Field Test Research Articles

Reassembling the Field-based Applicability of the Lactate Threshold for Old Age.

This study aimed to investigate the applicability of the Lactate Threshold (LT) to predict maximal oxygen uptake (˙VO2max) and demarcate the boundary between the moderate- to heavy-intensity domain (HRm-h) in old age in comparison to the most utilized methods. A cross-sectional validation study was conducted. Participants aged 61 to 77 performed a familiarization procedure, an incremental maximal exercise treadmill test (CPX) for ˙VO2max determination, the Six-minute Walk Test (6MWT), and a discontinuous incremental field test for LT determination. Lower (P<0.01) internal effort was required for LT testing (76±8%HRmax) compared to 6MWT (92±9%HRmax). The application of the 6MWT reference equations overestimated ˙VO2max by 10-23%. LTs better estimated the ˙VO2max (r ≈0.90, SEE: ≈3.0] compared to the 6MWT (r=0.68, SEE=5.5). HRm-h determined by the CPX differed (20%; P=0.001) from that obtained by LT. HRm-h stratification indicated participants fall into the very light to the vigorous intensity domains. LT testing is more submaximal than the 6MWT, and is a valuable tool to estimate the ˙VO2max in older male adults. Implementation of LT testing in physical activity programs might help improving the quality of aerobic exercise training in older men.

Hippocampal Crhr1 conditional gene knockout ameliorated the depression-like behavior and pathological damage in male offspring mice caused by chronic stress during pregnancy

Numerous studies have demonstrated that chronic stress during pregnancy (CSDP) can induce depression and hippocampal damage in offspring. It has also been observed that high levels of corticotropin-releasing hormone (CRH) can damage hippocampal neurons, and intraperitoneal injection of a corticotropin releasing hormone receptor 1 (CRHR1) antagonist decreases depression-like behavior and hippocampal neuronal damage in a mouse depression model. However, whether CSDP causes hippocampal damage and depression in offspring through the interaction of CRH and hippocampal CRHR1 remains unknown and warrants further investigation. Therefore, hippocampal Crhr1 conditional gene knockout mice and C57/BL6J mice were used to study these questions. Depression-related indexs in male offspring mice were examined using the forced swim test (FST), sucrose preference test (SPT), tail suspension test (TST) and open field test (OFT). Serum CRH levels were measured by enzyme-linked immunosorbent assay (ELISA). Golgi-Cox staining was used to examine the morphological changes of hippocampal neuronal dendrites. Neuronal apoptosis in the hippocampal CA3 regions was detected by terminal deoxynucleotidy transferase dUTP nick end labeling (TUNEL) staining. The levels of mammalian target of rapamycin (mTOR), phosphorylated mTOR (p-mTOR) and protein kinase B (AKT) proteins were measured by Western blot analysis. This study showed that CSDP induces depression-like behavior, hippocampal neuronal dendrite damage and apoptosis in male offspring mice. Conditional gene knockout of hippocampal Crhr1 in mice reduced CSDP-induced depression-like behavior, hippocampal neuronal dendrite damage and apoptosis in male offspring, and counteracted the CSDP-induced decreased expression of p-Akt and mTOR activity in male offspring hippocampus. These findings demonstrated that CSDP might inhibit the Akt/mTOR pathway by increasing the levels of CRH, leading to increased CRH-mediated activation of hippocampal CRHR1, thereby inducing synaptic impairment and apoptosis in hippocampal neurons, which in turn leads to depression-like behavior in offspring.

The effect of 10-week wholebody calisthenics training program on the muscular endurance of untrained collegiate students

The study aimed to investigate the effects of calisthenics exercise on muscular endurance by implementing a 10-week whole-body calisthenic training program on 183 randomly selected untrained collegiate students (108 females, 75 males). A two-group pretest-posttest design was employed (CG = 88; EG = 95), accompanied by three muscular endurance field tests to thoroughly observe the probable effects of the training program on this fitness component. The pretest involved administering fitness tests, followed by the 10-week training program for the EG. The CG was instructed to engage in one hour of preferred physical activity three times a week for 10 weeks. Post-testing was completed by administering the same fitness tests. The normality of the data was assessed using the Shapiro-Wilk test. For intragroup comparison, the Wilcoxon signed-rank test was used, while for intergroup comparison, the Mann-Whitney U test was employed. Among females in the CG, the One Minute Push-up Test showed a significant improvement from a mean of 10.80 (±7.18) to 13.97 (±7.53) (p &lt; .00001*), while the PT increased from 68.83 (±37.80) to 78.79 (±41.50) (p = .00036*), and the Wall Sit scores rose from 48.90 (±27.04) to 65.59 (±31.86) (p &lt; .00001*). In males, the Wall Sit demonstrated a significant improvement from 58.15 (±26.47) to 83.88 (±50.28) (p = .00022*). Conversely, the EG exhibited significant improvements in all three tests for both females and males. Inter-group comparisons revealed the EG's significantly higher mean scores in the One Minute Push-up Test (24.50 vs. 18.17, p = .00494*), PT(107.87 vs. 79.85, p = .01044* for males), and Wall Sit (112.34 vs. 83.88, p = .01255*). Both female and male participants in the EG showed significant improvements in the One Minute Push-up Test, Planking Test, and Wall Sit compared to the CG, with consistently higher mean scores across all tests.

A pressure-triggered isobaric sequential liquid sampling system for full-ocean-depth: Design and field deployment

Collecting pressure-retaining deep-sea liquid samples is important for the research on in-situ environment and life. A pressure-triggered isobaric sequential liquid sampling system (PTISLSS) was developed for the collection of seawater at target depths. The sampling system comprises six independent seawater collection modules, each containing a titanium sample container and a pre-charged accumulator. A motor-driven sampling mechanism was designed to open and close the fluid channels at depth. Theoretical studies have indicated that the mechanism can generate a contact pressures of up to 160 MPa to ensure the sealing of the samples. The relationship between the pressure of pre-charged gas and the volume of fluid sample has been derived considering the effects of seal friction. The sampling system was built for full-ocean-depth sampling operation and the reliability of the system was tested at a pressure of 120 MPa. The field test was conducted in the West Philippine Basin on a recent scientific research cruise. Pressurized seawater from depths of 2000 to 4500 meters was recovered, and the pressure-retaining rate exceeded 93.5%. The developed sampling system presents satisfactory performance and high operational efficiency, and it will have a wide range of applications in the field of large-scale deep-sea sampling.

JVC-02 Teleoperated Robot: Design, Implementation, and Validation for Assistance in Real Explosive Ordnance Disposal Missions

Explosive ordnance disposal (EOD) operations are hazardous due to the volatile and sensitive nature of these devices. EOD robots have improved these tasks, but their high cost limits accessibility for security institutions that do not have sufficient funds. This article presents the design, implementation, and validation of a low-cost EOD robot named JVC-02, specifically designed for use in explosive hazardous environments to safeguard the safety of police officers of the Explosives Disposal Unit (UDEX) of Arequipa, Peru. To achieve this goal, the essential requirements for this type of robot were compiled, referencing the capabilities of Rescue Robots from RoboCup. Additionally, the Quality Function Deployment (QFD) methodology was used to identify the needs and requirements of UDEX police officers. Based on this information, a modular approach to robot design was developed, utilizing commercial off-the-shelf components to facilitate maintenance and repair. The JVC-02 was integrated with a 5-DoF manipulator and a two-finger mechanical gripper to perform dexterity tasks, along with a tracked locomotion mechanism, which enables effective movement, and a three-camera vision system to facilitate exploration tasks. Finally, field tests were conducted in real scenarios to evaluate and experimentally validate the capabilities of the JVC-02 robot, assessing its mobility, dexterity, and exploration skills. Additionally, real EOD missions were carried out in which UDEX agents intervened and controlled the robot. The results demonstrate that the JVC-02 robot possesses strong capabilities for real EOD applications, excelling in intuitive operation, low cost, and ease of maintenance.

Footbridge damage detection using smartphone-recorded responses of micromobility and convolutional neural networks

This paper presents a footbridge damage detection and classification framework using smartphone-recorded responses of micromobility and deep learning techniques. Time–frequency representations (TFRs) of scooter vibrations are employed to detect and classify footbridge damage severities using a Two-Dimensional Convolutional Neural Network (2D CNN). A One-Dimensional (1D) CNN using scooter frequency spectra was also investigated for comparison. The effectiveness of the method was verified using a numerical model of scooter-footbridge interactions and field tests on a real footbridge. The results indicated that both CNNs were sensitive to footbridge frequency alterations caused by damage in the numerical simulations. Nevertheless, the performance of the 1D CNN experienced a substantial decline in field tests involving stochastic influencing factors, whereas the accuracy of damage classification using the 2D CNN remained high. Finally, reasonable interpretations for the superior performance of the 2D CNN are provided using Shapley Additive Explanations (SHAP) values.

The remarkable impact of Opuntia Ficus Indica fruit administration on metabolic syndrome: Correlations between cognitive functions, oxidative stress and lipid dysmetabolism in the high-fat, diet-fed rat model

BackgroundA wealth of evidence underscores the bioactive properties of nutraceuticals and functional foods in addressing oxyinflammatory-based diseases with implications at both peripheral and central levels. Opuntia ficus-indica (OFI) is well-documented for its health-promoting attributes, though its fruit (OFIF) remains relatively understudied. Not only poses Metabolic Syndrome (MetS) cardiometabolic risks but also contributes significantly to cognitive impairment, especially in crucial brain areas such as hippocampus and hypothalamus. MethodsFollowing 8 weeks of HFD to induce MetS, rats received OFIF oral supplementation for 4 weeks to evaluate cognitive and affective modifications using behavioural paradigms, i.e. open field, burrowing, white-dark box, novelty-suppressed feeding, and object recognition tests. Our investigation extended to biochemical evaluations of lipid homeostasis, central and peripheral oxidative stress and neurotrophic pathways, correlating these measures together with circulating leptin levels. ResultsOur data revealed that OFIF modulation of leptin positively correlates with systemic and brain oxidative stress, with markers of increased anxiety-like behaviour and impaired lipid homeostasis. On the other hand, leptin levels reduced by OFIF are associated with improved antioxidant barriers, declarative memory and neurotrophic signalling. DiscussionThis study underscores OFIF neuroactive potential in the context of MetS-associated cognitive impairment, offering insights into its mechanisms and implications for future therapeutic strategies.

Study on Field Test of Deformation and Stability Control Technology for Shallow Unsymmetrical Loading Section of Super-Large-Span Tunnel Portal

This study focuses on monitoring the deformation of the shallow unsymmetrical section of a super-large-span tunnel portal relying on the newly built Shimentangshan Tunnel, and through numerical simulations, the construction sequence and drift ratios were optimized to address challenges related to the stability of surrounding rock and structure. The findings indicate that employing the double-side drift method results in a maximum settlement value of 107.0 mm and a maximum convergence value of 108.8 mm, leading to larger deformations. Excavating the shallow buried side first followed by the deep buried side proves beneficial for deformation control of the support structure and effectively limits damage to the surrounding rock. A drift ratio of 0.3 ensures optimal support structure security and stability. Considering both structural deformation and surrounding rock damage, a ratio between 0.25 and 0.35 for the drifts is recommended. Taking into account construction efficiency and economic benefits, a construction plan for the shallow buried unsymmetrical section at the portal of super-large-span tunnels is proposed.

TORONTO: A trial-oriented multidimensional psychometric testing algorithm.

Bayesian adaptive methods for sensory threshold determination were conceived originally to track a single threshold. When applied to the testing of vision, they do not exploit the spatial patterns that underlie thresholds at different locations in the visual field. Exploiting these patterns has been recognized as key to further improving visual field test efficiency. We present a new approach (TORONTO) that outperforms other existing methods in terms of speed and accuracy. TORONTO generalizes the QUEST/ZEST algorithm to estimate simultaneously multiple thresholds. After each trial, without waiting for a fully determined threshold, the trial-oriented approach updates not only the location currently tested but also all other locations based on patterns in a reference data set. Since the availability of reference data can be limited, techniques are developed to overcome this limitation. TORONTO was evaluated using computer-simulated visual field tests: In the reliable condition (false positive [FP] = false negative [FN] = 3%), the median termination and root mean square error (RMSE) of TORONTO was 153 trials and 2.0dB, twice as fast with equal accuracy as ZEST. In the FP = FN = 15% condition, TORONTO terminated in 151 trials and was 2.2 times faster than ZEST with better RMSE (2.6 vs. 3.7dB). In the FP = FN = 30% condition, TORONTO achieved 4.2dB RMSE in 148 trials, while all other techniques had > 6.5dB RMSE and terminated much slower. In conclusion, TORONTO is a fast and accurate algorithm for determining multiple thresholds under a wide range of reliability and subject conditions.

Development of an overlaid concrete median barrier: Numerical studies and full-scale field tests

This study aims to develop an overlaid CMB(Concrete Median Barrier) with a containment level of SB5 (230 kJ of impact severity) based on a series of numerical simulations and full-scale field tests. The 810-mm CMB (CMB810) currently in service on roads, should be overlaid up to height of 1370 mm (CMB1370) with containment level of SB5 to prevent vehicles from traveling over it. From a series of numerical simulation, the effects of dowel/longitudinal bars on structural adequacy and occupant risk were quantitatively assessed in order to develop the CMB1370. Numerical analyses indicate that decreasing the spacing of dowel bars and the proximity of longitudinal bars from the top of the CMB1370 can significantly lessen the volume loss incurred during vehicle-to-barrier collisions. The numerically proposed CMB1370 underwent full-scale field tests in compliance with three evaluation criteria: (1) structural adequacy, (2) occupant risk, (3) vehicle's post-impact trajectory. The full-scale field test results demonstrated that the CMB1370 effectively contained and redirected the vehicle without any instance of damages, penetration or overriding. The measured deformation of CMB1370 by several LVDTs was within acceptable limits for use on the road. Previous full-scale field tests, the primary focus was on the structural adequacy of the CMB and the resulting damage it sustained. However, these findings provide new insights into the behavior and rehabilitation of the CMB, as well as the damage sustained at impact. Moreover, no significantly fragmented debris larger than 2.0 kg was observed from the barrier. Thus, the proposed CMB1370 meets all the requirements specified in the crash test guidelines in Korea.

Effects of temporary access to environmental enrichment on measures of laboratory mouse welfare

Laboratory mice are typically housed in “shoebox” cages with limited opportunities to engage in natural behaviour. Temporary access to environments with increased space and complexity (playpens) may improve mouse welfare. Previous work by our group has shown that mice are motivated to access and use these environments, but it is unknown how other aspects of welfare are impacted. Female C57BL/6J, BALB/cJ, and DBA/2J mice (n = 21; 7 mice per strain) were housed in mixed-strain trios and given temporary access to a large playpen with their cage mates three times per week. Control mice (n = 21; 7 mice per strain) remained in their home cages. Home cage behaviour (development of stereotypic behaviour over time, aggression following cage-changing) and anxiety tests were used to assess how playpen access impacted welfare. Contrary to our predictions, we found increased time spent performing stereotypies in playpen mice; this difference may be related to negative emotional states, increased motivation to escape the home cage, or active coping strategies. Playpen access resulted in strain-dependent improvements in aggression and some measures of anxiety. Aggression was lower for C57BL/6J mice in the playpen treatment following cage changing than it was for C57BL/6J control mice, while playpen mice, and particularly the C57BL/6J strain, spent more time in the center of the open field test and produced fewer fecal boli during anxiety testing, supporting other research showing that strain differences play an important role in behaviour and stress resiliency.

Tank-Mix Adjuvants Enhance Pesticide Efficacy by Improving Physicochemical Properties and Spraying Characteristics for Application to Cotton with Unmanned Aerial Vehicles.

Tank-mix adjuvants have been used to reduce spray drift and facilitate the efficacy of pesticides applied with unmanned aerial vehicles (UAVs). However, the effects of specific adjuvants on pesticide characteristics and the mechanism of action remain unclear. Herein, we analyzed the effects of three different types of tank-mix adjuvants (plant oil; mineral oil; and mixture of alcohol and ester) on the surface tension (ST), contact angle, wetting, permeation, evaporation, spray performance, and aphid-control effects of two types of pesticides. The mineral oil adjuvant Weichi (WCH) was highly effective in reducing the pesticide solution ST, improving the wetting and penetration ability, increasing droplet size, and promoting droplet deposition. The mixed alcohol and ester adjuvant Quanrun (QR) showed excellent wetting and antievaporation properties and promoted droplet deposition. A plant oil adjuvant (Beidatong) moderately improved wetting and penetration ability and reduced droplet drift. Field tests showed that the control efficiencies (CEs) of two pesticides were increased after the addition of adjuvants, even with 20% reductions in pesticide application. When the UAV was operated at 1.5 m, the CEs of two pesticides were increased from 65.39 and 66.63% to 73.11-76.52% and 77.91-88.31%, respectively. When operated at 2.5 m, the CEs were increased from 51.24 and 68.60% to 65.06-75.70% and 77.57-92.59%, respectively. Especially, the CEs of pesticides with WCH and QR increased obviously. Importantly, neither WCH nor QR inhibited hatching of the critical insect natural enemy ladybird beetle at concentrations used in the field. This study provides a framework for assessment of tank-mix adjuvants in aerial sprays and directly demonstrates the value of specific adjuvants in improving pesticide bioavailability and minimizing associated environmental pollution.

Obesity is associated with lower levels of negative emotions in polycystic ovary syndrome in clinical and animal studies

Background Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic disorders in women of reproductive age. It is frequently comorbid with obesity and negative emotions. Currently, there are few reports on the relationship between obesity and negative emotions in patients with PCOS. Here we performed both basic and clinical studies to study the relationship between obesity and negative emotions in PCOS. Methods We performed a cross-sectional study including 608 patients with PCOS and 184 healthy participants to assess the mental health status of people with different body mass indices (BMI). Self-rated anxiety, depression, and perceived stress scales were used for subjective mood evaluations. Rat PCOS models fed 45 and 60% high-fat diets were used to confirm the results of the clinical study. Elevated plus maze and open field tests were used to assess anxiety- and depression-like behaviors in rats. Results We observed overweight/obesity, increased depression, anxiety, and perceived stress in women with PCOS, and found that anxiety and depression were negatively correlated with BMI in patients with severe obesity and PCOS. Similar results were confirmed in the animal study; the elevated plus maze test and open field test demonstrated that only 60% of high fat diet-induced obesity partly reversed anxiety- and depression-like behaviors in PCOS rats. A high-fat diet also modulated rat hypothalamic and hippocampal luteinizing hormone and testosterone levels. Conclusion These results reveal a potential relationship between obesity and negative emotions in PCOS and prompt further investigation. The interactions between various symptoms of PCOS may be targeted to improve the overall well-being of patients.

Method of field measurement of electromagnetic environment of high speed maglev train

Abstract In order to reduce the complexity of the magnetic field test of maglev trains and improve the accuracy of measurement data, this paper proposes a field measurement method of maglev train radiation emission based on high-speed parallel adaptive filter denoising technology. This measurement method is not limited by special measurement sites, and has the characteristics of high-speed measurement, real-time data processing, and large-capacity data storage. It breaks through the technical bottleneck of the traditional measurement system. The electromagnetic radiation emission of high-speed maglev trains is measured in real-time through multi-antenna synchronous measurement technology, and multi-channel high-speed RF signal measurement and acquisition of external signals are further carried out by blind source separation technology, environmental pre-scanning is carried out, environmental interference characteristics are obtained through feature statistics, and the radiation signal to be measured is estimated by blind source separation algorithm. It helps to achieve the purpose of accurately measuring the electromagnetic radiation emission of high-speed maglev trains. Through field testing, the denoising performance of the method reached 20 dB. Through field testing, the denoising performance of the method reached 20 dB.

Rockburst prediction based on multi-featured drilling parameters and extreme tree algorithm for full-section excavated tunnel faces

The suddenness, uncertainty, and randomness of rockbursts directly affect the safety of tunnel construction. The prediction of rockbursts is a fundamental aspect of mitigating or even eliminating rockburst hazards. To address the shortcomings of the current rockburst prediction models, which have a limited number of samples and rely on manual test results as the majority of their input features, this paper proposes rockburst prediction models based on multi-featured drilling parameters of rock drilling jumbo. Firstly, four original drilling parameters, namely hammer pressure (Ph), feed pressure (Pf), rotation pressure (Pr), and feed speed (VP), together with the rockburst grades, were collected from 1093 rockburst cases. Then, a feature expansion investigation was performed based on the four original drilling parameters to establish a drilling parameter feature system and a rockburst prediction database containing 42 features. Furthermore, rockburst prediction models based on multi-featured drilling parameters were developed using the extreme tree (ET) algorithm and Bayesian optimization. The models take drilling parameters as input parameters and rockburst grades as output parameters. The effects of Bayesian optimization and the number of drilling parameter features on the model performance were analyzed using the accuracy, precision, recall and value of the prediction set as the model performance evaluation indices. The results show that the Bayesian optimized model with 42 drilling parameter features as inputs performs best, with an accuracy of 91.89%. Finally, the reliability of the models was validated through field tests.

Reference Database for a Novel Binocular Visual Function Perimeter: A Randomized Clinical Trial

PurposeTo construct a comprehensive reference database for a novel binocular automated perimeter. DesignA four-site prospective randomized clinical trial. Subjects and controls356 healthy subjects without ocular conditions that might affect visual function were categorized into 7 age groups. MethodsSubjects underwent comprehensive ocular examination of both eyes before enrollment. Using the TEMPO/IMOvifa automated perimeter (Topcon Healthcare/CREWT Medical Systems, Tokyo, Japan), each subject completed four binocular threshold visual field (VF) tests during a single visit: First, practice 24-2 and 10-2 tests were obtained from both eyes. Next, study 24-2 and 10-2 tests were obtained from both eyes. Test order of each sequence was randomized, and the tests were conducted under Standard Automated Perimetry testing conditions (SAP): Goldmann stimulus size III, 3183 cd/m2 maximum stimulus intensity, and background intensity of 10 cd/m2, using AIZE-Rapid test strategy. Standard VF reliability indices were assessed. For each subject, 24-2 and 10-2 test results from one randomly selected eye were analyzed. Main Outcome MeasuresPerimetric threshold sensitivity and reference limits for each test analysis parameter. ResultsThe ages of the study cohort were widely distributed, with a mean age (SD) of 52.3 (18.5) years. Sex assignment was 44.0% male and 56.0% female. The majority of subjects self-identified as White (67.4%), followed by Black or African American (13.5%) and Asian (8.7%), with 14.6% self-identified as Hispanic or Latino ethnicity. Mean sensitivity (MS) (SD) was 29.1 (1.3) decibels (dB) for the 24-2 and 32.4 (1.0) dB for the 10-2 test. For the 24-2 and 10-2, MS (SD) age-related changes averaged -0.06 (0.01) dB and -0.05 (0.01) dB per year, respectively. The normal range of pointwise threshold sensitivity increased with eccentricity and showed asymmetry around the mean, particularly notable in the 24-2 test. Mean (SD) binocular test duration was 3.18 (0.38) minutes (1 minute 35 seconds per eye) for the 24-2 test and 3.58 (0.43) minutes (1minute 47 seconds per eye) for the 10-2 test. ConclusionsA reference database for the TEMPO/IMOvifa perimeter was established, highlighting the significance of considering both age and stimulus eccentricity in interpreting threshold visual field test results.

Frequency Identification using Resonance Curve-Based Drive-by Monitoring: Field Validation

Railway bridges have a long service life - in Germany, for example, the average is 122 years. During this time, vehicles are constantly evolving, leading to innovative axle configurations and higher speeds. This leads to loads for which the bridges were not originally designed, which can lead to resonant structural responses. A key parameter for calculating and evaluating the dynamic behaviour of bridge structures, is the resonance frequency. Due to the large number of bridges in the network, conventional methods using sensors on the structure would be very laborious. A cost-effective alternative would be drive-by monitoring, using sensors on a passing train. In railway bridge contexts, drive-by monitoring to identify frequencies faces challenges from short spans and high speeds, leading to brief contact periods. The brief periods cause a low resolution of the signals in the frequency domain. An approach to overcome this issue is the use of resonance curve-based drive-by monitoring. The term resonance curve describes the maximum structural responses as a function of speed. In conjunction with the known axle configuration of the train, the resonance frequency can be determined from the resonance curve. In this paper, data from two field tests are analysed, in which synchronised acceleration measurements were conducted on the main girders of the bridges and the axle boxes of the trains. An ICE 4 was used on a bridge with a 19.5-metre span, and an ICE TD on a bridge spanning 16.4 metres. The analyses show that frequency identification using indirect resonance curves is feasible under real operating conditions. Thus, this approach enables the determination of a key parameter essential for calibrating structural models. Furthermore, this method enables the avoidance of resonance crossings by speed adaptation, either by acceleration or deceleration. This strategy has the potential to significantly increase the service life of bridges.

Multi-vessel target tracking with camera fusion for unmanned surface vehicles

With the decreasing availability of sailors, there has been an increasing focus on the development of autonomous ships. Among the various components of autonomous ships, automatic recognition systems that can replace human vision are a crucial area of research. While ongoing studies utilize traditional perception sensors such as RADAR (RAdio Detection And Ranging) and AIS (Automatic Identification System), they have limitations such as blind spots and a restricted detection range. To address these limitations, this paper proposes a new recognition method that utilizes multiple cameras, including electro-optical and infrared radiation cameras, to supplement traditional perception sensors. This method aims to detect maritime obstacles accurately and estimate their dynamic motion using a tracking process. Initially, real-sea images were collected for maritime obstacle detection, and a deep-learning-based detection model was trained on them. The detection results were then employed in an adaptive tracking filter, which allowed the precise motion estimation of the obstacles. Furthermore, to compensate for the limitations of using individual cameras as sensors, this study introduces the simultaneous fusion of tracked data from multiple cameras. This fusion process enhances tracking results in various ways. In field tests using multiple Unmanned Surface Vehicles (USVs), the proposed method successfully converged tracking results within the range of GPS errors. In addition, the fusion of tracked data from multiple cameras significantly improved the tracking results obtained from a single camera.

Adjustment mechanism of blasting dynamic-static action in the water decoupling charge

Water decoupling charge blasting excels in rock breaking, relying on its uniform pressure transmission and low energy dissipation. The water decoupling coefficients can adjust the contributions of the stress wave and quasi-static pressure. However, the quantitative relationship between the two contributions is unclear, and it is difficult to provide reasonable theoretical support for the design of water decoupling blasting. In this study, a theoretical model of blasting fracturing partitioning is established. The mechanical mechanism and determination method of the optimal decoupling coefficient are obtained. The reliability is verified through model experiments and a field test. The results show that with the increasing of decoupling coefficient, the rock breaking ability of blasting dynamic action decreases, while quasi-static action increases and then decreases. The ability of quasi-static action to wedge into cracks changes due to the spatial adjustment of the blast hole and crushed zone. The quasi-static action plays a leading role in the fracturing range, determining an optimal decoupling coefficient. The optimal water decoupling coefficient is not a fixed value, which can be obtained by the proposed theoretical model. Compared with the theoretical results, the maximum error in the model experiment results is 8.03%, and the error in the field test result is 3.04%.

Long‐Term Performance on Drought Mitigation of Soil Slope Through Bio‐Approach of MICP: Evidence and Insight from Both Field and Laboratory Tests

AbstractDrought is a serious global environmental issue that causes water resource scarcity and threatens agriculture and food supplements. This study aims to investigate the long‐term performance of an eco‐friendly technique‐microbial induced carbonate precipitation (MICP) on drought mitigation at field and laboratory scales. Seven in‐situ slopes treated with different MICP rounds and cementation solution concentrations were subjected to 16‐month weathering. Tests were conducted to evaluate the evaporation characteristics, water retention capacity, and CaCO3 distribution. Laboratory soil samples were further prepared to provide evidence related to underlying weathering mechanisms. The results show that MICP has a time‐dependent performance on drought mitigation. After MICP treatment, soil performs a remarkable evaporation suppression ability and the evaporation rate can decrease by 50%. This is attributed to the soluble salts which increase soil water retention capability and dense hard crust which inhibits water vapor migration into the atmosphere. However, the soluble salts and crust are sensitive to weathering thus leading to degradation of MICP. Suffering 16‐month weathering, the MICP‐induced CaCO3 decreases by more than 60%. The evaporation rate of soil increases with MICP rounds and cementation solution concentrations and can reach nearly two times of untreated soil. MICP‐treated field soil exhibits weaker water retention capacity than untreated soil because MICP alters soil microstructure which expands macropores and decreases volume of micropores. Connected macropores act as favorable evaporation channels and accelerate evaporation. To ensure MICP long‐term effects, periodical treatments are necessary. The most effective MICP treatment scheme is four to six treatment rounds and 1.0 M cementation solution.