A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

A step to the decentralized real-time timekeeping network

The composite time scale(CTS) provides an accurate and stable time-frequency reference for modern science and technology. Conventional CTS always features a centralized network topology, which means that the CTS is accompanied by a local master clock. This largely restricts the stability and reliability of the CTS. We simulate the restriction and analyze the influence of the master clock on the CTS. It proves that the CTS's long-term stability is also positively related to that of the master clock, until the region dominated by the frequency drift of the H-maser(averaging time longer than ~10~5s).Aiming at this restriction, a real-time clock network is utilized. Based on the network, a real-time CTS referenced by a stable remote master clock is achieved. The experiment comparing two real-time CTSs referenced by a local and a remote master clock respectively reveals that under open-loop steering, the stability of the CTS is improved by referencing to a remote and more stable master clock instead of a local and less stable master clock. In this way, with the help of the proposed scheme, the CTS can be referenced to the most stable master clock within the network in real time, no matter whether it is local or remote, making democratic polycentric timekeeping possible.

Microcavity assisted graphene pressure sensor for single-vessel local blood pressure monitoring

Dynamic monitoring of blood pressure (BP) is beneficial to obtain comprehensive cardiovascular information of patients throughout the day. However, the clinical BP measurement method relies on wearing a bulky cuff, which limits the long-term monitoring and control of BP. In this work, a microcavity assisted graphene pressure sensor (MAGPS) for single-vessel local BP monitoring is designed to replace the cuff. The microcavity structure increases the working range of the sensor by gas pressure buffering. Therefore, the MAGPS achieves a wide linear response of 0–1050 kPa and sensitivity of 15.4 kPa^(−1). The large working range and the microcavity structure enable the sensor to fully meet the requirements of BP detection at the radial artery. A database of 228 BP data (60-s data fragment detected by MAGPS) and 11,804 pulse waves from 9 healthy subjects and 5 hypertensive subjects is built. Finally, the BP was detected and analyzed automatically by combining MAGPS and a two-stage convolutional neural network algorithm. For the BP detection method at local radial artery, the first stage algorithm first determines whether the subject has hypertension by the pulse wave. Then, the second stage algorithm can diagnose systolic and diastolic BP with the accuracy of 93.5% and 97.8% within a 10 mmHg error, respectively. This work demonstrates a new BP detection method based on single vessel, which greatly promotes the efficiency of BP detection.

Soft Electronics for Health Monitoring Assisted by Machine Learning

Due to the development of the novel materials,the past two decades have witnessed the rapid advances of soft electronics.The soft electronics have huge potential in the physical sign monitoring and health care.One of the important advantages of soft electronics is forming good interface with skin,which can increase the user scale and improve the signal quality.Therefore,it is easy to build the specific dataset,which is important to improve the performance of machine learning algorithm.At the same time,with the assistance of machine learning algorithm,the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis.The soft electronics and machining learning algorithms complement each other very well.It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future.Therefore,in this review,we will give a careful introduction about the new soft material,physiological signal detected by soft devices,and the soft devices assisted by machine learning algorithm.Some soft materials will be discussed such as two-dimensional material,carbon nanotube,nanowire,nanomesh,and hydrogel.Then,soft sensors will be discussed according to the physiological signal types(pulse,respiration,human motion,intraocular pressure,phonation,etc.).After that,the soft electronics assisted by various algorithms will be reviewed,including some classical algorithms and powerful neural network algorithms.Especially,the soft device assisted by neural network will be introduced carefully.Finally,the outlook,challenge,and conclusion of soft system powered by machine learning algorithm will be discussed.

High expression of PD-L1 mainly occurs in non-small cell lung cancer patients with squamous cell carcinoma or poor differentiation

Background:Lung cancer is one of the most lethal cancers worldwide,but studies have shown that the higher the expression of programmed cell death protein 1 ligand 1(PD-L1)in non-small cell lung cancer(NSCLC),the more likely it will benefit from anti-PD-L1 immunotherapy.The purpose of our study was to collect and analyze abundant clinical samples in order to provide evidence for clinicians and patients who might consider anti-PD-L1 immunotherapy while jointly formulating treatment plans.Methods:On the one hand,we obtained cases from The Cancer Genome Atlas(TCGA)database,including 498 lung squamous cell cancer(LUSC)patients and 515 lung adenocarcinoma(LUAD)patients.We studied the lung caner driver gene in LUSC and LUAD.On the other hand,PD-L1 expression was detected in lung cancer tissues of 1,008 NSCLC patients with immunohistochemistry staining(IHC),and we studied the correlation between PD-L1 protein expression and clinicopathological characteristics.Results:PD-L1 expression was higher in LUSC than in LUAD at the mRNA level.In univariate analysis,PD-L1 expression at the protein level was higher in patients who were males,were LUSC,were smokers,had a tumor diameter>3 cm,had poor differentiation,or had stages Ⅲ-Ⅳ disease.In multivariate analysis,PD-L1 expression was higher in patients who were LUSC or in poor differentiation.Conclusion:In term of protein level,PD-L1 expression was higher in NSCLC patients who were LUSC or in poor differentiation.We recommend that PD-L1 IHC detection can be routinely performed in such populations that are likely to benefit most from PD-L1 immunotherapy.

A Data Driven Security Correction Method for Power Systems with UPFC

The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.

Growth and Characterization of High-quality LiAlO2 Single Crystal

γ-LiAlO2 single crystal is a promising substrate for GaN heteroepitaxy. In this paper, we present the growth of large-sized LiAlO2 crystal by modified Czochralski method. The crystal quality was characterized by high-resolution X-ray diffraction and chemical etching. The results show that the as-grown crystal has perfect quality with the full width at half maximum （FWHM） of 17.7-22.6 arcsec and etch pits density of （0.3- 2.2）×10^4 cm^-2 throughout the crystal boule. The bottom of the crystal boule shows the best quality. The optical transmission spectra from UV to IR exhibits that the crystal is transparent from 0.2 to 5.5μm and becomes completely absorbing around 6.7μm wavelength, The optical absorption edge in near UV region is about 191 nm.

Diagnosis of hepatic inflammatory pseudotumor by fine-needle biopsy

Hepatic inflammatory pseudotumor(IPT)is a benign lesion characterized by chronic infiltration of inflammatory cells and fibrosis that clinically,radiologically,and pathologically mimics malignancy.However,the epidemiology of IPTs remains unclear.IPTs are often misdiagnosed as malignant lesions because of the lack of characteristic features.We present the case of a 32-year-old man that was misdiagnosed as intrahepatic cholangiocarcinoma by CECT,CEMRI,and CEUS,which was finally confirmed as IPT by fine-needle liver biopsy.In this report,the key factor in the diagnosis of liver inflammatory masses was the presence of hepatic perfusion disorder.

Protective Effects of Polyphenol Extracts from Sea Buckthorn (Hippophaë rhamnoides L.) on Rat Hearts

The objective of present study was to investigate the antioxidative and cardioprotective effects of polyphenol extracts from sea buckthorn (PESB) against myocardial ischemia reperfusion injury (MIRI). PESB was analyzed using HPLC-DAD and their antioxidant activities were evaluated by measuring the intrinsic free radicals cavenging capacity and inhibiting the formation of hydroxyl radical capacity. Experiments on the isolated rat hearts were carried out according to the improved Langendorff retrograde perfusion technology. Coronary effluent of lactate dehydrogenase (LDH) and creatine kinase isoenzyme (CK-MB) activities were analyzed to determine the extent of myocardial injury. Protein expression levels of Beclin-1, microtubule-associated protein 1 light chain 3 (LC3) I and II were measured to evaluate the degree of autophagy. In conclusion, coupled results from both in vivo and in vitro experiments have confirmed that PESB has potential health implications in both prevention and amelioration of MIRI, which may be attributed to the inhibition of autophagy.

Real-world data on ALK rearrangement test in Chinese advanced non-small cell lung cancer(RATICAL):a nationwide multicenter retrospective study

Background:Anaplastic lymphoma kinase(ALK)test in advanced non-small cell lung cancer(NSCLC)can help physicians provide target therapies for patients harboring ALK gene rearrangement.This study aimed to investigate the real-world test patterns and positive rates of ALK gene rearrangements in advanced NSCLC.Methods:In this real-world study(ChiCTR2000030266),patientswith advanced NSCLC who underwent an ALK rearrangement test in 30 medical centers in China between October 1,2018 and December 31,2019 were retrospectively analyzed.Interpretation training was conducted before the study was initiated.Quality controls were performed at participating centers using immunohistochemistry(IHC)-VENTANA-D5F3.The positive ALK gene rearrangement rate and consistency rate were calculated.The associated clinicopathological characteristics of ALK gene rearrangement were investigated as well.Results:The overall ALK gene rearrangement rate was 6.7%in 23,689 patients with advanced NSCLC and 8.2%in 17,436 patients with advanced lung adenocarcinoma.The quality control analysis of IHC-VENTANA-D5F3 revealed an intrahospital consistency rate of 98.2%(879/895)and an inter-hospital consistency rate of 99.2%(646/651).IHC-VENTANA-D5F3 was used in 53.6%,real-time polymerase chain reaction(RT-PCR)in 25.4%,next-generation sequencing(NGS)in 18.3%,and fluorescence in-situ hybridization(FISH)in 15.9%in the adenocarcinoma subgroup.For specimens tested with multiple methods,the consistency rates confirmed by IHC-VENTANA-D5F3 were 98.0%(822/839)for FISH,98.7%(1,222/1,238)forNGS,and 91.3%(146/160)for RT-PCR.The overall ALK gene rearrangement rateswere higher in females,patients of≤35 years old,never smokers,tumor cellularity of>50,and metastatic specimens used for testing in the total NSCLC population and adenocarcinoma subgroup(all P<0.05).Conclusions:This study highlights the real-world variability and challenges of ALK test in advanced NSCLC,demonstrating a predominant use of IHCVENTANA-D5F3 with high consistency and distinct clinicopathological features in ALK-positive patients.These findings underscore the need for a consensus on optimal test practices and support the development of refined ALK test strategies to enhance diagnostic accuracy and therapeutic decision-making in NSCLC.

rADSC-loaded tubular units composed of multilayer electrospun membranes promoted bone regeneration of critical-sized skull defects

Adipose-derived stem cells(ADSCs)have considerable potential for bone regeneration.However,their performance is limited by a lack of scaffolds that adequately mimic the hierarchical structure of bone to promote proliferation and osteogenic differentiation of ADSCs.In this study,nanofiber membranes composed of polycaprolactone,poly(lactide-co-glycolide),and hydroxyapatite(HAp)were prepared via electrospinning,and the membranes curled after responding to temperature stimuli in an aqueous solution.Transmission electron microscopy and scanning electron microscopy observations indicated that needle-like HAp nanoparticles with an average diameter of 57±39 nm and a length–diameter ratio of 7.4±1.56 were entrapped in the nanofiber matrix and did not affect the surface morphology of fibers.After cutting and deformation,the nanofibers changed from straight to bent,and the diameters increased;they were 1105±200 nm for BPLG85-H and 1120±199 nm for BPLG80-H.Additionally,tubular units with a single layer(BPLG-H(1.5))or multiple layers(BPLG-H(3.5))were obtained by controlling the initial shape and size of the membranes.rADSCs on the concave surface of BPLG-H(3.5)proliferated faster and exhibited better osteogenic activity than those on the convex side of BPLG-H(3.5)and both surfaces of BPLG-H(1.5),which was correlated with the higher expressions of vascular endothelial growth factor and bone morphogenetic protein 2.Additionally,rADSCs on both units maintained osteogenic activity after storage at-80◦C for 20 d.In rat skull defect(diameter of 8 mm)models,rADSC-loaded BPLG-H(3.5)units fixed using gelatin hydrogel(ADSC@BHM)exhibited 84.1±6.6%BV/TV after implantation for 12 weeks,which was 155.6%higher than that of the Blank group.H&E and Masson’s staining results demonstrated that there was more bone regeneration at the defect center of ADSC@BHM than in the BHM and Blank groups.In conclusion,rADSC-loaded BPLG-H(3.5)with an osteon-mimic structure provides a potential strategy to repair bone defects.

Anti-cd TCR antibody-expanded cd T cells:a better choice for the adoptive immunotherapy of lymphoid malignancies

Cell-based immunotherapy for lymphoid malignancies has gained increasing attention as patients develop resistance to conventional treatments.cd T cells,which have major histocompatibility complex(MHC)-unrestricted lytic activity,have become a promising candidate population for adoptive cell transfer therapy.We previously established a stable condition for expanding cd T cells by using anti-cd T-cell receptor(TCR)antibody.In this study,we found that adoptive transfer of the expanded cd T cells to Daudi lymphoma-bearing nude mice significantly prolonged the survival time of the mice and improved their living status.We further investigated the characteristics of these antibody-expanded cd T cells compared to the more commonly used phosphoantigen-expanded cd T cells and evaluated the feasibility of employing them in the treatment of lymphoid malignancies.Slow but sustained proliferation of human peripheral blood cd T cells was observed upon stimulation with anti-cd TCR antibody.Compared to phosphoantigen-stimulated cd T cells,the antibody-expanded cells manifested similar functional phenotypes and cytotoxic activity towards lymphoma cell lines.It is noteworthy that the anti-cd TCR antibody could expand both the Vd1 and Vd2 subsets of cd T cells.The in vitro-expanded Vd1 T cells displayed comparable tumour cell-killing activity to Vd2 T cells.Importantly,owing to higher C–C chemokine receptor 4(CCR4)and CCR8 expression,the Vd1 T cells were more prone to infiltrate CCL17-or CCL22-expressing lymphomas than the Vd2 T cells.Characterizing the peripheral blood cd T cells from lymphoma patients further confirmed that the anti-cd TCR antibody-expanded cd T cells could be a more efficacious choice for the treatment of lymphoid malignancies than phosphoantigen-expanded cd T cells.

High-precision orbit prediction and error control techniques for COMPASS navigation satellite

A new satellite orbit prediction method based on artificial neural network(ANN)model is proposed to improve the precision of orbit prediction.In order to avoid the difficulty of amending the dynamical model,it is attempted to use ANN model to learn the variation of orbit prediction error,and then the prediction result of ANN model is used to compensate the predicted orbit based on dynamic model to form a final predicted orbit.The experiment results showed that the orbit prediction error based on ANN model was less than that based on dynamical model,and the improvement effects for different satellites and different time were different.The maximum rates of improvement of predicting 8,15,30 d were respectively 80%,77.77%,85%.The orbit prediction error control technique based on the method of back overlap arc compare was brought forward to avoid the risk that the precision of predicted orbit is even worse after it is compensated by ANN model.The phenomena of failure were basically eliminated based on this technique,and the rate of failure was reduced from 30%to 5%.This technique could ensure that the engineering application of ANN model could come true.

Experimental Study on Melting in a Rectangular Enclosure Heated Below with Discrete Heat Sources

The melting process of n-octadecane in a rectangular cavity with three discrete protruding heat sources on its bottom surface was studied experimentally. It was observed that the experimental process, for the geometric arrangement in this paper, is neither a fixed melting nor a contact melting, but one m which fixed melting and contact melting take place alternatively. The effects of Stefan number, initial subcooling and aspect ratio on the melting process are reported. The larger the Stefan number, the more frequently the contact melting may occur, so does the aspect ratio. The initial subcooling plays a role only in early stage. As the melting process proceeds, its effect on the melting process becomes less.

Toward automatic estimation of urban green volume using airborne LiDAR data and high resolution Remote Sensing images

Urban green volume is an important indicator for analyzing urban vegetation structure, ecological evaluation, and green-economic estimation. This paper proposes an object-based method for automated estimation of urban green volume combining three-dimensional （3D） information from airborne Light Detection and Ranging （LiDAR） data and vegetation information from high resolution remotely sensed images through a case study of the Lujiazui region, Shanghai, China. High resolution airborne near-infrared photographs are used for identifying the urban vegetation distribution. Airborne LiDAR data offer the possibility to extract individual trees and to measure the attributes of trees, such as tree height and crown diameter. In this study, individual trees and grassland are identified as the independent objects of urban vegetation, and the urban green volume is computed as the sum of two broad portions： individual trees volume and grassland volume. The method consists of following steps： generating and filtering the normalized digital surface model （nDSM）, extracting the nDSM of urban vegetation based on the Normalized Difference Vegetation Index （NDVI）, locating the local maxima points, segment- ing the vegetation objects of individual tree crowns and grassland, and calculating the urban green volume of each vegetation object. The results show the quantity and distribution characteristics of urban green volume in the Lujiazui region, and provide valuable parameters for urban green planning and management. It is also concluded from this paper that the integrated application of LiDAR data and image data presents an effective way to estimate urban green volume.

A resilient adjustment method to weigh pseudorange observation in precise point positioning

The accurate weighting of pseudorange observations is important to improve the convergence time and positioning quality of Precise Point Positioning(PPP).Currently,the weight of a pseudorange observation is mainly determined with empirical stochastic models.However,in a complex environment,due to the inability to adapt for the dynamic changes of the user environment,the empirical stochastic models usually cannot reflect the real error level of pseudorange observations.To address this problem,a resilient adjustment method to weigh pseudorange observations is proposed,which constructs the real-time estimation and inflation model for the variance of pseudorange multipath error and measurement noise to replace the empirical stochastic model to determine the weights of pseudorange observations.A set of static and dynamic Global Positioning System(GPS)test data are used to verify the effectiveness of the proposed method.The test results indicate that the proposed real-time estimation model can provide a better representation of the pseudorange accuracy,and the positioning performance of PPP using the real-time estimation model is better than that with the empirical stochastic model.Compared with the optimal empirical stochastic model,the positioning accuracy of PPP with the real-time estimation model is improved by at least 20%,and the convergence time is reduced by at least 50%.

Models and performance of SBAS and PPP of BDS

Satellite Based Augmentation System(SBAS)is one of the services provided by the BeiDou Navigation Satellite System(BDS).It broadcasts four types of diferential corrections to improve user application performance.These corrections include the State Space Representation(SSR)based satellite orbit/clock corrections and ionospheric grid corrections,and the Observation Space Representation(OSR)based partition comprehensive corrections.The algorithms generating these SBAS corrections are not introduced in previous researches,and the user SBAS positioning performance with the contribution of BDS-3 has not been evaluated.In this paper,we present the BDS SBAS algorithms for these diferential corrections in detail.Four types of Precise Point Positioning(PPP)function models for BDS Dual-Frequency(DF)and Single-Frequency(SF)users using the OSR and SSR parameters are also proposed.One week of data in 2020 is collected at 20 reference stations including the observations of both BeiDou-2 Navigation Satellite System(BDS-2)and BeiDou-3 Navigation Satellite System(BDS-3)satellites,and the PPP under various scenarios are performed using all the datasets and the BDS SBAS broadcast corrections.The results show that the performance of BDS-2/BDS-3 combination is superior to that of BDS-2 only constellation.The positioning errors in Root Mean Square(RMS)for the static DF PPP are better than 8 cm/15 cm in horizontal/vertical directions,while for the static SF PPP are 11 cm/24 cm.In the scenarios of simulated kinematic PPP,three Dimension(3D)positioning errors can reach 0.5 m in less than 10 min for the DF PPP and 30 min for the SF PPP,and the RMSs of the DF and SF PPP are better than 17 cm/21 cm and 20 cm/32 cm in horizontal/vertical directions.In a real-time single-and dual-frequency kinematic positioning test,the positioning errors of all three components can reach 0.5 m within 30 min,and the positioning accuracy after solution convergence in the N,E and U directions is better than 0.3 m.

Needle-embedding therapy combined with basic treatment for stable angina pectoris

Objective： To clarify the clinical efficacy of needle-embedding therapy for stable angina pectoris. Methods： Seventy-six patients with stable angina pectoris were divided into needle-embedding therapy group （group A） and basic treatment group （group B） according to the random number table, with 38 patients in each group. Needle-embedding therapy combined with basic treatment was adopted in group A, and needle-embedding was given once every other day, the needles were retained for 24 h each time and three times of treatment were given each week. basic treatment was applied solely in group B. Four weeks of treatment which means one course were given in two groups, efficacy observation and evaluation were carried out after 1 course of treatment. Results： After treatment, the total effective rate of clinical efficacy was 89.47% in group A and 71.05% in group B （p 〈 0.05）, and the total effective rate of electrocardiograph （ECG） efficacy was 84.21% in group A and 63.16% in group B （p〈0.05）. After treatment, the score of limitation of motion, score of the sta- ble state of angina pectoris and the score of angina pectoris attack in group A increased by 0.7%, 34,5% and 16.9% respectively when compared with the scores before treatment （t= 1.623, p 〈0.0l; t=3.867, p 〈 0.01 ; t = 1.958, p 〈 0.05）, and according to the comparison of the score of satisfaction with treatment and the score of disease perception before and after treatment, the difference was not statistically significant （t=4.972, p 〉 0.05; t=0.999, p 〉 0.05）. According to the comparison of the score of limitation of motion, score of angina pectoris attack, score of satisfaction with treatment and the score of disease per- ception in group B before and after treatment, the differences were not statistically significant （t = 1.726, p 〉 0.05; t = 1.594, p 〉 0.05; t = 4.385, p 〉 0.05; t = 0.999, p 〉 0.05）. The score of： the stable state of angina pectoris increased by 4.9% （t = 1.780, p 〈 0.05）. Conclusion： Needle-embedding in acupoint therapy can effectively improve the clinical efficacy, ECG efficacy and the score of Seattle angina questionnaire （SAQ） of stable angina pectoris.

Exosomal long non-coding RNAs:Emerging players in cancer metastasis and potential diagnostic biomarkers for personalized oncology

Metastasis is a major challenge in the treatment of cancer.Exosomes are a class of small extracellular vesicles(EVs)that play critical roles in several human diseases,especially cancer,by transferring information(e.g.,DNA,RNA,and protein)via cell-to-cell communication.Numerous recent studies have shown that exosomal long non-coding RNAs(lncRNAs)play crucial regulatory roles in cancer metastasis in the tumor microenvironment by altering the expression of several key signaling pathways and molecules.Due to their specificity and sensitivity,exosomal lncRNAs have potential as novel tumor markers and therapeutic targets in the treatment of cancer metastasis.In this review,we aim to summarize the roles of exosomal lncRNAs in cancer metastasis,the mechanisms underlying their roles,and their potential clinical applications.

A microarray platform designed for high-throughput screening the reaction conditions for the synthesis of micro/nanosized biomedical materials

Materials research usually relies on lengthy and largely trial-and-error methods,high-throughput technology has thereby emerged as an alternative method which is proven to be a simple,rapid,accurate and sensitive technique.Here,we presented a microfluidic platform with a set of 6×6 microarray chips for high-throughput synthesis and rapid screening the reaction conditions of biomedical materials.The core design of this platform is to generate concentration gradient inside microarray chips.Considering that calcium phosphates(CaP)are the most important inorganic constituents of biological hard tissues,different phases of calcium phosphates particles were synthesized with various morphogenesis when the reaction conditions such as Ca/P concentration ratio,NaOH concentration were screened using our platform.And this platform is universal and expected to apply to other systems for high-throughput screening and synthesis.