Fiber optic monitoring of an anti-slide pile in a retrogressive landslide

Anti-slide piles are one of the most important reinforcement structures against landslides,and evalu-ating the working conditions is of great significance for landslide mitigation.The widely adopted analytical methods of pile internal forces include cantilever beam method and elastic foundation beam method.However,due to many assumptions involved in calculation,the analytical models cannot be fully applicable to complex site situations,e.g.landslides with multi-sliding surfaces and pile-soil interface separation as discussed herein.In view of this,the combination of distributed fiber optic sensing(DFOS)and strain-internal force conversion methods was proposed to evaluate the working conditions of an anti-sliding pile in a typical retrogressive landslide in the Three Gorges reservoir area,China.Brillouin optical time domain reflectometry(BOTDR)was utilized to monitor the strain distri-bution along the pile.Next,by analyzing the relative deformation between the pile and its adjacent inclinometer,the pile-soil interface separation was profiled.Finally,the internal forces of the anti-slide pile were derived based on the strain-internal force conversion method.According to the ratio of calculated internal forces to the design values,the working conditions of the anti-slide pile could be evaluated.The results demonstrated that the proposed method could reveal the deformation pattern of the anti-slide pile system,and can quantitatively evaluate its working conditions.

Thermo-hydro-poro-mechanical responses of a reservoir-induced landslide tracked by high-resolution fiber optic sensing nerves

Thermo-poro-mechanical responses along sliding zone/surface have been extensively studied.However,it has not been recognized that the potential contribution of other crucial engineering geological interfaces beyond the slip surface to progressive failure.Here,we aim to investigate the subsurface multiphysics of reservoir landslides under two extreme hydrologic conditions(i.e.wet and dry),particularly within sliding masses.Based on ultra-weak fiber Bragg grating(UWFBG)technology,we employ specialpurpose fiber optic sensing cables that can be implanted into boreholes as“nerves of the Earth”to collect data on soil temperature,water content,pore water pressure,and strain.The Xinpu landslide in the middle reach of the Three Gorges Reservoir Area in China was selected as a case study to establish a paradigm for in situ thermo-hydro-poro-mechanical monitoring.These UWFBG-based sensing cables were vertically buried in a 31 m-deep borehole at the foot of the landslide,with a resolution of 1 m except for the pressure sensor.We reported field measurements covering the period 2021 and 2022 and produced the spatiotemporal profiles throughout the borehole.Results show that wet years are more likely to motivate landslide motions than dry years.The annual thermally active layer of the landslide has a critical depth of roughly 9 m and might move downward in warmer years.The dynamic groundwater table is located at depths of 9e15 m,where the peaked strain undergoes a periodical response of leap and withdrawal to annual hydrometeorological cycles.These interface behaviors may support the interpretation of the contribution of reservoir regulation to slope stability,allowing us to correlate them to local damage events and potential global destabilization.This paper also offers a natural framework for interpreting thermo-hydro-poro-mechanical signatures from creeping reservoir bank slopes,which may form the basis for a landslide monitoring and early warning system.

Coalbursts in China: Theory, practice and management

Coalburst is one of the most serious disasters that threaten the safe production of coal mines, and this disaster is particularly serious in China. This paper presents an overview of coalbursts in China since 1980s. From the "stress and energy" and "regional and local" perspectives, the achievements in the theory, practice and management of coalbursts in China are systematically summarized. A theoretical system of coalbursts has been formed to reveal the deformational behavior of coalbursts and explain the mechanism of coalbursts. The occurrence conditions of coalbursts are put forward and the critical stress is obtained. The stress index method for risk evaluation of coalbursts before mining is proposed, and the deformation localization prediction method of coalbursts is put forward. The relationship between energy release and absorption in the process of coalbursts is found, and the prevention and control methods of coalbursts, including the regional method, the local method and support, are presented. The safety evaluation index of coalburst prevention and control is put forward. The integrated prevention and control method for coal and gas outbursts is proposed. The prevention and control technology and equipment of coalbursts have also been developed. Amongst them, the distribution law of the critical stress in China coalburst mines is discovered. The technology and equipment for monitoring, prevention and control of coalbursts, as well as for integrated prevention and control of combined coalbursts and other disasters, have been developed. The energy-absorbing and coalburst-preventing support technology for roadways is invented, and key engineering parameters of coalburst prevention and control are pointed out. In China, coalburst prevention and control laws and standards have been developed. Technical standards for coalbursts are formulated, statute and regulations for coal mines are established, and regulatory documents are promoted.

Harness High-Temperature Thermal Energy via Elastic Thermoelectric Aerogels

Despite notable progress in thermoelectric(TE)materials and devices,developing TE aerogels with high-temperature resistance,superior TE performance and excellent elasticity to enable self-powered high-temperature monitoring/warning in industrial and wearable applications remains a great challenge.Herein,a highly elastic,flame-retardant and high-temperature-resistant TE aerogel,made of poly(3,4-ethylene dioxythiophene):poly(styrenesulfonate)/single-walled carbon nanotube(PEDOT:PSS/SWCNT)composites,has been fabricated,displaying attractive compression-induced power factor enhancement.The as-fabricated sensors with the aerogel can achieve accurately pressure stimuli detection and wide temperature range monitoring.Subsequently,a flexible TE generator is assembled,consisting of 25 aerogels connected in series,capable of delivering a maximum output power of 400μW when subjected to a temperature difference of 300 K.This demonstrates its outstanding high-temperature heat harvesting capability and promising application prospects for real-time temperature monitoring on industrial high-temperature pipelines.Moreover,the designed self-powered wearable sensing glove can realize precise wide-range temperature detection,high-temperature warning and accurate recognition of human hand gestures.The aerogel-based intelligent wearable sensing system developed for firefighters demonstrates the desired self-powered and highly sensitive high-temperature fire warning capability.Benefitting from these desirable properties,the elastic and high-temperature-resistant aerogels present various promising applications including self-powered high-temperature monitoring,industrial overheat warning,waste heat energy recycling and even wearable healthcare.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and recommended.Liquid chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous compounds.This technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics analysis.TDM improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window.Based on TDM,the dose would be optimized individually to achieve favorable outcomes.Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome evaluation.This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades.Besides,we discussed the advantages and disadvantages of this technique in practical use.The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted.Lastly,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Recent advances in stretchable triboelectric nanogenerators for use in wearable bioelectronic devices

Wearable bioelectronic devices have the capacity for real-time human health monitoring,the provision of tailored services,and natural interaction with smart devices.However,these wearable bioelectronic devices rely on conventional rigid batteries that are frequently charged or replaced and are incompatible with the skin,leading to a discontinuity in complex therapeutic tasks related to human health monitoring and human-machine interaction.Stretchable triboelectric nanogenerator(TENG)is a high-efficiency energy harvesting technology that converts mechanical into electrical energy,effectively powering wearable bioelectronic devices.This study comprehensively overviews recent advances in stretchable TENG for use in wearable bioelectronic devices.The working mechanism of stretchable TENG is initially explained.A comprehensive discussion presents the approaches for fabricating stretchable TENG,including the design of stretchable structures and the selection of stretchable materials.Furthermore,applications of wearable bioelectronic devices based on stretchable TENG in human health monitoring(body movements,pulse,and respiration)and human-machine interaction(touch panels,machine control,and virtual reality)are introduced.Ultimately,the challenges and developmental trends regarding wearable bioelectronic devices based on stretchable TENG are elaborated.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Reactor field reconstruction from sparse and movable sensors using Voronoi tessellation-assisted convolutional neural networks

The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.Current field-reconstruction methods fail to handle spatially moving sensors.In this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this challenge.Observations from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the sensors.General convolutional neural networks were used to learn maps from observations to the global field.The proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.

多功能热电织物用于可穿戴无线传感系统

Flexible thermoelectric materials play an important role in smart wearables,such as wearable power generation,self-powered sensing,and personal thermal management.However,with the rapid development of Internet of Things(IoT)and artificial intelligence(AI),higher standards for comfort,multifunctionality,and sustainable operation of wearable electronics have been proposed,and it remains challenging to meet all the requirements of currently reported thermoelectric devices.Herein,we present a multifunctional,wearable,and wireless sensing system based on a thermoelectric knitted fabric with over 600 mm·s^(-1)air permeability and a stretchability of 120%.The device coupled with a wireless transmission system realizes self-powered monitoring of human respiration through an mobile phone application(APP).Furthermore,an integrated thermoelectric system was designed to combine photothermal conversion and passive radiative cooling,enabling the characteristics of being powered by solar-driven in-plane temperature differences and monitoring outdoor sunlight intensity through the APP.Additionally,we decoupled the complex signals of resistance and thermal voltage during deformation under solar irradiation based on the anisotropy of the knitted fabrics to enable the device to monitor and optimize the outdoor physical activity of the athlete via the APP.This novel thermoelectric fabricbased wearable and wireless sensing platform has promising applications in next-generation smart textiles.

Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Application and management of continuous glucose monitoring in diabetic kidney disease

Diabetic kidney disease(DKD)is a common complication of diabetes mellitus that contributes to the risk of end-stage kidney disease(ESKD).Wide glycemic var-iations,such as hypoglycemia and hyperglycemia,are broadly found in diabetic patients with DKD and especially ESKD,as a result of impaired renal metabolism.It is essential to monitor glycemia for effective management of DKD.Hemoglobin A1c(HbA1c)has long been considered as the gold standard for monitoring glycemia for>3 months.However,assessment of HbA1c has some bias as it is susceptible to factors such as anemia and liver or kidney dysfunction.Continuous glucose monitoring(CGM)has provided new insights on glycemic assessment and management.CGM directly measures glucose level in interstitial fluid,reports real-time or retrospective glucose concentration,and provides multiple glycemic metrics.It avoids the pitfalls of HbA1c in some contexts,and may serve as a precise alternative to estimation of mean glucose and glycemic variability.Emerging studies have demonstrated the merits of CGM for precise monitoring,which allows fine-tuning of glycemic management in diabetic patients.Therefore,CGM technology has the potential for better glycemic monitoring in DKD patients.More research is needed to explore its application and management in different stages of DKD,including hemodialysis,peritoneal dialysis and kidney transplantation.

Interplay of laser power and pore characteristics in selective laser melting of ZK60 magnesium alloys:A study based on in-situ monitoring and image analysis

This study offers significant insights into the multi-physics phenomena of the SLM process and the subsequent porosity characteristics of ZK60 Magnesium(Mg)alloys.High-speed in-situ monitoring was employed to visualise process signals in real-time,elucidating the dynamics of melt pools and vapour plumes under varying laser power conditions specifically between 40 W and 60 W.Detailed morphological analysis was performed using Scanning-Electron Microscopy(SEM),demonstrating a critical correlation between laser power and pore formation.Lower laser power led to increased pore coverage,whereas a denser structure was observed at higher laser power.This laser power influence on porosity was further confirmed via Optical Microscopy(OM)conducted on both top and cross-sectional surfaces of the samples.An increase in laser power resulted in a decrease in pore coverage and pore size,potentially leading to a denser printed part of Mg alloy.X-ray Computed Tomography(XCT)augmented these findings by providing a 3D volumetric representation of the sample internal structure,revealing an inverse relationship between laser power and overall pore volume.Lower laser power appeared to favour the formation of interconnected pores,while a reduction in interconnected pores and an increase in isolated pores were observed at higher power.The interplay between melt pool size,vapour plume effects,and laser power was found to significantly influence the resulting porosity,indicating a need for effective management of these factors to optimise the SLM process of Mg alloys.

A landslide monitoring method using data from unmanned aerial vehicle and terrestrial laser scanning with insufficient and inaccurate ground control points

Non-contact remote sensing techniques,such as terrestrial laser scanning(TLS)and unmanned aerial vehicle(UAV)photogrammetry,have been globally applied for landslide monitoring in high and steep mountainous areas.These techniques acquire terrain data and enable ground deformation monitoring.However,practical application of these technologies still faces many difficulties due to complex terrain,limited access and dense vegetation.For instance,monitoring high and steep slopes can obstruct the TLS sightline,and the accuracy of the UAV model may be compromised by absence of ground control points(GCPs).This paper proposes a TLS-and UAV-based method for monitoring landslide deformation in high mountain valleys using traditional real-time kinematics(RTK)-based control points(RCPs),low-precision TLS-based control points(TCPs)and assumed control points(ACPs)to achieve high-precision surface deformation analysis under obstructed vision and impassable conditions.The effects of GCP accuracy,GCP quantity and automatic tie point(ATP)quantity on the accuracy of UAV modeling and surface deformation analysis were comprehensively analyzed.The results show that,the proposed method allows for the monitoring accuracy of landslides to exceed the accuracy of the GCPs themselves by adding additional low-accuracy GCPs.The proposed method was implemented for monitoring the Xinhua landslide in Baoxing County,China,and was validated against data from multiple sources.

Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow

Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the southern Sichuan Basin of China.This workflow includes coherent event detection,phase picking,and earthquake location using three-component data from a seismic network.By combining Phase Net,we develop an ML-based earthquake location model called Phase Loc,to conduct real-time monitoring of the local seismicity.The approach allows us to use synthetic samples covering the entire study area to train Phase Loc,addressing the problems of insufficient data samples,imbalanced data distribution,and unreliable labels when training with observed data.We apply the trained model to observed data recorded in the southern Sichuan Basin,China,between September 2018 and March 2019.The results show that the average differences in latitude,longitude,and depth are 5.7 km,6.1 km,and 2 km,respectively,compared to the reference catalog.Phase Loc combines all available phase information to make fast and reliable predictions,even if only a few phases are detected and picked.The proposed workflow may help real-time seismic monitoring in other regions as well.

Clinical efficacy and mechanism study of mid-frequency anti-snoring device in treating moderate obstructive sleep apnea-hypopnea syndrome

BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is primarily caused by airway obstruction due to narrowing and blockage in the nasal and nasopha-ryngeal,oropharyngeal,soft palate,and tongue base areas.The mid-frequency anti-snoring device is a new technology based on sublingual nerve stimulation.Its principle is to improve the degree of oropharyngeal airway stenosis in OSAHS patients under mid-frequency wave stimulation.Nevertheless,there is a lack of clinical application and imaging evidence.METHODS We selected 50 patients diagnosed with moderate OSAHS in our hospital between July 2022 and August 2023.They underwent a 4-wk treatment regimen involving the mid-frequency anti-snoring device during nighttime sleep.Following the treatment,we monitored and assessed the sleep apnea quality of life index and Epworth Sleepiness Scale scores.Additionally,we performed computed tomo-graphy scans of the oropharynx in the awake state,during snoring,and while using the mid-frequency anti-snoring device.Cross-sectional area measurements in different states were taken at the narrowest airway point in the soft palate posterior and retrolingual areas.RESULTS Compared to pretreatment measurements,patients exhibited a significant reduction in the apnea-hypopnea index,the percentage of time with oxygen saturation below 90%,snoring frequency,and the duration of the most prolonged apnea event.The lowest oxygen saturation showed a notable increase,and both sleep apnea quality of life index and Epworth Sleepiness Scale scores improved.Oropharyngeal computed tomography scans revealed that in OSAHS patients cross-sectional areas of the oropharyngeal airway in the soft palate posterior area and retrolingual area decreased during snoring compared to the awake state.Conversely,during mid-frequency anti-snoring device treatment,these areas increased compared to snoring.CONCLUSION The mid-frequency anti-snoring device demonstrates the potential to enhance various sleep parameters in patients with moderate OSAHS,thereby improving their quality of life and reducing daytime sleepiness.These therapeutic effects are attributed to the device’s ability to ameliorate the narrowing of the oropharynx in OSAHS patients.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

Glucagon-like peptide-1 receptor agonists as a possible intervention to delay the onset of type 1 diabetes:A new horizon

Type 1 diabetes(T1D)is a chronic autoimmune condition that destroys insulinproducing beta cells in the pancreas,leading to insulin deficiency and hyperglycemia.The management of T1D primarily focuses on exogenous insulin replacement to control blood glucose levels.However,this approach does not address the underlying autoimmune process or prevent the progressive loss of beta cells.Recent research has explored the potential of glucagon-like peptide-1 receptor agonists(GLP-1RAs)as a novel intervention to modify the disease course and delay the onset of T1D.GLP-1RAs are medications initially developed for treating type 2 diabetes.They exert their effects by enhancing glucose-dependent insulin secretion,suppressing glucagon secretion,and slowing gastric emptying.Emerging evidence suggests that GLP-1RAs may also benefit the treatment of newly diagnosed patients with T1D.This article aims to highlight the potential of GLP-1RAs as an intervention to delay the onset of T1D,possibly through their potential immunomodulatory and anti-inflammatory effects and preservation of beta-cells.This article aims to explore the potential of shifting the paradigm of T1D management from reactive insulin replacement to proactive disease modification,which should open new avenues for preventing and treating T1D,improving the quality of life and long-term outcomes for individuals at risk of T1D.

Groundwater recharge via precipitation in the Badain Jaran Desert,China

Precipitation infiltration serves as a significant source of groundwater in the Badain Jaran Desert.To investigate variations in precipitation infiltration within the desert,this study collected data on moisture content and temperature from the vadose zone through in-situ field monitoring.Utilizing these data,a numerical model is employed to explore the mechanism of groundwater recharge via precipitation.The results are as follows:(1)Moisture content and temperature in the shallow vadose zone exhibit significant seasonal variations,with moisture content diminishing with increasing depth;(2)Groundwater recharge via precipitation infiltration initially increases and then decreases with groundwater level depth(GWD).Peak groundwater recharge via precipitation occurs at a GWD of 0.75 m,decreasing to merely 0.012 cm at GWDs exceeding 2 m;(3)Groundwater is no longer susceptible to phreatic water evaporation when the GWD reaches approximately 3.7 m.Therefore,GWD plays a crucial role in governing groundwater recharge via precipitation in the Badain Jaran Desert.

IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

Integrated biomarker response to assess toxic impacts of iron and manganese on deep-sea mussel Gigantidas platifrons under a deep-sea mining activity scenario

Deep-sea mining activities can potentially release metals,which pose a toxicological threat to deep-sea ecosystems.Nevertheless,due to the remoteness and inaccessibility of the deep-sea biosphere,there is insufficient knowledge about the impact of metal exposure on its inhabitants.In this study,deep-sea mussel Gigantidas platifrons,a commonly used deep-sea toxicology model organism,was exposed to manganese(100,1000μg/L)or iron(500,5000μg/L)for 7 d,respectively.Manganese and iron were chosen for their high levels of occurrence within deep-sea deposits.Metal accumulation and a battery of biochemical biomarkers related to antioxidative stress in superoxide dismutase(SOD),catalase(CAT),malondialdehyde(MDA);immune function in alkaline phosphatase(AKP),acid phosphatase(ACP);and energy metabolism in pyruvate kinase(PK)and hexokinase(HK)were assessed in mussel gills.Results showed that deep-sea mussel G.platifrons exhibited a high capacity to accumulate Mn/Fe.In addition,most tested biochemical parameters were altered by metal exposure,demonstrating that metals could induce oxidative stress,suppress the immune system,and affect energy metabolism of deep-sea mussels.The integrated biomarker response(IBR)approach indicated that the exposure to Mn/Fe had a negative impact on deep-sea mussels,and Mn demonstrated a more harmful impact on deep-sea mussels than Fe.Additionally,SOD and CAT biomarkers had the greatest impact on IBR values in Mn treatments,while ACP and HK were most influential for the low-and high-dose Fe groups,respectively.This study represents the first application of the IBR approach to evaluate the toxicity of metals on deep-sea fauna and serves as a crucial framework for risk assessment of deep-sea mining-associated metal exposure.