Parameter optimization and experiment of the negative pressure precision seed-metering device for wheat

In order to ensure the most reasonable distribution of wheat seeds in the field to improve seeding quality and uniformity,a set of negative pressure precision seed-metering device was designed,which shares a hollow shaft.Every seed-metering device can sow two rows of wheat.By the STAR-CCM+,the analysis of nephogram,vectogram and streamline graph showed that more ideal structural parameters of the seed-metering device are 0.5 mm width of the slit sucking seed(WSS),150-200 mm diameter of the seed-metering disc(DSD),2.0 mm axial depth of air chamber in the seed-metering disc(ADS),and arc-shaped cross-section shape of the ring groove sucking seed(CSGS).Single-factor test on the JPS-12 test-bed analyzed the influence of the CSGS,WSS,DSD,and ADS on the qualified index(Iq),multiple index(Imul),miss index(Imiss)and coefficient of variation of qualified seed spacing(CV).Through the orthogonal on the JPS-12 test-bed,it is found that the influence of vacuum negative pressure and seed-metering device shaft speed is significant on the Iq,Imiss and Imul.Based on these,the structural parameters of the seed-metering device were optimized.The DSD is 180 mm,the WSS is 0.7 mm,the ADS is 2.5 mm,and the CSGS is arc-shaped.The optimization seed-metering device was tested on the JPS-12 test-bed.The Iq is 86.66%,the Imiss is 5.09%,the Imul is 8.25%,and the CV is 24.50%.These testing results fully coincide with the standard JB/T 10293-2013 Specifications of single seed drill(precision drill).The seed-metering device meets fully the requirements for wheat precision seeding.

Optimized design of the pneumatic precision seed-metering device for carrots

The small size, light weight, irregular shape, and impurities that characterize seed groups increase clogging tendencies in the traditional seed-metering device thereby making it difficult to achieve high-speed precision seeding. A pneumatic seed-metering device with good seed-filling performance for carrot was designed in this study. By analyzing the movement state of seeds in the device under the theoretical condition, it was concluded that the minimum critical negative pressure value of air chamber was 0.32 kPa, which provided a theoretical basis for simulation and testing. ANSYS 17.0 Software was used to simulate the shape of the seeding plate hole. By comparing the pressure, air flow stability between the suction surface and the plug removal surface of the convection field, it was concluded that the conical hole was optimal. A bench verification test was conducted on the device. The average qualified rate, missing rate, and replaying rate were 81.48%, 4.07%, and 14.45%, respectively, which provided a strong reference for the design of carrot precision seed-metering device.

Design and experiment of conical diversion virus-free potato minituber precision seed-metering device

In order to accelerate the development of sowing mechanization of virus-free potato minituber,a conical diversion virus-free potato minituber precision seed-metering Device was designed according to the structural characteristics and agronomic requirements of virus-free potato minituber.The device is mainly composed of conical turntable,transmission shaft,outer baffle of seed-metering Device,baffle,seed outlet,seed cleaning device,type hole,etc.The working principle of conical diversion precision seed-metering device for virus-free potato minituber was expounded,and the stress analysis of virus-free potato minituber in each region was carried out.By EDEM discrete element simulation software,the structure of the type hole is optimized to determine the optimal structure of the type hole and according to the physical characteristics of virus-free potato minituber,the single factor experiments of the effects of length of type hole,cone disc speed and cone disc angle on seed filling performance were completed.The orthogonal regression test was carried out with the length of type hole,cone disc speed,and cone disc angle as the test objects,and the leakage rate and qualified rate as the response indexes.The regression models of leakage rate,replay rate,and qualified rate were established,and the parameters of the regression model were optimized.The optimal parameter combination is that the length of type hole is 33.61 mm,the cone disc speed is 6.35 r/min,and the cone disc angle is 26.59°.Bench test was carried out under the optimal conditions,the leakage rate was 3.80%,the replay rate was 0.80%,and the qualified rate was 95.40%,which was basically consistent with the prediction results of the regression model,and met the requirements of precision sowing of virus-free potato minituber.

Design of motor-driven precision seed-metering device with improved fuzzy PID controller for small peanut planters

Traditional passive ground wheel drive of peanut planters has displayed poor high-speed seeding performance and the slippage caused in case of sticky and wet soil.Given this,an integrated electric-driven precision seed metering device and controller were designed,which features the application of improved fuzzy PID algorithm.Based on a small peanut planter with one ridge width and duplicate rows,the servo motor drive is used to replace the traditional passive ground wheel.In addition,the satellite speed measurement is employed to complete the electric driving and controlling modification of the seed meter and precise seeding control.A working process mathematical model for the peanut metering device was established to conduct motor speed and field tests which aim at comparing performances between the conventional and the improved fuzzy PID controls.The motor speed trial shows that the average error of the actual speed of the improved fuzzy PID motor was±1 rad/min,and the coefficient of variation was less than 1%.Against the conventional one,it can better suppress overshoot and improve the response speed.The stable output speed can still be obtained even in case of step changes.Field tests show that when working at medium and low speeds,the qualified rate of plant spacing was greater than 98%,and the rate of missed sowing is<2%;while working at high speed,the qualified rate was greater than 94%,and the rate of missed sowing was less than 4%.The average plant spacing qualification rate of the seed device increased by 6.72%;compared with other electric-driven peanut seed meters,the plant spacing qualification rate increased by 4%during high-speed sowing.In summary,this study has provided an effective technical reference for high-speed precision planting of peanuts.

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.

Stability Analysis and Performance Evaluation of Additive Mixed-Precision Runge-Kutta Methods

Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed.These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations.In this work,we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors,and demonstrate their performance in terms of accuracy and efficiency.We develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta(MP-ARK)methods.The convergence,accuracy,and runtime of these methods are explored.We show that for a given level of accuracy,suitably chosen MP-ARK methods may provide significant reductions in runtime.

Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

Background:Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs(ARLncRNAs)on the prognosis of hepatocellular carcinoma(HCC).Methods:We analyzed 371 HCC samples from TCGA,identifying expression networks of ARLncRNAs using autophagy-related genes.Screening for prognostically relevant ARLncRNAs involved univariate Cox regression,Lasso regression,and multivariate Cox regression.A Nomogram was further employed to assess the reliability of Riskscore,calculated from the signatures of screened ARLncRNAs,in predicting outcomes.Additionally,we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis,using consensus clustering to identify subgroups related to ARLncRNAs.Results:The screening process identified 27 ARLncRNAs,with 13 being associated with HCC prognosis.Consequently,a set of signatures comprising 8 ARLncRNAs was successfully constructed as independent prognostic factors for HCC.Patients in the high-risk group showed very poor prognoses in most clinical categories.The Riskscore was closely related to immune cell scores,such as macrophages,and the DEGs between different groups were implicated in metabolism,cell cycle,and mitotic processes.Notably,high-risk group patients demonstrated a significantly lower IC50 for Paclitaxel,suggesting that Paclitaxel could be an ideal treatment for those at elevated risk for HCC.We further identified C2 as the Paclitaxel subtype,where patients exhibited higher Riskscores,reduced survival rates,and more severe clinical progression.Conclusion:The 8 signatures based on ARLncRNAs present novel targets for prognostic prediction in HCC.The drug candidate Paclitaxel may effectively treat HCC by impacting ARLncRNAs expression.With the identification of ARLncRNAsrelated isoforms,these results provide valuable insights for clinical exploration of autophagy mechanisms in HCC pathogenesis and offer potential avenues for precision medicine.

Bronchoalveolar lavage fluid assessment facilitates precision medicine for lung cancer

Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death.Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients.At present,the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers,and treatment is primarily hindered by drug resistance and high tumor heterogeneity.Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues.Bronchoalveolar lavage fluid(BALF)is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components.BALF contains information on the key characteristics of tumors,including the tumor subtype,gene mutation type,and tumor environment,thus BALF may be used as a diagnostic supplement to lung biopsy.In this review,the current research on BALF in the diagnosis,treatment,and prognosis of lung cancer is summarized.The advantages and disadvantages of different components of BALF,including cells,cell-free DNA,extracellular vesicles,and micro RNA are introduced.In particular,the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted.In addition,the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF,thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.

Hepatitis B virus genotypes in precision medicine of hepatitis Brelated hepatocellular carcinoma:Where we are now

Hepatitis B virus(HBV)infection is a major player in chronic hepatitis B that may lead to the development of hepatocellular carcinoma(HCC).HBV genetics are diverse where it is classified into at least 9 genotypes(A to I)and 1 putative genotype(J),each with specific geographical distribution and possible different clinical outcomes in the patient.This diversity may be associated with the precision medicine for HBV-related HCC and the success of therapeutical approaches against HCC,related to different pathogenicity of the virus and host response.This Editorial discusses recent updates on whether the classification of HBV genetic diversity is still valid in terms of viral oncogenicity to the HCC and its precision medicine,in addition to the recent advances in cellular and molecular biology technologies.

A new method for evaluating the firing precision of multiple launch rocket system based on Bayesian theory

How to effectively evaluate the firing precision of weapon equipment at low cost is one of the core contents of improving the test level of weapon system.A new method to evaluate the firing precision of the MLRS considering the credibility of simulation system based on Bayesian theory is proposed in this paper.First of all,a comprehensive index system for the credibility of the simulation system of the firing precision of the MLRS is constructed combined with the group analytic hierarchy process.A modified method for determining the comprehensive weight of the index is established to improve the rationality of the index weight coefficients.The Bayesian posterior estimation formula of firing precision considering prior information is derived in the form of mixed prior distribution,and the rationality of prior information used in estimation model is discussed quantitatively.With the simulation tests,the different evaluation methods are compared to validate the effectiveness of the proposed method.Finally,the experimental results show that the effectiveness of estimation method for firing precision is improved by more than 25%.

Comparison of the precision of glacier flow rates derived from offset-tracking using Sentinel-2 and Landsat-8/9 imagery

Offset-tracking is an essential method for deriving glacier flow rates using optical imagery.Sentinel-2(S2)and Landsat-8/9(L8/9)are popular optical satellites or constellations for polar studies,offering high spatial resolution with relatively short revisit time,wide swath width,and free accessibility.To evaluate and compare the precision of offset-tracking results yielded with these two kinds of data,in this study S2 and L8/9 imagery observed in Petermann Glacier in Greenland,Karakoram in High-Mountains Asia,and Amery Ice Shelf in the Antarctic are analyzed.Outliers and various systematic error sources in the offset-tracking results including orbital and strip errors were analyzed and eliminated at the pre-process stage.Precision at the off-glacier(bare rock)region was evaluated by presuming that no deformation occurred;then for both glacierized and the off-glacier regions,precision of velocity time series was evaluated based on error propagation theory.The least squares method based on connected components was used to solve flow rates time series based on multi-pair images offset-tracking.The results indicated that S2 achieved slightly higher precision than L8/9 in terms of both single-pair derived displacements and least square solved daily flow rates time series.Generally,the RMSE of daily velocity is 26%lower for S2 than L8/9.Moreover,S2 provided higher temporal resolution for monitoring glacier flow rates.

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

Reinforcement Learning Based Quantization Strategy Optimal Assignment Algorithm for Mixed Precision

The quantization algorithm compresses the original network by reducing the numerical bit width of the model,which improves the computation speed. Because different layers have different redundancy and sensitivity to databit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determinethe optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantizationcan effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In thispaper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bitwidth is proposed, and reinforcement learning is used to automatically predict the mixed precision that meets theconstraints of hardware resources. In the state-space design, the standard deviation of weights is used to measurethe distribution difference of data, the execution speed feedback of simulated neural network accelerator inferenceis used as the environment to limit the action space of the agent, and the accuracy of the quantization model afterretraining is used as the reward function to guide the agent to carry out deep reinforcement learning training. Theexperimental results show that the proposed method obtains a suitable model layer-by-layer quantization strategyunder the condition that the computational resources are satisfied, and themodel accuracy is effectively improved.The proposed method has strong intelligence and certain universality and has strong application potential in thefield of mixed precision quantization and embedded neural network model deployment.

Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus

Globally,type 2 diabetes mellitus(T2DM)is one of the most common metabolic disorders.T2DM physiopathology is influenced by complex interrelationships between genetic,metabolic and lifestyle factors(including diet),which differ between populations and geographic regions.In fact,excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM,whereas habitual intakes of plant-based healthy diets usually exert a protective effect.Moreover,genomic studies have allowed the characterization of sequence DNA variants across the human genome,some of which may affect gene expression and protein functions relevant for glucose homeostasis.This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression,some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions.Also,novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations.Furthermore,progresses in other omics areas(epigenomics,metagenomics,proteomics,and metabolomics)are improving current understanding of genetic insights in T2DM clinical outcomes.Although more investigation is still needed,the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening,prevention,diagnosis,management,and prognosis of T2DM through precision nutrition.

Integrating disulfidptosis-related long noncoding RNAs in colorectal cancer prognosis:A path to precision medicine

This commentary explores the burgeoning field of disulfidptosis-related long noncoding RNAs(lncRNAs)in the prognosis and therapeutic targeting of colorectal cancer(CRC).By evaluating recent research,including the pivotal study"Predicting colorectal cancer prognosis based on long noncoding RNAs of disulfidptosis genes"by Wang et al,this analysis underscores the critical role of lncRNAs in deciphering the molecular complexities of CRC.Highlighting the innovative methodologies and significant findings,I discuss the implications for patient survival,therapeutic response,and the potential of lncRNAs as biomarkers for precision medicine.The integration of bioinformatics,clinical databases,and molecular biology in these studies offers a promising avenue for advancing CRC treatment strategies and improving patient outcomes.

Re-evaluating the role of pelvic radiation in the age of modern precision medicine and systemic therapy

The efficacy of pelvic radiation in the management of locally advanced stage rectal cancer has come under scrutiny in the context of modern precision medicine and systemic therapy as evidenced by recent clinical trials such as FOWARC(J Clin Oncol 2019;37:3223-3233),NCT04165772(N Engl J Med 2022;386:2363-2376),and PROSPECT(N Engl J Med 2023;389:322-334).In this review,we comprehensively assess these pivotal trials and offer additional insights into the evolving role of pelvic radiation in contemporary oncology.

Design methodology of a mini-missile considering flight performance and guidance precision

The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.

Envita’s Precision Cancer Care: 35-Fold Improvement in Response Rates

New clinical approaches are imperative beyond the widely adopted National Comprehensive Cancer Network (NCCN) guidelines, utilized by prominent cancer institutions. Cancer is the leading cause of death among individuals younger than 85 years within the United States. Despite significant technological advances, including the expenditure of hundreds of billions, treatment outcomes and overall survival have not notably improved for most types of advanced cancer over the last several decades. Over the past 24 years, Envita Medical Centers has pioneered a unique form of personalized treatment approach for late-stage and refractory cancer patients, introducing groundbreaking innovations in the field. Our integrated algorithm utilizes advanced genomics, transcriptomics, and highly tailored immunotherapy, resulting in remarkable outcome improvements. This study presents Envita’s innovative personalized treatment algorithms and examines the response outcomes of 199 late-stage cancer patients treated at Envita Medical Centers over a two-year period. Compared to standard of care and palliative chemotherapy, Envita’s treatment demonstrated a remarkable 35-fold improvement in overall response rates (Figure 1). Moreover, 88% of the patients, the majority presenting with Stage 3 or 4 cancer, experienced a 43-fold improvement in quality of life with minimal side effects, as compared to standard of care chemotherapy and palliative care. This revolutionary success is attributed to Envita’s personalized therapeutic algorithms, which incorporate customized immunotherapy. Envita’s precision care approach has also achieved a 100% better response rate compared to over 65 global chemotherapy clinical trials with more than 2700 patients. The results from this study suggest that a wider utilization of Envita’s personalized approach can significantly benefit patients with late-stage and refractory cancer.

The Chinese Consumers’Service Quality Satisfaction Differences of Cruise Tourism and Precision Marketing Strategy

The paper selected Chinese Cruise Line as the case study. Having based on the survey data of Chinese cruise tourism consumers, the factor analysis method, one-way analysis of variances method, cluster analysis method, and other quantitative and qualitative methods were taken to analyze Chinese consumers’ satisfaction differences of cruise tourism service quality with different segmentation markets and clusters markets, and the reasons of satisfaction differences were also explored. Then precision marketing strategy of Chinese cruise tourism with different segmentation markets and clusters markets from the supply-side reform perspective was discussed. The purpose of current research was to provide suggestions of precision management and precision marketing of Chinese cruise tourism for relevant enterprises and government departments.

Coping with the Impact of Climate Change: A Dive into Precision Agriculture in the United States

With the continued increase in the number of people that are food insecure globally, which could be increasing because of the ongoing Ukraine-Russia war, leading to reduction in international agribusinesses, coupled with drastic climate change exacerbating the problem of food insecurity, there is a constant need to come up with innovative approaches to solve this global issue. In this article, we articulated how precision agriculture can be a tool for ensuring food security in the United States. This study aims to reiterate the significance of precision agriculture in solving global food insecurity.