Remote Field Research Articles

On-Command Disassembly of Microrobotic Superstructures for Transport and Delivery of Magnetic Micromachines.

Magnetic microrobots have been developed for navigating microscale environments by means of remote magnetic fields. However, limited propulsion speeds at small scales remain an issue in the maneuverability of these devices as magnetic force and torque are proportional to their magnetic volume. Here, a microrobotic superstructure is proposed, which, as analogous to a supramolecular system, consists of two or more microrobotic units that are interconnected and organized through a physical (transient) component (a polymeric frame or a thread). The superstructures consist of microfabricated magnetic helical micromachines interlocked by a magnetic gelatin nanocomposite containing iron oxide nanoparticles (IONPs). While the microhelices enable the motion of the superstructure, the IONPs serve as heating transducers for dissolving the gelatin chassis via magnetic hyperthermia. In a practical demonstration, the superstructure's motion with a gradient magnetic field in a large channel, the disassembly of the superstructure and release of the helical micromachines by a high-frequency alternating magnetic field, and the corkscrew locomotion of the released helices through a small channel via a rotating magnetic field, is showcased. This adaptable microrobotic superstructure reacts to different magnetic inputs, which can be used to perform complex delivery procedures within intricate regions of the human body.

How job resources can shape perspectives that lead to better performance: a remote worker field study

PurposeThe purpose of this study is to investigate the complexity of how demands and stress are mitigated to enhance employee performance in remote working arrangements.Design/methodology/approachA time-lagged snowball sample of 223 full-time remote working adults in the United States participated in an online survey. Data were analyzed using R 4.0.2 and structural equation modeling.FindingsResults suggest remote job resources involving organizational trust and work flexibility increase performance via serial mediation when considering information communication technology (ICT) demands and work–life interference (WLI). The findings provide insights into counterbalancing the negative aspects of specific demands and stress in remote work arrangements.Practical implicationsThis study provides insights for managers to understand how basic job resources may shape perspectives on demands and WLI to impact performance. Specific to remote working arrangements, establishing trust with the employees and promoting accountability with their work flexibility can play an important part in people and their performance.Originality/valueThis study contributes theoretically to the literature by evidencing how components of the E-Work Life (EWL) scale can be used with greater versatility beyond the original composite measurement because of the job-demand resource (JD-R) framework and conservation of resources theory (COR). This study answers several calls by research to investigate how ICT demands and WLI play a complex role in work performance.

Thirty Years of Change in the Land Use and Land Cover of the Ziz Oases (Pre-Sahara of Morocco) Combining Remote Sensing, GIS, and Field Observations

Remote sensing (RS) data and geographic information system (GIS) techniques were used to monitor the changes in the Oasis agroecosystem of the pre-Saharan province of Errachidia, southeastern Morocco. The land use and land cover (LULC) change of the agroecosystem of this province was processed using Landsat time series with 5-year intervals of the last thirty years. The normalized difference vegetation index (NDVI) and the maximum likelihood classification (MLC) were categorized into five classes, including water bodies, cultivated land, bare land, built-up, and desertified land. The overall accuracy of the MLC maps was estimated to be higher than 90%. The finding showed a degradation trend represented by an increase in desertified lands, which tripled in the ten last years, passing from 20.62% in 2011 to 58.49% in 2022. The findings also depicted a decreasing trend in the cultivated area in this period passing from 174.2 km2 in 1991 to 82.2 km2 in 2022. Using NDWI, Landsat images from 1991 to 2021 depicted a strong association between the water reserve in Hassan Eddakhil dam in the upstream area and the LULC changes. The oases from the dam (upstream) to Er-Rissani (downstream) recorded high rates of decline with an increasing trend of desertification due to drought and overuse mainly of groundwater. The outputs of this research effort constitute a significant source of information that may be used to support further research and decision-makers to manage arid ecosystems and achieve the sustainable development goals (SDGs), precisely the SDGs 15 (Life on land).

Remote field placements during the pandemic: Lessons learned at the University of British Columbia School of Social Work

COVID-19 and the global pandemic significantly shifted social work field education and required innovations in how practicum experiences could simultaneously meet experiential learning objectives and maintain safety. Remote practicums where students were connected to an agency/organization but completed all their learning/service delivery and supervision virtually was one of these innovations. As a quality assurance exercise, the Chair of the Field Education Program at the University of British Columbia (UBC) School of Social Work interviewed four MSW students about their experiences in remote practicums. This article describes some of the benefits and challenges outlined by the students and illustrates possible practices and policies that the UBC School of Social Work field team can make to harness the learning from these experiences.

Swimmable Micro‐Battery for Targeted Power Delivery

AbstractThe boom of microelectronic devices and their diverse applications has heightened the demand for innovative and effective energy supply strategies. The longevity of contemporary microelectronic devices predominantly depends on direct human intervention power supply methods, encompassing battery replacement or recharging. However, these methods may falter in specific scenarios, such as when facing liquid conditions in vivo. Here, a concept of swimmable micro‐batteries (MBs) for targeted power delivery is presented. This is achieved through the design of a flexible polydimethylsiloxane/Fe3O4 soft‐magnetic substrate for actuation, polydimethylsiloxane/neodymium‐iron‐boron (NdFeB) hard‐magnetic tabs for precise targeting, and quasi‐solid‐state Zn//MnO2 battery for power generation. These swimmable MBs exhibit an impressive areal capacity of 102.3 µAh cm‐2, remarkable waterproofing, adjustable output voltage or capacity, rapid response, and accurate remote magnetic field manipulation, enabling targeted power supply available. This novel swimmable MB design broadens the function of MBs and may open a new avenue for their future development.

Fabrication and Actuation of Magnetic Shape-Memory Materials.

Soft actuators are deformable materials that change their dimensions or shape in response to external stimuli. Among the various stimuli, remote magnetic fields are one of the most attractive forms of actuation, due to their ease of use, fast response, and safety in biological systems. Composites of magnetic particles with polymer matrices are the most common materials for magnetic soft actuators. In this paper, we demonstrate the fabrication and actuation of magnetic shape-memory materials based on hydrogels containing field-structured magnetic particles. These actuators are formed by placing the pregel dispersion into a mold of the desired on-field shape and exposing it to a homogeneous magnetic field until the gel point is reached. At this point, the material may be removed from the mold and fully gelled in the desired off-field shape. The resultant magnetic shape-memory material then transitions between these two shapes when it is subjected to successive cycles of a homogeneous magnetic field, acting as a large deformation actuator. For actuators that are planar in the off-field state, this can result in significant bending to return to the on-field state. In addition, it is possible to make shape-memory materials that twist under the application of a magnetic field. For these torsional actuators, both experimental and theoretical results are given.

Frequency Characteristics Analysis of Remote Field Eddy Current Testing on Ferromagnetic Pipes

Pipes made of ferromagnetic alloys are widely installed in petrochemical plants and the steel plants. To implement non-destructive corrosion inspections on these pipes, remote field eddy current testing (ECT) which installs a search coil inside the pipe is a practical inspection method. Remote field ECT has the advantage of being able to detect external surface defects while the distance between the detection coil and the excitation coil is twice of the outer diameter of the testing pipe. Nevertheless, the inspection principle such as the frequency characteristics etc. of ECT signals have not been elucidated, inspection devices based on remote field ECT had not been employed widely. In this paper, we measured the frequency characteristics of ferromagnetic pipes with artificial outer surface defects by remote field ECT, and then detailed finite element analysis are carried out by using the nonlinear eddy current analysis to clarify the inspection principle of the remote field ECT. In both measurement and analysis, peak signal occurs directly under the defect and the optimal frequency range are the same. The phase angle of flux density due to the excitation current and flux density due to eddy current are found to greatly affect the frequency characteristics.

Simulation of Soil Organic Carbon Dynamics in Postfire Boreal Forests of China by Incorporating High-Resolution Remote Sensing Data and Field Measurement

Soil organic carbon (SOC) is an important component of the ecosystem carbon pool, and fire is one of the important disturbances in forest ecosystems. With global warming, there has been a gradual increase in boreal forest fires, which has a nonnegligible impact on the SOC dynamics in forests. The CENTURY model was employed in our study to simulate the changes in SOC stocks in boreal forests of the Great Xing’an Mountains, China under different fire severity conditions. Fire severity was represented by the metric of difference normalized burn ratio (dNBR) derived from 30-m Landsat-8 imageries. Changes in forest SOC stocks following fire disturbance were predicted under four future Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). We found that the CENTURY model had good results in simulating the SOC stocks in the postfire of China’s boreal forests. Forest SOC dynamics responded differently to fire severities and the larger SOC loss was associated with increasing fire severity. Importantly, a feedback mechanism was found between climate change and SOC stocks, which reduces SOC stocks with increasing temperatures. High-severity forest fires tended to cause serious damage to the SOC pool and delay forest SOC recovery time; after such events, forest SOC stocks cannot be fully recovered to the prefire levels (6.74% loss). In addition, higher CO2 emissions and warmer temperatures significantly affected the recovery of SOC stocks after fire disturbance, resulting in larger SOC losses. Overall, we projected losses of 10.14%, 12.06%, 12.41%, and 15.70% of SOC stocks after high-severity fires in four RCP scenarios, respectively. Our findings emphasize the importance of fire disturbance and climate change on future dynamics of SOC stocks in China’s boreal forests, providing a scientific basis for future boreal forest management and fire management.

Cluster-based photography and modeling integrated method for an efficient measurement of cassava leaf area.

Leaf area (LA) and biomass are important agronomic indicators of the growth and health of plants. Conventional methods for measuring the LA can be challenging, time-consuming, costly, and laborious, especially for a large-scale study. A hybrid approach of cluster-based photography and modeling was, thus, developed herein to improve practicality. To this end, data on cassava palmate leaves were collected under various conditions to cover a spectrum of viable leaf shapes and sizes. A total of 1,899 leaves from 3 cassava genotypes and 5 cultivation conditions were first assigned into clusters by size, based on their length (L) and width (W). Next, 111 representative leaves from all clusters were photographed, and data from image-processing were subsequently used for model development. The model based on the product of L and W outperformed the rest (R2 = 0.9566, RMSE = 20.00). The hybrid model was successfully used to estimate the LA of greenhouse-grown cassava as validation. This represents a breakthrough in the search for efficient, practical phenotyping tools for LA estimation, especially for large-scale experiments or remote fields with limited machinery.

From outer space to inside the body: Ultra-high temperature ceramic matrix composites for biomedical applications

Ultra-high temperature ceramic matrix composites (UHTCMCs) are a new class of carbon fiber-reinforced non-brittle ceramics possessing a unique combination of properties (e.g. high fracture toughness, damage tolerance and corrosion resistance), originally developed for use in extreme hot and harsh environments, such as those found in aerospace and industrial applications. Interconnections between very remote fields more and more frequently come across to discover new solutions. In this study, we investigated the compression strength and cytotoxicity of UHTCMCs designed as biomaterials for future applications inside the body. Indeed, despite the advancements in the designing, manufacturing and surface modification, current prostheses are made of metals or alloys with well-known disadvantages. Near-fully dense Cf/ZrB2-SiC composites were manufactured through slurry impregnation followed by spark plasma sintering. A preliminary biological in vitro study demonstrated materials’ lack of cytotoxicity, making them promising candidates for further investigation for biomedical purposes.

Soils are a non-negligible source of NO in a UK suburban greenspace and SE Australian Eucalyptus forest

Nitrogen oxides, particularly NO and NO2 (NOx), are primary air pollutants that also play an essential role in the atmospheric oxidation of volatile organic compounds, resulting in ozone and secondary organic aerosol formation. It is therefore critical to fully characterise NOx sources and sinks to understand tropospheric photochemistry and hence local- to regional-scale air quality. Human activities such as transport and power plants are well-known NOx emission sources in urban areas, whereas natural sources such as soils have been considered to contribute more substantially in rural and remote areas. However, soil NO emissions are poorly characterised and therefore underrepresented in models. To improve our understanding of soil as a source of NO, we measured diurnal patterns in soil NO concentrations at a suburban site in the UK and a remote field site in Australia to determine whether soils contribute to local atmospheric NO, and to identify the potential drivers of soil NO emissions. Mean soil NO concentrations in both UK campaigns 1.76 ± 0.92 ppb in summer and 0.91 ± 0.37 ppb in winter) were higher than those measured in Australia (0.73 ± 0.73 ppb). The diel patterns of NO concentrations (both sites) and emissions rates (Australia) showed a clear peak corresponding to local emission sources, but variation in NO was also related to either vapour pressure deficit (R2 = 0.88 in UK summer, R2 = 0.51 in Australia, both p < 0.05) or solar radiation (R2 = 0.06 with p > 0.4 in UK summer, R2 = 0.71 with p < 0.05 in Australia) during the daylight hours, indicating biogenic origin of soil NO. Our work demonstrates that biogenic soil emissions of NO are non-negligible, estimated at around 1.32 % of total NO emissions at the remote site, and 0.22 % at the urban site, and must be accounted for in global and regional atmospheric chemistry-climate modelling and NOx reduction strategies.

Cyanobacterial Biomonitoring in Lake Avernus During the COVID-19 Pandemic: Integrating Remote Sensing and Field Data for Pollution Source Detection

Cyanobacterial Biomonitoring in Lake Avernus During the COVID-19 Pandemic: Integrating Remote Sensing and Field Data for Pollution Source Detection

Disentanglement and multi‐year survival of a free‐ranging California sea lion (Zalophus californianus) with an upper airway stoma secondary to fishing net entanglement

AbstractCalifornia sea lions (Zalophus californianus) are susceptible to entanglement in fishing gear and marine debris. Over time, entanglement material can become deeply embedded and disrupt underlying tissue layers, including skin, blubber, muscle, and regional structures. In the neck, chronic circumferential entanglement can result in airway laceration. We present a case study of an adult female California sea lion with an upper airway stoma secondary to chronic monofilament fishing net entanglement. The animal was disentangled in a remote field setting without access to surgical and rehabilitation facilities, and was released without additional treatment. Satellite telemetry data from the 5 months following disentanglement revealed movements comparable to those of other adult female California sea lions. Subsequent visual sightings ('resights') documented a minimum 2‐year survival following disentanglement.

A Deep Learning–Based Approach for Empirical Modeling of Single-Point Wave Spectra in Open Oceans

Abstract Directional wave spectra are of importance for numerous practical applications such as seafaring and ocean engineering. The wave spectral densities at a certain point in the open ocean are significantly correlated to the local wind field and historical remote wind field. This feature can be used to predict the wave spectrum at that point using the wind field. In this study, a convolutional neural network (CNN) model was established to estimate wave spectra at a target point using the wind field from the ERA5 dataset. A geospatial range where the wind could impact the target point was selected, and then the historical wind field data within the range were analyzed to extract the nonlinear quantitative relationships between wind fields and wave spectra. For the spectral densities at a given direction, the wind data along the direction where waves come from were used as the input of the CNN. The model was trained to minimize the mean square error between the CNN-predicted and ERA5 reanalysis spectral density. The data structure of the wind input is reorganized into a polar grid centered on the target point to make the model applicable to different open-ocean locations worldwide. The results show that the model can predict well the wave spectrum shapes and integral wave parameters. The model allows for the prediction of single-point wave spectra in the open ocean with low computational cost and can be helpful for the study of spectral wave climate. Significance Statement The directional wave spectra (DWS) describe the distribution of wave energy among different frequencies and directions. They are useful for many marine practical applications. Usually, DWS are modeled using numerical wave models (NWMs) based on wave action balance differential equations. Although contemporary NWMs perform well after years of development, their computational costs are relatively high. The fast-developed artificial intelligence (AI) might provide an alternative solution to this task. In this study, convolutional neural networks are used to model the DWS at some selected points in the open ocean. By “learning” from NWM data, AI can effectively simulate single-point DWS in open oceans with low computational cost, which can serve as a faster data-driven surrogate model in related applications.

Diabetic Retinopathy Screening Using Smartphone-Based Fundus Photography and Deep-Learning Artificial Intelligence in the Yucatan Peninsula: A Field Study.

To compare the performance of Medios (offline) and EyeArt (online) artificial intelligence (AI) algorithms for detecting diabetic retinopathy (DR) on images captured using fundus-on-smartphone photography in a remote outreach field setting. In June, 2019 in the Yucatan Peninsula, 248 patients, many of whom had chronic visual impairment, were screened for DR using two portable Remidio fundus-on-phone cameras, and 2130 images obtained were analyzed, retrospectively, by Medios and EyeArt. Screening performance metrics also were determined retrospectively using masked image analysis combined with clinical examination results as the reference standard. A total of 129 patients were determined to have some level of DR; 119 patients had no DR. Medios was capable of evaluating every patient with a sensitivity (95% confidence intervals [CIs]) of 94% (88%-97%) and specificity of 94% (88%-98%). Owing primarily to photographer error, EyeArt evaluated 156 patients with a sensitivity of 94% (86%-98%) and specificity of 86% (77%-93%). In a head-to-head comparison of 110 patients, the sensitivities of Medios and EyeArt were 99% (93%-100%) and 95% (87%-99%). The specificities for both were 88% (73%-97%). Medios and EyeArt AI algorithms demonstrated high levels of sensitivity and specificity for detecting DR when applied in this real-world field setting. Both programs should be considered in remote, large-scale DR screening campaigns where immediate results are desirable, and in the case of EyeArt, online access is possible.

Стратегические приоритеты применения беспилотных технологий при реализации энергетических проектов в Арктике

Energy projects in the Russian Arctic requires advanced, effective, and save technologies capable of working in harsh climatic conditions. Unmanned vehicles are a key trend in the contemporary oil and gas industry. They perform complex technological operations without direct human involvement. Unmanned vehicles deliver cargo to remote fields, monitor environment, do seismic exploration, provide photo and video surveillance, etc. The key advantage of unmanned vehicles is their uninterrupted round-the-clock operation, regardless of external circumstances. Drones make it possible to reduce the time of cargo delivery and ensure the stability of transportation in all weather conditions. Unmanned technologies increase the efficiency of logistics because they are reliable means of delivering equipment and materials to distant oil and gas fields. Submersible, land, and aerial drones of Russian production are used in the Arctic oil and gas fields. The achieved results create prerequisites for long-term development in this area. As the technical capabilities expand, the range of tasks increases to include magnetic exploration, mapping land plots, laser scanning for digital terrain models, etc. Russian oil and gas companies in the Arctic are likely to benefit from unmanned technologies in the long term.

Auditoría de estructura odontológica realizada de manera íntegramente virtual en contexto de pandemia

The Dental Audit entails a planned process of observation, analysis, verification of indicators, interpretation and presentation of data obtained. The Structure Audit of the Dental Office analyzed had an extraordinary characteristic for a field audit: itwas carried out completely virtual, in the context of preventive and mandatory social isolation by Covid-19. Objectives: Design a specific strategy to carry out the Structure Audit of a Dental Office in the context of a pandemic. Obtain the evidence necessary to qualify the aptitude of the dental office. Method: Synchronous and asynchronous technological resources were used, and collect information from the dental office through remote field observations, to identify the aspects required for a structure audit. Results: Information on infrastructure, resources, services, documents, biosafety, compliance with laws and care protocols was obtained remotely. Verifiable evidence was accessed on the minimum quality required of a health service. Strengths opportunities weakness threats analysis and audit report were carried out. The dental office was qualified without the need for on-site attendance. Conclusions: It has been demonstrated that it is possible to carry out a Dental Structure Audit using exclusively available technological tools. This work turned out to be unprecedented since no records in the literature of Dental Audit of Structure are carried out remotely, nor of direct evaluation of dental terrain through entirely digital means. The Dental Audit immersed in a digitized world advances towards achieving a dentistry of excellence

Identifying Colonial Roads in Southern New Jersey: An Application of Remote Sensing, Field, and Archival Methods to Document the Locations, Condition, and Routes of Critical American Revolutionary War Supply Chains

This paper explores the identification, use, and preservation of historic roads in the state of New Jersey that primarily travel through public lands. The authors examine in detail the historical significance of several unpaved routes that continue to exist in Burlington County, NJ, as well as discuss various methods that can be used to identify routes with historical significance and document their physical characteristics. Field research was conducted to establish the current location of these historic routes, using LiDAR, GPS, and geographic information systems methods to estimate their likely date of construction. Further examination and mapping of these routes was undertaken, followed by documentation of the historical events linked to their use, thus establishing historical context. We identified likely routes used as critical Revolutionary War supply routes. The paper concludes with a discussion of appropriate actions that should be considered in the preservation of these routes and offers planners some options in relation to public policy.

Better late than never: Optimising the proteomic analysis of field-collected octopus.

Proteomics, the temporal study of proteins expressed by an organism, is a powerful technique that can reveal how organisms respond to biological perturbations, such as disease and environmental stress. Yet, the use of proteomics for addressing ecological questions has been limited, partly due to inadequate protocols for the sampling and preparation of animal tissues from the field. Although RNAlater is an ideal alternative to freezing for tissue preservation in transcriptomics studies, its suitability for the field could be more broadly examined. Moreover, existing protocols require samples to be preserved immediately to maintain protein integrity, yet the effects of delays in preservation on proteomic analyses have not been thoroughly tested. Hence, we optimised a proteomic workflow for wild-caught samples. First, we conducted a preliminary in-lab test using SDS-PAGE analysis on aquaria-reared Octopus berrima confirming that RNAlater can effectively preserve proteins up to 6 h after incubation, supporting its use in the field. Subsequently, we collected arm tips from wild-caught Octopus berrima and preserved them in homemade RNAlater immediately, 3 h, and 6 h after euthanasia. Processed tissue samples were analysed by liquid chromatography tandem mass spectrometry to ascertain protein differences between time delay in tissue preservation, as well as the influence of sex, tissue type, and tissue homogenisation methods. Over 3500 proteins were identified from all tissues, with bioinformatic analysis revealing protein abundances were largely consistent regardless of sample treatment. However, nearly 10% additional proteins were detected from tissues homogenised with metal beads compared to liquid nitrogen methods, indicating the beads were more efficient at extracting proteins. Our optimised workflow demonstrates that sampling non-model organisms from remote field sites is achievable and can facilitate extensive proteomic coverage without compromising protein integrity.

Development of a field-deployable qPCR assay for real-time pest monitoring in algal cultivation systems

Outdoor cultivation is commonly used to produce algal biomass for a variety of bioproducts including food, feed, fuel, pharmaceuticals, and nutraceuticals. Outdoor cultivation ponds are highly susceptible to pest pressures that may lead to periods of low productivity or even entire loss of the algal crop. Therefore, there is a need for rapid, real-time tracking of pests for early intervention to mitigate crop loss. Herein, we describe the development of a field deployable, low-cost qPCR assay for detecting both known and novel pests of a farmed eukaryotic alga species, Nannochloropsis sp. We performed a proximity guided metagenome deconvolution approach (ProxiMeta™) to discover novel pests that temporally correspond to periods of reduced pond productivity. This approach provided high-quality metagenome assemblies that were used to design qPCR probes to detect specific pests of interest. The portable qPCR assay, designed to be deployed at remote field locations, enables low-cost surveillance with a rapid (2 h) turn-around time. Frequent sampling allows for early detection and prompts intervention strategies to remedy infected ponds to minimize crop loss. The qPCR assay was used to successfully detect a known predatory bacterium within the order Bdellovibrionales both in the lab and at a remote field location. Furthermore, we assembled the genome of two novel, site-specific pests in the Saprospiraceae family and successfully designed qPCR probes that differentially detected their presence in two different pond locations. Ultimately, this assay has the potential to monitor multiple pests simultaneously and tailor targets to match likely pest infections that differ across geographical locations, helping to mitigate crop loss on a large scale.