Harsh Weather Research Articles

Measurement of medium-voltage AC air arc temperature and particle number density based on dual-wavelength Moiré deflection technology

AC air arcs are generated in medium-voltage (MV) power systems under the effect of harsh weather conditions, equipment aging, and high penetration of distributed generation, threatening equipment and public safety. The arc current and temperature are low due to the wide application of arc suppression devices. In this scenario, the MV AC air arc does not satisfy the local thermodynamic equilibrium (LTE) condition. In addition, the repeated arcing and extinguishing processes further complicate the arc discharge mechanism, which bring challenges in the modeling and detection of MV AC air arcs. Experimental methods are a direct and efficient approach to determine the properties of arc plasmas. In this study, a dual-wavelength Moiré deflection diagnostic system was established to determine the time evolution of the particle density and radial distribution of the temperature in an MV AC air arc without relying on the LTE assumption. The electron number density and heavy particle number density change transiently during the arc discharge process and change gradient along the radial direction. The heavy particle temperature and electron temperature were then calculated based on the measured particle number density. During the arcing stage, the temperature of the electrons exceeded that of the heavy particles significantly, and the arc deviated from LTE. Finally, the limitations of the traditional single-wavelength Moiré deflection method are analyzed. The classic single-wavelength Moiré deflection method, while capable of estimating heavy particle temperature in plasma, exhibits a significant error in electron density estimation compared to the dual-wavelength Moiré deflection method.

Lightning-Induced Wildfires: An Overview

Wildfire causes environmental, economic, and human problems or losses. This study reviewed wildfires induced by lightning strikes. This review focuses on the investigations of lightning mechanisms in the laboratory. Also, the paper aims to discuss some of the modeling studies on lightning-induced wildfires at different geographical locations using satellite-recorded lightning data and different statistical analyses. This review established that irrespective of the different models used to predict lightning wildfires, there is still a lack of understanding of the lightning-strike ignition mechanism; few experiments have been modeled to establish the dynamics of lightning-strike ignition. Therefore, further research needs to be carried out in this area to understand lightning ignition. It was ascertained from the various statistical modeling that lightning-induced wildfires are exacerbated by the abundant availability of fuel with a lower moisture content and high lightning efficiency. Moreover, because of changes in the climate and weather conditions, i.e., harsh weather and climate conditions due to anthropogenic activities, lightning-induced ignition wildfires have increased over the years, and they are expected to increase in the future if the climate and weather conditions continue to aggravate. Although various modeling studies have identified that lightning-induced wildfires have increased recently, no preventive measures have been conclusively proposed to reduce lightning-caused wildfires. Hence, this aspect of research has to be given critical attention. This review presents information that gives a profound understanding of lightning-induced wildfires, especially factors that influence lightning wildfires, and the state-of-the-art research that has been completed to understand lightning-induced wildfires.

Evaluation and comparison of 11 sets of gridded precipitation products over the Qinghai-Tibet Plateau

The Qinghai Tibet Plateau (QTP) poses challenges in developing high-quality gridded precipitation data with high spatial and temporal resolution due to its complex terrain, harsh weather conditions, and sparse gauge observations. Previous research showed that gridded precipitation products from remote sensing satellites, reanalysis, and merged data are useful over the QTP. However, the precipitation products were usually calibrated against ground meteorological stations, so the evaluation based on these stations might be misleading. This study collected 11 sets of gridded precipitation products on the QTP, and evaluated them by using 53 independent rain gauges obtained from the hydrological yearbook (HY). The results showed that the CMFD precipitation product performed better than other products at meteorological sites from the National Meteorological Information Center (NMIC), with average daily and monthly correlation coefficients (CCs) of 0.55 and 0.94 and root mean square errors (RMSEs) of 3.78 and 0.44 mm/d, respectively. Following closely is CLDAS. In contrast, MSP performed best at HY sites, with average CCs of 0.70 and 0.91 and RMSEs of 2.47 and 0.65 mm/d, respectively. The following are TPHiPr, GSMAP, and CLDAS. Some global products, such as CHIPRS and CMORPH, performed poorly over the QTP. Most products overestimated the frequency of light precipitation (0.1– 0.5 mm/d) and underestimated the frequency of heavy precipitation. The fluctuation amplitudes of relative deviations for all precipitation products are markedly greater at hydrological sites compared to that at meteorological sites. Therefore, it is essential to consider correcting magnitude deviations before using these products. Based on independent assessment, this study suggests that further improvements are still needed for precipitation products on the QTP.

Low-Power and Wireless Communication Research on Underground Displacement Three-Dimensional Monitoring System.

Underground displacement monitoring is a crucial means of preventing geological disasters. Compared to existing one-dimensional methods (measuring only horizontal or vertical displacement), the underground displacement three-dimensional measurement method and monitoring system proposed by the author's research team can more accurately reflect the internal movement of rock and soil mass, thereby improving the timeliness and accuracy of geological disaster prediction. To ensure the reliability and long-term operation of the underground displacement three-dimensional monitoring system, this article further introduces low-power design theory and Bluetooth wireless transmission technology into the system. By optimizing the power consumption of each sensing unit, the current during the sleep period of a single sensing unit is reduced to only 0.09 mA. Dynamic power management technology is employed to minimize power consumption during each detection cycle. By using Bluetooth wireless transmission technology, the original wired communication of the system is upgraded to a relay-type wireless network communication, effectively solving the problem of the entire sensing array's operation being affected when a single sensing unit is damaged. These optimized designs not only maintain monitoring accuracy (horizontal and vertical displacement errors not exceeding 1 mm) but also enable the monitoring system to operate stably for an extended period under harsh weather conditions.

Optimizing the maintenance threshold in presence of shocks: A numerical framework for systems with non-monotonic degradation

Shocks have attracted considerable interest in reliability and maintenance engineering because of their impact on vulnerable systems. Most industrial systems suffer from both internal degradation caused by fatigue and wear-out, and external shocks that often occur randomly due to harsh weather conditions, overloading, etc. Developing maintenance optimization models without taking these stochastic shocks into account is often ineffective. This paper develops a model to optimize the maintenance alarm threshold for a single-component continuously monitored system which is exposed to both fatal and non-fatal shocks in the presence of lead time for hard time maintenance. The shocks occur randomly according to a homogeneous Poisson process during the whole degradation process and have a stochastic impact on the degradation level, while the system resistance to shocks decreases as the system approaches failure. We propose a new numerical maintenance optimization model to find the solution without Monte-Carlo simulation and the model is compared to the Wiener process. A numerical example and a real-time experimental case study on roller bearings are used to demonstrate the effectiveness of the model. The results show that the model is capable of improving maintenance decision-making in terms of failure probability and risk perspective.

Extreme Weather Risk to Military Operations in a Changing Climate

History demonstrates harsh weather conditions introduce uncertainty and risk into warfare. James L Regens examines the implications of extreme weather risk in a changing climate for military operations within and across the six domains of warfare and, therefore, for strategy. Because it is imperative that operations and campaigns are feasible meteorologically, reliably forecasting the frequency and intensity of extreme weather is one of the most important challenges posed by climate change for the US and allied militaries. That knowledge, combined with understanding extreme weather’s impacts on human performance, equipment and installations, is essential for conducting operations and informing strategy.◼

Impact of Climate Change on Coastal Tourism Destinations

This research paper aims to explore the multifaceted impacts of climate change on coastal tourism destinations. Coastal regions, known for their natural beauty and recreational opportunities, are increasingly vulnerable to the adverse effects of climate change. Rising sea levels, extreme weather events, and changes in temperature and precipitation patterns pose significant challenges to the sustainability and attractiveness of these destinations. Through an in-depth analysis of existing literature, case studies, and empirical data, this paper examines the direct and indirect consequences of climate change on coastal tourism, including impacts on infrastructure, ecosystems, local communities, and visitor experiences. Additionally, the paper explores adaptation and mitigation strategies that can help enhance the resilience of coastal tourism destinations in the face of climate change. The purpose of this study paper is to examine the significant effects that climate change will have on coastal tourist spots around the globe. Coastal regions are more susceptible to harsh weather, erosion, and habitat loss as a result of rising global temperatures and rising sea levels. The study will explore the particular difficulties that these modifications present to well-known tourist destinations, looking at the possible negative effects on the economy, the environment, and society. The study will also look at adaptation tactics used by coastal towns and the travel and tourism sector to lessen the negative consequences of climate change. The research endeavors to offer a complete understanding of the dynamic interaction between climate change and coastal tourism through the analysis of case studies from various places. In order to create sustainable tourism practices that strike a balance between the industry's economic benefits and the preservation of delicate coastal ecosystems, legislators, environmentalists, and the tourism sector need to take this research very seriously.

Does Inclement Weather Increase the Risk of Cardioembolic Stroke in Kashmir Valley?

Background Cardioembolic strokes are a common cause of mortality and morbidity because they are usually big and multiple. Despite extensive advances in the determination and management of modifiable risk factors of these strokes, a significant proportion are attributed to non-modifiable factors. We wanted to test the hypothesis that cardioembolic strokes and no other subtypes of ischemic stroke are associated with inclement weather in Kashmir Valley where winter seasons have harsh weather. Results A total of 540 ischemic stroke patients were included in the study of which cardioembolic strokes were most common. Cardioembolic strokes were more common in the winter season and associated with lower minimum and maximum temperatures. Conclusion Evaluation and management of cardioembolic strokes during winter months may demand more attention, particularly in elderly individuals and those with risk factors for atrial fibrillation.

A top-down and in situ strategy for intrinsic acicular nanostructure enhanced ultradurable superhydrophobic and anti-icing aramid fabric

Essential requirements of protective clothing with multi-scenario practicability deserve intensive attention. Aramid fabric is widely used to protect industrial and outdoor workers operating under various hazardous conditions but is susceptible to fouling, subzero cold water and icing, resulting in severely deteriorated protective properties. However, the chemical inertness of aramid fabrics limits their further functionalization. This issue is addressed herein by developing a novel top-down strategy to construct an intrinsic densely packed acicular nanostructure on the surface of aramid fiber through the proton donor-assisted deprotonation-induced roughening (PAIR) method. The PAIR treatment consists of extracting hydrogen protons from the amide moiety and controllably dissociating the outer shell of the aramid fibers without destroying its hard-core structure. Such a “rough-surface-on-intact-core” texture endows the fabric with greatly enhanced water repellency, anti-icing and anti-fouling properties without sacrificing its impressive mechanical properties, moisture permeability and flame retardancy. Remarkably, the treated fabric can load 37 times its own weight in water, presenting an increased buoyancy and demonstrates an icing delay time of 1920 s, which is 1150 % that of a pristine aramid fabric. Featuring the easy processability, high endurance and multiple functions, the fabric is promising for applications in personal protective equipment and advanced functional textiles with multiple tasks under harsh weather events.

Facultative migration in two thrush species (Fieldfare and Redwing): Rowanberry abundance is more important than winter weather

Facultative migration is thought to be influenced by food and weather, with birds remaining in northern areas if food is abundant and weather conditions are benign, but migrating south when food is scarce and weather is harsh. However, the relative importance of these two factors has rarely been tested with long-term data, and effects of weather are poorly documented. Here, I assess whether winter numbers of the Fieldfare (Turdus pilaris) and the Redwing (T. iliacus) in southern Norway during the period 1980–2020 varied in relation to the abundance of an important source of winter food (rowanberries, Sorbus aucuparia) and indices of winter harshness (North Atlantic Oscillation index, temperature, duration of snow cover). Two regions with contrasting winter harshness (western Norway with a maritime climate, eastern Norway with a continental climate) were compared. Winter numbers of Fieldfare in both regions, and Redwing in eastern Norway, were highest in years with high rowanberry abundance. Weather had mixed influence on thrush winter numbers, but interacted with rowanberry abundance in several cases so that small numbers of thrushes occurred with the combination of low rowanberry abundance and harsh weather. Such interactions occurred both in eastern and western Norway, and for both species, including for the Redwing in western Norway. In conclusion, facultative migration was strongly related to food availability with large numbers wintering in years with large rowanberry crops, and with additional effects of harsh weather working in concert with low rowanberry abundance to reduce wintering numbers to low levels in some years.

Variation of extreme values of rainfall and temperature in Subarnarekha River basin in India

Abstract In recent years, the Subarnarekha River basin has frequently experienced harsh weather and has also observed extreme floods during monsoons and a shortage of water during lean periods. Hence, in this study, the data of extreme values of rainfall and maximum–minimum temperatures from the years 1990 to 2020 in the Subarnarekha River basin have been analysed. The trend analysis of annual extreme rainfall, maximum–minimum temperatures, extreme diurnal temperature range, and number of rainy days have been determined using the Mann–Kendall test and Sen's slope estimator. Further, the analysis has also been carried out to study the shifting of the onset date of monsoon. The results show that extreme rainfall showed a significant increasing trend at a 95% level of confidence in the upper and middle parts of the basin, whereas it had a decreasing trend in the lower part. Annual extreme maximum temperature indicated a decreasing trend of 0.03 and 0.08 °C/year in the upper and middle parts, respectively, and the decrease in extreme minimum temperature in the lower part was 0.03 °C/year. No significant variations in the number of rainy days have been observed; however, a major shift in the onset date of the monsoon was observed during the selected time-period.

INVESTIGATING THE IMPACT OF INNOVATION TECHNOLOGIES IN LOGISTICS (CROSSING TRANSPORTATION MODEL: CASE STUDY OF THE LANGARA - KENDARI ROUTE)

Konawe Islands is a regency in the Southeast Sulawesi Province. This area heavily relies on Kendari City, the provincial capital, to support daily necessities, recreational activities, and higher education pursuits for the people of Konawe Islands. Wooden boats and ferries serve as the primary means of transportation for the locals. However, during harsh weather, only ferries is operational. Yet, there have been loading violations on ferries, increasing the risk to maritime safety. This research aims to formulate ways to address loading issues on ro-ro ferries along the Langara-Kendari route, ensuring compliance with laws and facilitating smooth cargo distribution. The distribution system is structured based on the method persona user and empathy mapping. Research findings indicate that distribution service users require a freight forwarder for large-scale cargo and consolidation for smaller-scale loads. Therefore, the author recommends the use of applications like Uber, Grab, and Uber to resolve this issue.

Temporal variations in female moose responses to roads and logging in the absence of wolves.

Animal movements, needed to acquire food resources, avoid predation risk, and find breeding partners, are influenced by annual and circadian cycles. Decisions related to movement reflect a quest to maximize benefits while limiting costs, especially in heterogeneous landscapes. Predation by wolves (Canis lupus) has been identified as the major driver of moose (Alces alces) habitat selection patterns, and linear features have been shown to increase wolf efficiency to travel, hunt, and kill prey. However, few studies have described moose behavioral response to roads and logging in Canada in the absence of wolves. We thus characterized temporal changes (i.e., day phases and biological periods) in eastern moose (Alces alces americana) habitat selection and space use patterns near a road network in a wolf-free area located south of the St. Lawrence River (eastern Canada). We used telemetry data collected on 18 females between 2017 and 2019 to build resource selection functions and mixed linear regressions to explain variations in habitat selection patterns, home-range size, and movement rates. Female moose selected forest stands providing forage when movement was not impeded by snow cover (i.e., spring/green-up, summer/rearing, fall/rut) and stands offering protection against incidental predation during calving. In winter, home-range size decreased with an increasing proportion of stands providing food and shelter against harsh weather, limiting the energetic costs associated with movement. Our results reaffirmed the year-round aversive effect of roads, even in the absence of wolves, but the magnitude of this avoidance differed between day phases, being lower during the "dusk-night-dawn" phase, perhaps due to a lower level of human activity on and near roads. Female moose behavior in our study area was similar to what was observed in landscapes where moose and wolves cohabit, suggesting that the risk associated with humans, perceived as another type of predator, and with incidental predators (coyote Canis latrans, black bear Ursus americanus), equates that of wolf predation in heavily managed landscapes.

Conspecific density drives sex-specific spatial wintertime distribution and hoarding behaviour of an avian predator

Most studies on intraspecific competition, i.e., competition among individuals of the same species, have been conducted during the breeding season. Yet, at northern latitudes, intraspecific competition is expected to be particularly strong under the harsh weather conditions of the non-breeding season with limited number of resources available per individual. We studied the food-hoarding behaviour of wintering Eurasian Pygmy Owls (Glaucidium passerinum) along with sex- and age-specific spatial distribution in relation to fluctuating main prey abundance (voles) and conspecific density using a 15-year dataset. In low vole abundance years, increasing conspecific density reduced the total prey number stored by an owl, suggesting high costs of exploitative competition. The distance between the stores of nearest neighbours was greater when both were females, suggesting that the spatial avoidance is driven by sex-specific competition. However, food stores of females had a larger amount of prey items, especially when the nearest neighbour was of the same sex. The number of stores hoarded by an owl increased with increasing conspecific densities. Distributing the prey items to multiple store-sites instead of one (shifting from larder-hoarding towards scatter-hoarding) can help to reduce the overall loss to potential pilfering when conspecific density is high. These results combined suggest that high conspecific density inflames sex-specific interference competition, rather than solely exploitative competition, and in turn drives the observed sex-specific spatial distribution. Adopting a sex-specific spatial distribution according to hoarding and aggressive behaviour can be a way to reduce the severity of intraspecific competition locally and could have cascading effects on the prey community.

GT-YOLO: Nearshore Infrared Ship Detection Based on Infrared Images

Traditional visible light target detection is usually applied in scenes with good visibility, while the advantage of infrared target detection is that it can detect targets at nighttime and in harsh weather, thus being able to be applied to ship detection in complex sea conditions all day long. However, in coastal areas where the density of ships is high and there is a significant difference in target scale, this can lead to missed detection of some dense and small targets. To address this issue, this paper proposes an improved detection model based on YOLOv5s. Firstly, this article designs a feature fusion module based on a fusion attention mechanism to enhance the feature fusion of the network and introduces SPD-Conv to improve the detection accuracy of small targets and low-resolution images. Secondly, by introducing Soft-NMS, the detection accuracy is improved while also addressing the issue of missed detections in dense occlusion situations. Finally, the improved algorithm in this article increased mAP0.5 by 1%, mAP0.75 by 5.7%, and mAP0.5:0.95 by 5% on the infrared ship dataset. A large number of comparative experiments have shown that the improved algorithm in this article is effective at improving detection capabilities.

Improving the flight endurance of multi-rotor drones in windy days

Most recently, the technology of unmanned vehicles/systems (UVs/USs) has experienced substantial growth. These vehicles can operate on land, in water as well as and even through the air. They have become increasingly important in various civil applications, incorporating surveillance, precise farming, imagery collection, and search and rescue operations, surpassing manned systems in many aspects. Increased mission safety and cheaper operating expenses are provided by unmanned vehicles. UAVs, often known as unmanned aerial vehicles, are one of them that are widely utilized in construction projects because of its benefits including low costs for upkeep, simple deployment, the capacity to hover, and outstanding mobility. The most significant challenge facing the application of drones is their endurance, especially in harsh and windy weather conditions where drones consume power at a faster rate. In this paper, this work explores improvements in drone endurance through lightweight material design, battery enhancements, and path planning by studying and organizing relevant literature from various authors. These advancements aim to effectively extend the flight time of drones, thereby enabling them to successfully complete missions.

Human intrusion detection for high-speed railway perimeter under all-weather condition

PurposeThe paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.Design/methodology/approachThis paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.FindingsSimulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.Originality/value(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.

Bionic vine-stems structure for enhancing electrochromic cyclic stability and mechanical stability of multiband spectral regulation fiber

Wearable electrochromic (EC) devices can adjust visible-infrared spectra demonstrate promising potential for applications in display, decoration, personal thermal management, and adaptive thermal camouflage. However, existing flat layer-layer EC devices are hindered by poor air permeability, limited flexibility, and integration difficulties with fabrics, particularly in the realm of intelligent wearables. The creation of highly efficient fiber-shaped infrared (IR) modulation devices with exceptional structural and performance stability represents a significant challenge. We draw inspiration from the arboreous vine-stems structure observed in Chinese wistaria, which effectively minimizes the risk of damage to their vine and stems during harsh weather conditions. We have successfully designed a wearable high efficient multiband spectral regulation fiber (MSRF) with a bioinspired vine-stems structure using carbon fiber and polyaniline (PANI) as the active layer. The planar working electrode (Au) with PANI deposited on its surface was spirally wound around the counter electrode (carbon fiber) and separated by a gel electrolyte (PC/LiClO4), with polyolefin serving as the encapsulation layer. The distribution of electrical potential and lithium ions in the MSRF were analyzed using finite element analysis, demonstrating exceptional electrochromic stability without the length limit of the fiber. Moreover, the MSRF exhibited exceptional IR emissivity (△ε = 0.528) within the 8–14 μm range, fast response time (2.44 s) at low applied potentials (−0.8 V and 0.8 V), robust long-term cycling stability (at least 5000 cycles), and remarkable mechanical stability (at least 5000 bending cycles). The compatibility of the fiber with fabric and potential for patterning using MSRF with high length was also explored, providing new insights into the development of wearable adaptive thermal camouflage and spectral regulation fiber devices.

Grid‐based assessment of hydrogen leakages for an offshore process to improve the design and human performance

AbstractHydrogen is gaining global recognition as a sustainable energy source, but its combustible nature raises concerns, especially in congested offshore settings. Steam methane reforming (SMR) remains the predominant hydrogen production method; however, offshore SMR facilities exposed to harsh weather could potentially compromise safety because of leakages. This study uses the fire dynamics simulator (FDS) to carry out the first‐of‐its‐kind CFD modeling of hydrogen leakage and its wind‐influenced dispersion on an offshore SMR platform. It also provides the spatial risk that accounts for the probabilities of human errors and wind speeds. The study uses a grid‐based approach with 120 monitor points (MPs) to measure locally dispersed gas concentration. At 2 m/s wind speed, only nine grids contain explosive concentrations while the rest remain safe. At 5 m/s, the flammable zones increase by 133%, affecting 21 grids. Extreme wind speeds of 12.5 m/s have limited impact, but SMR1 exhibits higher stoichiometric concentrations. MPs 43–48 record flammable concentrations at all wind speeds; however, at 12.5 m/s the explosion risk is well below the threshold of 1 × 10−4 due to the low wind occurrence probability. Overall, this research contributes to addressing the safety concerns associated with hydrogen in offshore settings and provides a foundation for future risk assessments.

Composite aerogel incorporating low temperature phase change microcapsules for enhanced thermal insulation

Cryogenic transportation and storage confront significant challenges from harsh weather conditions, heightened energy consumption, and epidemic situations, compelling the need for the creation of exceptionally efficient thermal insulation materials. To address this demand, a composite phase change aerogel was designed in this study through incorporating low-temperature microencapsulated phase change microcapsules (MPCM) into a cellulose nanofiber/polyvinyl alcohol (CNF/PVA) system. The MPCM, consisting of a polyurethane-acrylate (PUA) shell and an n-tetradecane core, exhibited excellent encapsulation performance with leak-proof capability. Remarkable low-temperature phase change energy storage properties were observed, including a phase change temperature of approximately 6 °C and an impressive phase change enthalpy of 112 J/g. The MPCM also demonstrated stability during successive heating–cooling repetitions, maintaining its heat storage capacity and morphology for at least 300 cycles. These exceptional thermal characteristics endowed the resulting aerogel with effective thermal insulation and temperature retardation abilities. Meanwhile, the integration of CNF/PVA as the matrix in the composite aerogel led to minimal degradation of thermal storage performance compared to pure MPCM. Moreover, the addition of MPCM significantly enhanced the compressive strength, reaching 5.6 times that of the neat CNF/PVA aerogel. The composite aerogel showed a notably low density of 0.165 g/cm3 and could be reshaped through heating. This work provides a simple yet effective idea for designing bulk materials with low-temperature phase change capabilities, offering promising prospects in the field of thermal insulation.