Harsh Weather Conditions Research Articles

From operational design domain to test cases: A methodology to include harsh weather

Background To gain widespread use, assisted and automated driving (AAD) systems will have to cope with harsh weather conditions, such as rain, fog, and snow. This affects the development and testing of perception and decision-making systems. Since the weather cannot be controlled in field tests, the availability and use of virtual simulation and test facilities that can accurately reproduce harsh weather becomes vital. Test cases subjecting the system under test to harsh conditions, covering all expected weather phenomena in both typical and challenging scenarios, must be defined to evaluate all aspects of the system. Methods State-of-the-art in scenario-based and hash weather testing for AAD systems was analysed; based on the analysis, a team with diverse expertise in AAD development and testing defined a methodology for defining a set of harsh weather test cases. Results This paper proposes, and exemplifies the use of, a methodology to develop a representative set of test cases based on the defined operational design domain and use cases for an AAD system under development, considering the possibility of reproducing tests in different test environments with a focus on harsh weather. Conclusions We believe that our proposed methodology can accelerate the overall testing process and contribute to the difficult safety assurance challenges for automated vehicles.

Differential responses to weather and land‐cover conditions explain spatial variation in winter abundance trends in a migratory bird of conservation concern

Abstract Effective conservation strategies for animal populations require knowledge of relationships between population dynamics and their environmental drivers. However, these processes often vary within animal populations, requiring site‐specific conservation planning. Given limited financial resources, identifying groups of sites with similar population dynamics can help practitioners efficiently implement conservation programs to larger areas. We evaluated spatial patterns and environmental drivers of wintering site trends in a migratory bird of conservation concern, the Greenland white‐fronted goose (Anser albifrons flavirostris). We used latent class analysis to identify trend patterns in 35 years of abundance data among 59 geographically discrete Greenland white‐fronted goose wintering sites. We developed a state‐space abundance model in a Bayesian framework to quantify the effects of weather and land‐cover conditions experienced throughout spring migration, summer breeding, autumn migration and wintering periods on variation in wintering site abundance. We identified two main patterns in Greenland white‐fronted goose abundance trends: northeastern wintering sites declined on average by 3% per year, while southwestern wintering sites declined on average by 14% per year. Differential responses to weather and habitat conditions likely explained variation among groups, as geese at southwestern wintering sites were more negatively affected by harsh weather conditions (e.g. low temperatures and high precipitation on breeding areas) and poor habitat conditions (i.e. low‐quality grasslands and croplands) on wintering areas. Future conservation efforts to improve the suitability and nutritional quality of agricultural areas, especially cereal croplands in autumn and early winter and grasslands in late winter and early spring, could potentially improve local habitat conditions, especially in the southwestern wintering sites where abundance declines were steepest. Synthesis and applications. We demonstrate the potential to delineate animal populations based on spatial patterns in population dynamics using long‐term abundance monitoring data, which are commonly the only available data for conservation practitioners. By grouping sites based on spatial patterns in local abundance trends, we can further test hypotheses about how these groups are differentially affected by changing environmental conditions. This information is important for informing efficient conservation planning over large areas when financial resources are limited.

Assessing the Impact of Geospatial Susceptibility on the Rural Agricultural Landscapes of Village Settlements in Southwestern Nigeria

A theoretical framework for agricultural landscape pattern transitions in rural areas is proposed to fill the gap of current research with an empirical study in the Alabata farm settlement in Ogun State, Southwest Nigeria. Adopting the use of ArcGIS 10.8 and Surfer 27.3 the surface area and volume of the ground surface degraded and exposed to harsh weather conditions due to both natural and man-made anthropogenic activities causing runoffs and continuous soil erosion were calculated, which have affected agricultural production and sent some of the farmers packing, abandoning their farmlands. The farm settlement within the total sampled frame area of 1.50 km2 covers a total distance of 5.11 km. The sample frame was divided into 36 frames with similar ecological microclimates, topographical features, terrain, and soil types that fell into either of the two identified soil types: 1 and 2. The study involved the completion of a questionnaire onsite using three major criteria and only 23 farmers responded positively to the few questions as farmers who were either living on the farm or working as hired laborers on-site at the time of the visit. The transition characteristics of agricultural landscape patterns as represented in abandoned, degraded farmlands and orchards are analyzed from a local perspective.

Temporal-enhanced Radar and Camera Fusion for Object Detection

Recently, object detection methods based on multimodal fusion have gained widespread adoption in autonomous driving, proving to be valuable for detecting objects in dynamic environments. Among them, millimetre wave (mmWave) radar is commonly utilized as an effective complement to cameras, as it is almost unaffected by harsh weather conditions. However, current approaches that fuse mmWave radar and camera often overlook the correlation between the two modalities, failing to fully exploit their complementary features. To address this, we propose a temporal-enhanced radar and camera fusion network to explore the correlation between these two modalities and learn a comprehensive representation for object detection. In our model, a temporal fusion model is introduced to fuse mmWave radar features from different moments, thus mitigating the problem of mmWave radar point-object mismatch due to object movement. Moreover, a new correlation-based fusion strategy using the dedicated mask cross attention is proposed to fuse mmWave radar and vision features more effectively. Finally, we design a gate feature pyramid network that selects shallow texture information based on deep semantic information to obtain more representative features. The experimental results on the nuScenes benchmark demonstrate the effectiveness of our proposed method.

DGRO: Doppler Velocity and Gyroscope-Aided Radar Odometry

A stable and robust odometry system is essential for autonomous robot navigation. The 4D millimeter-wave radar, known for its resilience in harsh weather conditions, has attracted considerable attention. As the latest generation of FMCW radar, 4D millimeter-wave radar provides point clouds with both position and Doppler velocity information. However, the increased uncertainty and noise in 4D radar point clouds pose challenges that prevent the direct application of LiDAR-based SLAM algorithms. To address this, we propose a SLAM framework that fuses 4D radar data with gyroscope readings using graph optimization techniques. Initially, Doppler velocity is employed to estimate the radar’s ego velocity, with dynamic points being removed accordingly. Building on this, we introduce a pre-integration factor that combines ego-velocity and gyroscope data. Additionally, leveraging the stable RCS characteristics of radar, we design a corresponding point selection method based on normal direction and propose a scan-to-submap point cloud registration technique weighted by RCS intensity. Finally, we validate the reliability and localization accuracy of our framework using both our own dataset and the NTU dataset. Experimental results show that the proposed DGRO system outperforms traditional 4D radar odometry methods, especially in environments with slow speeds and fewer dynamic objects.

Evaluation of alternative joining methods in softshell fabric types

Parameters such as high performance, durability and comfort are very important in protective and sports clothing produced to increase the technical or functional properties of clothing products, as well as aesthetic and decorative features. Fabrics that provide comfort to the user by regulating body temperature, protect against harsh weather conditions, and are waterproof and windproof, as well as breathable, are used for these purposes. One of the most important fabrics with these features is the fabric called ‘softshell’. Softshell is a fabric specially created to release moisture and regulate body temperature. Therefore, the outer layer of the softshell is not waterproof, but water-repellent, ensuring that it remains dry and protective while a person is wearing it. Creating a three-dimensional product from a two-dimensional fabric with these features is achieved through the sewing process. As traditional methods are used in the sewing process, an alternative joining method called ‘ultrasonic joining’ can also be used. While alternative joining methods provide joining without sewing thread, these methods do not create holes in the fabric surfaces since there is no sewing needle. Joining processes with thermal, laser and ultrasound energy are based on the principle of melting, fusing and cooling the joined surfaces. In this study, it was aimed to analyze the change in the physical properties of different softshell fabrics as a result of joining them with classical and innovative sewing/joining methods. In this context, lockstitch, lockstitch & tape welding, ultrasonic welding, and ultrasonic welding & tape welding are applied to the softshell, ripstop softshell and Lycra softshell fabrics used in the market. The thickness, air permeability, seam strength and elongation at break properties of the bonded fabrics were examined. Within the scope of this study, obtaining successful results in softshell fabric types, which is one of the bulky fabrics, contributes to the idea that the usage area of ultrasonic welding will expand day by day.

The Wind Power Watch, "Guarding" for Safety - Data-Driven Intelligent Deterrence System for Monitoring Ships in Offshore Wind Farms

This study successfully developed a ship monitoring and repulsion system for offshore wind farms aimed at ensuring the safety and stable operation of the wind farms. The system is capable of real-time monitoring of ship activities and environmental conditions, quickly identifying and eliminating potential safety risks. The research content includes various aspects such as ship detection, path tracking, repulsion decision-making, and data processing. The system integrates multi-sensor data, Geographic Information Systems (GIS), Automatic Identification Systems (AIS) for ships, artificial intelligence algorithms, and advanced communication technologies, constructing an efficient and intelligent monitoring and repulsion framework. Field test results indicate that the system exhibits stable performance and efficient monitoring capabilities under harsh weather conditions, while the intelligent voice repulsion function has shown significant effects.

Nocturnal moth pollination in an alpine orchid, Platanthera tipuloides

AbstractPollination success of alpine plants is often restricted by low and unpredictable pollinator activity because of harsh and unstable weather conditions, where nocturnal pollination is rare. The alpine orchid, Platanthera tipuloides (Orchidaceae), has inconspicuous greenish yellow flowers with a sweet scent and a long spur that contains nectar. These floral traits are expected to be related to nocturnal moth pollination. To elucidate the pollination mode and reproductive characteristics of this species, we measured floral traits (spur length, nectar content in the spur, floral scent), documented flower visitors using camera traps, and quantified self‐compatibility and the degree of pollen limitation through controlled pollinations at two study plots in the Taisetsu Mountains, northern Japan. It was revealed that P. tipuloides is self‐incompatible and pollen limitation was absent at one of the study plots. The flowers emitted more volatile substances during the night, including lilac aldehyde isomers, which are known to attract moths. A nocturnal moth, Entephria amplicosta, was observed foraging nectar from the flowers, while no diurnal visitors were observed. The proboscis of E. amplicosta was shorter than the spur length, but it was long enough to access the accumulated nectar in the spurs. These results suggest that nocturnal pollination by moths is possible and can be efficient even in an alpine ecosystem with harsh environmental conditions.

Assessing downtown recovery rates and determinants in North American cities after the COVID-19 pandemic

North American downtowns are struggling to recover from the global COVID-19 pandemic. This study aims to investigate the varying rates of recovery experienced by downtown areas in the 66 largest cities of the United States and Canada. Leveraging Location-Based Services data extracted from mobile phone location trajectories, we assess the recovery rates in the 2023 post-pandemic period, juxtaposed against pre-pandemic 2019 levels. We find significant disparities in downtown recovery rates. Economic factors emerge as crucial determinants, where downtowns hosting a concentration of sectors with remote/hybrid work options – such as information, finance, professional services and management – displayed sluggish recovery. Conversely, downtowns with a focus on industries like accommodation, manufacturing, education, retail, construction, entertainment and healthcare exhibited greater resilience post pandemic. Furthermore, higher density, crime rates and education levels were correlated with slower recovery rates, as were harsher weather conditions and longer commuting times. Lower-density and auto-orientated downtowns demonstrated a swift rebound, even surpassing pre-pandemic activity levels. These findings underscore the necessity for tailored policies to bolster the revival of North American downtown areas.

Climate change and deer in boreal and temperate regions: From physiology to population dynamics and species distributions.

Climate change causes far-reaching disruption in nature, where tolerance thresholds already have been exceeded for some plants and animals. In the short term, deer may respond to climate through individual physiological and behavioral responses. Over time, individual responses can aggregate to the population level and ultimately lead to evolutionary adaptations. We systematically reviewed the literature (published 2000-2022) to summarize the effect of temperature, rainfall, snow, combined measures (e.g., the North Atlantic Oscillation), and extreme events, on deer species inhabiting boreal and temperate forests in terms of their physiology, spatial use, and population dynamics. We targeted deer species that inhabit relevant biomes in North America, Europe, and Asia: moose, roe deer, wapiti, red deer, sika deer, fallow deer, white-tailed deer, mule deer, caribou, and reindeer. Our review (218 papers) shows that many deer populations will likely benefit in part from warmer winters, but hotter and drier summers may exceed their physiological tolerances. We found support for deer expressing both morphological, physiological, and behavioral plasticity in response to climate variability. For example, some deer species can limit the effects of harsh weather conditions by modifying habitat use and daily activity patterns, while the physiological responses of female deer can lead to long-lasting effects on population dynamics. We identified 20 patterns, among which some illustrate antagonistic pathways, suggesting that detrimental effects will cancel out some of the benefits of climate change. Our findings highlight the influence of local variables (e.g., population density and predation) on how deer will respond to climatic conditions. We identified several knowledge gaps, such as studies regarding the potential impact on these animals of extreme weather events, snow type, and wetter autumns. The patterns we have identified in this literature review should help managers understand how populations of deer may be affected by regionally projected futures regarding temperature, rainfall, and snow.

Multivariate ocean waves dynamics in North Sea and Norwegian Sea by Gaidai reliability method

Current study presents state-of-the-art approach for evaluating spatiotemporal multivariate environmental risks, especially suitable for complex environmental systems that have been either numerically simulated or physically observed. Advocated methodology provides accurate hazard risk forecasts, based on real-time in situ environmental data. Design of offshore structures requires multivariate risk assessment – offshore and naval operations require both short- and long-term risk and reliability analyses. Contemporary risk evaluation techniques often struggle with raw timeseries multivariate data due to intrinsic multidimensionality and nonlinear interconnections among critical system’s dimensions/components. In the current study effectiveness of the Gaidai multivariate risk evaluation method is illustrated by utilizing significant wave heights dataset, measured within two offshore zones: Heidrun and Troll Norwegian oil fields. Analyzing offshore waves being particularly challenging due to their complexity, high nonlinearity, multidimensionality, yet dynamic inter-correlations. Global warming being among several significant factors, affecting ocean and sea wave heights. For naval, offshore and marine structures operating in harsh weather conditions, robust multivariate environmental risk evaluation methods being crucial for both design and safe operations. Current study aims to validate and benchmark state-of-the-art methodology, enabling extraction. Advocated approach allows for efficient yet accurate assessment of global damages, failures or hazard risks for a wide range of complex nonlinear multivariate environmental and energy systems. Primary advantage of presented multivariate reliability methodology lies within its ability to treat complex systems with practically unlimited number of dimensions, while existing reliability methods being mostly limited to univariate and bivariate analyses.

Utilization of School Infrastructure and Its Influence on Students' Academic Performance in Public Secondary Schools in Makueni County, Kenya

School infrastructure forms a major part of housing learners in learning institutions. Utilization of school infrastructure in sheltering students against harsh weather conditions facilitates better attainment of school goals. Academic performance of learners in public county secondary schools in Makueni County was low a reason to carry out this study. The purpose of this study was to determine utilization of school infrastructure and its influence on academic performance in secondary schools in Makueni County. The objective of this study was to establish the level of utilization of school infrastructure and its influence on student’s academic performance in public county secondary schools in Makueni County. The study adopted a mixed methods research design, specifically a convergent parallel research design and was supported by Education Production Function Theory. Research instruments were questionnaires and interview schedules. Validity was achieved through expert judgment and reliability by test-retest technique. The target population was 60 county secondary schools, 60 principals and 1004 teachers. Simple random and stratified sampling techniques were used to select the schools while systematic and purposive sampling was used to sample teachers and principals. The selected sample was 30 county schools, 30 principals, and 286 teachers. Total number of respondents was 316. Descriptive and inferential statistics (means, percentages, and multiple regression) and thematic analysis worked out the level of utilization of school infrastructure on students’ academic performance. Multiple regression showed that Utilisation of school infrastructure showed moderate means of 3.86, which revealed moderate influence existed between its utilisation and students’ academic performance. Qualitative data revealed different themes meant that effective utilization of school infrastructure positively influenced students’ academic performance in county secondary schools in Makueni County. Major conclusion was that there was needed to ensure effective utilisation of school infrastructure in order to improve academic performance. This study would provide important information useful to education policy makers in formulating additional policies leading to effective utilisation of school infrastructure in secondary schools.

Assessments and application of low-cost sensors to study indoor air quality in layer facilities

Indoor poultry facilities often experience poor air quality due to intensive farming and restricted ventilation. Monitoring the air quality in these barns is crucial considering the health of both the birds and producers. Advancements in sensor technologies have led to the development of low-cost sensors (LCS) that can continuously monitor air pollutants. Even though most poultry facilities in Canada are indoors due to harsh winter weather conditions, there is a lack of indoor air quality (IAQ) studies. This study aimed to evaluate the field performance of the LCS network in a table egg farm in Canada, where the sensors were designed specifically for operating in dusty poultry facilities continuously. The LCS monitored IQA parameters such as particulate matter (PM), carbon dioxide (CO2), relative humidity, and temperature in real-time. By implementing a correction factor, the sensor data resulted in an agreement range of 80 ± 20% with a reference instrument. The study observed that PM concentration exceeded several thousand μg/m3, with PM10 at 5.5 × 104 ± 2.2 × 104 and PM2.5 at 6.3 × 103 ± 2.3 × 103, which was found to be most affected by the chicken activity and light regime. The IAQ parameters also exhibited a complex intercorrelation with each other, as well as the outdoor temperature and the building ventilation rate. Sensors were able to make observations that were found only with research-grade instruments in previous studies. Overall, the study showcases the potential of the LCS network as an affordable solution for environmental monitoring in poultry facilities.

Enhancing the performance of photovoltaic using exhausted air from thermal comfort spaces

This paper presents an experimental investigation using the exhaust air from the central air conditioning system as cooling air for the PV modules. Experimental tests were conducted under harsh outdoor weather conditions in Baghdad, Iraq, during the summer session, where the recorded ambient temperature was around 33 to 47 °C. In this study, the exhaust air was flowing in the back side of the PV module to reduce the operating temperature of the PV module and thus improve its performance and electrical efficiency. The results show that the temperature of the PV module decreased from 62.42 to 47.42 °C, the output voltage increased from 14.28 to 16.17 V, the generated electrical power increased from 80.39 to 87.89 W, and the electrical efficiency increased from 13.88% to 15.18%. Overall, the enhancement percentage of the PV temperature, voltage, power, and electrical efficiency is 23.7%, 13%, 9.33%, and 9.33%, respectively, compared to the PV module without cooling.

How Do Butterflies Use Silk to Attach their Pupae to Trees?

Butterflies constitute approximately 10% of lepidopteran insects, and along with silkworms, they can produce silk; however, this feature is often ignored. In the present study, we observed two primary methods used by butterflies to hang pupae on trees using silk: pupa adheraena (Danaus chrysippus) and pupa contigua (Papilio polytes). Anchoring the abdominal ends of pupae with a silk pad was the most common method used in both cases, whereas wrapping silk around the body using a silk girdle was a method unique to pupa contigua. The connection between the cremaster and silk pad was observed to be similar to that between the hook and loop of a Velcro fastener, except that the cremaster hook is anchor-shaped rather than being a single hook. Such a connection will remain secure, ensuring the safety of the pupae during exposure to wind and rain. Through determining the mechanical properties of silk, the performance of butterfly silk was found to be weaker than that of silkworm silk. Therefore, the P. polytes silk girdle adopts the strategy of merging a dozen silk threads to improve its strength and toughness, thereby making it difficult to break. In addition, we explained how the protein sequence and structure of butterfly silk impact its performance. In conclusion, we discovered that butterfly pupae develop unique body features to establish secure bonds with silk. This enables them to effectively undergo metamorphosis and endure harsh weather conditions and surroundings.

Biological and fishery indicators for the small-scale marble crab fishery in Northern Patagonia: recommendations for improving a monitoring program and stock assessment of a data-limited fishery

Small-scale fisheries have been typically data-limited despite their economic importance for local communities. This is especially true in zones where fishing operations occur in remote areas under harsh weather conditions. Crab fishery in Chile is exclusively artisanal, and marble crab (Metacarcinus edwardsii) has the highest landing records. This species is found in most parts of the coast of Chile, but it is mainly caught in the south of the country (including Patagonia). Fishery management is data-limited, and monitoring has not established the spatial and temporal variability baseline necessary to determine its exploitation status. This fishery is currently evaluated annually under a scheme based on reporting biological and fishery information, primarily from the landing ports and secondarily from fishing grounds. In the present study, we collected data from fishing grounds on board artisanal fishing vessels around 45°S during an annual cycle to establish indicators based on catch per unit effort (above and below minimum legal size), size, sex ratio, and the relationship between weight and size. Our results showed that fishery and biological indicators respond more to seasonal patterns than to expected spatial heterogeneity related to different fishing grounds: proportional stock density (lowest in winter), sex ratio (biased toward males in winter), retained catch (highest in autumn), and released catch (highest in winter), while the average size of the largest 10% of the sample only showed differences between males and females. Additionally, released catch varied according to soak time, which indicates the effectiveness of escape rings incorporated in the traps. These results lead to recommendations related to the current monitoring program, which should include the selection of a limited number of fishing grounds standardized by season and the incorporation of information related to soak time and the presence of escape rings. Finally, this study highlights the importance of on-board scientific monitoring for any fisheries, even those of small scale.

К ТЕХНОЛОГИИ ВОЗДЕЛЫВАНИЯ ЯРОВОЙ ПШЕНИЦЫ НА ЧЕРНОЗЕМЕ ОБЫКНОВЕННОМ В КРАСНОЯРСКОЙ ЛЕСОСТЕПИ

The purpose of research is to develop an effective technology based on assessing the impact of reducing energy costs for soil cultivation with an increase in the use of chemicals (fertilizers and herbicides) on the productivity of different varieties of wheat. Based on the results of many years of research at the laboratory of varietal agricultural technologies of the Krasnoyarsk Research Institute of Agriculture, an assessment was made of the effect of surface tillage using the BDM-6 “Rubin” disc harrow and milling, without main treatment, on the yield of 4 varieties of spring wheat in comparison with traditional technology based on moldboard plowing (control ). The harvest was formed under harsh weather conditions, which limited productivity to 0.6–3.6 t/ha. The energy coefficient with minimal processing using ammonium nitrate was 4.8 and with direct sowing without the use of mineral fertilizers it was 4.4. This circumstance necessitates the need to expand methods of soil preparation for sowing, especially after the use of minimal tillage. As an experiment, the surface of the soil was milled with FBN 1.1 for high-quality sowing using a disc seeder SN-16. Treatment with a milling cutter was carried out after the scattering of ammonium nitrate. In general, resource-saving technologies (sowing after disking and sowing without main tillage before milling) reduced production costs by 11–13 %, and fuel consumption decreased by 42–43 % compared to technology based on plowing. Carrying out pre-sowing treatment with a milling cutter guarantees complete cleansing of the soil from early weed shoots; control is carried out using a UAV (unmanned aerial vehicle). Differences in yield levels between tillage options are insignificant; NSR05 was 0.4 t/ha. And the influence of mineral fertilizers, well mixed with the soil in the surface layer using a milling cutter, has increased sharply.

The dynamic behavior and nonlinear characteristics of aircraft landing gear retraction mechanism considering atmospheric corrosion

Atmospheric corrosion poses a significant challenge for the components of aircraft exposed to prolonged harsh weather conditions, critically impacting the safety property of aircraft landing gear retraction mechanism (ALGRM). This paper focuses on the ALGRM of a specific aircraft type, presenting a new modeling and analysis approach to assess the influence of atmospheric corrosion on dynamic behavior and nonlinear characteristics of mechanism. Initially, the dynamic model of ALGRM incorporating clearance joints is established using Lagrangian method. Numerical solutions are then obtained using the Runge-Kutta method. Subsequently, COMSOL simulation software is employed to simulate the corrosion morphology of the bearing under atmospheric corrosion, integrating the corroded bearing surfaces into the dynamic model of the mechanism. Finally, the study investigates the effects of corrosion time and different bearing materials on the dynamic behavior and nonlinear characteristics of ALGRM considering atmospheric corrosion. The results indicate that as corrosion time increases, the degradation of the dynamic behavior of ALGRM becomes more pronounced, and there are significant variations for corrosion morphology of bearing made of different materials under atmospheric corrosion. The findings of this study contribute to a broader understanding of the complex interactions between the dynamic behavior of aircraft and environmental degradation, providing some insights for designing ALGRM that are more durable and adaptable to atmospheric corrosion environments.

Perceptions of El Niño-Southern Oscillation (ENSO) and La Niña Shape Fishers’ Adaptive Capacity and Resilience

Much research has raised concerns about how a warming planet will interact with natural cyclical climatic variations, and the implications for the resilience and vulnerability of coastal communities. As the anticipated effects of climate change will continue to intensify, it is necessary to understand the response and adaptive capacity of individuals and communities. Coastal communities in Ecuador have evolved in an environment of such cyclical climatic variations referred to as El Niño-Southern Oscillation (ENSO) and La Niña. These climatic events are frequently characterized by extreme variations in precipitation, violent storms, and coastal flooding during El Niño and lowered sea water temperatures and drought during La Niña. This paper draws on survey data and long-term ethnographic research in Ecuadorian coastal communities to explore how fishers understand the impacts of ENSO and implications for their livelihood decisions and resilience to climate variability. The results suggest that fishers along the coast of Ecuador understand and respond differentially to the impacts of ENSO depending on social, cultural, environmental, and geographical factors. These differential levels of response suggest that livelihood diversification may uphold social resilience, which has implications for how coastal communities may adapt to the increasingly harsh weather conditions predicted by many climate models. Our findings further suggest that the impacts of El Niño are more salient than the impacts of La Niña; these findings have significant implications for fisheries management and science communication.

Lightweight, robust and conductive MXene/SiO2 nanofiber aerogels for excellent sensing and thermal management properties

Flexible pressure sensors embody outstanding mechanical and sensing performance, particularly in the fields of personal health monitoring and artificial intelligence, while catering to multifunctional applications resilient against harsh weather conditions. Among these, Ti3C2Tx MXene-based aerogel materials with high surface area and excellent conductivity have attracted a lot of attention. However, there are big challenges in improving the mechanical properties at low densities and designing multi-level pore structures. Herein, the prepared silane monomers (MP) are firstly synthesized by 3-(Trimethoxysilyl) propyl methacrylate (MPTES) and polyethylene glycol diacrylate (PEGDA), then polydopamine-modified silicon dioxide (PDA-SiO2) nanofibers employed with MXene nanosheets form covalent cross-linking nanofiber aerogels. The multi-level stable structure improves both mechanical strength and elasticity. The assembled MXene/MP/PDA-SiO2 pressure sensors exhibit a high sensitivity of −0.83 kPa−1, a rapid response time of 48 ms, a minimum 1 % strain detection limit, and reliable stability over 10,000 cycles. Furthermore, these sensors can be used for human motion detection and health diagnostics, and show good personal thermal management performance. This work holds a promising candidate for the next generation of multifunctional flexible electronic devices.