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.

Precise point positioning and its application in mining deformation monitoring

Precise point positioning (PPP)-based deformation monitoring scheme is presented for the use in mining deformation monitoring. Within the solutions of daily observation, outliers are detected and removed to avoid any potential misinterpretation of the results and then the deformation can be extracted by the coordinate differences between the two consecutive solutions. Meanwhile, because of the special location of a rover station in mining areas, the satellite geometry may be insufficient for a reasonable PPP solution, and the multipath impact an also be significant. Therefore, it is necessary to predict the satellite geometry before any daily observation. To evaluate the ability of extracting the deformation using the PPP-based method, various quality measures were introduced. The results of three datasets of the same station show that the precision of deformation monitored by PPP can reach up to cm level and even mm level.

Design of Signal Lamp Filament Monitoring Alarm Instrument

To improve the reliability of the light emitting diode(LED)signal lamp filament current monitoring alarm instrument for metro systems,a new type of hot standby online monitoring apparatus was developed which is based on synchronous transmission data(STD)bus technology.In this system,a double hot standby mode can be achieved by adopting bus arbitration.In addition,to detect the effective value of alternating current which is from 0 to 200 mA in the signal lamp lighting circuit,a precision rectifier signal conditioning circuit and an isolated acquisition circuit were designed.This new type of alarm instrument has high detection accuracy and could meet the functional requirements for metro signal systems after comparing it with some industry products that were applied on the spot.

Application and Practice of High-Precision Solar Resource Monitoring Technology in Photovoltaic Power Plant Area

Solar resource monitoring and evaluation is the foundation of informatization of photovoltaic power station. In 2016, China began to bring in high-precision solar resource monitoring technology which provides reliable basic data for the photovoltaic informatization development. This paper systematically sorts out design basis, monitoring elements and system architecture of high-precision monitoring station, and analyzes operation effect of high-precision solar resource monitoring station from performance of solar radiation meter and prediction results of luminous power, which provide important data support for analysis of power generation efficiency of photovoltaic module, prediction of power generation of power station, evaluation of operation effect of power station, etc.

Engineering vibration monitoring by GPS:long duration records

Monitoring the performance of any structure requires real-time measurements of the change of position of critical points. Different techniques can be used for this purpose, each one offering advantages and disadvantages. The technique based on satellite positioning systems （GPS, GLONASS and the future GALILEO） seems to be very promising at least for long period structures. The GPS in particular provides sampling rates that are able to track dynamic displacements with high accuracy. Its service ability is independent of atmospheric conditions, temperature variations and visibility of the monitored object. This paper investigates the reliability and accuracy of the measurements of dual frequency GPS receivers. A linear electromagnetic motor moves an object along a given direction. The changes of position are compared witb their estimates as recorded by a GPS receiver, whose antenna is located on the reference object. The comparison is based on sufficiently long records.

Precise Agriculture:Effective Deep Learning Strategies to Detect Pest Insects

Pest insect monitoring and control is crucial to ensure a safe and profitable crop growth in all plantation types,as well as guarantee food quality and limited use of pesticides.We aim at extending traditional monitoring by means of traps,by involving the general public in reporting the presence of insects by using smartphones.This includes the largely unexplored problem of detecting insects in images that are taken in noncontrolled conditions.Furthermore,pest insects are,in many cases,extremely similar to other species that are harmless.Therefore,computer vision algorithms must not be fooled by these similar insects,not to raise unmotivated alarms.In this work,we study the capabilities of state-of-the-art(SoA)object detection models based on convolutional neural networks(CNN)for the task of detecting beetle-like pest insects on nonhomogeneous images taken outdoors by different sources.Moreover,we focus on disambiguating a pest insect from similar harmless species.We consider not only detection performance of different models,but also required computational resources.This study aims at providing a baseline model for this kind of tasks.Our results show the suitability of current SoA models for this application,highlighting how FasterRCNN with a MobileNetV3 backbone is a particularly good starting point for accuracy and inference execution latency.This combination provided a mean average precision score of 92.66%that can be considered qualitatively at least as good as the score obtained by other authors that adopted more specific models.

Land deformation monitoring in mining area with PPP-AR

The mining area deformation monitoring theory and method using precise point positioning （PPP） ambi- guity resolution （AR） were studied, and an ambiguity fixing model with satellite and receiver combina- tion phase delay （CPD） was proposed for zero-differenced PPP ambiguity fixing and its corresponding formula derivation was given. The data processing results for I h at six IGS stations in China show that 93% of ambiguities can be fixed within 10 min and all ambiguities can be fixed within 15 min. After ambi- guity fixing, the positioning accuracy is improved by more than 85% in the E and N directions, with abso- lute positioning accuracy reaching millimeter level, and it was improved by 70% in the U direction, reaching centimeter level; the proposed zero-differenced ambiguity fixing model can effectively improve the convergence rate and positioning accuracy in PPP. Data monitoring continuously conducted for half a year at four COPS stations of Shanxi China Coal Pingshuo Group validated the feasibility of using PPP in mining area deformation monitoring.

Development of Dual-light Path Monitoring System of Optical Thin-film Thickness

The accurate monitoring of optical thin-film thickness is a key technique for depositing optical thin-film. For existing coating equipments, which are low precision and automation level on monitoring thin-film thickness, a new photoelectric control and analysis system has been developed. In the new system, main techniques include a photoelectric system with dual-light path, a dual-lock-phase circuit system and a comprehensive digital processing-control-analysis system.The test results of new system show that the static and dynamic stabilities and the control precision of thin-film thickness are extremely increased. The standard deviation of thin-film thickness, which indicates the duplication of thin-film thickness monitoring, is equal to or less than 0.72%. The display resolution limit on reflectivity is 0.02 %. In the system, the linearity of drift is very high, and the static drift ratio approaches zero.

Multiple Regression and Big Data Analysis for Predictive Emission Monitoring Systems

Predictive Emission Monitoring Systems (PEMS) offer a cost-effective and environmentally friendly alternative to Continuous Emission Monitoring Systems (CEMS) for monitoring pollution from industrial sources. Multiple regression is one of the fundamental statistical techniques to describe the relationship between dependent and independent variables. This model can be effectively used to develop a PEMS, to estimate the amount of pollution emitted by industrial sources, where the fuel composition and other process-related parameters are available. It often makes them sufficient to predict the emission discharge with acceptable accuracy. In cases where PEMS are accepted as an alternative method to CEMS, which use gas analyzers, they can provide cost savings and substantial benefits for ongoing system support and maintenance. The described mathematical concept is based on the matrix algebra representation in multiple regression involving multiple precision arithmetic techniques. Challenging numerical examples for statistical big data analysis, are investigated. Numerical examples illustrate computational accuracy and efficiency of statistical analysis due to increasing the precision level. The programming language C++ is used for mathematical model implementation. The data for research and development, including the dependent fuel and independent NOx emissions data, were obtained from CEMS software installed on a petrochemical plant.

Special Marking of 3D Networks＇ Points for the Monitoring of Modern Constructions

In order to monitor the deformations of modern constructions a local 3D network was usually being established at the surrounding area. The centering error, of both the instrument and targets, causes significant uncertainties in the determination of the x, y, z coordinates of the network＇s points. In order to assure precise centering for both the instrument and targets, not only for the accessible but also for the inaccessible network＇s points, a prototype way of marking is being implied. A special semi-permanent portable metallic stand （Photo 1） was manufactured for marking the accessible points. The stand provides forced instrument centering of the order of_＋0, lmm. It is light enough to carry, it accelerates and facilitates the centering and leveling of the instrument as well as it eliminates the time needed for the measurements. The applied laboratory checks in order to certify the suitability of its use and the provided accuracy are being described. For the inaccessible points special targets were used. The targets were put in permanent attachments （Photos 7-8）, which were also manufactured. Useful conclusions were drawn when these special accessories were used in to a 3D network, which was established for the monitoring of a new football stadium. Two measurement phases were carried out. The first one is with the stadium empty and the second one is when it was crowded （about 32000 people） during a significant football match.

Calibration of CO and CO2 Monitors Used in Periodic Inspection of Vehicles at Fixed Stations for Environmental Control

Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuring the quantitative assessment of emissions for informed decisions on environmental treatments. This paper describes a method for the calibration of CO/CO2 monitors used for periodic inspections of vehicles in cites. The calibration was performed in the selected ranges: 900 - 12,000 µmol/mol for CO and 2000 - 20,000 µmol/mol for CO2. The traceability of the measurement results to the SI units was ensured by using certified reference materials from CO/N2 and CO2/N2 primary gas mixtures. The method performance was evaluated by assessing its linearity, accuracy, precision, bias, and uncertainty of the calibration results. The calibration data exhibited a strong linear trend with R² values close to 1, indicating an excellent fit between the measured values and the calibration lines. Precision, expressed as relative standard deviation (%RSD), ranged from 0.48 to 4.56% for CO and from 0.97 to 3.53% for CO2, staying well below the 5% threshold for reporting results at a 95% confidence level. Accuracy measured as percent recovery, was consistently high (≥ 99.1%) for CO and ranged from 84.90% to 101.54% across the calibration range for CO2. In addition, the method exhibited minimal bias for both CO and CO2 calibrations and thus provided a reliable and accurate approach for calibrating CO/CO2 monitors used in vehicle inspections. Thus, it ensures the effectiveness of exhaust emission control for better environment.

Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.

Quality monitoring of real-time GNSS precise positioning service system

The Real-Time Global Navigation Satellite System(GNSS)Precise Positioning Service(RTPPS)is recognized as the most promising system by providing precise satellite orbit and clock correc-tions for users to achieve centimeter-level positioning with a stand-alone receiver in real-time.Although the products are available with high accuracy almost all the time,they may occasionally suffer from unexpected significant biases,which consequently degrades the positioning perfor-mance.Therefore,quality monitoring at the system-level has become more and more crucial for providing a reliable GNSS service.In this paper,we propose a method for the monitoring of realtime satellite orbit and clock products using a monitoring station network based on the Quality Control(QC)theory.The satellites with possible biases are first detected based on the outliers identified by Precise Point Positioning(PPP)in the monitoring station network.Then,the corresponding orbit and clock parameters with temporal constraints are introduced and esti-mated through the sequential Least Square(LS)estimator and the corresponding Instantaneous User Range Errors(IUREs)can be determined.A quality indicator is calculated based on the IUREs in the monitoring network and compared with a pre-defined threshold.The quality monitoring method is experimentally evaluated by monitoring the real-time orbit and clock products generated by GeoForschungsZentrum(GFZ),Potsdam.The results confirm that the problematic satellites can be detected accurately and effectively with missed detection rate 4×10^(-6) and false alarm rate 1:2×10^(-5).Considering the quality alarms,the PPP results in terms of RMS of positioning differences with respect to the International GNSS Service(IGS)weekly solution in the north,east and up directions can be improved by 12%,10%and 27%,respectively.

Real-time integrity monitoring for a wide area precise positioning system

The wide area precise positioning system(WAPPS)is a high-precision positioning system based on a global navigation satellite system.Using a GEO satellite or a communication network,it provides users,in its service area,with real-time satellite orbit,clock,and other corrections.Users can achieve centimeter-level static positioning or decimeter-level kinematic positioning by precise point positioning.With the demands for applications of both high-precision and safety of life in real time,WAPPS is facing urgent needs to improve its service integrity.This study presents a real-time integrity monitoring approach for WAPPS.Using dual-frequency ionosphere-free corrections of GPS and BDS,along with monitor station data,related error models are established and the integrity monitoring is achieved,based on the analysis of satellite corrected residuals.In addition,satellite faults are simulated for performance verification.The results show that the algorithm can monitor both step and drift faults effectively and alert users in time.

学生体质健康提升各阶段干预策略的研究

疫情后,学生体质健康水平出现了一定程度的下降。扭转学生体质健康水平下降的趋势,大范围、大幅度提高学生体质健康水平需要唤醒学生运动锻炼的内生动力;让学生掌握相应的锻炼技能;反复进行科学、有效的运动锻炼来促进身体相关机能的提高,从而达到体质健康水平的提高。该研究采用有效、精准的干预策略,从学生运动兴趣的培养、锻炼动机的形成、运动锻炼技能的掌握、运动锻炼习惯的形成和体质提升的反馈等角度进行了探索,以期为高职校学生体质健康水平的提升提供清晰、有效的路径。

基于无人机遥感技术的大田作物精准施肥决策研究进展

近年来无人机遥感技术在作物施肥智慧决策与精准作业领域应用广泛,现将无人机遥感技术在监测作物长势并指导施肥、无人机精准作业等方面的研究现状作以综述。基于信息化方法的施肥决策可通过数据驱动和机理驱动2种方式制定,其中农情监测为施肥决策的制定提供了数据支撑,目前研究主要以机器学习、回归分析等数据驱动方法监测作物长势,存在农学机理与普适性不足等问题;部分研究通过耦合辐射传输模型、作物生长模型等机理模型提升了无人机遥感对作物大规模监测的物理意义与普适性。制定施肥决策方面重点探讨了通过无人机遥感数据建立回归模型等数据驱动方式制定作物精准施肥决策的研究现状,并对目前制定施肥决策缺乏机理性的问题进行了深入讨论与展望。无人机精准作业方面,综述无人机遥感、作业处方图生成和精准喷施技术等无人机执行精准施肥决策的关键作业环节,并对相关技术进行展望。深入分析基于无人机遥感方法开展大田作物精准施肥决策的研究进展及存在的问题,旨在为利用无人机实现作物精准施肥提供科学依据和参考。

近地小行星天地基协同监测和轨道确定试验

基于中国科学院国家天文台空间碎片试验望远镜,联合“仰望一号”“吉林一号”卫星,设计并开展了近地小行星天地基协同监测试验,利用图像处理和定轨方法,实现了天地基观测图像的目标检测和天文定位,完成了近地小行星轨道的精确确定。经分析,基于现有的天地基设备可实现对近地小行星的协同监测和轨道编目,为研判近地小行星撞击风险提供轨道数据支持。

地面沉降钻孔全断面光纤多参量精细化监测——以杭州萧山区山末址村为例

为了科学防控地面沉降,文章以杭州萧山区山末址村地面沉降重点区为研究对象,在系统分析其地面沉降成因机理的基础上,建立了钻孔全断面光纤多参量地面沉降自动化监测示范点,识别了不同深度土层的沉降变化特征和主要沉降层位,探究了弱透水层与含水砂层在不同水位变化模式下的变形特征。结果表明:①示范点处当前主要沉降层位集中在第二弱透水层和第I2承压含水层,平均沉降量占比分别为29.59%和33.21%,且有增大的趋势;②监测期内随着地下水位的持续回升,第I2承压含水层主要表现为弹性变形,且存在较小的残余变形;③第二弱透水层变形明显滞后于孔隙水压力的变化,具有塑性变形和蠕变的特点。实践表明,建立的监测示范点能够准确获取地面沉降发育过程中高精度的多参量数据,可为地面沉降的机理研究和模型预测提供数据支撑。

母猪精准养殖智能感知技术研究进展

母猪的生长状况、繁殖性能与健康状况是猪场管理的重要生产要素,直接关系到猪场的经济效益。我国母猪养殖还存在生产管理智能化水平低、健康管理效率低、生产力水平低等突出问题,制约了我国养殖业的高质量发展。本文从母猪生长信息感知技术、繁殖行为监测技术、健康状态感知技术等3个方面,总结了母猪精准养殖管理中生长、生理、健康监测的研究和发展现状,分析了母猪精准养殖技术的薄弱环节,对母猪养殖智慧管控系统的建设提出了建议,并对未来的发展趋势进行了展望,以期为我国养猪业绿色高效智能转型升级与智能养猪工厂的建设提供参考。

基于STM32的低功耗高精度智能体温无线检测系统

文章设计了以STM32L051C8T6单片机为核心的低功耗高精度智能体温无线检测系统,实现了高精度的体温监测、人性化智能语音播报、稳定的无线传输、低功耗电源管理等功能。该系统传输稳定,抗干扰能力强,续航持久,低辐射,为父母照顾生病发烧的婴幼儿提供了便利。本系统落实科技改变生活,顺应时代发展,解决千万父母的疑难问题。