Building the Capacity of Health Professionals in Monitoring and Evaluation in a Public Health Institution: Experience of the National Institute of Public Health (NIPH) of Côte d’Ivoire

Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis of the national plan for monitoring and evaluating the fight against HIV (2006-2010) that was aimed at strengthening the capacities of actors in this area. To increase the critical mass of competent human resources in the short term, the National Institute of Public Health (NIPH) of Côte d’Ivoire organized monitoring and evaluation training sessions for healthcare professionals from 2011 to 2016. Methods: A single case study with multiple levels of analysis was carried out, combining a qualitative survey and a literature review. An evaluation was carried out six months after each training session. In addition, the results of the pre- and post-tests and of the daily and final evaluations that accompanied the various training sessions were used to provide further information. The qualitative data collected were analyzed using INVIVO 15 software. Results: Some 89 health professionals (69% men and 31% women) working at the national level (51% at the central level, including 58% in health programs) and in development partner agencies (37%) participated in this capacity building program. Most participants were senior health managers (56%), data managers (23%), and statisticians and computer scientists (10%). Almost all the trainings were financed by 16 technical and financial partners (85%), mainly the MEASURE Evaluation project (27%). Conclusion: M&E training, despite all its imperfections, has made it possible to identify M&E training needs at the national level and to increase the critical mass of national skills and to have some culture in M&E.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

Technical Analysis of Safety Monitoring and Evaluation of Existing Bridge Structures

Bridge structure safety monitoring and assessment has been a great concern for the government and the public,and bridge structure safety monitoring and assessment technology has also developed rapidly over the years.Its goal is to equip relevant organizations and professionals with a deep understanding of the principles and practical applications of these technologies.By doing so,it seeks to facilitate the effective implementation of safety monitoring and assessment practices in bridge management.Ultimately,the aim is to foster the constructive development of road and bridge construction and operational management at a broader level.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

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.

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.

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.

Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

Identification and evaluation of shale oil micromigration and its petroleum geological significance

Taking the Lower Permian Fengcheng Formation shale in Mahu Sag of Junggar Basin,NW China,as an example,core observation,test analysis,geological analysis and numerical simulation were applied to identify the shale oil micro-migration phenomenon.The hydrocarbon micro-migration in shale oil was quantitatively evaluated and verified by a self-created hydrocarbon expulsion potential method,and the petroleum geological significance of shale oil micro-migration evaluation was determined.Results show that significant micro-migration can be recognized between the organic-rich lamina and organic-poor lamina.The organic-rich lamina has strong hydrocarbon generation ability.The heavy components of hydrocarbon preferentially retained by kerogen swelling or adsorption,while the light components of hydrocarbon were migrated and accumulated to the interbedded felsic or carbonate organic-poor laminae as free oil.About 69% of the Fengcheng Formation shale samples in Well MY1 exhibit hydrocarbon charging phenomenon,while 31% of those exhibit hydrocarbon expulsion phenomenon.The reliability of the micro-migration evaluation results was verified by combining the group components based on the geochromatography effect,two-dimension nuclear magnetic resonance analysis,and the geochemical behavior of inorganic manganese elements in the process of hydrocarbon migration.Micro-migration is a bridge connecting the hydrocarbon accumulation elements in shale formations,which reflects the whole process of shale oil generation,expulsion and accumulation,and controls the content and composition of shale oil.The identification and evaluation of shale oil micro-migration will provide new perspectives for dynamically differential enrichment mechanism of shale oil and establishing a“multi-peak model in oil generation”of shale.

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.

Comprehensive Evaluation of Flower Border Application Value of New and Superior Plants in Hefei Area

An analytic hierarchy process(AHP)was employed to assess the applicability of 18 new and superior varieties of flowers in Hefei City flower border applications.A total of 12 indicators were selected from three distinct aspects of adaptability,ornamental characteristics and use traits,in order to establish a comprehensive evaluation model.The results demonstrate that grade I(J≥2.685)exhibits excellent application value,encompassing six species of plants,such asHydrangeamacrophylla‘Endless Summer’;grade II(2.684≤J≤2.420)is also of notable application value,encompassing five species of plants,such asCallistemonrigidus;grade III(2.419≤J≤2.615)is of average application value,including five species of plants,such asCrocosmiacrocosmiflora;grade IV(J≤2.16)is of relatively poor application value.The evaluation results may be utilized as a theoretical reference for the promotion of new and superior varieties in the flower border of Hefei.

Design and Construction of Automatic Monitoring System for Open-pit Coal Mine Slopes

[Objectives]To monitor the stability of open-pit coal mine slopes in real time and ensure the safety of coal mine production.[Methods]The automatic monitoring system of coal mine slope was explored in depth,and the core functions of the system were designed comprehensively.According to the design function of the automatic monitoring system,the slope automatic monitoring system was constructed.Besides,in accordance with the actual situation of the slope,the monitoring frequency of slopes was set scientifically,and the key indicators such as rainfall,deep displacement and surface displacement of the slopes were monitored in an all-round and multi-angle way.[Results]During the monitoring period,the overall condition of the slope remained good,and no landslides or other geological disasters occurred.At the same time,the overall rainfall in the slope area remained low.In terms of monitoring data,the horizontal displacement and settlement of the slopes increased first and then tended to be stable.Specifically,the maximum horizontal displacement during the monitoring period was 22.74 mm,while the maximum settlement was 18.65 mm.[Conclusions]The automatic slope monitoring system has obtained remarkable achievements in practical application.It not only improves the accuracy and efficiency of slope stability monitoring,but also provides valuable reference experience for similar projects.

Accuracy of FreeStyle Libre flash glucose monitoring in patients with type 2 diabetes who migrated from highlands to plains

BACKGROUND The FreeStyle Libre flash glucose monitoring(FGM)system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose.Due to its increased usage in clinics,the number of studies investigating its accuracy has increased.However,its accuracy has not been investigated in highland populations in China.AIM To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes(T2D)who had migrated within 3 mo from highlands to plains.METHODS Overall,68 patients with T2D,selected from those who had recently migrated from highlands to plains(within 3 mo),were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring(CGM)with the FreeStyle Libre FGM system for 14 d.Throughout the study period,fingertip capillary blood glucose was measured daily using the enzyme electrode method(Super GL,China),and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals.Moreover,the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to<5 min.The accuracy of the FGM system was evaluated according to the CGM guidelines.Subsequently,the factors influencing the mean absolute relative difference(MARD)of this system were analyzed by a multiple linear regression method.RESULTS Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated(R=0.86,P=0.00).The aggregated MARD of scanned glucose was 14.28±13.40%.Parker's error analysis showed that 99.30%of the data pairs were located in areas A and B.According to the probe wear time of the FreeStyle Libre FGM system,MARD_(1 d) and MARD_(2-14 d) were 16.55%and 14.35%,respectively(t=1.23,P=0.22).Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion(LAGE)was<5.80 mmol/L but negatively correlated with blood glucose when the LAGE was≥5.80 mmol/L.CONCLUSION The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains.This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains.MARD is mainly influenced by glucose levels and fluctuations,and the accuracy of the system is higher when the blood glucose fluctuation is small.In case of higher blood glucose level fluctuations,deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Nanomaterial-assisted wearable glucose biosensors for noninvasive real-time monitoring:Pioneering point-of-care and beyond

This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose detection.In addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of contexts.The unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related infections.The potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also explored.The challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet needs.Also,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic population.The paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.

Clinical/Behavioral Monitoring of Rodents and Rabbits Undergoing Scientific Experiments

Background: We currently have international and national guidelines regarding the assessment and monitoring of clinical signs and humane endpoints in animals used in teaching and research, which make the performance of these activities mandatory for any experiment and professional working in this area. Assigning the severity of a research experiment is the result of an analysis of records of observations of the animal’s behavior, and clinical signs. The aim of this study was to describe the importance of carrying out a severity assessment associated with clinical and behavioral monitoring of rodents and rabbits during experimentation to maintain the welfare of these animals undergoing scientific research. Methods: The literature search was carried out using the following terms: “Monitoring”;“Humane endpoints”;“Animal welfare”, “Rodents”;“Rabbits”, and as connectors “and”;“or”, in the following databases: PubMed;LILACS/BIREME and SciELO. Results: A total of 987 articles were identified in the databases, and 20 of these studies were included in this review. Conclusions: Humane endpoint protocols and procedure severity tables are of the utmost importance, both from an ethical point and to refine the results of research conducted on laboratory animals. They should be drawn up jointly by the teams responsible for the project and the maintenance of the animals during the research period, and the data obtained should be published so that the scientific community can have access to it, helping to disseminate these practices, as well as helping to draw up new procedures. Monitoring and evaluating the welfare and clinical condition of animals undergoing scientific research procedures is the responsibility of the professors, researchers, veterinarians, and animal facility coordinators. The Ethics Committee on the Use of Animals must monitor all the activities conducted with the animals, by inspecting the experimental procedures and the physical environment of the laboratory animal facility where the animals are housed.

Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.

Machine learning in metal-ion battery research: Advancing material prediction, characterization, and status evaluation

Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.

An improved typhoon monitoring model based on precipitable water vapor and pressure

The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy. Hence,based on PWV and meteorological data, we propose an improved typhoon monitoring mode. First, the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV(ERA5-PWV) and the Global Navigation Satellite System-derived PWV(GNSS-PWV) were compared with the reference radiosonde PWV(RS-PWV). Then, using the PWV and atmospheric parameters derived from ERA5, we discussed the anomalous variations of PWV, pressure(P), precipitation, and wind speed during different typhoons. Finally, we compiled a list of critical factors related to typhoon movement, PWV and P. We developed an improved multi-factor typhoon monitoring mode(IMTM) with different models(i.e.,IMTM-I and IMTM-II) in different cases with a higher density of GNSS observation or only Numerical Weather Prediction(NWP) data. The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network(CMOTN). The results show that the root mean square(RMS) of the IMTM-I is 1.26 km/h based on ERA5-P and ERA5-PWV,and the absolute bias values are mostly within 2 km/h. Compared with the models considering the single factor ERA5-P/ERA5-PWV, the RMS of the IMTM-I is improved by 26.3% and 38.5%, respectively. The IMTM-II model manifests a residual of only 0.35 km/h. Compared with the single-factor model based on GNSS-PWV/P, the residual of the IMTM-II model is reduced by 90.8% and 84.1%, respectively. These results propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.

Pretreatment and analysis techniques development of TKIs in biological samples for pharmacokinetic studies and therapeutic drug monitoring

Tyrosine kinase inhibitors(TKIs)have emerged as the first-line small molecule drugs in many cancer therapies,exerting their effects by impeding aberrant cell growth and proliferation through the modulation of tyrosine kinase-mediated signaling pathways.However,there exists a substantial inter-individual variability in the concentrations of certain TKIs and their metabolites,which may render patients with compromised immune function susceptible to diverse infections despite receiving theoretically efficacious anticancer treatments,alongside other potential side effects or adverse reactions.Therefore,an urgent need exists for an up-to-date review concerning the biological matrices relevant to bioanalysis and the sampling methods,clinical pharmacokinetics,and therapeutic drug monitoring of different TKIs.This paper provides a comprehensive overview of the advancements in pretreatment methods,such as protein precipitation(PPT),liquid-liquid extraction(LLE),solid-phase extraction(SPE),micro-SPE(μ-SPE),magnetic SPE(MSPE),and vortex-assisted dispersive SPE(VA-DSPE)achieved since 2017.It also highlights the latest analysis techniques such as newly developed high performance liquid chromatography(HPLC)and high-resolution mass spectrometry(HRMS)methods,capillary electrophoresis(CE),gas chromatography(GC),supercritical fluid chromatography(SFC)procedures,surface plasmon resonance(SPR)assays as well as novel nanoprobes-based biosensing techniques.In addition,a comparison is made between the advantages and disadvantages of different approaches while presenting critical challenges and prospects in pharmacokinetic studies and therapeutic drug monitoring.