Search Results (387)

Purpose: The aim of this study was to investigate the protective effects of systemically administered tauroursodeoxycholic acid (TUDCA) in an optic nerve crush (ONC) mouse model of retinal ganglion cell (RGC) death. Methods: C57BL/6J mice were injected intraperitoneally (i.p.) three times per week with TUDCA (500 mg/kg) for two weeks, after which unilateral ONC was performed. A control cohort was identically treated with a drug vehicle (phosphate buffered saline; PBS). A separate cohort did not undergo any injections or surgeries (this was termed the “Naïve” group). Pattern electroretinography (PERG) was recorded 3 days after ONC. Retinas were harvested for whole-mount immunofluorescence staining with an antibody against RGC marker Brn3a and imaged by fluorescent confocal microscopy. Apoptotic cells in the ganglion cell layer (GCL) were detected by Terminal Deoxynucleotidyl Transferase-Mediated dUTP Nick End Labeling (TUNEL) performed on fixed retina sections. Glial fibrillary acidic protein (GFAP) immunostaining on fixed retina sections was conducted to detect the activation of Müller cells. Total RNA was extracted from retinas and expression of interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and IL-10 was determined by digital droplet PCR (ddPCR). Results: TUDCA treatment preserved visual function as assessed by PERG. P1 and N2 amplitudes from the PBS-treated ONC group were significantly diminished compared to those of the Naïve group (p < 0.001). TUDCA treatment prevented this diminution. The amplitudes of P1 and N2 in the TUDCA-treated ONC group were statistically indistinguishable from those of the Naïve group and were higher than the PBS-treated ONC group (TUDCA+ONC vs. PBS+ONC, P1: 6.99 ± 0.89 µV vs. 3.60 ± 0.69 µV, p < 0.01; N2: −9.30 (IQR: −13.43–−6.44) µV vs. −4.47 (IQR: −10.26–−2.17) µV). TUDCA treatment preserved RGCs. The ONC-vehicle-only group had 25% fewer RGCs (Brn3a-positive cells) than Naïve eyes (p < 0.0001). TUDCA treatment nearly completely prevented this loss, preserving all but 7.7% of the RGCs, and the number of RGCs in the TUDCA-treated ONC group was significantly higher than in the PBS-treated ONC group (TUDCA+ONC vs. PBS+ONC, 1738.00 ± 14.43 cells per field vs. 1454.00 ± 6.55 cells per field, p < 0.0001). The number of TUNEL-positive cells in the GCL (Naïve vs. PBS+ONC group: 1.00 (IQR: 0.00–2.00) % vs. 37.00 (IQR: 8.50–48.50) %, p < 0.05) and GFAP-positive fibers transversing retina sections (Naïve vs. PBS+ONC group: 33.00 ± 1.15 vs. 185.70 ± 42.37 fibers/retina, p < 0.05), and the expression of IL-6, TNF-α were significantly greater in the PBS-treated ONC group compared to that of the Naïve group (Naïve vs. PBS+ONC group, IL-6: 0.07 (IQR: 0.06–0.31) vs. 0.99 (IQR: 0.56–1.47), p < 0.05, TNF-α: 0.19 ± 0.069 vs. 1.39 ± 0.23; p < 0.01), an increase not observed with TUDCA treatment. Conclusions: Systemic TUDCA treatment significantly preserved RGC function and survival in the mouse ONC model of RGC damage. TUDCA treatment prevented RGC apoptosis, Müller glial cell activation, and retinal expression of several inflammatory cytokines. These data suggest that TUDCA is a promising therapeutic candidate for preserving RGC numbers and function. Full article

High-Static–Low-Dynamic Stiffness (HSLDS) isolators have been extensively studied, primarily considering continuous stiffness and viscous damping, often overlooking stiffness discontinuities and dry friction forces. This paper aims to provide a more accurate model of real systems by investigating the dynamic behavior of HSLDS isolators, including piecewise nonlinear–linear stiffness, viscous damping, and dry friction. The equation of motion is analyzed using the Krylov–Bogoliubov–Mitropolsky (KBM) averaging method, deriving approximate analytical expressions to evaluate the frequency response curves and stability boundaries near primary resonance conditions. The model is validated by comparing the approximate solution with direct numerical integration and Den Hartog’s closed-form solution. A parametric analysis explores the impact of key parameters through amplitude–frequency diagrams and critical forcing boundaries. A numerical example is presented, demonstrating how the present method can be used to identify critical dynamic conditions, such as saddle-node bifurcations and activation of the piecewise restoring force nonlinearity. Results confirm the reliability of the KBM method in dealing with piecewise restoring forces while highlighting its limitations in case of high dry friction. This study offers an approximate yet effective approach for evaluating the system’s dynamic behavior, providing insights that could facilitate the design of isolation mounts and serve as benchmarks for future research. Full article

The detrimental effects of low-frequency vibrations on the measurement accuracy of commercial high-precision instrumentation demand urgent resolution, particularly for instruments requiring <1 μm positioning stability. Conventional base-mounted active damping systems exhibit limitations in suppressing the structural resonance induced by passive isolators—especially when the environmental vibration intensity surpasses the standard thresholds. Therefore, in this study, we developed an innovative multi-mode control architecture to substantially enhance the vibration-damping capabilities of the DCSMS. The proposed methodology synergistically integrates foundation vibration isolators with embedded passive modules through a dual-stage spring-mass system optimization framework. Experimental validation combining ADAMS–MATLAB multi-physics co-simulation, complemented by a decoupling analytical control model based on the vibrational transmission characteristics of the source propagation path, substantiated the efficacy of the proposed control methodology. Full article

This paper presents a comprehensive vehicle model featuring an active suspension system integrated with semi-active seat and engine mounting controls. The time-domain stochastic excitation of the four tires was modeled using the filtered white noise method, and the required road excitation was simulated using MATLAB software R2022b. Four comprehensive performance indices, including engine dynamic displacement, vehicle body acceleration, suspension dynamic deflection, and tire dynamic displacement, were selected and made dimensionless by the performance indices of a passive suspension under the same working conditions to construct the fitness function. A fractional-order PI^λD^μ (FOPID) controller was proposed, and its structural parameters were optimized using a gray wolf optimization algorithm. Furthermore, the optimized FOPID controller was evaluated under five road conditions, and its performance was compared with integer-order PID control and passive suspensions. The results demonstrate that the FOPID controller effectively improves the smoothness of the vehicle by reducing engine mounting deflection, vehicle body acceleration, suspension deflection, and tire displacement. Moreover, the simulation results indicate that, compared to the passive suspension, the FOPID-controlled suspension achieves an average optimization of over 42% in the root mean square (RMS) of body acceleration under random road conditions, with an average optimization of more than 38% for suspension deflection, 4.3% for engine mounting deflection, and 2.5% for tire displacement. In comparison to the integer-order PID-controlled suspension, the FOPID-controlled suspension demonstrates an average improvement of 28% in the RMS of acceleration and a 2.1% improvement in suspension deflection under random road conditions. However, the engine mounting deflection and tire displacement are reduced by 0.05% and 0.3%, respectively. FOPID control has better performance in vehicle acceleration control but shows asymmetrical effects on tire dynamic deflection. Full article

Promoting alternative modes of transportation such as cycling represents a valuable strategy to minimize environmental impacts, as confirmed in the main targets set out by the European Commission. In this regard, in cities throughout the world, there has been a significant increase in the construction of bicycle paths in recent years, requiring effective maintenance strategies to preserve their service levels. The continuous monitoring of road networks is required to ensure the timely scheduling of optimal maintenance activities. This involves regular inspections of the road surface, but there are currently no automated systems for monitoring cycle paths. In this study, an integrated monitoring and assessment system for cycle paths was developed exploiting Raspberry Pi technologies. In more detail, a low-cost Inertial Measurement Unit (IMU), a Global Positioning System (GPS) module, a magnetic Hall Effect sensor, a camera module, and an ultrasonic distance sensor were connected to a Raspberry Pi 4 Model B. The novel system was mounted on a e-bike as a test vehicle to monitor the road conditions of various sections of cycle paths in Rome, characterized by different pavement types and decay levels as detected using the whole-body vibration $a_{wz}$ index (ISO 2631 standard). Repeated testing confirmed the system’s reliability by assigning the same vibration comfort class in 74% of the cases and an adjacent one in 26%, with an average difference of 0.25 m/s², underscoring its stability and reproducibility. Data post-processing was also focused on integrating user comfort perception with image data, and it revealed anomaly detections represented by numerical acceleration spikes. Additionally, data positioning was successfully implemented. Finally, $a_{wz}$ measurements with GPS coordinates and images were incorporated into a Geographic Information System (GIS) to develop a database that supports the efficient and comprehensive management of surface conditions. The proposed system can be considered as a valuable tool to assess the pavement conditions of cycle paths in order to implement preventive maintenance strategies within budget constraints. Full article

Multispectral sensors are integral to vegetation analysis, particularly in the calculation of various vegetation indices (VIs). The use of integrated multispectral sensors has become prevalent in research, although their effectiveness is influenced by several factors. This highlights the need for ongoing research into enhancement techniques to improve the accuracy and reliability of vegetation status estimation. This study investigated the impact of field of view (FOV) variability on normalized differential vegetation index (NDVI) accuracy using a multispectral sensor. Data were collected from a wheat field at four growth stages (GS) (GS 1, GS 2, GS 3, and GS 4, at 10, 34, 70, and 84 days after sowing (DAS), respectively) and the sensors were mounted around 100 cm above the crop canopy. An active sensor was used to provide reference data for assessing multispectral measurement. A program was developed using the Python (ver. 3.10) programming language to process the global navigation satellite system (GNSS) coordinates and segment the images to align with the FOV of the active sensor and extracting the reflectance data for NDVI calculation. The results showed that proper FOV alignment significantly improved regression metrics (R² and RMSE) at all growth stages, with R² improvements ranging from 3% to 33%, and RMSE reductions from 0.03 to 0.06, respectively. The high vegetative growth stage was less affected due to the FOV misalignment. These techniques are promising toward improving NDVI accuracy, especially during early and mid-growth stages of the crop. Full article

To achieve deep decarbonization, renewable energy generation must be substantially increased. The technologies with the lowest levelized cost of electricity (LCOE) are land-based photovoltaics (PVs) and wind energy. Agri-PVs offer the potential for dual land use, combining energy generation with agricultural activities. However, the costs of agri-PVs are higher than those of ground-mounted PV. To enhance the competitiveness of agri-PV, we investigate the synergies between agri-PVs and hydrogen electrolysis through process simulation. Additionally, we analyse current technological developments in agri-PVs based on a market analysis of start-up companies. Our results indicate that the levelized cost of hydrogen (LCOH) can be comparable for agri-PVs and ground-mounted PVs due to the somewhat smoother electricity generation for the same installed capacity. The market analysis reveals the emergence of a technology ecosystem that integrates agri-PVs with next-generation agricultural technologies, such as sensors, robotics, and artificial intelligence (AI) agents, along with localized electricity generation forecasting. The integrated agri-PV and hydrogen generation system has significant global scaling potential for renewable energy generation. Furthermore, it positively impacts local economies and energy resilience, may reduce water scarcity in agriculture, and leverages advancements in AI, robotics, PV, and hydrogen generation technologies. Full article

This study details the design and implementation of a real-time river monitoring station established on the Sakarya River, capable of instantaneously tracking water levels and flow rates. The system comprises an ultrasonic distance sensor, a GSM module (Global System for Mobile Communications), which enables real-time wireless data transmission to a server via cellular networks, a solar panel, a battery, and a microcontroller board. The river monitoring station operates by transmitting water level data collected by the ultrasonic distance sensor to a server via a communication module developed on a microcontroller board using an Arduino program, and then sharing these data through a web interface. The developed system performs regular and continuous water level readings without the need for human intervention. During the installation and calibration of the monitoring station, laboratory and field tests were conducted, and the obtained data were validated by comparison with data from the hydropower plant located upstream. This system, mounted on a bridge, measures water levels twice per minute and sends these data to the relevant server via the GSM module. During this process, precipitation data were utilized as a critical reference point for validating measurement data for the 2023 hydrological year, with changes in precipitation directly correlated with river water levels and calculated flow values, which were analyzed accordingly. The real-time river monitoring station allows for instantaneous monitoring of the river, achieving a measurement accuracy of within 0.1%. The discharge values recorded by the system showed a high correlation (r² = 0.92) with data from the hydropower plant located upstream of the system, providing an accurate and comprehensive database for water resource management, natural disaster preparedness, and environmental sustainability. Additionally, the system incorporates early warning mechanisms that activate when critical water levels are reached, enabling rapid response to potential flood risks. By combining energy-independent operation with IoT (Internet Of Things)-based communication infrastructure, the developed system offers a sustainable solution for real-time environmental monitoring. The system demonstrates strong applicability in field conditions and contributes to advancing technologies in flood risk management and water resource monitoring. Full article

Player-tracking systems provide vital time–motion and tactical data for analyzing athletic performance. Ultra-wideband (UWB) systems are promising for racquet sports due to their accuracy and cost-effectiveness compared to GNSS and optical systems. This study evaluated the accuracy of a UWB tracking system (GenGee Insait KS) for tennis-specific movements by comparing it with an optical motion capture system (VICON). Ten amateur players (International Tennis Numbers: 2–5) participated, performing seven exercises, including warm-up, agility drills, and tactical drills, with and without racquets. Raw data from both systems were processed to calculate the distances traversed. The average root mean square error between the two systems was 0.65 m (X-axis) and 0.76 m (Y-axis). Significant measurement discrepancies were observed (standardized mean difference: 0.86–1.95), except for jogging and walking exercises (p > 0.05). The overall percentage error was 16.29%. The intraclass correlation coefficient for distance measurements was 0.91, indicating good reliability. Tasks involving rapid acceleration and directional changes, such as the spider run, exhibited larger errors (mean bias: 4.13 m, effect size: 1.03). While the UWB system demonstrated acceptable accuracy for steady movements, it showed notable discrepancies during high-speed, tennis-specific activities. Overestimation due to arm movement and hip rotation suggests caution when applying arm-mounted UWB devices in training and competitive settings. Full article

APOL1 Renal Risk Variants (APOL1RRVs, G1, and G2) are known to be toxic to glomerular podocytes and causally associated with an enhanced prevalence and progression of many different etiologies of chronic kidney disease (CKD), leading to the delineation of a new disease designation of APOL1-Mediated Kidney Disease (AMKD). Notably, APOL1RRVs have not consistently been shown to increase the prevalence or severity of diabetic kidney disease (DKD) progression, which is the most common cause of End-Stage Kidney Disease (ESKD). While this apparent discrepancy seems perplexing, its clarification should provide important mechanistic and therapeutic insights. Activation of the Renin–Angiotensin System (RAS) plays a critical role in the development and progression of DKD. Recent in vitro and in vivo studies also demonstrated that RAS activation contributes to kidney cell injury in AMKD experimental models. Both high glucose, as well as APOL1RRVs escalate the podocyte expression of miR193a, a known mediator of glomerulosclerosis, including idiopathic Focal Segmental Glomerular Sclerosis (FSGS) and DKD. We propose that either the RAS and/or miR193a levels in the diabetic milieu are already maximally conducive to kidney target cell injury and, therefore, are agnostic to further injury in response to APOL1RRVs. Similarly, the contributory role of hypertension (which is frequently reported as the second most common cause of ESKD) in the progression of AMKD remains a controversial issue. Since several clinical reports have shown that controlling hypertension does not consistently slow the progression of AMKD, this has led to a formulation wherein APOL1-RRVs primarily lead to kidney injury with accompanying hypertension. Notably, half a decade later, the notion that hypertension is not a cause but rather a consequence of kidney injury was contested by investigators analyzing the Mount Sinai BioMe repository, a comprehensive clinical and genetic database including participants with APOL1RRVs. These investigators observed that hypertension predated the observed decline in GFR in individuals with APOL1RRVs by ten years. In the present study, we discuss the mechanistic forces that may underpin the gaps in these clinical manifestations, which did not allow the temporal association of hypertension with AMKD to be translated into causation and may also dissociate DKD and AMKD. We have hypothesized models that need to be validated in future experimental studies. Full article

Background/Objectives: Mounting evidence indicates that the short-chain fatty acid butyrate protects against obesity and associated comorbidities, partially through the induction of adipose tissue thermogenesis. However, the effects of butyrate on white adipose tissue (WAT) browning and its molecular mechanism are still elusive. The objective of this study was to investigate butyrate-induced thermogenesis in white adipose tissue and its underlying mechanism. Methods: We studied the effects of butyrate on diet-induced obesity in the humanized APOE*3-Leiden.CETP transgenic mouse model and explored factors related to white adipose browning. Specifically, mice were challenged with a high-fat diet supplemented with butyrate. Adiposity was measured to assess obesity development. Energy metabolism was detected using an indirect calorimetry system. RNA-seq analysis was conducted to analyze the transcription landscape of WAT and responsible targets. Furthermore, the revealed molecular mechanism was verified in vitro. Results: Butyrate alleviated high-fat diet-induced obesity and promoted energy expenditure accompanied by brown adipose tissue activation and WAT browning. Mechanistically, RNA-seq analysis revealed that butyrate downregulated HDAC9 in WAT. Additionally, butyrate decreased HDAC9 while increasing thermogenesis in vitro. Inhibition of HDAC9 with TMP269 promoted thermogenic gene expression, mimicking the effects of butyrate. Conclusions: Butyrate protects against diet-induced obesity accompanied by decreasing the expression of HDAC9 in white adipose tissue and inducing browning. This study reveals a new mechanism whereby butyrate activates adaptive thermogenesis and provides new insights for the development of weight-loss drugs targeting adipose HDAC9. Full article

The fifth generation of wireless communication (5G) technology is becoming more innovative with the increasing need for high data rates because of the incremental rapidity of mobile data growth. In 5G systems, enhancing device-to-device communication, ultra-low latency (1 ms), outstanding dependability, significant flexibility, and data throughput (up to 20 Gbps) is considered one of the most essential factors for wireless networks. To meet these objectives, a sub-6 5G wideband multiple-input multiple-output (MIMO) array microstrip antenna for 5G Worldwide Interoperability for Microwave Access (WiMAX) applications on hotspot devices has been proposed in this research. The 1 × 4 MIMO array radiating element antenna with a partial ground proposed in this research complies with the 5G application standard set out by the Federal Communications Commission. The planned antenna configuration consists of a hollow, regular circular stub patch antenna shaped like a crescent with a rectangular defect at the top of the patch. The suggested structure is mounted on an FR-4 substrate with a thickness “h” of 1.6, a permittivity “${\epsilon }_r$” of 4.4, and a tangential loss of 0.02. The proposed antenna achieves a high radiation gain and offers a frequency spectrum bandwidth of 3.01 GHz to 6.5 GHz, covering two 5G resonant frequencies “$f_r$” of 3.5 and 5.8 GHz as the mid-band, which yields a gain of 7.66 dBi and 7.84 dBi, respectively. MIMO antenna parameters are examined and introduced to assess the system’s performance. Beneficial results are obtained, with the channel capacity loss (CCL) tending to 0.2 bit/s/Hz throughout the operating frequency band, the envelope correlation coefficient (ECC) yielding 0.02, a mean effective gain (MEG) of less than −6 dB over the operating frequency band, and a total active reflection coefficient (TARC) of less than −10 dB; the radiation efficiency is equal to 71.5%, maintaining impedance matching as well as good mutual coupling among the adjacent parameters. The suggested antenna has been implemented and experimentally tested using the 5G system Open Air Interface (OAI) platform, which operates at sub-6 GHz, yielding −67 dBm for the received signal strength indicator (RSSI), and superior frequency stability, precision, and reproducibility for the signal-to-interference-plus-noise ratio (SINR) and a high level of positivity in the power headroom report (PHR) 5G system performance report, confirming its operational effectiveness in 5G WiMAX (Worldwide Interoperability for Microwave Access) application. Full article

This study addresses a critical gap in human activity recognition (HAR) research by enhancing both the explainability and efficiency of activity classification in collaborative human–robot systems, particularly in agricultural environments. While traditional HAR models often prioritize improving overall classification accuracy, they typically lack transparency in how sensor data contribute to decision-making. To fill this gap, this study integrates explainable artificial intelligence, specifically SHapley Additive exPlanations (SHAP), thus enhancing the interpretability of the model. Data were collected from 20 participants who wore five inertial measurement units (IMUs) at various body positions while performing material handling tasks involving an unmanned ground vehicle in a field collaborative harvesting scenario. The results highlight the central role of torso-mounted sensors, particularly in the lumbar region, cervix, and chest, in capturing core movements, while wrist sensors provided useful complementary information, especially for load-related activities. The XGBoost-based model, selected mainly for allowing an in-depth analysis of feature contributions by considerably reducing the complexity of calculations, demonstrated strong performance in HAR. The findings indicate that future research should focus on enlarging the dataset, investigating the use of additional sensors and sensor placements, and performing real-world trials to enhance the model’s generalizability and adaptability for practical agricultural applications. Full article

Fixed solar panels face significant energy loss as they cannot consistently capture optimal sunlight. Because of that, the overall efficiency of the PV panel will be reduced, and the installation requires larger land space to generate appropriate power; this stems from the use of a dual-axis solar tracking system, which can significantly increase overall energy production. The system is based on the combination of two approaches to precisely track the sunlight: first, using multiple LDRs (light-dependent resistors) as photo sensors to track the position of the sun by balancing the resistivity using a proportional integral deprival (PID) controller, and the second approach using the time-based control for cloudy days when sunlight is diffused, getting the time GPS coordinates and time to calculate the accurate position of the sun by determining the azimuth and altitude angle. This dual system significantly improves energy production by 33.23% compared to fixed systems and eliminates errors during shaded conditions while reducing unnecessary energy use from continuous GPS activation. The prototype uses two linear actuators for both angles and a 100-watt solar panel mounted on the dual-axis platform. Full article

Thermospheric mass densities are investigated to explore their responses to solar irradiance and geomagnetic activity during the period from 31 October to 7 November 2021. Utilizing data from the Global Navigation Satellite System (GNSS) payload and an ionization gauge mounted on the Orbital Neutral Atmospheric Detector (OAD) payload onboard the QQ-Satellite, thermospheric mass densities are derived through two independent means: precise orbit determination (POD) and pressure measurements. For the first time, observations of these two techniques are compared and analyzed in this study to demonstrate similarities and differences. Both techniques exhibit similar spatial–temporal variations, with clear dependences on local solar time (LT). However, the hemispheric asymmetry is almost absent in simulations from the NRLMSISE-00 and DTM94 models compared with observations. At high latitudes, density enhancements of observations and simulations are shown, characterized by periodic bulge structures. In contrast, only the OAD-derived densities exhibit wave-like disturbances that propagate from two poles to lower latitudes during geomagnetic storm periods, suggesting a connection to traveling atmospheric disturbances (TADs). Over the long term, thermospheric mass densities derived from the two means of POD and the OAD show good agreements, yet prominent discrepancies emerge during specific periods and under different space-weather conditions. We propose possible interpretations as well as suggestions for utilizing these two means. Significantly, neutral winds should be considered in both methods, particularly at high latitudes and under storm conditions. Full article