Limited Range Research Articles

A solar-powered self-clean gas-sensing neural modulator for behavioral intervention with spatiotemporal flexibility

The amalgamation of high-sensitivity gas sensors with neural electrical stimulation technology stands as a compelling solution for eliciting behavioral responses in the presence of low-level hazardous gases. The utilization of battery-powered or coil-based configurations introduces spatiotemporal limitations, encompassing constrained experimental durations due to battery life or the necessity to confine subjects to specific locales for wireless power transmission. In this study, we present an advanced wireless neural modulator, meticulously engineered for behavioral intervention in unrestricted environments. This device integrates a solar-powered unit, gas sensor, brain stimulation signal management system, and a neurostimulation electrode. The solar energy utilization eliminates the necessity for battery replacements and local range limitations. The surface of the solar cells is treated with a superhydrophobic coating, enhancing performance in outdoor settings by mitigating surface contamination issues inherent in traditional solar cells. This innovation guarantees continuous, long-term, on-demand operational capacity, ensuring uninterrupted power supply to the system. Experimentation revealed shortened locomotor activity in mice, induced by stimulation of the periaqueductal gray (PAG) brain region, for up to thirty minutes. These results underscore the significant potential of our technology for spatially and temporally unrestricted neuromodulatory applications, offering a viable strategy to alleviate the detrimental effects of hazardous gas exposure on physiological functions.

Magnetic graphene oxide functionalized dimercaptosuccinic acid/putrescine as a selective and stable solid-phase extraction adsorbent for preconcentration and speciation of arsenic (III) in water samples

ABSTRACT It is challenging for environmental scientists to identify the trace value of arsenite (As(III)) as an essential hazardous material in the presence of arsenate (As(V)) and other metal ions. This paper proposes a method of magnetic solid-phase extraction (MSPE) for the trace analysis of As(III) using magnetite graphene oxide (MGO) covalently functionalised with dimercaptosuccinic acid (DMSA) and putrescine (PUT). The hydrothermally synthesised MGO/DMSA-PUT adsorbent was carefully characterised by using energy-dispersive X-ray spectroscopy analysis, Fourier transform infrared, dynamic light scattering, scanning electron microscopy, zeta potential analyser, X-ray diffraction, and vibrating sample magnetometer techniques in detail. Maximum adsorption capacity of MGO/DMSA-PUT for As(III) was determined 144 mg g−1 which considerably improved vs. graphene oxide with the adsorption capacity of 54.8 mg g−1. Sample pH of 6 with a volume of 50 mL, contact time of 5 minutes, initial concentration of 50 μg L−1, adsorbent dosage of 0.1 g and volume of eluent 3 mL were obtained as the optimised parameters for the developed MSPE procedure. According to experimental data obtained with hydride generation atomic absorption spectroscopy, the linear range and detection limit of the proposed method for As(III) measurement was found to be 0.4–5000 µg L−1 and 9.914 ng L−1, respectively. According to experimental results, a preconcentration limit (PL) of 1.72 µg L−1 was achieved for As(III), corresponding to a preconcentration factor of 965. Statistical analysis of standard reference materials confirmed the accuracy of the method against systematic and constant errors (>95% recovery with <5% RSD). Because of the selectivity of MGO/DMSA-PUT towards the As(III), the developed MSPE procedure is capable for successful speciation and determination of As(III) in water samples with satisfactory analytical results.

Distributed Computation Offloading and Power Control for UAV-Enabled Internet of Medical Things

The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT services, Mobile Edge Computing (MEC) has emerged as an indispensable technology in smart health. Benefiting from the cost-effectiveness of deployment, unmanned aerial vehicles (UAVs) equipped with MEC servers in Non-Orthogonal Multiple Access (NOMA) have emerged as a promising solution for providing smart health services in proximity to medical devices (MDs). However, the escalating number of MDs and the limited availability of communication resources of UAVs give rise to a significant increase in transmission latency. Moreover, due to the limited communication range of UAVs, the geographically-distributed MDs lead to workload imbalance of UAVs, which deteriorates the service response delay. To this end, this paper proposes a UAV-enabled Distributed computation Offloading and Power control method with Multi-Agent, named DOPMA, for NOMA-based IoMT environment. Specifically, this paper introduces computation and transmission queue models to analyze the dynamic characteristics of task execution latency and energy consumption. Moreover, a credit assignment scheme-based reward function is designed considering both system-level rewards and rewards tailored to each MD, and an improved multi-agent deep deterministic policy gradient algorithm is developed to derive offloading and power control decisions independently. Extensive simulations demonstrate that the proposed method outperforms existing schemes, achieving \(7.1\% \) reduction in energy consumption and \(16\% \) decrease in average delay.

Receding optimal synthesis of robust consensus for multi-agent systems with limited communication

ABSTRACT A novel strategy based on the robust distributed model predictive control (DMPC) is proposed in this paper to address the consensus of multi-agent systems subjected to unknown-but-bounded disturbances with limited communication range. The proposed strategy utilises the formulation of the tube-based predictive control and has the ability to handle the explicit input constraints and achieve the bounded consensus with initial communication topology preserved under the disturbances. In this proposed strategy, a novel constraint is designed to guarantee the connectivity of the system under the disturbances, and the synthesis methods are proposed for the controller. Meanwhile, it is proved that the proposed algorithm in this paper is recursively feasible, the connectivity can always be preserved and the system can finally reach bounded consensus under the disturbances. A simulation example is provided to demonstrate the proposed robust DMPC-based strategy.

Justification of range limits of root spray angle of an adaptive spraying device

BACKGROUND: Oscillations of the sprayer field boom in the transverse-vertical plane causes a decrease in the quality of the technological operation. This is especially true in relation to the operation of small-sized single-support barrow-type sprayers. One of the possible solutions to compensate the effect of transverse oscillations of the boom on the quality of spraying is the use of adaptive sprayers with a variable root angle of the spray jet, responding to the position taken by the sprayer in relation to the surface being treated. AIM: Justification of the necessary limits for changing the spray angles of an adaptive sprayer for a single-support spraying device. The novelty of the research lies in the fact that insufficient attention is paid to the implementation of technologies using means of small-scale mechanization, unlike industrial agricultural machinery. METHODS: A prototype of a single-support boom motor sprayer was used as the study object. The field experiment was carried out at the experimental area of the Oryol State Agrarian University. Data acquisition on the deviation of the sprayer from the vertical axis was carried out using a specially developed angle gauge. A spreadsheet processor in the Microsoft Excel environment was used to perform mathematical processing of the decrypted experimental data. The study of the obtained analytical dependencies was carried out in the environment of the Mathcad 14.0 mathematical calculation system. RESULTS: It has been experimentally found that the maximum deviations of the sprayer from the vertical can be up to 30° during operation. At the same time, the average amplitude of the transverse operating oscillations of the boom of a single-support barrow-type boom sprayer ranges from +11° to -18°. The amplitude of the transverse oscillations of a single-support sprayer depends on the operator’s skills and the unit motion velocity. Balancing the sprayer is important due to the moment of force caused by the weight of the one-sided field boom. A formula for calculation of the spray width of one sprayer, taking into account the geometric parameters of a single-support sprayer, as well as its inclination angle in the transverse-vertical plane, has been derived. An analytical relationship that makes it possible to calculate the required limits of the root angle of the spray jet of an adaptive sprayer, taking into account the installation distance of the sprayer relative to the vertical plane passing through the support point of the sprayer, has been obtained. The values of the root spray angles for the deflectors of adaptive sprayers, with the sprayer oscillations amplitude from -18° to +11° in the transverse-vertical plane, were found. CONCLUSIONS: The practical value of the study lies in the potential of using the formula to determine the range limits of root spray angles when designing and developing adaptive sprayers.

The intra- and inter-rater reliability of measuring trunk coronal asymmetry by adjusting positioning variability: A prospective study.

Chronic low back pain (LBP) can lead to muscle spasms, limited range of motion, and abnormal posture, resulting in trunk muscle asymmetry. This study aimed to assess the intra- and inter-rater reliability of a quantitative measurement of trunk coronal asymmetry in patients with chronic LBP, minimizing unnecessary gravity and friction force using a manual table in the prone position. This prospective study was conducted at a single center, targeting patients with chronic LBP to measure trunk coronal asymmetry on a manual table in the prone position. The intra-class correlation coefficient (ICC) was calculated using one-way random-effects and two-way mixed-effects models. Fifty-eight patients who had LBP for more than three months were enrolled from May 1, 2021, to December 31, 2021. The intra- and inter-rater reliabilities of the two examiners' measurements were 0.872 and 0.899, and 0.852, respectively. Based on pain severity, the participants were classified into mild and severe groups, with ICCs of 0.823 and 0.889, and 0.936 and 0.918, respectively. Measurement of trunk coronal asymmetry in the prone position using a manual table demonstrates high intra- and inter-rater reliability. In addition, the reliability increases with greater pain severity.

Heart-Cutting Bidimensional Liquid Chromatography for the Simultaneous Analysis of Veterinary Drugs Residues and Nucleotide Monophosphates in Sheep's Milk.

Sheep's milk is a significant source of nucleotide monophosphates (NMPs) but can also contain undesirable residues from veterinary drugs, posing a potential human health risk. This study introduces a novel application of two-dimensional liquid chromatography (2D-LC), in heart-cutting mode, for the simultaneous determination of nucleotides and veterinary drug residues in sheep's milk. 2D-LC allows for the separation of these compounds in a single chromatographic run despite their differing physicochemical properties. The proposed method separates six veterinary drug residues and five NMPs in a single injection. The compounds were separated using a C18 reversed-phase column in the first dimension and a Primesep SB analytical column in the second dimension. The method performance was evaluated in terms of linearity range, detection and quantification limits, matrix effects, precision, and accuracy. The results demonstrated good linearity and sensitivity, with quantification limits allowing for the quantification of veterinary drugs at the maximum residue level and nucleotides at typical levels found in milk samples. The method has been successfully applied to the analysis of sheep's milk samples acquired from local supermarkets, with recoveries within a range of 70-119% and 82-117% for veterinary residues and NMPs, respectively.

Inverted Transflection Spectroscopy of Live Cells Using Metallic Grating on Elevated Nanopillars.

Water absorption of mid-infrared (MIR) radiation severely limits the options for vibrational spectroscopy of the analytes-including live biological cells-that must be probed in aqueous environments. While internal reflection elements, such as attenuated total reflection prisms and metasurfaces, partially overcome this limitation, such devices have their own limitations: ATR prisms are difficult to integrate with multiwell cell culture workflows, while metasurfaces suffer from a limited spectral range and small penetration depth into analytes. In this work, we introduce an alternative live cell biosensing platform based on metallic nanogratings fabricated on top of elevated dielectric pillars. For the MIR wavelengths that are significantly longer than the grating period, reflection-based spectroscopy enables broadband sensing of the analytes inside the trenches separating the dielectric pillars. Because the depth of the analyte twice-traversed by the MIR light excludes the highly absorbing thick water layer above the grating, we refer to the technique as inverted transflection spectroscopy (ITS). The analytic power of ITS is established by measuring a wide range of protein concentrations in solution, with the limit of detection in the single-digit mg mL-1. The ability of ITS to interrogate live cells that naturally wrap themselves around the grating is used to characterize their adhesion kinetic.

Proteomics of prostate cancer serum and plasma using low and high throughput approaches

Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.

Classifying Breast Tumors in Digital Tomosynthesis by Combining Image Quality-Aware Features and Tumor Texture Descriptors

Digital breast tomosynthesis (DBT) is a 3D breast cancer screening technique that can overcome the limitations of standard 2D digital mammography. However, DBT images often suffer from artifacts stemming from acquisition conditions, a limited angular range, and low radiation doses. These artifacts have the potential to degrade the performance of automated breast tumor classification tools. Notably, most existing automated breast tumor classification methods do not consider the effect of DBT image quality when designing the classification models. In contrast, this paper introduces a novel deep learning-based framework for classifying breast tumors in DBT images. This framework combines global image quality-aware features with tumor texture descriptors. The proposed approach employs a two-branch model: in the top branch, a deep convolutional neural network (CNN) model is trained to extract robust features from the region of interest that includes the tumor. In the bottom branch, a deep learning model named TomoQA is trained to extract global image quality-aware features from input DBT images. The quality-aware features and the tumor descriptors are then combined and fed into a fully-connected layer to classify breast tumors as benign or malignant. The unique advantage of this model is the combination of DBT image quality-aware features with tumor texture descriptors, which helps accurately classify breast tumors as benign or malignant. Experimental results on a publicly available DBT image dataset demonstrate that the proposed framework achieves superior breast tumor classification results, outperforming all existing deep learning-based methods.

Taxonomic and functional-trait metrics track recovery of demersal fish and shrimp communities following system collapse

Monitoring programs that integrate both structural and functional ecosystem components play integral roles in ecosystem management and conservation planning. In the early 1990’s, the marine ecosystem of the waters surrounding Newfoundland and Labrador (NL) underwent a regime shift. Several demersal and pelagic fish stocks collapsed simultaneously, and this had significant ecological and socioeconomic consequences. As this regime shift impacted numerous commercial and non-commercial species, assessments based on individual species would be insufficient. We explored a variety of metrics that capture different facets of diversity across multiple species to provide a more robust ecosystem assessment. These were species richness, evenness, community-weighted means of maximum body length and trophic level (i.e., the mean maximum body size or trophic level of the species present in a community), and functional dispersion (FDis). The objectives of this study were 1) to assess trends in community structure of the NL demersal community during the post-collapse period (1995-2018), 2) explore how the various community-level metrics differ or are redundant, and 3) investigate how these metrics are associated with important covariates. Several metrics were redundant and displayed strongly positive, temporal trends being consistent with expectations for a recovery encompassing the entire demersal community. In particular, unweighted community-weighted means of body length and trophic level displayed nearly equal temporal patterns, showing increasing trends throughout the study period which were most prominent in the northern study area and within a limited depth range at the upper shelf break. Corresponding biomass-weighted metrics were also correlated with each other but only showed similar increasing tendencies after the first decade. In contrast, species richness did not show any temporal increase. Evenness and biomass-weighted FDis showed similar temporal patterns, decreasing during the first decade followed by strong increases during subsequent years, patterns that were directly linked to variation in Northern shrimp and Atlantic cod biomass. This study demonstrates how a variety of community metrics can provide insight into different aspects of the post-collapse recovery of the demersal community and help us better understand the complexity of the changes the ecosystem is undergoing.

One-pot synthesis of two novel Ce-MOFs for the detection of tetracyclic antibiotics and Fe3+

In this article, two novel Ce-MOFs were prepared by hexacarboxylic acid and Ce(NO3)3·6H2O with the hydrothermal method, while the yellow cubic structure is named MOF-1 and the colorless transparent strip structure is named MOF-2. The physicochemical properties of the two MOFs were characterized by FTIR, TG, DSC, BET, SEM, EDS etc. Both MOFs are composed of four elements: C, H, O, N, and Ce. Single crystal X-ray diffraction showed that MOF-1 belongs to trigonal system, R-3 space group, and it presents a three-dimensional structure. The specific surface area of MOF-1 was 13.461 m2/g with an average pore radius of 14.23 nm and that of MOF-2 was 2.5669 m2/g with an average pore radius of 8.91 nm. In addition, the fluorescence sensing performance of the two MOFs were also tested. MOF-1 and MOF-2 showed good sensing properties for tetracycline antibiotics and Fe3+ ions, respectively. Both MOFs exhibited a wide detection range and low detection limit, such as the detection range of MOF-2 for Fe3+ is 40–180 μM, and the detection limit is 0.01 nM. The sensing mechanism of the two MOFs can be explained by FRET and competitive absorption. These two MOFs have great application prospects in the fields of antibiotics and industrial wastewater detection due to their good water stability and sensing performance.

Older individuals and preventative behavioural interventions for COVID-19: a scoping review and perspective on wellbeing

Background In response to the COVID-19 pandemic, nations around the world introduced a range of behavioural interventions and restrictions in order to manage the spread of the virus. These included social distancing, lockdowns, and use of personal protective equipment, amongst others. The aim of the present paper is to examine some of the effects of these interventions on the psychological wellbeing and mental health of older adults, especially those with hearing loss. Methods The present review focused on published peer reviewed studies focusing on older adults. Search engines included Google Scholar, SpringerLink Journals, ProQuest Central, and PubMed employing different combinations of search terms such as “COVID-19”, “older adults”, and “isolation”. Results Older adults were at risk of experiencing increased anxiety and depression and poorer wellbeing during lockdowns across nations, with those self-reporting loneliness reporting more severe symptomatology. Reductions in wellbeing were observed both amongst community-dwelling older adults and those living in residential care facilities. Use of personal protective equipment, especially masks, and social distancing requirements impacted communication amongst older adults with hearing loss, with this subgroup reporting increased depression, anxiety, and stress, with symptoms increasing with the severity of the hearing loss. Conclusions While technology can help to mitigate the impacts of lockdowns and restrictions, limited access to devices and a range of challenges in upskilling older adults has impacted the utility of these technologies for promoting wellbeing. Education and training in the use of technologies and digital devices for both older adults and families might assist in promoting wellbeing, with increased accessibility needed in aged care facilities to further support the wellbeing of residents.

Interspecific competition impacts the occupancy and range limits of two ptarmigan species along the elevation gradient in Norway

Many mountain species are expected to respond to climate change through upslope shifts of their range limits, but competition may restrict or alter this response. Under traditional range‐limit theory, it is expected that lower‐elevation species are better competitors than closely related higher‐elevation species. However, recent work finds that this prediction is often unmet. We investigated evidence for the impact of competition during breeding season on the elevational range limits of a pair of closely related bird species, willow ptarmigan Lagopus lagopus and rock ptarmigan L. muta, in mainland Norway. The species share overlapping ranges that loosely divide slightly upslope from the treeline ecotone, with willow ptarmigan generally occupying lower sites and rock ptarmigan occupying higher sites. We used multi‐species occupancy models to test four competing hypotheses for how competition may affect the range limit between willow ptarmigan and rock ptarmigan: 1) asymmetric competition that restricts the lower range limit of rock ptarmigan; 2) asymmetric competition that restricts the upper range limit of willow ptarmigan; 3) condition‐specific competition that restricts both species' range limits; and 4) range limits unaffected by competition. We found evidence for a negative pairwise interaction between the two species. Changes in interaction strength along the elevation gradient suggested evidence for condition‐specific competition. However, a strong positive correlation between rock ptarmigan and higher‐elevation habitat resulted in a highly asymmetric outcome, where the upper range limit of willow ptarmigan was restricted but rock ptarmigan occupancy was fairly independent of willow ptarmigan. This outcome is opposite to the prediction of traditional range‐limit theory and may suggest a greater climate threat to willow ptarmigan than has been previously projected. Thus, our results demonstrate the importance of considering biotic interactions at both the higher and lower ends of species' range limits along elevation gradients.

σ-Hole Effect-Induced Electroluminescence of Halogen Cocrystals for Determination of Iodide in Seawater.

Developing new electrochemiluminescence (ECL) luminators with high stability, wide applicability, and strong designability is of great strategic significance to promote the ECL field to the frontier. Here, driven by the I···N bond, 1,3,5-trifluoro-2,4,6-triiodobenzene (TFTI) and 2,4,6-trimethyl-1,3,5-triazine (TMT) self-assembled into a novel halogen cocrystal (TFTI-TMT) through slow solution volatilization. Significant difference of charge density existed between the N atoms on TMT and the σ-hole of the I atoms on TFTI. Upon the induction of σ-hole effect, high-speed and spontaneous charge transferring from TMT to the σ-hole of TFTI occurred, stimulating exciting ECL signals. Besides, the σ-hole of the I atoms could capture iodine ions specifically, which blocked the original charge transfer from the N atoms to the σ-hole, causing the ECL signal of TFTI-TMT to undergo a quenching rate as high as 92.9%. Excitingly, the ECL sensing of TFTI-TMT toward I- possessed a wide linear range (10-5000 nM) and ultralow detection limit (3 nM) in a real water sample. The halogen cocrystal strategy makes σ-hole a remarkable new viewpoint of ECL luminator design and enables ECL analysis technology to contribute to addressing the environmental and health threats posed by iodide pollution.

Ultrasonic flexible array for non-destructive testing of complex curved surfaces

Ultrasound detection technology in Non-Destructive Testing (NDT) is widely used. Ultrasonic transducer arrays effectively solved the problem of limitation in the detection range of single beam scanning transducers. However, the common used ultrasonic transducer arrays are rigid that are difficult to achieve complete contact with complex curved surfaces. Flexible arrays can be bent to a certain extent and can adaptively fit the surface of different curvature structures for detection. This work reported ultrasonic transducer flexible arrays that combine 2D arrays and linear arrays. The arrays have eight lines and each can be individually controlled. Each line has eight elements. The arrays expand the detection range and greatly reduce the control circuit difficulty and signal processing difficulty. The average operating frequency of the measured arrays is 2.5 MHz, the bandwidth is close to 30% and the insertion loss is close to −33 dB. Also, the arrays can detect defects through curved surface testing. Based on these advantages, this study paved the way for further investigation into the flexible ultrasonic arrays.

Real-time application and modelling of the NOx-sorption reaction on a particulate calcium carbonate surface-flow filter exposed to combustion exhaust.

Of major interest, especially in city environments, and increasingly inside vehicles or industrial plants, is the drive to reduce human exposure to nitrogen oxides (NOx). This trend has drawn increasing attention to filtration, which has developed remarkably owing to the capabilities of recently developed mathematical models and novel filter concepts. This paper reports on the study of the kinetic modelling of adsorption of nitrogen dioxide (NO2), collected from the tailpipe of a diesel engine, reacting to calcium nitrate salt (Ca(NO3)2) on a surface flow filter consisting of a coating of fine ground limestone or marble (CaCO3) in combination with micro-nanofibrillated cellulose (MNFC) acting as binder and humectant applied onto a multiply recycled newsprint substrate. The coating and substrate are both porous, but on different pore size scales, with the coating having significantly lower permeability. To maximise gas-coating contact, therefore, the coating deposition is pixelated, achieved by pin coating. An axially dispersed gaseous plug flow model (dispersion model) was used to simulate the transport within the coating pore network structure, following earlier flow modelling studies, and a kinetic reaction model was used to examine NO2 to NO3- conversion in correlation with experimental results. Modelling results indicate a 60.38% conversion of exposed NO2 gas to Ca(NO3)2 under the specific conditions applied, with an absolute relative error between the predicted and experimentally estimated value being 0.81%. The model additionally enabled a prediction of effects of changing parameters over a limited perturbation range, thus assisting in predicting filter element consumption, with attention given to the active component CaCO3 surface as a function of particle size in relation to the gas contact exchange, promoting the reaction over time. It is intended that the Ca(NO3)2 formed from the reaction can go on to be used as a value-added fertiliser, thus contributing to circular economy.

Windshear Detection in Rain Using a 30 km Radius Coherent Doppler Wind Lidar at Mega Airport in Plateau

Convective weather is often accompanied by precipitation and windshear, seriously endangering the safety of aircraft during takeoff and landing. However, under rainfall conditions, conventional wind lidars have a limited detection range due to significant signal attenuation. To solve this problem, a 200 mm temperature-controlled telescope coated with a hydrophobic film is applied in the coherent Doppler wind lidar system to improve the detection capability in rain. The maximum detection range of the lidar is extended to 30 km and demonstrated at Kunming Changshui International Airport at an altitude of 2102 m. Firstly, the detection accuracy and maximum detection range of the lidar are verified. Through the analysis of the horizontal wind field under two typical convective weather conditions, it is found that convective weather often accompanies low-level convergence and divergence structures, leading to headwind shear and crosswind shear on the airport runway. From the vertical profile, it is shown that the triggering of convective weather is accompanied by low-level southwest winds and high-altitude northeastern winds. According to the statistics of wind speed and direction on clear and rainy days over 9 months, rainy days are usually caused by the invasion of cold air from Northeast China, resulting in airport windshear. In summary, the enhanced lidar can effectively identify and analyze windshear during rainy days, which is very useful for aviation safety, especially for takeoff and landing in all weather conditions.

Electroextraction of methylene blue from aqueous environmental samples using paper points coupled with hollow fiber membranes

This article introduces a novel approach by coupling paper points with hollow fiber membrane for electroextraction (PP–HF-EE). The method was innovatively applied to extract methylene blue (MB) from large water volumes (up to 580 mL). A comprehensive study of six key parameters – organic filter, acceptor and donor phase composition, extraction time, applied voltage, and sample volume – was conducted using conventional flatbed scanning and digital image analysis. Our results revealed that extraction performance was primarily influenced by time, with low voltages (50 V) and low-conductivity organic filters (1-decanol) yielding comparable results to higher settings (300 V or 1-pentanol). Under optimized conditions (50 V, 60 min, 1-decanol as the organic filter), analytical performance parameters were assessed, demonstrating acceptable precision (RSD <18% for intra- and inter-day measurements) within a linear range of 5–100 μg L−1 (r = 0.98). PP–HF–EE demonstrated reliability through stable and reproducible electric current measurements during all extraction studies. Utilizing an extremely cost-effective detection system, PP–HF–EE achieved detection limits in the low ppb range, highlighting its potential as a promising variation of electromembrane extraction for environmental sample analysis.

Relative vectoring using dual object detection for autonomous aerial refueling

AbstractOnce realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process of capturing an image, finding 2D points in the image, matching those points to 3D object features, and analytically solving for the object pose. However, we extend this pipeline by simultaneously performing these operations across two objects instead of one using machine learning and add a fifth stage that transforms the two pose estimates into a relative vector. Furthermore, we propose a novel supervised learning method using bounding box corrections such that our trained artificial neural networks can accurately predict 2D image points corresponding to known 3D object points. Simulation results show that this method is reliable, accurate (within 3 cm at contact), and fast (45.5 fps).