Different Types Of Environments Research Articles

Types of Severe Convective Wind Events in Eastern Australia

Abstract Severe winds associated with thunderstorms and convection are a hazard affecting key aspects of society, including emergency management and infrastructure design. Several studies around the world have shown that severe convective winds (SCWs) can occur due to several different processes, in a range of atmospheric environments, with significant regional and temporal variations. However, in eastern Australia, the types of SCWs and their variability have not been assessed outside of individual case studies. Here, a combination of reanalysis, lightning, radar, and station data are used to characterize a set of 36 SCW events in four locations in eastern Australia. These events are objectively chosen based on the strongest measured wind gusts from station data (greater than 25 m s−1) over a 14-yr period, with 6-hourly lightning data and a 30-dBZ radar reflectivity threshold used to infer moist convective processes. Radar data analysis suggests that these SCW events are produced by several different types of parent thunderstorms, with station observations suggesting a range of temporal characteristics for these different event types. A clustering algorithm applied to environmental data is used to suggest three dominant types of events, based on low-level moisture, low-level temperature lapse rate, and deep-layer mean wind speed and vertical shear. Based on the distribution of synoptic conditions and thunderstorm properties for each environmental cluster, it is suggested that these three event types correspond to the following: 1) shallow vertical transport of strong synoptic-scale winds to the surface, 2) downbursts driven by subcloud evaporation, and 3) intense thunderstorms including supercells. Significance Statement The purpose of this study is to better understand the different types of severe wind events in eastern Australia that are produced by convective storms. We looked at 36 historical cases in four locations and find that severe winds can be produced by very different classes of convective storms. We also suggest that there are three key types of atmospheric environment that are associated with events in this region. These environments vary in terms of the vertical structure of temperature, moisture, and wind speed above the surface. Understanding the different types of environments that lead to severe convective winds can help to reduce uncertainties in future climate projections for this region based on environmental changes.

Development of Cloud Autonomous System for Enhancing the Performance of Robots’ Path

With the development of computer technology and artificial intelligence (AI), service robots are widely used in our daily life. At the same time, the manufacturing cost of the robots is too expensive for almost all small companies. The greatest technical limitations are the design of the service robot and the resource sharing of the robot groups. Path planning for robots is one of the issues playing an important role in every application of service robots. Path optimization, fast computation, and minimum computation time are required in all applications. This paper aims to propose the Google Cloud Computing Platform and Amazon Web Service (AWS) platforms for robot path planning. The aim is to identify the effect and impact of using a cloud computing platform for service robots. The cloud approach shifts the computation load from robots to the cloud server. Three different path-planning algorithms were considered to find the path for robots using the Google Cloud Computing Platform, while with AWS, three different types of environments, namely dense, moderate, and sparse, were selected to run the path-planning algorithms for robots. The paper presents the comparison and analysis of the results carried out for robot path planning using cloud services with that of the traditional approach. The proposed approach of using a cloud platform performs better in this case. The time factor is crucially diagnosed and presented in the paper. The major advantage derived from this experiment is that as the size of the environment increases, the respective relative delay decreases. This proves that increasing the scale of work can be beneficial by using cloud platforms. The result obtained using the proposed methodology proves that using cloud platforms improves the efficiency of path planning. The result reveals that using the cloud computing platform for service robots can change the entire perspective of using service robots in the future. The main advantage is that with the increase in the scale of services, the system remains stable, while the traditional system starts deteriorating in terms of performance.

The exploration of marginal spaces in Central-West Patagonia and the role of discontinuous occupation of forests and highlands

Regions with low population density, which are geographically marginal with respect to the most frequently occupied areas, are theoretically more prone to discontinuities in human occupation. This is the case in Central-West Patagonia (Chile, South America), where the discontinuities have had different characteristics and extents, some even lasting millennia. This work proposes that, given the prolonged and repeated periods of abandonment of some areas in Central-West Patagonia, its exploration is not to be considered a unique, one-time process; rather, it occurred more than once throughout its history. Because ascertaining each exploration is complex, this process can be investigated by focusing on spaces that represent the incorporation of new areas as human groups were enlarging their ranges of action. With this objective, updated archaeological data are presented in two different types of environments of the region: forests and highlands. These environments were marginal sectors that were not utilized as frequently or intensely as the valleys and where the archaeological record would be expected to preserve the actions associated with exploration contexts. The preliminary nature of data precludes defining exploratory contexts, but it is distinct in orienting its search in time and space.

Towards a Novel Cost-Effective and Versatile Bioink for 3D-Bioprinting in Tissue Engineering

3D-bioprinting for tissue regeneration relies on, among other things, hydrogels with favorable rheological properties. These include shear thinning for cell-friendly extrusion, post-printing structural stability as well as physiologically relevant elastic moduli needed for optimal cell attachment, proliferation, differentiation and tissue maturation. This work introduces a cost-efficient gelatin-methylcellulose based hydrogel whose rheological properties can be independently optimized for optimal printability and tissue engineering. Hydrogel viscosities were designed to present three different temperature regimes: low viscosity for eased cell suspension and printing with minimal shear stress, form fidelity directly after printing and long term structural stability during incubation. Enzymatically crosslinked hydrogel scaffolds with stiffnesses ranging from 5 to 50 kPa were produced, enabling the hydrogel to biomimic cell environments for different types of tissues. The bioink showed high intrinsic cytocompatibility and tissues fabricated by embedding and bioprinting NIH 3T3 fibroblasts showed satisfactory viability. This novel hydrogel uses robust and inexpensive technology, which can be adjusted for implementation in tissue regeneration, e.g., in myocardial or neural tissue engineering.

A new and rare epigean asellid from western Mexico Caecidotea contrerasbalderasi sp. nov. (Isopoda: Asellidae) with a new suture pattern in pleopod IV for the Mexican epigean species

A new epigean asellid isopod, Caecidotea contrerasbalderasi sp. nov. is described from Nayarit, northwestern Mexico. This new species has morphological characters belonging to two different types of environments, both depigmentation and anophthalmia, indicators of organisms adapted to live in constant darkness as cavernicolous species. Despite showing characteristics of hypogean species, the new taxon does not show elongation of appendages, such as pereiopods, antennae or uropods. Its pleopod IV exopod lacks false sutures. This is a new pattern type “C”, and differs from that observed in types A and B. The description of this new species brings a new total of 101 species and three subspecies, for the genus Caecidotea in North America all morphologically poorly differentiated and with a restricted distribution.

Laser-Powered UAVs for Wireless Communication Coverage: A Large-Scale Deployment Strategy

The use of unmanned aerial vehicles (UAVs) is strongly advocated for sixth-generation (6G) networks, as the 6G standard will not be limited to improving broadband services, but will also target the extension of the geographical cellular coverage. In this context, the deployment of UAVs is considered a key solution for seamless connectivity and reliable coverage. That being said, it is important to underline that although UAVs are characterized by their high mobility and their ability to establish line-of-sight (LOS) links, their use is still impeded by several factors such as weather conditions, their limited computing power, and, most importantly, their limited energy. In this work, we are aiming for the novel technology that enables indefinite wireless power transfer for UAVs using laser beams. We propose a novel UAV deployment strategy, based on which we analyze the overall performance of the system in terms of wireless coverage. To this end, we use tractable tools from stochastic geometry to model the complex communication system. We analyze the user's connectivity profile under different laser charging capabilities and in different type of environments. We show a decrease in the coverage probability by more than 12% in moderate-to-strong turbulence conditions compared to low turbulence conditions. We also show how the connection rate to the aerial network significantly decreases in favor of the terrestrial network for short laser charging ranges. We conclude that laser-powered drones are considered interesting alternatives when placed in LOS with users, in low-to-moderate optical turbulence, and at reasonable ranges from the charging stations.

COST 231-Hata Propagation Model Optimization in 1800 MHz Band Based on Magnetic Optimization Algorithm: Application to the City of Limbé

Network planning is essential for the construction and the development of wireless networks. The network planning cannot be possible without an appropriate propagation model which in fact is its foundation. Initially used mainly for mobile radio networks, the optimization of propagation model is becoming essential for efficient deployment of the network in different types of environment, namely rural, suburban and urban especially with the emergence of concepts such as digital terrestrial television, smart cities, Internet of Things (IoT) with wide deployment for different use cases such as smart grid, smart metering of electricity, gas and water. In this paper we use an optimization algorithm that is inspired by the principles of magnetic field theory namely Magnetic Optimization Algorithm (MOA) to tune COST231-Hata propagation model. The dataset used is the result of drive tests carry out on field in the town of Limbe in Cameroon. We take into account the standard K-factor model and then use the MOA algorithm in order to set up a propagation model adapted to the physical environment of a town. The town of Limbe is used as an implementation case, but the proposed method can be used everywhere. The calculation of the root mean square error (RMSE) between the real data from the radio measurements and the prediction data obtained after the implementation of MOA allows the validation of the results. A comparative study between the value of the RMSE obtained by the new model and those obtained by the optimization using linear regression, by the standard COST231-Hata models, and the free space model is also done, this allows us to conclude that the new model obtained using MOA for the city of Limbe is better and more representative of this local environment than the standard COST231-Hata model. The new model obtained can be used for radio planning in the city of Limbé in Cameroon.

Learning social navigation from demonstrations with conditional neural processes

Abstract Sociability is essential for modern robots to increase their acceptability in human environments. Traditional techniques use manually engineered utility functions inspired by observing pedestrian behaviors to achieve social navigation. However, social aspects of navigation are diverse, changing across different types of environments, societies, and population densities, making it unrealistic to use hand-crafted techniques in each domain. This paper presents a data-driven navigation architecture that uses state-of-the-art neural architectures, namely Conditional Neural Processes, to learn global and local controllers of the mobile robot from observations. Additionally, we leverage a state-of-the-art, deep prediction mechanism to detect situations not similar to the trained ones, where reactive controllers step in to ensure safe navigation. Our results demonstrate that the proposed framework can successfully carry out navigation tasks regarding social norms in the data. Further, we showed that our system produces fewer personal-zone violations, causing less discomfort.

LoRaWAN: Lost for Localization?

Nowadays, the flexible localization solution for various devices for workplace safety is one of the most demanding research questions. Notably, it is expected to provide an acceptable level of precision in different types of environments empowered by wearable technology and Internet-of-Things (IoT) devices. Existing leading localization technologies are adapted for certain conditions, for example, Wi-Fi, Bluetooth low energy (BLE), and ultra-wideband (UWB) are used for indoor areas and various global navigation satellite system (GNSS)-based ones for outdoors. This work focuses on investigating the long-range wide-area network (LoRaWAN) (868-MHz band) as a potential candidate to bridge this gap, being one of the most reliable and recognized communication technologies for the Industrial IoT (IIoT). In the past, the research community had a lot of critics with respect to the applicability of LoRaWAN for localization, while the vision is facing tremendous change over the past two years. The purpose of this work is to assess the feasibility of LoRaWAN as a localization solution for work safety applications in the industrial scenario from different angles. The work is based on two measurement campaigns conducted at the Brno University of Technology (BUT), Brno, Czech Republic, and the University Politechnica of Bucharest (UPB), Bucharest, Romania. The campaigns cover both indoor and outdoor scenarios and provide the practical limitations of the positioning in standalone and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -nearest neighbors ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -NN) powered localization systems. According to the results, LoRaWAN-based localization with relatively dense gateways (GWs) deployment allows for achieving a meter-level accuracy, which may be suitable for the localization of workers.

Corrosion Inhibition, Inhibitor Environments, and the Role of Machine Learning

Machine learning (ML) is providing a new design paradigm for many areas of technology, including corrosion inhibition. However, ML models require relatively large and diverse training sets to be most effective. This paper provides an overview of developments in corrosion inhibitor research, focussing on how corrosion performance data can be incorporated into machine learning and how large sets of inhibitor performance data that are suitable for training robust ML models can be developed through various corrosion inhibition testing approaches, especially high-throughput performance testing. It examines different types of environments where corrosion by-products and electrolytes operate, with a view to understanding how conventional inhibitor testing methods may be better designed, chosen, and applied to obtain the most useful performance data for inhibitors. The authors explore the role of modern characterisation techniques in defining corrosion chemistry in occluded structures (e.g., lap joints) and examine how corrosion inhibition databases generated by these techniques can be exemplified by recent developments. Finally, the authors briefly discuss how the effects of specific structures, alloy microstructures, leaching structures, and kinetics in paint films may be incorporated into machine learning strategies.

Cooperative R&D investment decisions: A fuzzy real option approach

We study the optimal firms' strategies in an R&D oligopoly environment for different types of cooperative agreements under fuzzy uncertainty about the effects of cooperation. We address the problem as an R&D fuzzy bargaining game, in which the firms' fuzzy payoffs are computed using the real exchange option methodology that takes into account the managerial flexibility embedded in the R&D opportunities. The main novelty of our contribution is the parametric description both of the intensity of the collaboration for each dimension involved in the agreement and of its fuzzy impact on the firms' payoffs. Interestingly, we show that the degree of imprecise knowledge has a significant impact on the strategic alliances adopted by firms.

Resistance of 3D-Printed Components, Test Specimens and Products to Work under Environmental Conditions-Review.

The development of additive manufacturing methods known as “3D printing” started in the 1980s. In these methods, spatial models are created from a semi-finished product such as a powder, filament or liquid. The model is most often created in layers, which are created from the semi-finished product, which is most often subjected to thermal treatment or using light or ultraviolet rays. The technology of additive manufacturing has both advantages and disadvantages when compared to the traditionally used methods of processing thermoplastic materials, such as, for example, injection or extrusion. The most important advantages are low cost, flexibility and speed of manufacturing of elements with different spatial shapes. From the point of view of the user of the product, the most important disadvantages are the lower mechanical properties and lower resistance to environmental factors that occur during the use of the manufactured products. The purpose of this review is to present current information and a compilation of features in the field of research on the effects of the interactions of different types of environments on the mechanical properties of 3D-manufactured thermoplastic products. Changes in the structure and mechanical properties of the material under the influence of factors such as humidity, salt, temperature, UV rays, gasoline and the environment of the human body are presented. The presented article enables the effects of environmental conditions on common materials used in 3D printing technology to be collated in one place.

ROMERIN: A new concept of a modular autonomous climbing robot

Climbing robots play an essential role in performing inspection work in civil infrastructures. These tasks require autonomous robots with competitive costs and the ability to adapt to different types of environments. This article presents ROMERIN, a new concept of a modular legged climbing robot where each leg is an autonomous robotic module in terms of processing capacity, control, and energy. The legs are equipped with suction cups that allow the robot to adhere to different types of surfaces. The proposed design allows the creation of climbing robots with a different number of legs to perform specific inspection tasks. Although each of the legs acts as an independent robot, they have the ability to share information and energy. The proposed control concept enables the development of climbing robots with the ability to adapt to different types of inspection tasks and with resilience characteristics. This article includes a description of the mechatronic design, the kinematics of the seven degree-of-freedom robotic legs, including the adhesion system, and the architecture of the control and simulation system. Finally, we present experimental results to test the modularity concept, mechanical design, and electronics using a four-legged robot configuration. We analyze the performance of the gripping system in different situations on four different surfaces and the behavior of the control architecture for two different robot body trajectories.

The vertical light-gradient and its potential impact on animal distribution and behavior

The visual environment provides vital cues allowing animals to assess habitat quality, weather conditions or measure time of day. Together with other sensory cues and physiological conditions, the visual environment sets behavioral states that make the animal more prone to engage in some behaviors, and less in others. This master-control of behavior serves a fundamental and essential role in determining the distribution and behavior of all animals. Although it is obvious that visual information contains vital input for setting behavioral states, the precise nature of these visual cues remains unknown. Here we use a recently described method to quantify the distribution of light reaching animals’ eyes in different environments. The method records the vertical gradient (as a function of elevation angle) of intensity, spatial structure and spectral balance. Comparison of measurements from different types of environments, weather conditions, times of day, and seasons reveal that these aspects can be readily discriminated from one another. The vertical gradients of radiance, spatial structure (contrast) and color are thus reliable indicators that are likely to have a strong impact on animal behavior and spatial distribution.

Additively Manufactured “Smart” RF/mm-Wave Packaging Structures: A Quantum Leap for On-Demand Customizable Integrated 5G and Internet of Things Modules

5G and Internet of Things (IoT) technologies are rapidly expanding fields, utilizing cutting edge processes and manufacturing techniques that enable wide connectivity coverage and promise to connect billions of devices in all different types of environments. This critical requirement of ubiquitous implementation necessitates an adaptive system that can be easily modified on demand to be utilized in different areas of deployment.

Phenology effects on productivity and hatching-asynchrony of American kestrels (Falco sparverius) across a continent

Optimal reproductive performance occurs when birds time reproduction to coincide with peak food availability. Deviation from optimal timing, or mismatch, can affect productivity, though birds may mediate some mismatch effects by altering their incubation behavior. We studied the consequences of nesting timing (i.e., clutch initiation relative to an index of spring start) on productivity across the breeding range of American kestrels ( Falco sparverius ) in the United States and southern Canada, and associations between nesting timing, incubation behavior, and hatching asynchrony. We used observations from long-term nest box monitoring, remote trail cameras, and community-scientist-based programs to obtain data on clutch initiation, productivity, incubation, and hatching synchrony. Kestrels that initiated clutches after the extended spring index (SI-x, start of spring estimate) had higher rates of nest failure and fewer nestlings than earlier nesters, and effects of nesting timing on productivity were strongest in the Northeast. In contrast, kestrels in the Southwest experienced a more gradual decline in productivity across the season. Spatial effects may be the result of regional differences in growing seasons and temporal nesting windows (duration of nesting season). Specifically, resource availability in the Northeast was highly peaked during the breeding season, potentially resulting in shorter nesting windows. Conversely, resource curves were more prolonged in the Southwest, and growing seasons are becoming longer with climate change, potentially resulting in longer nesting windows. We found an inverse relationship between nesting timing and the onset of male incubation. Males from breeding pairs that initiated clutches after SI-x began incubation sooner than males from breeding pairs that initiated clutches before SI-x. Early-onset of male incubation was positively associated with hatching asynchrony, creating increased age variation in developing young. In sum, nesting phenology relative to the SI-x has consequences for American kestrels’ productivity, and these consequences vary across space. The early onset of incubation may act as a potential adaptive behavior to advance the average hatch date and spread out energetic demands. Given the effects of nesting timing on productivity, kestrels are likely to be sensitive to climate-driven advances in growing seasons and vulnerable to phenological mismatch, particularly in the Northeast. Top panel show availability of food (green polygon) in two different types of environments, a highly seasonal environment with peaked productivity and a less seasonal environment with prolonged growing seasons, and the outcome of two nesting attempts, one before the start of spring (yellow) and another after (purple). The later nesting attempt results in fewer young, especially in the seasonal environment. The bottom panel shows that in pairs that nest before the start of spring (yellow), males delay incubation and young hatching at the same time, whereas in later nesting pairs (purple), males may incubate earlier and young hatch asynchronously. • We studied the phenology and productivity of an avian predator across North America. • American kestrels nesting after the start of spring had lower productivity. • Effects of late nesting on productivity were strongest in the Northeast. • Later nesting kestrels altered incubation so that eggs hatched asynchronously. • Spatial patterns of phenology effects reveal populations sensitive to mismatch.

[Antibiotic resistance genes in aerosols: a review].

Recently, drug resistance resulted from the extensive abuse and over-use of antibiotics has posed a great threat to human health. Scholars have conducted numerous studies on the impacts of antibiotic resistant bacteria and antibiotic resistance genes (ARGs) in different types of environments. Aerosol is not only a potential reservoir for ARGs, but also an important route for transmission of ARGs in the environment. However, a systematic summary of its sources, transmission, human exposure, and health risks is lacking. This review focused on four types of typical sites for aerosol research: human functional living places, farms, urban wastewater treatment plants, and hospitals. The sources, transmission routes, human exposure, and health risks of ARGs in the aerosol of these four typical sites were reviewed. This article also provides a reference for prevention and control of ARGs in aerosols.

Sustaining Business Projects on Challenging Environments

For a progressive business, there are necessary projects. All business implements their growth strategic plan through the development of projects. The business projects can either be identified as financial or non-financial. Every type of project has its unique environmental challenges. These become amplified in the context of complex environments or when projects deteriorate to the point they should be killed or need recovery. This paper focuses on strategies how to sustain business projects in challenging environments. The pillars of all business projects are the project period, cost, and resources. Project environment challenges will always affect these pillars. To mitigate the environmental challenges the paper narrowed the scope to project identification/ initiation, planning, and implementation in order to successfully handle the project environment. Different types of environments are also discussed in this paper; macro, micro, and intermediate environment on how they affect business projects. All these environments are examined to highlight how best a project business can navigate successfully through its challenges. In an operating environment that is dynamic and highly challenging, business projects need to appreciate the importance of crafting and effectively executing strategies that can help them navigate the environment challenge to carry it through any unexpected and challenging eventuality. The paper concludes that good and sincere project identification/ initiation, and planning will ultimately ensure smooth project implementation through a challenging project environment.

Plant mineral nutrition on ultramafic rocks of New Caledonia

Plant mineral nutrition on ultramafic rocks of New Caledonia

Object recognition using tactile sensing in a robotic gripper

Object recognition using the tactile sense is one of the leading human capacities. This capability is not as developed in robotics as other sensory abilities, for example visual recognition. In addition to a robot's ability to grasp objects without damaging them, it is also helpful to provide these machines with the ability to recognise objects while gently manipulating them, as humans do in the absence of or complementary to other senses. Advances in sensory technology have allowed for the accurate detection of different types of environment; however, the challenge of being able to efficiently represent sensory information persists. In this paper, a sensory system is proposed that allows a robotic gripper armed with pressure sensors to recognise objects through tactile manipulation. A pressure descriptor is designed to characterise the voltage magnitudes across different objects and, finally, machine learning algorithms are used to recognise each object category. The results show that the pressure descriptor characterises the different classes of objects in this experimental set-up. This system can complement other sensory data to perform different tasks in a robotic environment and future research areas are proposed to handle problems with tactile manipulation.