Search Results (42)

Termites pose significant threats to the structural integrity of embankments due to their nesting and tunneling behavior, which leads to internal voids, water leakage, or even dam failure. This review systematically classifies and evaluates current termite detection techniques in the context of embankment maintenance, focusing on physical sensing technologies and biological characteristic-based methods. Physical sensing methods enable non-invasive localization of subsurface anomalies, including ground-penetrating radar, acoustic detection, and electrical resistivity imaging. Biological characteristic-based methods, such as electronic noses, sniffer dogs, visual inspection, intelligent monitoring, and UAV-based image analysis, are capable of detecting volatile compounds and surface activity signs associated with termites. The review summarizes key principles, application scenarios, advantages, and limitations of each technique. It also highlights integrated multi-sensor frameworks and artificial intelligence algorithms as emerging solutions to enhance detection accuracy, adaptability, and automation. The findings suggest that future termite detection in embankments will rely on interdisciplinary integration and intelligent monitoring systems to support early warning, rapid response, and long-term structural resilience. This work provides a scientific foundation and practical reference for advancing termite management and embankment safety strategies. Full article

HIV-associated lymphoma (HAL) is a heterogeneous and highly aggressive group of malignancies. Although antiretroviral therapy (ART) has significantly prolonged the survival of people living with HIV (PLWH), the risk of malignancy secondary to HIV infection remains higher than in HIV-negative individuals, with HAL being among the most frequent. The pathogenesis of HAL is complex, involving multifactorial interactions. In current clinical practice, HAL faces a double challenge: the lack of effective biological risk warning systems and the lack of precise prognostic stratification tools. In recent years, the construction of multidimensional biomarker systems has shown critical value in the comprehensive management of HAL. This review aims to systematically summarize recent advances in circulating biomarkers for HAL, focusing on the potential applications of immune environment indicators, such as inflammatory cytokine profiles and microbial translocation markers, as well as serum protein profiles, lymphocyte subsets, extracellular vesicles (EVs), circulating microRNAs (miRNAs), and viral biomarkers. These biomarkers offer promising avenues for early risk prediction, therapeutic monitoring, and prognostic evaluation. Developing an assessment system based on multidimensional biomarkers will optimize early risk stratification, enable precise prognostic classification, and support personalized therapeutic strategies, thereby providing a novel theoretical basis and practical direction for the clinical management of HAL. Full article

The desert locust is documented as one of the most destructive polyphagous plant pests that require preventive or proactive management practices due to its phase polyphenism, rapid breeding, transnational migration, and heavy feeding behaviour. Desert locust situation analysis, forecasting and early warning are complex due to the systemic interaction of biological, meteorological, and geographical factors that play different roles in facilitating the survival, breeding and migration of the pest. This article seeks to elucidate the factors that affect desert locust distribution and review the application of earth observation (EO) data in explaining the pest’s infestations and impact. The review presents details concerning the application of EO data to understand factors that affect desert locust breeding and migration, elaborates on impact assessment through vegetation change detection and discusses modelling techniques that can support the effective management of the pest. The review reveals that the application of EO technology is inclined in favour of desert locust habitat suitability assessment with a limited financial quantification of losses. The review also finds a progressive advancement in the use of multi-modelling approaches to address identified gaps and reduce computational errors. Moreover, the review recognises great potential in applications of EO tools, products and services for anticipatory action against desert locusts to ensure resource use efficiency and environmental conservation. Full article

Chinese forests, particularly the coniferous forest ecosystems represented by pines, play a crucial role in the global carbon cycle, significantly contributing to mitigating climate change, regulating regional climates, and maintaining ecological balance. However, pine wilt disease (PWD), caused by the pine wood nematode (PWN), has become a major threat to forest carbon stocks in China. This study evaluates the impact of PWN invasion on forest carbon stocks in China using multi-source data and an optimized MaxEnt model, and the study analyzes this invasion’s spread trends and potential risk areas. The results show that the high-suitability area for PWN has expanded from 68,000 km² in 2002 to 184,000 km² in 2021, with the spread of PWN accelerating, especially under warm and humid climate conditions and due to human activities. China’s forest carbon stocks increased from 111.34 billion tons of carbon (tC) to 168.05 billion tC, but the carbon risk due to PWN invasion also increased from 87 million tC to 99 million tC, highlighting the ongoing threat to the carbon storage capacity. The study further reveals significant differences in tree species’ sensitivity to PWN, with highly sensitive species such as Masson’s pine and black pine mainly concentrated in the southeastern coastal regions, while less sensitive species such as white pine and larch show stronger resistance in the northern and southwestern areas. This finding highlights the vulnerability of high-sensitivity tree species to PWN, especially in high-risk areas such as Guangdong, Guangxi, and Guizhou, where urgent and effective control measures are needed to reduce carbon stock losses. To address this challenge, the study recommends strengthening monitoring in high-risk areas and proposes specific measures to improve forest management and policy interventions, including promoting cross-regional joint control, enhancing early warning systems, and utilizing biological control measures, while encouraging local governments and communities to actively participate. By strengthening collaboration and implementing control measures, the health and sustainable development of forest ecosystems can be ensured, safeguarding the forests’ important role in climate regulation and carbon sequestration and contributing to global climate change mitigation. Full article

Biological invasions threaten biodiversity and agroecosystems, and early warning systems can minimise the spread of invasive alien species with limited resources. This study documents the presence of the alien plant Asclepias speciosa Torr., native to North America, that was first discovered in 2022 on Mount Vrontou, Central Macedonia, Northern Greece. This is the second European record of this alien species, after Lithuania, confirming its adaptability to contrasting European biogeographical regions. To enable future monitoring, this study provided new data on morphological traits of the species (above-ground parts), climatic tolerance (precipitation and temperature regimes), habitats with co-occurring species, pollinators, current reproductive potential, and seed germination at controlled temperatures (10 °C, 15 °C, and 20 °C). The high probability of misidentification with the highly invasive A. syriaca in European inventories supports the theory that A. speciosa may have been present in Europe long before it was officially reported. The lack of an EU-mandated reassessment of A. syriaca monitoring raises concerns regarding the potential invasion risk of A. speciosa in European natural and semi-natural areas or agricultural lands. Inspection mechanisms, early warning systems, and preventive measures are therefore essential to protect local biodiversity and agriculture from potential A. speciosa invasion, a risk that may be exacerbated by climate change. Full article

The biological early warning system with fish behavior as the detection index is an efficient and rapid early warning technology for the ecological damage caused by water pollutants. However, the attempt to apply the scototaxis (dark preference) behavior of fish to biological early warning is still relatively lacking. In this study, we delved into the dark and light preferences of the rare minnows (Gobiocypris rarus), employing three distinct tank configurations. Additionally, we systematically examined the modulating effects of environmental illumination, nutritional status, and the number of test subjects on this behavior, aiming to establish optimal experimental parameters for its observation. Furthermore, cadmium ions [Cd²⁺], tricaine methanesulfonate [MS222], and p-chloroaniline were employed as representative heavy metal ions, neuroactive agents, and organic toxicants, respectively, to test the impact of chemicals on scototaxis in gradient concentrations. The results demonstrated that the rare minnow exhibited a clear scototaxis (dark preference), and this behavior was not affected by the nutritional status of the test fish, the illumination, or the number of subjects. While the dark chamber was consistently the preferred location of rare minnows during the chemical exposure tests, the degree of scototaxis by the rare minnow significantly decreased at Cd²⁺ ≥ 3 mg/L, MS222 ≥ 11 mg/L, and p-chloroaniline ≥ 29 mg/L, suggesting a potential disruption of their innate behavioral patterns by these chemicals. These findings underscore the sensitivity of rare minnows to water pollutants. Therefore, the scototaxis behavior of rare minnows can be a potential and useful behavioral indicator for biological early warning, which can be used for early biological warning of sudden water pollution caused by chemicals such as Cd²⁺, MS222, and p-chloroaniline. Full article

Mercury (Hg) pro-oxidant role on biological systems and its biogeochemical cycle represent a serious threat due to its persistence in marine environment. As the mitochondrial genome is exposed to reactive oxygen species (ROS), the aim of the present study is the validation of the variation in the number of mitochondrial DNA copies (mtDNAcn) as biomarker of oxidative stress in aquatic environment. During summer 2021, three selected fish species (Mullus barbatus, Diplodus annularis and Pagellus erythrinus) were collected in Augusta Bay, one of the most Mediterranean contaminated areas remarkable by past Hg inputs, and in a control area, both in the south-east of Sicily. The relative mtDNAcn was evaluated by qPCR on specimens of each species from both sites, characterized respectively by higher and lower Hg bioaccumulation. M. barbatus and P. erythrinus collected in Augusta showed a dramatic mtDNAcn reduction compared to their control groups while D. annularis showed an incredible mtDNAcn rising suggesting a higher resilience of this species. These results align with the mitochondrial dynamics of fission and fusion triggered by environmental toxicants. In conclusion, we suggest the implementation of the mtDNAcn variation as a valid tool for the early warning stress-related impacts in aquatic system. Full article

Owing to global climate change or the ever-more frequent human activities in the offshore areas, it is highly probable that an imbalance in the offshore ecosystem has been induced. However, the importance of maintaining and protecting marine ecosystems’ balance cannot be overstated. In recent years, various marine disasters have occurred frequently, such as harmful algal blooms (green tides and red tides), storm surge disasters, wave disasters, sea ice disasters, and tsunami disasters. Additionally, overpopulation of certain marine organisms (particularly marine faunas) has led to marine disasters, threatening both marine ecosystems and human safety. The marine ecological disaster monitoring system in China primarily focuses on monitoring and controlling the outbreak of green tides (mainly caused by outbreaks of some Ulva species) and red tides (mainly caused by outbreaks of some diatom and dinoflagellate species). Currently, there are outbreaks of Cnidaria (Hydrozoa and Scyphozoa organisms; outbreak species are frequently referred to as jellyfish), Annelida (Urechis unicinctus Drasche, 1880), Mollusca (Philine kinglipini S. Tchang, 1934), Arthropoda (Acetes chinensis Hansen, 1919), and Echinodermata (Asteroidea organisms, Ophiuroidea organisms, and Acaudina molpadioides Semper, 1867) in China. They not only cause significant damage to marine fisheries, tourism, coastal industries, and ship navigation but also have profound impacts on marine ecosystems, especially near nuclear power plants, sea bathing beaches, and infrastructures, posing threats to human lives. Therefore, this review provides a detailed introduction to the marine organisms (especially marine fauna species) causing marine biological disasters in China, the current outbreak situations, and the biological backgrounds of these outbreaks. This review also provides an analysis of the causes of these outbreaks. Furthermore, it presents future prospects for marine biological disasters, proposing corresponding measures and advocating for enhanced resource utilization and fundamental research. It is recommended that future efforts focus on improving the monitoring of marine biological disasters and integrating them into the marine ecological disaster monitoring system. The aim of this review is to offer reference information and constructive suggestions for enhancing future monitoring, early warning systems, and prevention efforts related to marine ecological disasters in support of the healthy development and stable operation of marine ecosystems. Full article

Background/Objectives: Evidence indicates that persistent transgressive behaviors often begin early in development and increase around age twelve, and warns that children who exhibit transgressive behaviors in childhood or early adolescence tend to develop criminal behaviors in adulthood which makes childhood a critical unit of analysis for timely intervention. The study examines risk and protective factors in childhood related to illegal behavior, through the perspective of developmental criminology. The observation of risk and protective factors in early stages allows us to design interventions that prevent social adjustment problems in children from becoming more complex by maintaining the transgression of social norms over time. Factors identified by developmental criminology can be organized according to ecological systems theory and discussed in relation to previous criminological studies. Methods: Using a systematic review based on the PRISMA method, the study identifies 24 updated developmental criminology articles that study early protective factors between birth and age twelve. Result: Risk factors at the individual level include biological, socioemotional, behavioral, symptomatic aspects and adverse life experiences. Individual protective factors include cognitive, socioemotional, and personality development aspects. Risk factors at an interpersonal and contextual level are related to family, school, peers, socioeconomic situation and governance. Conclusions: This review highlights the importance of recognizing risk and protective factors in child development, contemplating interventions at multiple levels where an articulation between the various institutions involved in child care is possible. Full article

The behavioral (filtration activity) and biochemical (oxidative stress) effects of Roundup 360 Plus (active substance glyphosate) herbicide on two species of unionid mussels, Unio tumidus (Philipsson, 1788) and Anodonta anatina (L.), were evaluated at concentrations ranging from 15 to 1500 μg L⁻¹ of glyphosate for five days. During all experiments, we did not record the mortality of the studied mussel species. Exposure to Roundup herbicide induced dose-dependent filtration disruptions in both U. tumidus and A. anatina. Exposure of the mussels to a low and environmentally relevant concentration 15 µg glyphosate L⁻¹ resulted in a slight (<20%) and temporary decrease in mean valve dilation. Exposure of the mussels to Roundup at relatively high concentrations caused drastic and prolonged shell closure and a reduction in the mussel shell opening rate. Exposure of both mussel species to herbicide resulted in oxidative stress; an increase in superoxide dismutase enzymatic activity was detected. The most significant increase in SOD activity was observed after the exposure to the highest Roundup concentration. However, no correlation between the Roundup concentration and enzymatic activity was found. The use of unionid mussels to detect environmentally relevant concentrations of Roundup, as a part of biological early warning system for pollution, is limited, but they can serve to detect the incidental pollution of aquatic ecosystems with high concentrations of this herbicide. Full article

Air pollution is one of the greatest environmental risks to health, with 99% of the world’s population living where the World Health Organization’s air quality guidelines were not met. In addition to the respiratory and cardiovascular systems, the brain is another potential target of air pollution. Population- and experiment-based studies have shown that air pollution may affect mental health through direct or indirect biological pathways. The evidence for mental hazards associated with air pollution has been well documented. However, previous reviews mainly focused on epidemiological associations of air pollution with some specific mental disorders or possible biological mechanisms. A systematic review is absent for early effect biomarkers for characterizing mental health hazards associated with ambient air pollution, which can be used for early warning of related mental disorders and identifying susceptible populations at high risk. This review summarizes possible biomarkers involved in oxidative stress, inflammation, and epigenetic changes linking air pollution and mental disorders, as well as genetic susceptibility biomarkers. These biomarkers may provide a better understanding of air pollution’s adverse effects on mental disorders and provide future research direction in this arena. Full article

Evaluation of water quality and accurate prediction of water pollution indicators are key components in water resource management and water pollution control. The use of biological early warning systems (BEWS), in which living organisms are used as biosensors, allows for a comprehensive assessment of the aquatic environment state and a timely response in the event of an emergency. In this paper, we examine three machine learning algorithms (Theta, Croston and Prophet) to forecast bivalves’ activity data obtained from the BEWS developed by the authors. An algorithm for anomalies detection in bivalves’ activity data was developed. Our results showed that for one of the anomalies, Prophet was the best method, and for the other two, the anomaly detection time did not differ between the methods. A comparison of methods in terms of computational speed showed the advantage of the Croston method. This anomaly detection algorithm can be effectively incorporated into the software of biological early warning systems, facilitating rapid responses to changes in the aquatic environment. Full article

Citizen science reinforces the development of emergent tools for the surveillance, monitoring, and early detection of biological invasions, enhancing biosecurity resilience. The contribution of farmers and farm citizens is vital, as volunteers can strengthen the effectiveness and efficiency of environmental observations, improve surveillance efforts, and aid in delimiting areas affected by plant-spread diseases and pests. This study presents a robust, user-friendly, and cost-effective smart module for citizen science that incorporates a cutting-edge developed hyperspectral imaging (HI) module, integrated in a single, energy-independent device and paired with a smartphone. The proposed module can empower farmers, farming communities, and citizens to easily capture and transmit data on crop conditions, plant disease symptoms (biotic and abiotic), and pest attacks. The developed HI-based module is interconnected with a smart embedded system (SES), which allows for the capture of hyperspectral images. Simultaneously, it enables multimodal analysis using the integrated environmental sensors on the module. These data are processed at the edge using lightweight Deep Learning algorithms for the detection and identification of Tuta absoluta (Meyrick), the most important invaded alien and devastating pest of tomato. The innovative Artificial Intelligence (AI)-based module offers open interfaces to passive surveillance platforms, Decision Support Systems (DSSs), and early warning surveillance systems, establishing a seamless environment where innovation and utility converge to enhance crop health and productivity and biodiversity protection. Full article

We developed a macroscopic description of the evolutionary dynamics by following the temporal dynamics of the total Shannon entropy of sequences, denoted by S, and the average Hamming distance between them, denoted by H. We argue that a biological system can persist in the so-called quasi-equilibrium state for an extended period, characterized by strong correlations between S and H, before undergoing a phase transition to another quasi-equilibrium state. To demonstrate the results, we conducted a statistical analysis of SARS-CoV-2 data from the United Kingdom during the period between March 2020 and December 2023. From a purely theoretical perspective, this allowed us to systematically study various types of phase transitions described by a discontinuous change in the thermodynamic parameters. From a more-practical point of view, the analysis can be used, for example, as an early warning system for pandemics. Full article

This manuscript describes the design, development, and implementation of a prototype system based on seismogeodetic techniques, consisting of a low-cost MEMS seismometer/accelerometer, a biaxial inclinometer, a multi-frequency GNSS receiver, and a meteorological sensor, installed at the Doñana Biological Station (Huelva, Spain) that transmits multiparameter data in real and/or deferred time to the control center at the University of Cadiz. The main objective of this system is to know, detect, and monitor the tectonic activity in the Gulf of Cadiz region and adjacent areas in which important seismic events occur produced by the interaction of the Eurasian and African plates, in addition to the ability to integrate into a regional early warning system (EWS) to minimize the consequences of dangerous geological phenomena. Full article