Search Results (45)

Catastrophic mass flows originating from the high mountain cryosphere often cause cascading hazards. With increasing human activities in the alpine region and the sensitivity of the cryosphere to climate warming, cryospheric hazards are becoming more frequent in the mountain regions. Monitoring the evolution and impact of the glaciers and ice-rock avalanches and hazard consequences in the mountain regions is crucial to understand nature and drivers of mass flow process in order to prevent and mitigate potential hazard risks. In this study, the glacier and ice-rock avalanches that occurred in the Tibetan Plateau (TP) were investigated based on the Sentinel-2 satellite data and in situ observations, and the main driving forces and impacts on the regional environment, landscape, and geomorphological conditions were also analyzed. The results showed that the avalanche deposit of Arutso glacier No. 53 completely melted away in 2 years, while the deposit of Arutso glacier No. 50 melted in 7 years. Four large-scale ice-rock avalanches in the Sedongpu basin not only had significant impacts on the river flow, landscape, and geomorphologic shape in the basin, but also caused serious disasters in the region and beyond. These glacier and ice-rock avalanches were caused by temperature anomaly, heavy precipitation, climate warming, and seismic activity, etc., which act on the specific glacier properties in the high mountain regions. The study highlights scientific advances should support and benefit the remote and vulnerable mountain communities to make mountain regions safer. Full article

Flexible upconversion (UC) devices, owing to their unique combination of high–efficiency optical energy conversion and mechanical flexibility, have attracted increasing attention in the fields of optoelectronics, wearable devices, flexible displays, and biomedical applications. However, significant challenges remain in balancing optical performance, mechanical adaptability, long–term stability, and scalable fabrication, which limit their practical deployment. This review systematically introduces five representative upconversion mechanisms—excited–state absorption (ESA), energy transfer upconversion (ETU), energy migration upconversion (EMU), triplet–triplet annihilation upconversion (TTA–UC), and photon avalanche (PA)—highlighting their energy conversion principles, performance characteristics, and applicable scenarios. The article further delves into the flexible transition of upconversion devices, detailing not only the evolution of the luminescent layer from bulk crystals and nanoparticles to polymer composites and hybrid systems, but also the optimization of electrodes from rigid metal films to metal grids, carbon–based materials, and stretchable polymers. These developments significantly enhance the stability and reliability of flexible upconversion devices under bending, stretching, and complex mechanical deformation. Finally, emerging research directions are outlined, including multi–mechanism synergistic design, precise nanostructure engineering, interface optimization, and the construction of high–performance composite systems, emphasizing the broad potential of flexible UC devices in flexible displays, wearable health monitoring, solar energy harvesting, flexible optical communications, and biomedical photonic applications. This work provides critical insights for the design and application of high–performance flexible optoelectronic devices. Full article

In this paper, climate evolution is revisited in terms of the theory of dynamical systems, which has been successfully used in predictions of catastrophic events such as avalanches, landslides, or economy and civilization collapses. Such tipping events are announced by warning signs, named “pre-critical fluctuations” or “critical softening”, allowing a tipping date estimate through well-known equations. In the case of climate, the warning signs are extreme events of increasing amplitudes. We show that in such a context, numerical simulations can hardly predict incoming tipping points, due to a divergence in computational time at the singularity. Based on the dynamical systems theory, a recent publication from Copenhagen University shows that the Atlantic Meridional Oceanic Circulation is likely to collapse well before the end of the century, triggering switchover cascades, eventually culminating in global climate tipping. Paleoclimatic studies also show that tipping events occurred in the past, particularly during the PETM period 56 Myrs ago. If this was to happen now, average global temperatures might reach an unbearable level, with a deadline much closer than expected. This extreme emergency has major consequences on the implementation times of sustainability policies and in energy production, mobility, agriculture, housing, etc., that absolutely must be operational on time. Full article

Under the complex geological structural stress of the Western Himalayan syntaxis, the widespread distribution of hard and brittle rocks (such as sandstone and limestone) makes them prone to the formation of conjugate joints, also known as X-joints. These joints create weak structural planes in the slope rock mass, and when combined with weak interlayers within the slope, they result in a complex dynamic response and hazard situation in this region, which is further exacerbated by frequent seismic activity. This poses a serious threat to the planning, construction, and safe operation of the Belt and Road Initiative. To study the slope vibration response and instability mechanisms under these conditions, we conducted a shaking table test using the Iymek avalanche as a case study and performed Hilbert–Huang Transform (HHT) analysis. We also compared the results of the shaking table test on slope models without X-joints but containing weak interlayers. The findings show that the presence of X-joints leads to an earlier onset of plastic failure in the slope. During the failure development, X-joints cause stress concentration and the diversification of stress redistribution paths, delaying energy release. Ultimately, the avalanche failure mode in the X-joint slopes is more dispersed compared to the landslide failure mode in the model without X-joints. At the toe of the slope beneath the weak interlayer, low-frequency seismic waves can cause a significant amplification of acceleration, and the weak interlayer is often the shear outlets of the slope. These findings provide new insights into the seismic failure evolution of jointed slopes with weak interlayers and offer practical references for seismic hazard mitigation in mountainous infrastructure. Full article

Spectroscopic observations of Earth-like exoplanets and ultra-faint galaxies–top scientific priorities for the coming decades–involve measuring broadband signals at rates of only a few photons per square meter per hour. This imposes exceptional requirements on the detector performance, necessitating dark currents below 1 e⁻/pixel/kilo second, read noise under 1 e⁻/pixel/frame, and the ability to handle large-format arrays–capabilities that are not yet met by most existing infrared detectors. In addition, spaceborne LiDAR systems require photodetectors with exceptional sensitivity, compact size, low power consumption, and multi-channel capability to facilitate long-range range finding, topographic mapping, and active spectroscopy without increasing the instrument burden. MCT Avalanche photodiodes arrays offer high internal gain, pixelation, and photon-counting performance across SW to MW wavelengths needed for multi-beam and multi-wavelength measurements, marking them as a critical enabling technology for next-generation planetary and Earth science LiDAR missions. This work reports the latest progress in developing Hg_1−xCd_xTe linear-mode e-APDs at premier industrial research institutions, including relevant experimental data, simulations and major project planning. Related studies are summarized to demonstrate the practical and iterative approach for device fabrication, which have a transformative impact on the evolution of this discipline. Full article

Avalanches occur frequently in mountainous areas and pose significant threats to roads and infrastructure. Clarifying how terrain conditions influence avalanche initiation and movement is critical to improving hazard assessment and response strategies. This study focused on a wet-snow slab avalanche that occurred on 26 March 2024, in the Simutas region of the northern Tianshan Mountains, Xinjiang, China. The authors combined remote sensing imagery, high-resolution meteorological station observations, field investigations, and numerical simulations (RAMMS::Avalanche) to analyze the avalanche initiation mechanism, dynamic behavior, and path recurrence characteristics. Results indicated that persistent heavy snowfall, rapid warming, and substantial daily temperature fluctuations triggered this avalanche. The predominant southeasterly (SE) winds and the northwest-facing (NW) shaded slopes created favorable leeward snow deposition conditions, increasing snowpack instability. High-resolution meteorological observations provided detailed wind, temperature, and precipitation data near the avalanche release zone, clearly capturing snowpack evolution and meteorological conditions before avalanche initiation. Numerical simulations showed a maximum avalanche flow velocity of 19.22 m/s, maximum flow depth of 12.42 m, and peak dynamic pressure of 129.3 kPa. The simulated avalanche deposition area and depth closely matched field observations. Multi-temporal remote sensing images indicated that avalanche paths in this area remained spatially consistent over time, with recurrence intervals of approximately 2–3 years. The findings highlight the combined role of local meteorological processes and terrain factors in controlling avalanche initiation and dynamics. This research confirmed the effectiveness of integrating remote sensing data, high-resolution meteorological observations, and dynamic modeling, providing scientific evidence for avalanche risk assessment and disaster mitigation in mountain regions. Full article

Laser ranging technology holds a key position in the military, aerospace, and industrial fields due to its high precision and non-contact measurement characteristics. As a core component, the performance of the photon detector directly determines the ranging accuracy and range. This paper systematically reviews the technological development of photonic detectors for laser ranging, with a focus on analyzing the working principles and performance differences of traditional photodiodes [PN (P-N junction photodiode), PIN (P-intrinsic-N photodiode), and APD (avalanche photodiode)] (such as the high-frequency response characteristics of PIN and the internal gain mechanism of APD), as well as their applications in short- and medium-range scenarios. Additionally, this paper discusses the unique advantages of special structures such as transmitting junction-type and Schottky-type detectors in applications like ultraviolet light detection. This article focuses on photon counting technology, reviewing the technological evolution of photomultiplier tubes (PMTs), single-photon avalanche diodes (SPADs), and superconducting nanowire single-photon detectors (SNSPDs). PMT achieves single-photon detection based on the external photoelectric effect but is limited by volume and anti-interference capability. SPAD achieves sub-decimeter accuracy in 100 km lidars through Geiger mode avalanche doubling, but it faces challenges in dark counting and temperature control. SNSPD, relying on the characteristics of superconducting materials, achieves a detection efficiency of 95% and a dark count rate of less than 1 cps in the 1550 nm band. It has been successfully applied in cutting-edge fields such as 3000 km satellite ranging (with an accuracy of 8 mm) and has broken through the near-infrared bottleneck. This study compares the differences among various detectors in core indicators such as ranging error and spectral response, and looks forward to the future technical paths aimed at improving the resolution of photon numbers and expanding the full-spectrum detection capabilities. It points out that the new generation of detectors represented by SNSPD, through material and process innovations, is promoting laser ranging to leap towards longer distances, higher precision, and wider spectral bands. It has significant application potential in fields such as space debris monitoring. Full article

Southeast Tibet is characterized by extensive alpine glaciers and deep valleys, making it highly prone to cryospheric disasters such as avalanches, ice/ice–rock avalanches, glacial lake outburst floods, debris flows, and barrier lakes, which pose severe threats to infrastructure and human safety. Understanding how cryospheric disasters respond to climate warming remains a critical challenge. Using 3.3 km resolution meteorological downscaling data, this study analyzes the spatiotemporal evolution of multiple climate indicators from 1979 to 2022 and assesses their impacts on cryospheric disaster occurrence. The results reveal a significant warming trend across Southeast Tibet, with faster warming in glacier-covered regions. Precipitation generally decreases, though the semi-arid northwest experiences localized increases. Snowfall declines, with the steepest decrease observed around the lower reaches of the Yarlung Zangbo River. In the moisture corridor of the lower reaches of the Yarlung Zangbo River, warming intensifies freeze–thaw cycles, combined with high baseline extreme daily precipitation, which increases the likelihood of glacial disaster chains. In northwestern Southeast Tibet, accelerated glacier melting due to warming, coupled with increasing extreme precipitation, heightens glacial disaster probabilities. While long-term snowfall decline may reduce avalanches, high baseline extreme snowfall suggests short-term threats remain. Finally, this study establishes meteorological indicators for predicting changes in cryospheric disaster risks under climate change. 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

Research on the scraping effects of rock–ice avalanches remains relatively limited. This study investigates the evolution of rock–ice avalanches with varying ice content and initial accumulation forms during motion, scraping, and deposition using laboratory physical model experiments. Changes in pre- scraping velocity, scraping length, scraping depth, maximum deposition length, and deposition thickness were analyzed as functions of ice content. The analysis revealed the influence of ice content and initial accumulation on scraping effects, as well as on motion and deposition characteristics. The experimental results indicate that, compared to typical debris flows (without ice), the presence of ice significantly enhances the mobility, deposition features, and scraping effects of rock–ice avalanches. Through analysis, it is shown that the low friction of ice debris enhances the kinetic energy of ice-rock debris flows, thereby increasing the energy required for scraping. Full article

Rockfall is a typical successive hazard with a high incidence rate following primary geological disasters such as landslides, rock avalanches, and debris flows. The lateral dispersion of rockfall is significantly affected by the loose granular cushion layer deposited on slopes. This paper aims to develop a quick estimation model for this effect based on the 3D-DEM (discrete element method) numerical simulations. The DEM model employs particles with different bonding properties to create a modeling double-layer granular slope. The present model is also verified by comparing the data from the antecedent large-scale outdoor rockfall experiment with the numerical simulations. Accordingly, the influences of four factors: the initial horizontal release velocity, the size of the rock mass, the granular cushion thickness, and the slope angle on the lateral dispersion of the rockfall trajectory are analyzed, and the underlying physical mechanism is discussed thoroughly. Ultimately, we identify a nondimensional parameter that demonstrates a strong correlation with the evolution of the lateral dispersion ratio of the rockfall trajectory. Based on this insight, we propose an estimation model for predicting the lateral dispersion of the rockfall trajectory. This model can assist engineering and construction personnel in rapidly determining the lateral dispersion range of the rockfall. Full article

Traditional cryptographic methods often need complex designs that require substantial memory and battery power, rendering them unsuitable for small handheld devices. As the prevalence of these devices continues to rise, there is a pressing need to develop smart, memory-efficient cryptographic protocols that provide both high speed and robust security. Current solutions, primarily dependent on dynamic permutations, fall short in terms of encryption and decryption speeds, the cryptographic strength, and the memory efficiency. Consequently, the evolution of lightweight cryptographic algorithms incorporating randomised substitution properties is imperative to meet the stringent security demands of handheld devices effectively. In this paper, we present an advanced design of lightweight block ciphers that enhances traditional dynamic permutations with innovative randomised substitutions. This design utilises straightforward randomized encryption methods such as XOR, nibble swap, count ones, and left shift. The cryptographic robustness of our proposed block cipher has been rigorously tested through several standardised statistical tests, as recommended by the National Institute of Standards and Technology (NIST). These evaluations confirm that our algorithm maintains strong cryptographic properties with randomised substitutions and outperforms existing models in several key aspects. Moreover, comparative assessments reveal that our algorithm achieves a throughput of 853.31 Kbps while consuming only 1510 bytes of memory and demonstrating over 60% avalanche properties, significantly outperforming other solutions in terms of CPU utilisation and memory consumption. These results underscore the efficacy of our approach in fulfilling the advanced security requirements of modern handheld devices. Full article

Under atmospheric pressure, partial discharge initiated by free metallic particles has consistently been a significant factor leading to failures in high-voltage electrical equipment. Simulating the propagation of negative streamer discharge in N₂/O₂ mixtures contributes to a better understanding of the occurrence and evolution of partial discharge, optimizing the insulation performance of electrical equipment. In this study, a two-dimensional plasma fluid dynamics model coupled with the current module was employed to simulate the evolution process of negative streamer discharge caused by one free metallic particle under a suspended potential at 220 kV applied voltage conditions. Simulation results indicated that the discharge process could be divided into two distinct stages: In the first stage, the electron ionization region detached from the electrode surface and propagated independently. During this stage, the corona discharge on the negative electrode surface provided seed electrons crucial for the subsequent development of negative corona discharge. The applied electric field played a dominant role in the propagation of the electron region, especially in the electron avalanche region. In the second stage, space charge gradually took over, causing distortion in the spatial field, particularly generating a substantial electric field gradient near the negative electrode surface, forming an ionization pattern dominated by ionization near the negative electrode surface. These simulation results contribute to a comprehensive understanding of the complex dynamic process of negative streamer discharge initiated by free metallic particles, providing essential insights for optimizing the design of electrical equipment and insulation systems. Full article

Supra-glacial debris cover is important for the control of surface ice melt and glacier retreat in mountain regions. Despite the progress in techniques based on various satellite imagery, the mapping of debris-covered glacier boundaries over large regions remains a challenging task. Previous studies of the debris-covered glaciers in the Greater Caucasus have only focused on limited areas. In this study, using the Sentinel 1–2 imagery (2020), DebCovG-carto toolbox, and existing glacier inventory (2020), we produced the first detailed assessment of supra-glacial debris cover for individual glaciers in the entire Greater Caucasus. Our study shows that in 2020, 10.3 ± 5.6% of the glacier surface in this mountain region was covered by debris. A comparison of sub-regions such as the Elbrus Massif and other individual glaciers from the central Greater Caucasus shows an increasing trend of supra-glacial debris cover from 2014 to 2020. The total area of supra-glacial debris cover expanded from ~4.6% to ~5.8% for Elbrus and from ~9.5% to ~13.9% for the glaciers of the central Greater Caucasus during the same period. Supra-glacial debris cover also expanded upward on these glaciers between 2014 and 2020. A recent increase in rock-ice avalanche activity in combination with increased air temperature and decreased precipitation in the Greater Caucasus may be responsible for this upward migration and expanded area of supra-glacial debris cover. This study provides valuable insights into the spatial distribution, temporal evolution, and factors influencing supra-glacial debris cover in the Greater Caucasus. The findings contribute to our understanding of glacier dynamics and highlight the importance of continuous monitoring and assessment of supra-glacial debris cover in the context of climate change and glacier retreat. We recommend using the DebCovG-carto toolbox for regional assessment of supra-glacial debris coverage in other mountain regions as well. Full article

A methodology to study statistical properties of anomalous transport in fusion plasma is investigated. Three time traces generated by the full-f gyrokinetic code GKNET are analyzed for this purpose. The time traces consist of heat flux as a function of the radial position, which is studied in a novel manner using statistical methods. The simulation data exhibit transport processes with both medium and long correlation length along the radius. A typical example of a phenomenon with long correlation length is avalanches. In order to investigate the evolution of the turbulent state, two basic configurations are studied, one flux-driven and one gradient-driven with decaying turbulence. The information length concept in tandem with Boltzmann–Gibbs and Tsallis entropy is used in the investigation. It is found that the dynamical states in both flux-driven and gradient-driven cases are surprisingly similar, but the Tsallis entropy reveals differences between them. This indicates that the types of probability distribution function are nevertheless quite different since the higher moments are significantly different. Full article