead zone into the space vector pulse width modulation (SVPWM) algorithm to form the newly proposed dSVPWM algorithm, which successfully changes the direction of the bus current in a PWM period and forms AC, and the amplitude of the battery alternating current (AC) can also be controlled by adjusting the heating intensity defined by the ratio of the dead zone and the compensation vector to the original zero vector. Through the Simulink model of the motor driving system, the temperature hysteresis locking strategy, grounded in the field-oriented control (FOC) method and employing the dSVPWM algorithm, has been confirmed to provide controllable and sufficiently stable motor speed regulation. During the low-speed phase of the China Light Vehicle Test Cycle (CLTC), the battery temperature fluctuation is meticulously maintained within a range of ±0.2 °C. The battery’s minimum temperature has been successfully locked at around −10 °C. In contrast, the battery temperature would decrease by a significant 1.44 °C per minute without the implementation of the temperature-locking strategy. The voltage of the battery pack is always regulated within the range of 255~378 V. It remains within the specified upper and lower thresholds. The battery voltage overrun can be effectively avoided. Full article

This paper proposes a current balancing loop that is obtained using the threshold median adjustment (TMA-CBL) to achieve the accurate current balancing of an interleaved constant frequency hysteresis (CFH) buck converter. The CFH control is implemented with a frequency phase loop based on a threshold width adjustment (TWA-FPL). To ensure the loop’s stability and minimize the steady-state error, a multi-phase, coupled, small-signal model (MPC-SSM) is derived with a consideration of the coupling effect among the multiple phases. Furthermore, the current balancing error is analyzed in detail, with a consideration of the sensing resistance deviations in the loop. Finally, based on a 180 nm BCD process, a four-phase interleaved buck converter is fabricated to verify the effectiveness of the proposed TMA-CBL. The maximum current balancing error is within 0.68% when the sensing resistors are deviated by 5%. Full article

Estimation of power consumption in digital circuits is performed at gate-level simulation. Its accuracy depends on the models of gate delays that capture the effects of spurious signal transitions, called “glitches”. Electronic Design Automation (EDA) software considers inertial gate delays and represses a glitch in the cell’s output if its width is below a threshold. Selecting threshold values for the inertial glitch classification and filtering is crucial for precise power estimations. In this direction, we explore the effectiveness of automatically adjusting such thresholds on a cell-specific basis according to the local cell’s information. We used a commercial industry-standard gate-level power estimation tool and a 32 nm CMOS standard cell library. Via power measurements in circuit simulations, we created customized lookup tables for each library cell employed in the benchmark circuits. We compared the proposed approach’s performance with other methods for glitch threshold definition. Our method demonstrated good power estimation accuracy while presenting the lowest mean absolute error among all the cells of the circuits under test and the smallest standard deviation. The latter suggests that the proposed method achieves better cell-specific accuracy, which is expected to allow for more precise circuit-level power estimations in complex circuits with a large number of combinational cells. Full article