Search Results (46,390)

Accurate precipitation forecasting is paramount for water security and disaster mitigation, yet it remains formidable due to atmospheric stochasticity and the inherent class imbalance in rainfall datasets. This study proposes an integrated “architecture-feature-augmentation” framework to circumvent these limitations. Through a systematic evaluation of CNN-LSTM and Transformer architectures, we delineate distinct performance profiles: The Transformer model, when coupled with feature engineering and physics-informed augmentation, yields a peak F1-score of 0.1429, marking the optimal configuration for harmonizing precision and recall. Conversely, CNN-LSTM demonstrates superior robustness in extreme event detection, consistently maintaining high recall rates (up to 0.90) across diverse scenarios. We identify feature engineering as a critical performance modulator, substantially bolstering CNN-LSTM’s baseline metrics while enabling the Transformer to realize its maximum predictive capacity. Although synthetic oversampling techniques—such as SMOTE and GAN—effectively extend the detection range for heavy precipitation, physics-informed augmentation provides the most consistent performance gains, particularly in multi-class contexts. We conclude that the Transformer, augmented by physical constraints, is the optimal candidate for high-precision requirements, whereas CNN-LSTM, integrated with synthetic augmentation, offers a more sensitive alternative for early warning systems prioritizing recall. These findings provide empirical guidance for advancing extreme weather preparedness and strategic water resource management. Full article

Biofouling arises from non-specific adsorption of several components present in complex biofluids, such as full blood, on the surface of electrochemical biosensors, with a resulting loss of functionality. Most biomarkers of clinical relevance are present in biological fluids at extremely low concentrations, making antibiofouling strategies necessary in electrochemical biosensing. Here, we demonstrate the effect of a highly porous gold (h-PG) film electrodeposited on a gold screen-printed electrode (AuSPE) using a self-templated method via hydrogen bubbling as an antibiofouling strategy in electrochemical biosensor development following exposure of the electrode to bovine serum albumin (BSA) at two different concentrations (2 and 32 mg/mL). The h-PG film has a high electrochemically active surface area, 88 times higher than the AuSPE electrode, with a pore size ranging from 2 to 50 μm. A rapid decrease in the Faradaic current was observed with the unmodified AuSPE, attesting to the strong biofouling effect of BSA at both concentrations tested. Notably, the h-PG-modified electrode showed an initial peak current decline, more evident at a higher BSA concentration, followed by rapid electrode regeneration when the electrode was left idle in the biofouling solution. Similar results were obtained for unmodified and modified electrodes in real serum and plasma samples. The regeneration process, explained in terms of balance between h-PG pore size and protein size, the nanoscale architecture of the h-PG electrodes, and repulsive electrostatic forces, indicates the huge potential of the h-PG film for use in biomedical electrochemical sensing. Full article

Compared with other forest vegetation, bamboo forests have a stronger carbon sequestration capacity, which plays a vital role in achieving the national goals of carbon peak and carbon neutrality. Global warming has profoundly impacted the adaptive distribution and landscape fragmentation of bamboo forests. This study utilized an optimized MaxEnt model to calculate the current habitat range of Neosinocalamus affinis (Rendle) Keng f. forests across China and project their potential distribution under three future climate scenarios (SSP126, SSP370, SSP585) for the 2050s and 2090s and analyzed the landscape fragmentation of their land use using landscape indices. The results reveal that Neosinocalamus affinis forests are currently primarily distributed in Chongqing Municipality, eastern and southeastern Sichuan Province, and northern Guizhou Province. The key environmental factors influencing their distribution are identified as: mean diurnal temperature range (Bio2), precipitation of warmest quarter (Bio18), and precipitation of wettest quarter (Bio16). Across the three future scenarios, the suitable habitat area for Neosinocalamus affinis forests demonstrates an overall expanding trend. Rising CO₂ concentrations correlate with a reduction in suitable habitat. The habitat centroid shifts southward in the 2050s and northeastward in the 2090s. In the future, the fragmentation degree of highly suitable areas for Neosinocalamus affinis forests will be higher than at present and show an increasing trend, with forest fragmentation significantly intensifying and overall landscape quality further declining. The predictive results of this study provide a scientific basis for the effective conservation and management of Neosinocalamus affinis forests, thereby contributing to the sustainable utilization of bamboo forest resources. Full article

This paper proposes a comprehensive framework for integrating Digital Twins (DT) with real-time traffic optimization systems to enhance urban mobility management in Smart Cities. Using the Pobitno Roundabout in Rzeszów as a case study, we established a calibrated microsimulation model (validated via the GEH statistic) that serves as the core of the proposed Digital Twin. The study goes beyond static scenario analysis by introducing an Adaptive Inflow Metering (AIM) logic designed to interact with IoT sensor data. While traditional geometrical upgrades (e.g., turbo-roundabouts) were analyzed, simulation results revealed that geometrical changes alone—without dynamic control—may fail under peak load conditions (resulting in LOS F). Consequently, the research demonstrates how the DT framework allows for the testing of “Software-in-the-Loop” (SiL) solutions where Python-based algorithms dynamically adjust inflow parameters to prevent gridlock. The findings confirm that combining physical infrastructure changes with digital, real-time optimization algorithms is essential for achieving sustainable “green transport” goals and reducing emissions in congested urban nodes. Full article

The analysis of ground-penetrating radar data generally relies on the visual identification of structures on selected profiles and their interpretation in terms of buried features. In simple cases, inverse modelling of the acquired data set can facilitate interpretation and reduce subjectivity. These methods suffer from severe restrictions due to antenna resolution limits, which prevent the identification of tiny structures, particularly in forensic, stratigraphic, and engineering applications. Here, we describe a technique to obtain a high-resolution characterization of the underground, based on the forward modelling of individual traces (A-scans) of selected radar profiles. The model traces are built by superposition of Ricker wavelets with different polarities, amplitudes, and arrival times and are used to create reflectivity diagrams that plot reflection amplitudes and polarities versus depth. A thin bed is defined as a layer of higher or lower permittivity relative to the surrounding material, such that the top and bottom reflections are subject to constructive interference, determining the formation of an anomalous peak in the trace (tuning effect). The proposed method allows the detection of ultra-thin layers, well beyond the Rayleigh vertical resolution of GPR antennas. This approach requires a preliminary estimation of the instrumental uncertainty of common monostatic antennas and takes into account the frequency-dependent attenuation, which causes a spectral shift of the dominant frequency acquired by the receiver antenna. Such a quantitative approach to analyzing radar data can be used in several applications, notably in stratigraphic, forensic, paleontological, civil engineering, heritage protection, and soil stratigraphy applications. Full article

The accurate estimation of outflow discharge from Piano Key Weirs (PKWs) under unsteady flow conditions is critical for effective flood management and the safety of dams. While extensive research exists on PKWs under steady flow, their hydraulic behavior during unsteady flow remains poorly understood. This study addresses this gap by investigating a Type-A PKW using combined physical and numerical modeling. A total of eight steady-flow and fifty-three unsteady-flow experiments were conducted. The steady flow experiments covered a range of Q = 5.13–40.76 L/s (H = 1.29–10.45 cm), while the unsteady experiments employed hydrographs with peak discharges up to ~68 L/s. Outflow was estimated via the Modified Puls method (hydrological routing) and a validated 3D numerical model (hydraulic routing). The results revealed significant discrepancies between steady and unsteady stage-discharge relationships, with a mean relative error of up to 41.37% and instantaneous errors exceeding 150% during the rising limbs of hydrographs with high rates of change in discharge, associated with intensified unsteady flow effects. A validated looped stage-discharge curve was observed under unsteady conditions, showing lower discharge on the rising limb for the same head. The Modified Puls method exhibited high accuracy, with relative errors below 5% when compared to hydraulic routing results. Additionally, three comparative indices were proposed and used to evaluate the performance of outflow estimation methods. The findings underscore the importance of incorporating unsteady flow conditions in the design and analysis of PKWs, particularly in the context of climate change and increasing flood uncertainties. Full article

This study develops and evaluates a regionally calibrated magnitude scaling and early warning framework based on the ElarmS–EPIC algorithm using the 23 April 2025 Silivri (Istanbul) Earthquake (Mw = 6.2) scenario. A comprehensive dataset comprising the mainshock and its aftershocks was used to derive local regression relationships between earthquake magnitude (Mw) and the peak displacement amplitude ($Pd$) and predominant period ($T_p^{max}$) parameters. Replay simulations were conducted to assess real-time performance, and the results of the regional models were compared with those of the default EPIC configuration. The results indicate that the $Pd$-based magnitude estimation model produces faster and more stable results than the $T_p^{max}$-based approach, significantly improving accuracy and operational reliability. The region-specific $Pd$–Mw scaling provided higher consistency with catalog magnitudes compared to the default EPIC relationships. The calculated distribution of warning times shows that the system can provide actionable warning times of 5–9 s in districts near the epicenter (e.g., Silivri, Avcılar, Beylikdüzü) and 20–50 s in more distant districts and city centers (e.g., Kadıköy, Pendik, Bursa, Sakarya). These values demonstrate that a regionally optimized early warning system can provide critical decision-making time for automatic safety systems and emergency responses in the densely populated Marmara Region. Overall, this study emphasizes the importance of regional calibration in improving earthquake early warning (EEW) performance in Türkiye. The findings show that the success of EEW systems depends on station density, network latency, data transmission speed, processing capacity, and algorithmic optimization. The proposed $Pd$-based regional framework provides a scientifically robust and operationally applicable foundation for future EEW implementations in Istanbul and the Marmara Region. Full article

Raccoon dog fur is a commercially valuable animal product. As the scale of raccoon dog breeding continues to expand, ensuring the health of these animals has become an urgent priority. The gut microbiota plays a central role in regulating animal health; however, current research on the composition of raccoon dog gut microbiota remains limited. This study aimed to characterize changes in the gut microbiota of suckling raccoon dogs across different stages, providing a foundation for future scientific feeding practices. Fecal samples of eight lactating raccoon dogs were collected and tested for microbiota on days 14, 21, and 45. Our results showed that the richness and diversity of microbiota increased with age in suckling raccoon dogs, peaking on the 45th day. Significant separation between groups was observed in both PCoA and NMDS analyses. UPGMA analysis indicated temporal fluctuations in gut microbiota composition. At the phylum level, Firmicutes and Bacteroidetes were the dominant taxa across all stages. LEfSe analysis at the genus level showed that Bacteroides was the most enriched taxon on the 14th day, Fusobacterium on the 21st day, and Prevotella_9 on the 45th day. Tax4Fun and PICRUSt analyses identified metabolism and genetic information processing as the primary functional roles of the gut microbiota. Further investigation suggested that the microbiota may benefit raccoon dogs through membrane transport, carbohydrate metabolism, amino acid metabolism, and energy metabolism. These findings establish a theoretical basis for improving the survival rate of suckling raccoon dogs and developing scientifically informed feeding and management protocols. Full article

Quantum communication presents new opportunities for overcoming the limitations of classical wireless systems, particularly those associated with noise, fading, and interference. Building upon the principles of classical orthogonal frequency division multi-plexing (OFDM), this work proposes a quantum OFDM architecture tailored for video transmission. In the proposed system, video sequences are first compressed using the versatile video coding (VVC) standard with different group of pictures (GOP) sizes. Each GOP size is processed through a channel encoder and mapped to multi-qubit states with various qubit configurations. The quantum-encoded data is converted from serial-to-parallel form and passed through the quantum Fourier transform (QFT) to generate mutually orthogonal quantum subcarriers. Following reserialization, a cyclic prefix is appended to mitigate inter-symbol interference within the quantum channel. At the receiver, the cyclic prefix is removed, and the signal is restored to parallel before the inverse QFT (IQFT) recovers the original quantum subcarriers. Quantum decoding, classical channel decoding, and VVC reconstruction are then employed to recover the videos. Experimental evaluations across different GOP sizes and channel conditions demonstrate that quantum OFDM provides superior resilience to channel noise and improved perceptual quality compared to classical OFDM, achieving peak signal-to-noise ratio (PSNR) up to 47.60 dB, structural similarity index measure (SSIM) up to 0.9987, and video multi-method assessment fusion (VMAF) up to 96.40. Notably, the eight-qubit encoding scheme consistently achieves the highest SNR gains across all channels, underscoring the potential of quantum OFDM as a foundation for future high-quality video transmission. Full article

We present a mixed-signal front-end ASIC designed for compact Silicon Photomultiplier (SiPM) sensor interfaces, implemented in the AMS 0.35 µm CMOS technology. The chip integrates two independent analog channels, each composed of five custom second-generation current conveyors (CCII⁺), a fast zero-crossing discriminator, and a peak-and-hold stage based on a tailored operational amplifier. The CCII⁺ and discriminator blocks were designed in-house, based on literature designs and adapted to the technology to ensure low input impedance and fast current-mode signal propagation. This architecture enables precise detection of small signals with reduced pile-up, important for time-resolved photon detection. Bias and threshold control are provided by programmable current mirrors and SPI-configurable DACs, including a 10-bit current-mode DAC based on a current-splitting structure with approximately 200 nA resolution. A custom SiPM behavioral model was developed in the Cadence environment to support design and simulation, reproducing realistic pulse shapes and recovery dynamics for timing applications. Circuit-level simulations confirm correct analog functionality and stable operation across the intended dynamic range, with a per-channel consumption of about 5.9 mA at 3.3 V (19.5 mW), reflecting a tradeoff between speed and robustness. The system is compatible with external timing architectures, while internal CCII⁺ stages ensure low-impedance current reception, fast discrimination, and accurate current-to-voltage conversion for peak detection. Full article

With the rapid development of mobile robotics, wheeled bipedal robots, which combine the terrain adaptability of legged robots with the high mobility of wheeled systems, have attracted increasing research attention. To address the balance control problem during both standing and locomotion while reducing the influence of noise on control performance, this paper proposes a balance control framework based on a Linear Quadratic Regulator integrated with an Extended Kalman Filter (KLQR). Specifically, a baseline LQR controller is designed using the robot’s dynamic model, where the control input is generated in the form of wheel-hub motor torques. To mitigate measurement noise and suppress oscillatory behavior, an Extended Kalman Filter is applied to smooth the LQR torque output, which is then used as the final control command. Filtering experiments demonstrate that, compared with median filtering and other baseline methods, the proposed EKF-based approach significantly reduces high-frequency torque fluctuations. In particular, the peak-to-peak torque variation is reduced by more than 60%, and large-amplitude torque spikes observed in the baseline LQR controller are effectively eliminated, resulting in continuous and smooth torque output. Static balance experiments show that the proposed KLQR algorithm reduces the pitch-angle oscillation amplitude from approximately ±0.03 rad to ±0.01 rad, corresponding to an oscillation reduction of about threefold. The estimated RMS value of the pitch angle is reduced from approximately 0.010 rad to 0.003 rad, indicating improved convergence and steady-state stability. Furthermore, experiments involving constant-speed straight-line locomotion and turning indicate that the KLQR algorithm maintains stable motion with velocity fluctuations limited to within ±0.05 m/s. The lateral displacement deviation during locomotion remains below 0.02 m, and no abrupt acceleration or deceleration is observed throughout the experiments. Overall, the results demonstrate that applying Extended Kalman filtering to smooth the control torque effectively improves the smoothness and stability of LQR-based balance control for wheeled bipedal robots. Full article

This study analyzes the provisioning strategy of the European Scops Owl (Otus scops) via continuous video monitoring of a breeding pair in a peri-urban Mediterranean forest in NE Spain (n = 724 deliveries). Invertebrates dominated numerically, with Orthoptera constituting 64.6%. Although vertebrates were scarce (1.8%), they contributed disproportionately to total biomass (20.8%), with rodents alone accounting for 20.3% of delivered energy. Parental effort followed a bimodal nocturnal rhythm, peaking at darkness onset (22:00 h) and before dawn. Crucially, we found a significant predation bias towards female orthopterans (65.6% vs. 34.3%; p < 0.001). While driven by Meconema thalassinum, selection in larger species like Tettigonia viridissima evidences a strategy focused on biomass profitability. Since Ensifera biomass scales allometrically (W $~ L^{2.797}$), selecting females yields disproportionate energetic gains. We also report the systematic removal of ovipositors prior to delivery, a behavior that optimizes intake but renders high-value females undetectable in traditional pellet analyses. These results suggest O. scops exploits artificial light sources (“streetlight traps”) to maximize foraging efficiency. Full article

To address the impact-induced damage to concrete pile foundations of transmission structures caused by nearby blasting vibrations, this study investigates the dynamic splitting tensile behavior of an environmentally friendly lightweight rubberized concrete—Rubber-Toughened Ceramsite Concrete (RTCC)—under impact loading. Quasi-static tests show that the static splitting tensile strength increases first and then decreases with increasing rubber content, reaching a maximum value of 2.01 MPa at a 20% replacement ratio. Drop-weight impact tests indicate that RTCC20 exhibits the highest peak impact force (42.48 kN) and maximum absorbed energy (43.23 J) within the medium strain-rate range. Split Hopkinson Pressure Bar (SHPB) tests further demonstrate that RTCC20 shows the highest strain-rate sensitivity. Overall, RTCC with 20% rubber content provides the best comprehensive performance, achieving a favorable balance between strength and toughness across the entire strain-rate range. These findings offer experimental support for applying RTCC to blast-vibration-resistant transmission structure foundations. Full article

The vibration compaction behavior of fully graded fresh concrete differs fundamentally from that of conventional two-graded concrete. Based on measured vibration responses of an internal vibrator and sinking-ball tests, an energy transfer model for fully graded concrete was established by incorporating the effects of aggregate-specific surface area, paste–aggregate ratio, dynamic damping, and natural frequency, and the spatiotemporal attenuation of vibration energy in fresh concrete was systematically analyzed. Experimental results indicate that fully graded concrete exhibits a higher energy absorption capacity during the early stage of vibration, with a maximum energy absorption rate of 423 W and a peak energy transfer efficiency of 76.3%, both of which are significantly higher than those of two-graded concrete at the same slump. However, as a dense aggregate skeleton rapidly forms, the energy absorption efficiency of fully graded concrete decreases more rapidly during the middle and later stages of vibration, showing a characteristic pattern of “high initial absorption followed by rapid attenuation.” Through segregation assessment and porosity analysis, a safe vibration energy range for fully graded concrete was quantitatively determined, with lower and upper energy thresholds of 159.7 J·kg⁻¹ and 538.5 J·kg⁻¹, respectively. In addition, the experiments identified recommended vibration durations of 30–65 s and effective vibration influence radii of 22–85 mm for fully graded concrete under different slump conditions. These findings provide a quantitative basis for the control of vibration parameters and energy-oriented construction of fully graded concrete. Full article

The combined effects of climate change and socio-economic development have intensified the risk of water supply–demand imbalance in China. To project future trends, this study develops a multi-scenario coupled prediction framework integrating climate, socio-economic, and human activity drivers, combining data-driven and physically based modeling approaches to assess terrestrial water storage imbalance in nine major river basins under six representative SSP–RCP scenarios through the end of the 21st century. Using ISIMIP multi-model runoff outputs along with GDP and population projections, agricultural, industrial, and domestic water demands were estimated. A Water Conflict Index was proposed by integrating the Water Supply–Demand Stress Index and the Standardized Hydrological Runoff Index to identify high-risk basins. Results show that under high-emission scenarios, the WCI in the Yellow River, Hai River, and Northwest Rivers remains high, peaking during 2040–2069, while low-emission scenarios significantly alleviate stress in most basins. Water allocation inequity is mainly driven by insufficient supply in arid northern regions and limited redistribution capacity in resource-rich southern basins. Targeted strategies are recommended for different risk types, including inter-basin water transfer, optimization of water use structure and pricing policies, and the development of resilient management systems, providing scenario-based quantitative support for future water security and policy-making in China. Full article