Search Results (697)

Single-Photon Avalanche Photodiodes (SPADs) are increasingly utilized in high-temperature-operated, high-performance Light Detection and Ranging (LiDAR) systems as well as in ultra-low-temperature-operated quantum science applications due to their high photon sensitivity and timing resolution. Consequently, the jitter value of SPADs at different temperatures plays a crucial role in LiDAR systems and Quantum Key Distribution (QKD) applications. However, limited studies have been conducted on this topic. In this study, we analyze the jitter characteristics of SPAD devices, focusing on the influence of device structures in two SPAD designs fabricated using the TSMC 18HV and TSMC 13HV processes. Using picosecond lasers with wavelengths ranging from ultraviolet (405 nm) to near-infrared (905 nm), we investigate the impact of different diffusion carrier types on jitter values and their temperature dependence across a range of 0 °C to 60 °C. Our results show that the jitter value of SPAD devices with low electric field regions varies significantly with temperature. This variation can be attributed to the higher temperature-dependent diffusion constant, as demonstrated by fitting the jitter diffusion tail with two diffusion time constants. In contrast, SPADs designed with modified electric field distributions exhibit smaller diffusion time constants and weaker temperature dependence, resulting in a much smaller temperature-dependent jitter value. Full article

With the wide application of UAVs in modern intelligent warfare as well as in civil fields, the demand for C-UAS technology is increasingly urgent. Traditional detection methods have many limitations in dealing with “low, slow, and small” targets. This paper presents a pure laser automatic tracking system based on Geiger-mode avalanche photodiode (Gm-APD). Combining the target motion state prediction of the Kalman filter and the adaptive target tracking of Camshift, a Cam–Kalm algorithm is proposed to achieve high-precision and stable tracking of moving targets. The proposed system also introduces two-dimensional Gaussian fitting and edge detection algorithms to automatically determine the target’s center position and the tracking rectangular box, thereby improving the automation of target tracking. Experimental results show that the system designed in this paper can effectively track UAVs in a 70 m laboratory environment and a 3.07 km to 3.32 km long-distance scene while achieving low center positioning error and MSE. This technology provides a new solution for real-time tracking and ranging of long-distance UAVs, shows the potential of pure laser approaches in long-distancelow, slow, and small target tracking, and provides essential technical support for C-UAS technology. Full article

Background/Objectives: The evolution of digital technology enhances the broadening of a person’s intellectual growth. Research points out that implementing innovative applications of the digital world improves human social, cognitive, and metacognitive behavior. Artificial intelligence chatbots are yet another innovative human-made construct. These are forms of software that simulate human conversation, understand and process user input, and provide personalized responses. Executive function includes a set of higher mental processes necessary for formulating, planning, and achieving a goal. The present study aims to investigate executive function reinforcement through artificial intelligence chatbots, outlining potentials, limitations, and future research suggestions. Specifically, the study examined three research questions: the use of conversational chatbots in executive functioning training, their impact on executive-cognitive skills, and the duration of any improvements. Methods: The assessment of the existing literature was implemented using the systematic review method, according to the PRISMA 2020 Principles. The avalanche search method was employed to conduct a source search in the following databases: Scopus, Web of Science, PubMed, and complementary Google Scholar. This systematic review included studies from 2021 to the present using experimental, observational, or mixed methods. It included studies using AI-based chatbots or conversationalists to support executive functions, such as anxiety, stress, depression, memory, attention, cognitive load, and behavioral changes. In addition, this study included general populations with specific neurological conditions, all peer-reviewed, written in English, and with full-text access. However, the study excluded studies before 2021, the literature reviews, systematic reviews, non-AI-based chatbots or conversationalists, studies not targeting the range of executive skills and abilities, studies not written in English, and studies without open access. The criteria aligned with the study objectives, ensuring a focus on AI chatbots and the impact of conversational agents on executive function. The initial collection totaled n = 115 articles; however, the eligibility requirements led to the final selection of n = 10 studies. Results: The findings of the studies suggested positive effects of using AI chatbots to enhance and improve executive skills. Although, several limitations were identified, making it still difficult to generalize and reproduce their effects. Conclusions: AI chatbots are an innovative artificial intelligence tool that can function as a digital assistant for learning and expanding executive skills, contributing to the cognitive, metacognitive, and social development of the individual. However, its use in executive skills training is at a primary stage. The findings highlighted the need for a unified framework for reference and future studies, better study designs, diverse populations, larger sample sizes of participants, and longitudinal studies that observe the long-term effects of their use. Full article

Supraglacial debris cover considerably influences sub-debris ablation patterns and the surface morphology of glaciers by modulating the land–atmosphere energy exchange. Understanding its spatial distribution and temporal variations is crucial for analyzing melting processes and managing downstream disaster mitigation efforts. In recent years, the overall slightly positive mass balance or stable state of eastern Pamir glaciers has been referred to as the “Pamir-Karakoram anomaly”. It is important to note that spatial heterogeneity in glacier change has drawn widespread research attention. However, research on the spatiotemporal changes in the debris cover in this region is completely nonexistent, which has led to an inadequate understanding of debris-covered glacier variations. To address this research gap, this study employed Landsat remote sensing images within the Google Earth Engine platform, leveraging the Random Forest algorithm to classify the supraglacial debris cover. The classification algorithm integrates spectral features from Landsat images and derived indices (NDVI, NDSI, NDWI, and BAND RATIO), supplemented by auxiliary factors such as slope and aspect. By extracting the supraglacial debris cover from 1994 to 2024, this study systematically analyzed the spatiotemporal variations and investigated the underlying drivers of debris cover changes from the perspective of mass conservation. By 2024, the area of supraglacial debris in eastern Pamir reached 258.08 ± 20.65 km², accounting for 18.5 ± 1.55% of the total glacier area. It was observed that the Kungey Mountain region demonstrated the largest debris cover rate. Between 1994 and 2024, while the total glacier area decreased by −2.57 ± 0.70%, the debris-covered areas expanded upward at a rate of +1.64 ± 0.10% yr⁻¹. The expansion of debris cover is driven by several factors in the context of global warming. The rising temperature resulted in permafrost degradation, slope destabilization, and intensified weathering on supply slopes, thereby augmenting the debris supply. Additionally, the steep supply slope in the study area facilitates the rapid deposition of collapsed debris onto glacier surfaces, with frequent avalanche events accelerating the mobilization of rock fragments. Full article

Photoionization is a significant factor influencing the morphology and propagation characteristics of streamers in insulating oil, yet research on the impact of photoionization on streamer branching is almost nonexistent. In this study, we employed an ultraviolet absorber to regulate the photoionization behavior of streamer discharges in rapeseed insulating oil. A quantitative assessment was conducted on the propagation morphology, length, and temperature distribution of positive and negative streamers. The results indicated that the streamer branches propagated in a dendritic manner. When photoionization was suppressed by the ultraviolet absorber, the streamer tended to generate more radially propagating branches, thereby shortening the axial stop length of the streamer branches by 1~3 mm. In addition, suppressing photoionization caused the maximum temperature to rise by approximately 74~220 K, generating more high-temperature hot spots within the streamer branches and promoting the formation of more radially propagating branches in the streamer. The analysis results demonstrated that suppressing photoionization weakened the axial electric field strength in the head region of the streamer branches, thereby inhibiting the electron avalanche behavior at the head of the streamer and thus reducing the rate of axial propagation of the streamer branches. Full article

Cloud computing has revolutionized the digital era by providing a more efficient, scalable, and cost-effective infrastructure. Secure systems that encrypt and protect data before it is transmitted over a network and stored in the cloud benefit the entire transmission process. Transmission data can be encrypted and protected with a secure dynamic substitution box (S-box). In this paper, we propose the QuantumGS-box, which is a dynamic S-box for high-speed cloud-based storage encryption generated by bit shuffling with a genetic algorithm and a quantum random number generator (QRNG). The proposed work generates the S-box optimized values in a dynamic way, and an experimental evaluation of the proposed S-box method has been conducted using several cryptographic criteria, including bit independence criteria, speed, non-linearity, differential and linear approximation probabilities, strict avalanche criteria and balanced output. The results demonstrate that the QuantumGS-box can enhance robustness, is resilient to differential and provide improved linear cryptoanalysis compared to other research works while assuring non-linearity. The characteristics of the proposed S-box are compared with other state of the art S-boxes to validate its performance. These characteristics indicate that the QuantumGS-box is a promising candidate for cloud-based storage encryption applications. Full article

In this work, the InGaAs/InAlAs multi-gain-stage APD model is established. The gain and the noise performance of multi-gain-stage APDs are analyzed based on DSMT. By studying the influence of different doping concentrations of the dropping layer and the charge layer on the gain and noise characteristics of the device, the photocurrent, dark current, noise, and gain characteristics of the device are analyzed, and the device structure is optimized. The results show that the maximum gain of the three-gain-stage APD is 416, and the noise factor is 3.5 when the gain is 100. The five-gain-stage APD has a maximum gain of 450 and a noise factor of 4.5 when the gain is 100. The maximum gain of the 10-gain-stage APD can reach more than 850, and the noise factor reaches 6.5 when the gain is 100. Full article

Blockchain has several unique features: data integrity, security, privacy, and immutability. For this reason, it is considered one of the most promising new technologies for a wide range of applications. Initially prominent in cryptocurrencies such as Bitcoin, its applications have expanded into areas such as the Internet of Things. However, integrating blockchain into IoT systems is challenging due to the limited computing and storage capabilities of IoT devices. Efficient blockchain mining requires lightweight hash functions that balance computational complexity with resource constraints. In this study, we employed a structured methodology to evaluate hash functions for blockchain–IoT systems. Initially, a survey is conducted to identify the most commonly used hash functions in such environments. Also, this study identifies and evaluates a lightweight hash function, designated as HashLEA, for integration within blockchain-based IoT systems. Subsequently, these functions are implemented and evaluated using software coded in C and Node.js, thereby ensuring compatibility and practical applicability. Performance metrics, including software efficiency, hardware implementation, energy consumption, and security assessments, were conducted and analyzed. Ultimately, the most suitable hash functions, including HashLEA for blockchain–IoT applications, are discussed, striking a balance between computational efficiency and robust cryptographic properties. Also, the HashLEA hash function is implemented on a Raspberry Pi 4 with an ARM processor to assess its performance in a real-world blockchain–IoT environment. HashLEA successfully passes security tests, achieving a near-ideal avalanche effect, uniform hash distribution, and low standard deviation. It has been shown to demonstrate superior execution time performance, processing 100 KB messages in 0.157 ms and 10 MB messages in 15.48 ms, which represents a significant improvement in execution time over other alternatives such as Scrypt, X11, and Skein. Full article

This paper explores a recently proposed scalable z-pinch-based space propulsion engine in greater detail. This concept involves a “modified plasma focus with a tapered anode that transports current from a pulsed power source to a consumable portion of the anode in the form of a hypodermic needle tube continuously extruded along the axis of the device”. This tube is filled with a gas at a high pressure and also optionally with an axial magnetic field. The current enters the metal tube through its contact with the anode and returns to the cathode via the plasma sliding over its outer wall. The resulting rapid electrical explosion of the metal tube partially transfers current to a snowplough shock in the fill gas. Both the metal plasma and the fill gas form axisymmetric converging shells. Their interaction forms a hot and dense plasma of the fill gas surrounded by the metal plasma. Its ejection along the axis provides the impulse needed for propulsion. In a nonnuclear version, the fill gas could be xenon or hydrogen. Its unique energy density scaling could potentially lead to a neutron-deficient nuclear fusion drive based on the proton-boron avalanche fusion reaction by lining the tube with solid decaborane. In order to explore the inherent potential of this idea as a scalable space propulsion engine, this paper discusses its theoretical foundations and outlines the first iteration of a conceptual engineering design study for a proof-of-concept experiment based on the UNU-ICTP Plasma Focus facility at the Nanyang Technological University, Singapore. Full article

Snow avalanche is one of the major natural hazards in the mountain region, yet it has received less attention compared to other mountain hazards, such as landslides, floods, and droughts. After a comprehensive overview of snow avalanche hazards in Tibet area, the spatial distribution and main driving factors of snow avalanche hazards in the high mountain region in Tibet were presented in the study first. Snow avalanche-prone areas in Tibet were then mapped based on the snow cover distribution and DEM data and were validated against in situ observations. Results show that there are the highest frequencies of avalanche occurrences in the southeastern Nyainqentanglha Mountains and the southern slope of the Himalayas. In the interior of plateau, avalanche development is constrained due to less precipitation and much flatter terrain. The perennially snow avalanche-prone areas in Tibet account for 1.6% of the total area of the plateau, while it reaches 2.9% and 4.9% of the total area of Tibet in winter and spring, respectively. Snow avalanche hazards and fatalities appear to be increasing trends under global climate warming due to more human activities at higher altitudes. In addition to the continuous implementation of engineering prevention and control measures in pivotal regions in southeastern Tibet, such as in the Sichuan–Tibet highway and railway sections, enhancing monitoring, early warning, and forecasting services are crucial to prevent and mitigate avalanche hazards in the Tibetan high mountain regions, which has significant implications for other global high mountain areas. Full article

Avalanches present substantial hazard risk in mountainous regions, particularly when avalanches obstruct roads, either hitting vehicles directly or leaving traffic exposed to subsequent avalanches during cycles. Traditional detection methods often are designed to cover only a limited section of a road stretch, hampering effective risk management. This research introduces a novel approach using Distributed Acoustic Sensing (DAS) for avalanche detection. The monitoring site in Northern Norway is known to be frequently impacted by avalanches. Between 2022–2024, we continuously monitored the road for avalanches blocking the traffic. The automated alert system identifies avalanches affecting the road and estimates accumulated snow. The system provides continuous, real-time monitoring with competitive sensitivity and accuracy over large areas (up to 170 km) and for multiple sites on parallel. DAS powered alert system can work unaffected by visual barriers or adverse weather conditions. The system successfully identified 10 road-impacting avalanches (100% detection rate). Our results via DAS align with the previous works and indicate that low frequency part of the signal (<20 Hz) is crucial for detection and size estimation of avalanche events. Alternative fiber installation methods are evaluated for optimal sensitivity to avalanches. Consequently, this study demonstrates its durability and lower maintenance requirements, especially when compared to the high setup costs and coverage limitations of radar systems, or the weather and lighting vulnerabilities of cameras. Furthermore the system can detect vehicles on the road as important supplemental information for search and rescue operations, and thus the authorities can be alerted, thereby playing a vital role in urgent rescue efforts. Full article

Device simulation plays a crucial role in complementing experimental device characterisation by enabling deeper understanding of internal physical processes. However, for simulations to be trusted, experimental validation is essential to confirm the accuracy of the conclusions drawn. In the framework of semiconductor detector characterisation, one powerful tool for such validation is the Two Photon Absorption-Transient Current Technique (TPA-TCT), which allows for highly precise, three-dimensional spatially-resolved characterisation of semiconductor detectors. In this work, the TCAD framework Synopsys Sentaurus is used to simulate depth-resolved TPA-TCT data for both p-type pad detectors (PINs) and Low Gain Avalanche Detectors (LGADs). The simulated data are compared against experimentally measured TPA-TCT results. Through this comparison, it is demonstrated that TCAD simulations can reproduce the TPA-TCT measurements, providing valuable insights into the TPA-TCT itself. Another significant outcome of this study is the successful simulation of the gain reduction mechanism, which can be observed in LGADs with increasing densities of excess charge carriers. This effect is demonstrated in an p-type LGAD with a thickness of approximately 286 µm. The results confirm the ability of TCAD to model the complex interaction between carrier dynamics and device gain. Full article

The development and calibration of a measurement system designed for assessing the performance of the avalanche photodiodes (APDs) used in the Compton scattering polarimeter of the CUSP project is discussed in this work. The designed system is able to characterize the APD gain $G_{APD}$ and energy resolution across a wide range of temperatures T (from −20 °C to +60 °C) and bias voltages $V_{bias}$ (from 260 V to 410 V). The primary goal was to experimentally determine the $G_{APD}$ dependence on the T and $V_{bias}$ in order to establish a strategy for stabilizing $G_{APD}$ by compensating for T fluctuations, acting on $V_{bias}$. The results demonstrate the system capability to accurately characterize APD behavior and develop feedback mechanisms to ensure its stable operation. This work provides a robust framework for calibrating APDs for space environments. It is essential for the successful implementation of spaceborne polarimeters such as the Compton scattering polarimeter foreseen aboard the CUbeSat Solar Polarimeter (CUSP) mission under development to perform solar flare X-ray polarimetry. Full article

Low-Gain Avalanche Diodes (LGADs) are critical sensors for the ATLAS and CMS timing detectors at the High Luminosity Large Hadron Collider (HL-LHC), offering enhanced timing resolution with gain factors of 20 to 50. However, their radiation tolerance is hindered by the Acceptor Removal Phenomenon (ARP), which deactivates boron in the gain layer, reducing gain below the threshold for accurate timing. This study investigates the radiation hardness of thin, carbon-doped LGAD sensors developed by Brookhaven National Laboratory (BNL) to address ARP-induced limitations. Active dopant profiles in the gain layer, junction, and bulk were measured using a Spreading Resistance Probe (SRP) profilometer, and the effects of annealing and neutron irradiation at fluences of 3 × 10¹⁴, 1 × 10¹⁵, and 3 × 10¹⁵ neq/cm² (1 MeV equivalent) were analyzed. Low carbon dose rates showed minimal improvement due to enhanced deactivation, while higher doses improved radiation hardness, demonstrating a non-linear dose–response relationship. These findings highlight the potential of optimizing gain layers with high carbon doses and low-diffusion boron to extend LGAD lifetimes in high-radiation environments. Future research will refine carbon implantation strategies and explore alternative approaches to further enhance the radiation hardness of LGADs. Full article

The millimeter-wave wireless transmission system is widely regarded as a promising solution for applications of future 6G communication. This paper presents an experimental comparison between all-optical and all-electric receivers for millimeter-wave communication systems over a 15 m wireless link and demonstrates 200 m and 2 km real-time uncompressed HD video transmission using an all-optical transceiver at 100 GHz. The systems leverage photonics-assisted heterodyne beating techniques at the transmitter, while the receivers employ either an avalanche photodiode (APD)-based all-optical approach or an envelope detection-based all-electric approach. Experimental results show that the all-optical transceiver supports significantly higher transmission rates, achieving error-free transmission at up to 11.318 Gbps over a 200 m wireless link without clock recovery, compared to the all-electric receiver, which is limited to only 3.125 Gbps error-free 15 m transmission. This work proves that the proposed system based on the all-optical receiver is more promising for supporting future 6G scenarios requiring ultra-wideband, high capacity, and wide coverage high-speed wireless communications. Full article