Search Results (202)

As a critical infrastructure, the transportation network impacts health, safety, comfort, and the economy, making it highly vulnerable to disruptions that significantly affect social and economic well-being. To maintain optimal service during such disruptions, the critical links that are vulnerable to disruptions must be identified and their impact on network performance must be understood. This study proposes a method for identifying network vulnerabilities by targeting critical links based on topological parameters, assessing worst-case scenarios under severe conditions. These parameters serve as proxies for performance and are utilized to generate critical-link attacks to assess the network vulnerability. In addition, this study proposes a straightforward and simplistic modeling framework using topological parameters to assess the impact of such attacks on traffic flow changes. To characterize network performance and traffic volume changes under critical-link attacks, this study utilizes the complementary cumulative distribution function (CCDF), which highlights the upper tail of the distribution where extreme or rare events occur. The proposed method was applied to a real network in the Colombo Municipal Council (CMC) area in Sri Lanka. The findings of this study will help us understand the impact of critical-link attacks on transportation network performance and traffic flow and develop proactive policies to address vulnerabilities and improve overall network performance. Full article

Background/Objectives: Composite hemangioendothelioma (CHE) is a rare vascular endothelial tumor with borderline malignancy. This study presents a case of CHE and an updated systematic review of previously reported cases, providing insights into recurrence patterns and survival outcomes. Methods: A comprehensive electronic search was conducted across PubMed, Scopus, the Cochrane Library, and Web of Science up to 31 December 2024, to identify eligible case reports. Kaplan–Meier curves were used to estimate event-free survival. Results: We report a 61-year-old man with a splenic lesion associated with weight loss and abdominal pain persisting for 1 year. Intraoperative findings revealed an enlarged spleen and multiple hepatic deposits. Splenectomy and liver biopsy revealed a well-demarcated, nodular tumor measuring 160 × 145 × 100 mm, with histological and immunohistochemical findings consistent with CHE, complicated by hepatic metastasis. Of 405 potentially eligible studies, 59 were included in the review, covering cases from 2000 to 2024, with a peak in 2020 and 2023. The median age of patients was 42 years, with the most common tumor sites being the lower extremities (30.48%), followed by the face, head, and neck (20.95%), and upper extremities (18.1%). Surgical intervention was the most common treatment (60.95%). Recurrence-free survival was observed in 42.86% of cases, while 15.24% experienced recurrence with or without metastasis. Two patients (1.90%) died from the disease. The median recurrence-free survival was 48 months (95% CI: 7.3–88.7). Conclusions: CHE exhibits significant morphological variation and can mimic other vascular tumors. Accurate diagnosis is crucial for proper prognosis and avoiding overtreatment due to misdiagnosis as more aggressive neoplasms. Patients with high-risk CHE should undergo closer surveillance to ensure timely detection of progression. Full article

Imaging Atmospheric Cherenkov Telescopes (IACTs) have revolutionized our understanding of the universe at very high energies (VHEs), enabling groundbreaking discoveries of extreme astrophysical phenomena. These instruments capture the brief flashes of Cherenkov light produced when VHE particles interact with Earth’s atmosphere, providing unique insights into cosmic accelerators and high-energy radiation sources. A fundamental challenge in IACT observations lies in distinguishing the rare gamma-ray signals from an overwhelming background of cosmic-ray events. For every gamma-ray photon detected from even the brightest sources, thousands of cosmic-ray-induced atmospheric showers trigger the telescopes. This profound signal-to-background imbalance necessitates sophisticated discrimination techniques that can effectively isolate genuine gamma-ray events while maintaining high rejection efficiency for cosmic-ray backgrounds. The most common method involves the parametrization of the morphological feature of the shower images. However, we know that gamma-ray and hadron showers also differ in their time evolution. Here, we describe how the pixel time tags (i.e., the record of when each camera pixel is lit up by the incoming shower) can help in the discrimination between photonic and hadronic showers, with a focus on the ASTRI Mini-Array Cherenkov Event Reconstruction. Our methodology employs a Random Forest classifier with optimized hyperparameters, trained on a balanced dataset of gamma and hadron events. The model incorporates feature importance analysis to select the most discriminating temporal parameters from a comprehensive set of time-based features. This machine learning approach enables effective integration of both morphological and temporal information, resulting in improved classification performance, especially at lower energies. Full article

This study delves into the once-in-a-century extreme precipitation events in the northern region of the Pearl River Basin during the 2022 Dragon Boat Festival period. Through a comprehensive analysis spanning various temporal scales, from synoptic-scale systems to subseasonal oscillations, including the rare triple-peaked La Niña phenomenon, we illuminate the intricate interactions among these factors and their impact on extreme precipitation events. Specifically, we present a conceptual model of multiscale interaction systems contributing to extreme precipitation in the BeiJiang Basin. Our findings reveal that, during the 2022 Dragon Boat Festival period, precipitation in the BeiJiang Basin exhibited characteristics across multiple time scales, with the synoptic-scale environment proving highly conducive. Systems such as the South Asian High, Western Pacific Subtropical High, and South China Sea summer monsoon were identified as the direct influencing factors of precipitation. Importantly, our study highlight the pivotal role of subseasonal oscillation propagation stagnation in extreme precipitation in the BeiJiang Basin, with synoptic-scale systems playing a contributing role. We emphasize the indirect influence of ENSO signals, regulating not only monsoons but also the propagation of subseasonal oscillations. The interplay of these factors across different temporal scales significantly impacts flood hazards. Overall, our study significantly enhances the understanding of mechanisms driving extreme precipitation events in the Pearl River Basin, with profound implications for water resource management and disaster prevention. Full article

Climate change has affected forest ecosystems across the world over the past century. However, its impact is particularly high in the Himalayas due to increasing temperatures, extreme precipitation events, and regional droughts. In this context, a review of the current stage of research was deemed necessary to understand the adaptation of a key conifer species to climate variability in the Central Himalayas. Hence, we conducted a systematic review of published peer-reviewed journal articles addressing the growth performance of Abies spectabilis (D. Don) Spach in the Central Himalayas. From this review, three main patterns of climate response have emerged: a positive correlation of radial tree growth with temperature of the current and previous growing seasons, tree growth limitation by winter temperature, and by temperature or moisture in the pre-monsoon season. Overall, results indicate an elevation-dependent temperature sensitivity, a crucial role of moisture availability, and seasonal shifts in climate–growth relationships, reflecting the species’ adaptability to changing climate conditions. Our review revealed that studies on elevation-dependent adaptation of wood anatomical traits by A. spectabilis are still rare. The tree-ring growth of this species shows a complex response to climate variability, with increasing as well as decreasing growth trends across its distribution range. Full article

Low-dose oral minoxidil (LDOM) has emerged as a widely used off-label treatment for different types of alopecia, showing a favorable safety profile and effectiveness. Despite its growing use, it is essential to understand the possible associated adverse events (AEs) and their appropriate management to optimize this therapy. The aim of this article was to comprehensively review the AEs of LDOM treatment, describing their frequency, risk factors, affected anatomical sites, and management strategies. A search in the PubMed and EMBASE databases was performed for studies published before 31 December 2024, reporting the treatment of any type of hair loss with oral minoxidil. The most frequent AE is hypertrichosis, occurring in approximately 15% of patients, with a higher incidence in women and patients with higher doses. Fluid retention affects 1.3–10% of patients, particularly women, and typically occurs within 1–3 months of treatment. Other cardiovascular AEs, such as tachycardia or dizziness, occur in fewer than 5% of cases and are usually mild and transient. Severe AEs, including pericardial effusion, are extremely rare and often linked to compounding errors comprising an excessive dose. Management strategies include dose reduction, pharmacological interventions like diuretics for edema, and lifestyle measures such as sodium restriction. In most cases, AEs resolve without the need for treatment discontinuation. The favorable safety profile of LDOM makes it a valuable therapeutic option for alopecia, though careful patient selection, dose titration, and monitoring are essential to minimize risks. Full article

Gas embolism is a rare but life-threatening process characterized by the presence of gas bubbles in the venous or arterial systems. These bubbles, if sufficiently large or numerous, can block the delivery of oxygen to critical organs, in particular the brain, and subsequently they can trigger a cascade of adverse biochemical reactions with severe medical outcomes. Despite its critical nature, gas embolism remains poorly understood, necessitating extensive investigation, particularly regarding its manifestations in the human body and its modulation by various biological conditions. However, given its elusive nature, as well as potential lethality, gas embolism is extremely difficult to study in vivo, and nearly impossible to be the subject of clinical trials. To this end, we developed a microfluidic device designed to study in vitro the impact of blood properties and vascular geometries on the formation and evolution of gas bubbles. The system features a biomimetic vascular channel surrounded by two pressure chambers, which induce the genesis of bubbles under varying circumstances. The bubble parameters were correlated with different input parameters, i.e., channel widths, wall thicknesses, viscosities of the artificial blood, and pressure levels. Smaller channel widths and higher equivalent hematocrit concentrations in synthetic blood solutions increased the nucleation density and bubble generation frequencies. Small channel widths were also more prone to bubble formation, with implications for the vulnerability of vascular walls, leading to increased risks of damage or compromise to the integrity of the blood vessels. Larger channel widths, along with higher equivalent hematocrit concentrations, translated into larger bubble volumes and decreased bubble velocities, leading to an increased risk of bubble immobilization within the blood vessels. This biomimetic approach provides insights into the impact of patient history and biological factors on the incidence and progression of gas embolism. Medical conditions, such as anemia, along with anatomical features related to age and sex—such as smaller blood vessels in women and children or larger vascular widths in adult men—affect the susceptibility to the initiation and progression of gas embolism, explored here in vitro through the development of a controlled, physiological-like environment. The analysis of the videos that recorded gas embolism events in vitro for systems where pressure is applied laterally on the microvasculature with thin walls, i.e., 50 μm or less, suggests that the mechanism of gas transfer for the pressure area to the blood is based on percolation, rather than diffusion. These findings highlight the importance of personalized approaches in the management and prevention of gas embolism. Full article

The Sufi dimension is usually underestimated within the debate on Islam and modernity as well as in discussions about resistance to Western ideas within contemporary Islamic culture. In contrast, Islamic modernism is often defined as the result of a coherent process of modernization and reform, which stems from cultural confrontation with European Western thought and is accelerated by certain key historical events between the 19th and 20th centuries. This modernization, in the last decades of the 19th century, led to the emergence of a cultural Arab renaissance, known as naḥḍa, and a religious reform, iṣlāḥ; both are strongly influenced by modern Western thought. At the opposite end of this current of thought is the perspective of Sīdī Salāma al-Rāḍī, who denounced the damage that the scientistic view of Western origin was doing to Egyptian culture. His most important work, from this point of view, is an untranslated book entitled al-Insāniyya (“Humanity”), in which the author criticizes, from a traditional perspective, the biochemical, medical, evolutionary, and spiritualist conceptions of the physical, psychic, and spiritual constitution of the human being. The general tenor of this work is highly critical of modern Western civilization and represents an attempt to propose a traditional Islamic viewpoint, which is of extreme interest due to its uniqueness. Al-Insāniyya highlights a topic rarely addressed in academic literature on early twentieth-century Sufism: the involvement of a Sufi master in the dialogue between Western modernity and the Sufi Islamic tradition. This reveals a historical framework in which the Sufis of Cairo’s cosmopolitan environment, while mastering scientistic themes, reject modernity in favor of a classical Sufi vision of evolution understood as an initiatory path of spiritual perfection. Full article

Has the mean-variance framework become obsolete? In this paper, we replace traditional variance–covariance methods of portfolio optimisation with relative Tsallis entropy and mutual information measures. Its goal is to enhance risk management and diversification in complicated finance ecosystems. We utilize the S&P 500 and Bitwise 10 cryptocurrency indices’ daily returns (2019–2024 data) and conduct our analysis to the year 2020 under extreme shocks. Many models were trained with different configurations, like mean-variance (MV), mean-entropy (ME), and mean-mutual information (MI) traders and their corresponding variants, using Sharpe’s ratio, Jensen’s alpha, and entropy value of risk (EVAR). The findings indicate that entropic models outperform conventional models in terms of diversification and, especially, extreme risk management. Because the appropriate normalization conditions often fail to be satisfied, we can informally see that after a recalibration of the effective frontier, we obtain from EVAR an accumulated resilience aspect to these rare events while also observing the great potential of entropy-based models to replicate non-linear dependencies between assets. The results show that models combining entropy and mutual information optimise the gain–loss ratio (GLR), providing stable diversification and improved risk management, while maximising returns in complex and volatile market environments. Full article

In the Atlantic region of northern Spain, heat extremes were historically rare, but in recent decades, they have become more intense and persistent. This article characterizes heat events in Asturias (NW Spain) between 2001 and 2023, focusing on their frequency, intensity, and duration, as well as their temporal trends. Additionally, it explores the synoptic patterns linked to these episodes to enhance understanding of their occurrence and evolution over the study period. The research is based on official meteorological records, and it distinguishes between officially declared heatwaves (DHs) and significant heat events (SHEs) identified through regional press reports. This methodology enables the study to capture a broader spectrum of heat-related impacts. During the study period, 17 episodes were documented (11 DHs and 6 SHEs). The frequency, intensity, and duration of heat events have significantly increased, particularly since 2016, standing the last two years (2022 and 2023). Both DHs and SHEs have progressively shifted toward the early and late periods of the astronomical summer, with some events occurring during spring and autumn in the second half of the study period (years 2017, 2022, and 2023). Three atmospheric patterns have been identified as responsible for extreme heat episodes; Type 1 (warm tropical continental air masses, combined with atmospheric stability) is responsible for 10 of the episodes. Furthermore, urban areas and main river valleys were the most affected areas, while coastal regions remained largely unaffected. This research aims to contribute to a broader understanding of how heatwaves are evolving in a temperate climate area under the influence of global warming, providing insights to inform and improve adaptation strategies for mitigating their impacts. Full article

Puya raimondii Harms is a charismatic species discovered in the Cordillera Blanca (now Huascarán National Park, Peru) in 1867 by the great Italian-born Peruvian geographer and naturalist Antonio Raimondi. The importance of this plant is due to its imposing size, the rare and extreme ecosystem that depends on it, and the fact that it is linked to the name Antonio Raimondi. Four studies on its genetic diversity revealed a range of patterns, with a fixation index of 0.740 as weighted mean and gene flow as low as 0.02–0.03. In fact, the vast majority of the total genetic variation was documented between populations, with very low genetic variation found within populations (weighted mean genetic diversity as low as Hs = 0.072 and mean genetic similarity very high, ranging from 96% up to 99%). We hypothesize that the narrow genetic base of P. raimondii populations may be due to a combination of factors: (i) an inbreeding-based reproductive strategy (i.e., mating between individuals related by common ancestry), which leads to homozygosity and genomic uniformity; (ii) strong environmental selective pressure (e.g., day–night temperature excursion, long dry period, etc.), which favors only the highest fitness individual genotypes; and (iii) a long life cycle, which hampers recombination events and reduces genetic diversity. Overall, these factors suggest that P. raimondii is a genetically fragile, fragmented, and endangered species. Full article

Weather forecasting, a vital task for agriculture, transportation, energy, etc., has evolved significantly over the years. Comprehensive surveys play a crucial role in synthesizing knowledge, identifying trends, and addressing emerging challenges in this dynamic field. In this survey, we critically examines machine learning (ML)-based weather forecasting methods, which demonstrate exceptional capability in handling complex, high-dimensional datasets and leveraging large volumes of historical and real-time data, enabling the identification of subtle patterns and relationships among weather variables. Research on specific tasks such as global weather forecasting, downscaling, extreme weather prediction, and how to combine machine learning methods with physical principles are very active in the current field. However, several unresolved or challenging issues remain, including the interpretability of models and the ability to predict rare weather events. By identifying these gaps, this research provides a roadmap for advancing machine learning-based weather forecasting techniques to complement and enhance weather prediction results. Full article

As climate change intensifies, extreme drought events have become more frequent, and investigating the mechanisms of watershed drought has become highly significant for basin water resource management. This study utilizes the WRF-Hydro model in conjunction with standardized drought indices, including the standardized precipitation index (SPI), standardized soil moisture index (SSMI), and Standardized Streamflow Index (SSFI), to comprehensively investigate the spatiotemporal characteristics of drought in the Huai River Basin, China, from 2012 to 2018. The simulation performance of the WRF-Hydro model was evaluated by comparing model outputs with reanalysis data at the regional scale and site observational data at the site scale, respectively. Our results demonstrate that the model showed a correlation coefficient of 0.74, a bias of −0.29, and a root mean square error of 2.66% when compared with reanalysis data in the 0–10 cm soil layer. Against the six observational sites, the model achieved a maximum correlation coefficient of 0.81, a minimum bias of −0.54, and a minimum root mean square error of 3.12%. The simulation results at both regional and site scales demonstrate that the model achieves high accuracy in simulating soil moisture in this basin. The analysis of SPI, SSMI, and SSFI from 2012 to 2018 shows that the summer months rarely experience drought, and droughts predominantly occurred in December, January, and February in the Huai River Basin. Moreover, we found that the drought characteristics in this basin have significant seasonal and interannual variability and spatial heterogeneity. On the one hand, the middle and southern parts of the basin experience more frequent and severe agricultural droughts compared to the northern regions. On the other hand, we identified a time–lag relationship among meteorological, agricultural, and hydrological droughts, uncovering interactions and propagation mechanisms across different drought types in this basin. Finally, we concluded that the WRF-Hydro model can provide highly accurate soil moisture simulation results and can be used to assess the spatiotemporal variations in regional drought events and the propagation mechanisms between different types of droughts. Full article

Gem-quality garnets, with their high closure temperature (750–800 °C), high transparency, uniform composition, and purity, offer promising prospects for U-Pb dating. Despite decades of recognition that garnets can be dated using the U-Pb method, direct dating remains extremely limited. Tsavorite is a rare gem-quality green vanadium-rich grossular hosted in the Neoproterozoic Metamorphic Mozambique Belt (NMMB). Until now, the accurate crystallization age of the tsavorite in Kenya and Lemshuku (Tanzania) has remained unknown. Here, we conducted in situ laser U-Pb geochronological analysis on gem-quality tsavorite samples from Tanzania and Kenya. U-Pb dating of tsavorite sourced from the Lemshuku mine (Tanzania) and the Tsavorite mine (Kenya) yielded ages of 643.9 ± 3.2 Ma and 617.4 ± 4.8 Ma, respectively. The high closure temperature of the U-Pb system within garnets renders it more inclined to preserve crystallization ages rather than documenting cooling events or metamorphic overprinting. Consequently, these ages are indicative of the tsavorite mineralization epochs. These findings align with the most significant metamorphic period documented in the Mozambique Belt, known as the East African Orogen, which occurred between 640 and 600 Ma. U-Pb data have revealed distinct formation times for each district. Dating specific deposits can provide more precise information about the origin of tsavorite, rather than solely relying on isotope or trace element data that have long been used for provenance studies of tsavorite. Full article

Extreme weather events, considered to be the most destructive natural hazards connected with rapid climate changes in the temperate zone of Europe, necessitate swift adjustments to the selection of ornamental plants for cultivation in multi-stress urbanized areas, public greeneries, and gardens. Moreover, given the rising average air temperature and prolonged growing season, as well as the delay and shortening of the dormancy period, plant phenology is subject to significant alternations. Herbaceous plants fulfill most elements of ecosystem service, e.g., they may enhance biodiversity in climate-warming conditions and create a favorable environment for trees in cities. In this work, we consider the advantages and disadvantages of the dissemination or introduction of annuals and perennials. We draw attention to species rarely or never known to have been cultivated in Europe, which currently occupy hotspots with the highest biodiversity value, including (i) the Mediterranean Basin, (ii) the Caucasus, (iii) Irano-Anatolian, (iv), and the mountains of Central Asia. We emphasize the importance of protecting threatened taxa through safe ex situ cultivation. Ornamentals should be characterized not only by aesthetic values but also by their ability to adapt to environmental changes. However, bearing in mind that horticulture is an important source of invasive alien species, further research assessing the ecological threats and advantages should be conducted. Full article