Forest fires pose severe ecological, climatic, and socio-economic threats, destroying habitats and emitting greenhouse gases. Early and timely warning is particularly challenging because fires often originate from small-scale, low-temperature ignition sources. Traditional monitoring approaches primarily rely on single-source satellite imagery and empirical threshold algorithms, and most forest fire monitoring tasks remain human-driven. Existing frameworks have yet to effectively integrate multiple data sources and detection algorithms, lacking the capability to provide continuous, automated, and generalizable fire monitoring across diverse fire scenarios. To address these challenges, this study first improves multiple monitoring algorithms for forest fire detection, including a statistically enhanced automatic thresholding method; data augmentation to expand the U-Net deep learning dataset; and the application of a freeze–unfreeze transfer learning strategy to the U-Net transfer model. Multiple algorithms are systematically evaluated across varying fire scales, showing that the improved automatic threshold method achieves the best performance on GF-4 imagery with an F-score of 0.915 (95% CI: 0.8725–0.9524), while the U-Net deep learning algorithm yields the highest F-score of 0.921 (95% CI: 0.8537–0.9739) on Landsat 8 imagery. All methods demonstrate robust performance and generalizability across diverse scenarios. Second, data-driven scheduling technology is developed to automatically initiate preprocessing and fire detection tasks, significantly reducing fire discovery time. Finally, an integrated framework of multi-source remote sensing data, advanced detection algorithms, and a user-friendly visualization interface is proposed. This framework enables all-weather, fully automated forest fire monitoring and early warning, facilitating dynamic tracking of fire evolution and precise fire line localization through the cross-application of heterogeneous data sources. The framework’s effectiveness and practicality are validated through wildfire cases in two regions of Yunnan Province, offering scalable technical support for improving early detection of and rapid response to forest fires.
Eda Gündem, Sabine Stehling, Astrid Borchert
et al.
Arachidonic acid lipoxygenases (ALOXs) play important roles in cell differentiation and in the pathogenesis of cardiovascular, hyperproliferative, neurodegenerative, and metabolic diseases. The human genome involves six intact ALOX genes and knockout studies of the corresponding mouse orthologs indicated that the coding multiplicity of ALOX isoforms is not an indication for functional redundancy. Despite their evolutionary relatedness human and mouse ALOX15 and ALOX15B orthologs exhibit different catalytic properties. Human ALOX15 oxygenates arachidonic acid mainly to 15S-hydroperoxy-5Z,8Z,11Z,13E-eicosatetraenoic acid but 12S-hydroperoxy-5Z,8Z,10E,14Z-eicosatetraenoic acid is the dominant oxygenation product of mouse Alox15. This functional difference is the results of a targeted enzyme evolution but the driving forces for this process have not been well defined. For human and mouse ALOX15B orthologs similar functional differences have been reported but for the time being it was unclear whether these differences might also be a consequence of targeted enzyme evolution. To address this question, we systematically searched the public databases for ALOX15B genes, expressed selected enzymes, and characterized their functional properties. We found that functional ALOX15B genes frequently occur in Prototheria and Eutheria but orthologous genes are rare in Metatheria. The vast majority of mammalian ALOX15B orthologs constitute arachidonic acid 15-lipoxygenating enzymes and this property did not depend on the evolutionary ranking of the animals. Only several Muridae species including M. musculus, M. pahari, M. caroli, M. coucha, and A. niloticus express arachidonic acid 8-lipoxygenating ALOX15B orthologs. Consequently, the difference in the reaction specificity of mouse and human ALOX15B orthologs may not be considered a functional consequence of targeted enzyme evolution.
Urban electricity power consumption (EPC) prediction plays a crucial role in urban management and sustainable development. Nighttime light (NTL) remote sensing imagery has demonstrated significant potential in estimating urban EPC due to its strong correlation with human activities and energy use. However, most existing models focus on annual-scale estimations, limiting their ability to capture month-scale EPC. To address this limitation, a novel monthly EPC prediction model that incorporates monthly average temperature, and the interaction between NTL data and temperature was proposed in this study. The proposed method was applied to cities within the Yangtze River Delta (YRD) urban agglomeration, and was validated using datasets constructed from NPP/VIIRS and SDGSAT-1 satellite imageries, respectively. For the NPP/VIIRS dataset, the proposed method achieved a Mean Absolute Relative Error (MARE) of 7.96% during the training phase (2017–2022) and of 10.38% during the prediction phase (2023), outperforming the comparative methods. Monthly EPC spatial distribution maps from VPP/VIIRS data were generated, which not only reflect the spatial patterns of EPC but also clearly illustrate the temporal evolution of EPC at the spatial level. Annual EPC estimates also showed superior accuracy compared to three comparative methods, achieving a MARE of 7.13%. For the SDGSAT-1 dataset, leave-one-out cross-validation confirmed the robustness of the model, and high-resolution (40 m) monthly EPC maps were generated, enabling the identification of power consumption zones and their spatial characteristics. The proposed method provides a timely and accurate means for capturing monthly EPC dynamics, effectively supporting the dynamic monitoring of urban EPC at the monthly scale in the YRD urban agglomeration.
The secondary suspended river increases the probability of the occurrence of “Heng river”, “Xie river” and “Gun river” in the lower Yellow River, and is the main factor threatening the safety of human life and property in the Yellow River levee and beach area. Here, the Dongbatou–Gaocun section of the severe secondary suspended river in the lower Yellow River was taken as the research object. The trend and periodicity of the evolution characteristics of the secondary suspended river in the study area from 1960–2021 were systematically analyzed using the Theil-Sen estimator and wavelet analysis, and the factors influencing its development were quantitatively explored. Over the past 62 years, development of secondary suspended rivers can be divided into four stages: initial formation (1960–1973), slow development (1974–1986), rapid development (1987–1999) and stable (2000–2021) periods. The evolution period of the beach transverse gradient differed significantly before and after operation of Xiaolangdi Reservoir commenced, prior to which there was a first main period of 31 years followed by a second main period of 21 years. Development of secondary suspended rivers was primarily related to floodplain flooding and human activity. When the inflow sediment coefficient of a floodplain flood (ζ) was < 0.04 and the floodplain coefficient was < 1.29, the secondary suspended river was relieved; when ζ > 0.04 or ζ < 0.04 and the floodplain coefficient was > 1.29, the secondary suspended river was intensified. The production levees have exacerbated development of secondary suspended rivers to some extent.
Athiwat Wattanapituksakul, Rasmi Shoocongdej, Cyler Conrad
Ban Rai Rockshelter in northwest Thailand, dating to the Terminal Pleistocene and Middle Holocene, includes evidence for hunter-gatherer exploitation of mammals, birds, reptiles, fish, and arthropods. Abundant faunal remains, identified throughout site deposits, include macaques (<i>Macaca</i> sp.) and Sambar deer (<i>Rusa unicolor</i>), but these identifications are influenced by an assemblage largely comprised of preserved tooth elements and fragmented bone. Area 3 at Ban Rai has the largest abundance and diversity of faunal remains recovered and identified in this study. Here, we examine the zooarchaeological assemblage from Ban Rai Rockshelter, to understand long-term hunter-gatherer subsistence change, influenced by site preservation, during and after the Pleistocene–Holocene transition. Our results support the presence of the exploitation of arboreal taxa during the Early and Middle Holocene in northwest Thailand.
Household water food and energy (WFE) expenditures, reflect respective survival needs for which their resources and social welfare are inter-related. We developed a policy driven quantitative decision-making strategy (DMS) to address the domain geospatial entities' (nodes or administrative districts) of the WFE nexus, assumed to be information linked across the domain nodal-network. As investment in one of the inter-dependent nexus components may cause unexpected shock to the others, we refer to the WFE normalized expenditures product (Volume) as representing the nexus holistic measure. Volume rate conforms to Boltzman entropy suggesting directed information from high to low Volume nodes. Our hypothesis of causality-driven directional information is exemplified by a sharp price increase in wheat and rice, for U.S. and Thailand respectively, that manifests its impact on the temporal trend of Israel's administrative districts of the WFE expenditures. Welfare mass (WM) represents the node's Volume combined with its income and population density. Formulation is suggested for the nodal-network WM temporal balance where each node is scaled by a human-factor (HF) for subjective attitude and a superimposed nodal source/sink term manifesting policy decision. Our management tool is based on two sequential governance processes: one starting with historical data mapping the mean temporal nodal Volumes to single out extremes, and the second is followed by WM balance simulation predicting nodal-network outcome of policy driven targeting. In view of the proof of concept by model simulations in in our previous research, here HF extends the model and attention is devoted to emphasize how the current developed decision-making approach categorically differs from existing nexus related methods. The first governance process is exemplified demonstrating illustrations for Israel's districts. Findings show higher expenditures for water and lower for energy, and maps pointing to extremes in districts' mean temporal Volume. Illustrations of domain surfaces for that period enable assessment of relative inclination trends of the normalized Water, Food and Energy directions continuum assembled from time stations, and evolution trends for each of the WFE components.
Adriana Teodora Campeanu, Elena Dumea, Mihaela Rus
et al.
Lesions commonly associated with HIV infection include oral candidiasis, herpes simplex infection, oral Kaposi’s sarcoma, hairy leukoplakia, periodontal diseases (linear gingival erythema and necrotizing ulcerative periodontitis), xerostomia, human papillomavirus-associated warts, aphthous ulcers, non-Hodgkin’s lymphoma, histoplasmosis, carcinoma, exfoliative cheilitis, and HIV salivary gland disease. Non-Hodgkin’s lymphoma (NHL) is the most common cancer in people living with HIV (PLWH), and the incidence is increased for aggressive B-cell NHL. Plasmablastic lymphoma (PbL) is a rare and aggressive B-cell malignancy that is often unresponsive to chemotherapy and usually has a poor prognosis. We hereby present the case of a patient with a recent history of COVID-19 infection who was diagnosed with HIV and NHL, with manifestations in the oral cavity and a favorable evolution after the introduction of antiviral therapy, specific chemotherapy, and radiotherapy. Dental expertise is necessary for the appropriate management of oral manifestations of HIV infection or AIDS, and lymphoma should be included in the differential diagnosis of any oral lesions.
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Saulo Folharini, António Vieira, Regina Célia de Oliveira
In the Brazilian state of São Paulo, the coastal municipalities have watersheds in mountains with active relief evolution (Serra do Mar). The coastal regions are more vulnerable to flooding and landslides. A large number of people live on the slopes of Serra do Mar; these places are more vulnerable to landslides, which cause biodiversity loss and damage to human and natural environments. This study seeks to present an ecohydrological analysis to categorize coastal watersheds into clusters, considering the spatial characteristics of NDVI, DTM, soil depth, climate, and Soil Organic Carbon (SOC), and identify areas’ susceptibility to landslides in the coastal watersheds of the State of São Paulo. The results show that vegetation cannot prevent landslides from happening on its own. The higher altitude regions, where the tropical forest is still present, are those most prone to landslides, designated as cluster 2.
A major phenomenon of the contemporary world, artificial intelligence (AI) represents the
ability of electronic equipment to perform duties and skills naturally associated with human
intelligence. John McCarthy (1955) defines it as a situation where "... the machine behaves
in a way that could be considered intelligent, if it were human." AI has experienced a
technological trend, which has exploded in the last decade, being a concept with continuous
evolution, offering a very attractive market, with many new opportunities for various
businesses. The field of commerce offers the widest applicable range to artificial
intelligence because it ensures contact with most of the population as potential clientele.
Andy S. Gale, Crispin T.S. Little, Joel E. Johnson
et al.
Valves of a thoracican cirripede belonging to a new species of the Neolepadidae, Ashinkailepas indica Gale sp. nov. are described from a Late Pleistocene cold seep (52.6 ka), cored in the Krishna-Godavari Basin, offshore from the eastern coast of India. This constitutes the first fossil record of the genus, and its first occurrence in the Indian Ocean. Other fossil records of the Neolepadidae (here elevated to full family status) are discussed, and it is concluded that only Stipilepas molerensis from the Eocene of Denmark, is correctly referred to the family. Cladistic analysis of the Neolepadidae supports a basal position for Ashinkailepas, as deduced independently from molecular studies, and the Lower Cretaceous brachylepadid genus Pedupycnolepas is identified as sister taxon to Neolepadidae. Neolepadids are not Mesozoic relics as claimed, preserved in association with the highly specialised environments of cold seeps and hydrothermal vents, but are rather an early Cenozoic offshoot from the clade which also gave rise to the sessile cirripedes.
For centuries the meaning of man in the world has been tried to be meaningful in
all branches of art in the world literature. It is important to look at the literary text
in order to investigate the self-view of man and his struggle for existence according
to centuries. Classical poets have tried to understand and position themselves on
the earth in the context of the mystic which is the equivalent of evolution in Sufism
on an individual level. The aim of this study is to research Muhibbi, who is a sultan
poet, through his poems in order to get to know personality and literary sense.
For this reason, the concept of insan-ı kâmil was taken as a subject. For ordinary
people, insan-ı kâmil perception is different. The difference of the perception of
this concept for a sultan is revealed in the text.
Here, also, reference is made to the sultan-poet who has not seen many examples
in the history of world literature. Muhibbi is one of the important sultan poets of
Ottoman literature. Apart from being Muhibbi, sultan or poet, the couplets he wrote
as servants are quite remarkable. The poet expresses being a servant to Allah as
a sultan by means of nurturing his self. In this study, couplets in which Muhibbi
emphasizes the sultanate in his ghazals are highlighted. The themes of poet sultan,
human, servant and perfect human are emphasized with extreme examples. In
these couplets, it is important that Suleiman the Magnificent promotes being a
perfect human being as a sultan.
Alberto J. C. Micheletti, Graeme D. Ruxton, Andy Gardner
Recent years have seen great interest in the suggestion that between-group aggression and within-group altruism have coevolved. However, these efforts have neglected the possibility that warfare – via its impact on demography – might influence human social behaviours more widely, not just those directly connected to success in war. Moreover, the potential for sex differences in the demography of warfare to translate into sex differences in social behaviour more generally has remained unexplored. Here, we develop a kin-selection model of altruism performed by men and women for the benefit of their groupmates in a population experiencing intergroup conflict. We find that warfare can promote altruistic, helping behaviours as the additional reproductive opportunities winners obtain in defeated groups decrease harmful competition between kin. Furthermore, we find that sex can be a crucial modulator of altruism, with there being a tendency for the sex that competes more intensely with relatives to behave more altruistically and for the sex that competes more intensely with non-relatives in defeated groups to receive more altruism. In addition, there is also a tendency for the less-dispersing sex to both give and receive more altruism. We discuss implications for our understanding of observed sex differences in cooperation in human societies.