Multi Parameter Research Articles

Fine Tuning Bispecific Activity in CLL: Harmonizing a CD19/20-T Cell Bispecific with a CD28 or 4-1BBL Costimulatory Bispecific

Introduction: T cell bispecific antibodies (TCBs), such as blinatumomab, mosunetuzumab or glofitamab, redirect T cells toward cancer cells and rely on endogenous T cell activation and proliferation (Boissel et al., Nature 2023). Physiological T cell activation not only requires signal 1 provided by TCR engagement but also a signal 2 delivered by positive costimulatory molecules. Like a first-generation CAR-T, TCBs only provide signal 1 through CD3 engagement. Hence, TCB-mediated T-cell activation depends on the expression profile of inhibitory and costimulatory checkpoint molecules expressed by tumor cells (Marcinek et al., Cancer Immunology 2023). As tumor cells often lack expression of positive co-stimulatory ligands like CD80, CD86 and 4-1BBL, we hypothesized that the combination of target-antigen specific TCBs with a co-stimulatory agonistic bispecific can increase TCB efficacy by promoting T cell activity and persistence. Methods: We first evaluated the expression level of CD80, CD86 and 4-1BBL on CD19 positive, primary CLL (pCLL) cells by multi parameter flow cytometry (MPFC, n = 6). Next, we co-cultured healthy donor T cells with pCLL cells at a ratio of 1:1 and 1:5 for 6 days in the presence of a CD19- or CD20-TCB in conjunction with a co-stimulatory CD19 directed bispecific providing either CD28 or 4-1BB co-stimulation. T-cell proliferation and cytotoxicity against pCLL cells were analysed by MPFC at day 3 and day 6. Cytokine secretion (IFNγ, IL-2, TNFα) was assessed by cytokine bead array. To further dissect the impact of positive co-stimulation in counteracting evolving TCB-mediated T cell exhaustion, an in vitro model system was used. For this, healthy donor T cells were co-cultured with the lymphoma cell line OCI-Ly1 and continuously stimulated with a CD20 directed TCB over 28 days. The exhausted T cells from different time points were co-cultured with pCLL cells and stimulated with CD19 directed costimulatory bispecifics (CD19-CD28 or CD19-4-1BBL) for the assessment of T-cell fitness. Results: The phenotype profile of pCLL cells showed only dim expression of various positive costimulatory molecules (CD80: 0.5 %, CD86: 14.4 %, 4-1BBL: 9.7 %). Looking at the impact of positive costimulatory bispecifics in short term cultures with healthy donor T cells and pCLL cells, a significant increase in CD19 and CD20-TCB-mediated cytotoxicity was observed through the addition of CD19-CD28 and CD19-4-1BBL bispecific (CD19-TCB vs CD19-TCB + CD19-CD28: 29.9 % vs 56.1 %, p = 0.0014, CD20-TCB vs CD20-TCB + CD19-CD28: 30.2 % vs 64.8 %, p = 0.0112, CD20-TCB vs CD20-TCB + CD19-4-1BBL: 30.2 % to 50.4 %). In line with these findings, T-cell proliferation increased significantly through the addition of the costimulatory bispecifics (CD19-TCB vs CD19-TCB + CD19-CD28: 12.1 % vs 50.0 %, p = 0.0009; CD20-TCB vs CD20-TCB + CD19-CD28: 24.7 % vs 51.8 %, day 3, E:T = 1:1; CD19-TCB vs CD19-TCB + 4-1BBL: 30.5 % vs 63.2 %, p = 0.0048, day 6, E:T = 1:5). Interestingly, the secretion of IFNy, IL-2 and TNFα was mainly increased through the addition of the CD19-CD28 bispecific (IFNy: 141.6 vs 3151.9 pg/mL, IL-2: 21.5 vs 2311.1 pg/mL, TNFα: 60.8 vs 1945.0 pg/mL, n = 4). Importantly, exhausted T cells exposed to CD20-TCB for 28 days in our long-term culture were characterized as dysfunctional showing i.e. an increased expression of exhaustion markers (LAG3 +PD1 +Tim3 + 37.4 % to 70.4 %, day 3 vs day 28) and a reduced cytokine secretion ability (IFNγ: 7949.9 to 693.5 pg/mL, day 3 vs day 24). T cell fitness could be reinvigorated in follow up short term assays through the addition of both CD19 directed costimulatory bispecifics. Specifically, exhausted T cells stimulated with CD20-TCB and CD19-CD28 or CD19-4-1BBL showed a significant increase in TCB-mediated cytotoxicity against primary pCLL cells (CD20-TCB vs CD19-CD28: 15.5 % to 37.7 %, p = 0.0109, CD20-TCB vs CD19-4-1BBL: 15.5 % to 32.9 %, n = 3). Conclusion: In conclusion, our data demonstrates the impact of positive co-stimulation on TCB-mediated T cell function. Costimulatory bispecifics provide co-stimulation to T cells in cases of missing expression of costimulatory molecules on tumor cells as well as improving function of exhausted T cells. Clinical trials will be needed to assess the impact of combinatorial strategies to improve T-cell efficacy and to overcome resistance.

A special phenomenon of wave interactions: An application of nonlinear evolution equation in (3+1)-dimension

The Lie group transformation approach can be used in the reduction of the generalized (3+1)-dimensional nonlinear evolution equation to ordinary differential equations (ODEs). In this work, infinitesimal generators, commutator table of Lie algebra, adjoint representation of subalgebras, symmetry group, and similarity reduction for (3+1)-dimensional shallow-water-like (gSWL) equation are obtained. Interactions of soliton solutions of a gSWL equation are evaluated that depict how near-inertial waves affect the dynamics of barotropic and baroclinic balanced flows. It is shown that the temporo-spatial localization of multi-soliton complexes (MSCs), gradually escalating incoherent interactivity amidst multi parameter group of MSCs along with spatial inhomogeneity alter the shape of quasi-periodic MSCs. The interactions among bright and dark solitons are shown. The increased number of solitons and increased self-interactions among solitary waves contribute to an unstable wave field. Breathers have a well-separating and initial localized energy domain. A limiting case of breather solutions is the peregrine soliton. Thus, interactions among these soliton structures show that multiple breathers retain their wave characteristic.

Multiutility & Customizable Environment Monitoring System With The Healthcare Utilities

IoT based approach of the Remote Monitoring System (RMS). To serve data to the user over long distances wirelessly, Chatbots, web servers and cloud storage could be the best alternative of all and to make the device which satisfies the user's needs we have combined all of them to create a multi utility environmental parameters monitoring and recording system. The device is capable of broadcasting real-time sensor data over the cloud server, social media and a local host web server with the speed depending upon the internet. Integration of API has enabled the device to connect with social media and cloud storage services.

Role of Red Cell Distribution Width and Platelet Count Ratio to Predict the Severity and Outcome in Acute Pancreatitis

Clinical course of acute pancreatitis (AP) varies widely, its clinical features exhibit very low sensitivity for the prediction of severity of disease which is associated with high morbidity and mortality. Several single or multi parameter scoring systems have been described to evaluate the severity of AP. But sometimes, it is not clinically practicable to use these scoring systems for evaluation. This study aimed to find out the Role of Red Cell Distribution Width and Platelet Count Ratio (RPR) to predict the Severity and Outcome in AP. This prospective longitudinal study was carried out from July 2019 to July 2020, at the in-patient department of Gastrointestinal, Hepatobiliary and Pancreatic Disorders, BIRDEM General Hospital, Dhaka. Total 100 patients with AP were included for this study according to selection criteria. An informed written consent was taken from all the participants. Detail history was taken and thorough physical examination was done along with relevant laboratory investigations. Ranson's score, Modified Glasgow score, Bedside index of severity in acute pancreatitis (BISAP), red cell distribution width and platelet count ratio (RPR) were calculated. All data were recorded and analyzed by Statistical package for social sciences (SPSS) 23. In this study 44% patients were more than 60 years with a mean age of 51.34 (±15.45) year. More than two thirds patients were (67%) male. In mild acute pancreatitis mean value of Ranson's score, BISAP score and modified Glasgow score was 0.79 (±0.14), 0.90 (±0.1) and 0.80 (±0.14) and 3.29 (±1.16), 1.77 (±0.46) ,2.74 (±0.69) in moderate to severe pancreatitis respectively with statistically difference were found in both severities (p<.05). The patients with mild pancreatitis and the patients with moderate to severe pancreatitis had significant difference (p<.05) between mean RDW (14.68±1.59% versus 15.51±3.27%), mean RPR (0.043±0.06 versus .062±.002) and platelet count (340.9±841.6 cells/mm3 Versus 236.4±825.4 cells/mm3). The ROC analysis of RPR in predicting severity of pancreatitis showed a cut-off value of ≥ 0.056 and diagnostic accuracy test showed sensitivity, specificity, PPV, NPV and accuracy as 63.6%, 82.2%, 81.4%, 64.9% and 72% respectively. Mean Ranson's score, BISAP score and Modified Glasgow score was 2.09 (±1.45), 1.34 (±0.39) and 1.83 (±1.08) in survived patients and 5.50 (±0.70), 4 and 3.50 (±0.70) in dead patients with significant difference between both groups (p<.05). Mean RDW (15.08±2.67% Vs 17.85±0.21%), mean platelet count (284.43±143×109/L Vs 236.4± 825.4×109/L) and mean RPR (0.053±0.02 Vs 0.094± 0.005) was also significant between survived and dead patients (p<.05). The ROC analysis of RPR in predicting outcome showed cut-off value of ≥ 0.06 and diagnostic accuracy test showed sensitivity, specificity, PPV, NPV and accuracy as 100%, 63.27%, 5.26%, 100% and 64% respectively. Red cell distribution width and platelet count ratio (RPR) can be used as a novel biomarker to predict the severity and mortality of acute pancreatitis in very early stage. Bangladesh Med J. 2021 Sept; 51(1): 18-24

Characterisation of Multi Parameter Sensor for Aero Engine

A multi parameter sensor (Pressure and Temperature) has been developed for use in the harsh environment during aero engine testing. The sensor will be subjected to extreme environmental changes from room temperature and pressure to negative temperature and pressure within a small span of time. It is also very difficult to choose a category of micro behaviors to be characterized among the so many associated with its performance. The multi parameter sensor presented in this paper has been characterized for accuracy, linearity, drift, hysteresis, repeatability, offset and time response. The sensor is intended for applications in the developmental aero engine testing. The evaluation of the performance characteristics carried out in this work is chosen with reference to aero engine testing requirements.

Epidemiological Investigation: Important Measures for the Prevention and Control of COVID-19 Epidemic in China

Based on China’s summary of three years of experience and measures in the prevention and control of the COVID-19 epidemic, we have built a COVID-19 prevention and control model integrating health and medical detection, big data information technology to track the trend of the epidemic throughout the whole process, isolation of key epidemic areas, and dynamic prevention and control management throughout the whole process. This model provides a simple, feasible, and theoretically reliable prevention and control model for future large-scale infectious disease prevention and control. The Lyapnov functional method is replaced by the global exponential attractor theory, which provides a new mathematical method for studying the global stability of the multi parameter, multi variable infectious disease prevention and control system. We extracted mathematical methods and models suitable for non-mathematical infectious disease researchers from profound and difficult to understand mathematical theories. Using the results of the global exponential Attractor theory obtained in this paper, we studied the global dynamics of the COVID-19 model with an epidemiological investigation. The results demonstrated that the non-constant disease-free equilibrium is globally asymptotically stable when λ*<0, and the COVID-19 epidemic is persisting uniformly when λ*>0. In order to understand the impact of the epidemiological investigation under different prevention and control stages in China, we compare the control effects of COVID-19 under different levels of epidemiological investigation policies. We visually demonstrate the global stability and global exponential attractiveness of the COVID-19 model with transferors between regions and epidemiological investigation in a temporal-spatial heterogeneous environment with the help of numerical simulations. We find that the epidemiological investigation really has a significant effect on the prevention and control of the epidemic situation, and we can also intuitively observe the relationship between the flow of people (including tourism, shopping, work and so on) and epidemiological investigation policies. Our model is adapted to different stages of prevention and control; the emergency “circuit breaker” mechanism of the model is also consistent with actual prevention and control.

Optimization of multi parameters of WEDM using ANN based on principal component analysis for AA6063/B4C metal matrix composites

Improved mechanical characteristics for composites using a linear low-density propylene (PP) matrix and a carbon fibre (CF) filler were the focus of this study. The material was fabricated by a hand layup process in an oven. Oxygen plasma treatment of the PP matrix enhanced adherence. Before being filtered and dried for manufacture, CF and PP were first combined with standard stirring, ultrasonication, and mechanical stirring. The highest tensile strength was achieved in plasma-treated propylene (PPP) with 10 wt% CF, with overall property performance increasing by 13.46 % comparison to non-PP with the same CF addition. Tensile strength was reduced from 19.4 MPa to 18.3 MPa when carbon fibers were added at 14 and 16 wt%. As a result of CF aggregation with plasma-treated and untreated PP, tensile strength (TS) was reduced. Better tensile qualities were seen in a factory setting with temperatures of 180 °C for 20 min. After plasma treatment, the PP/8% CF blend had a flexural strength (FS) of 26.19 MPa, which was higher than that of untreated PP by a significant margin.

Diagnosis of Different Spinal Lesions by Multi Parametric MRI

Diagnosis of Different Spinal Lesions by Multi Parametric MRI

Effect of multi parameter synergy on the upgrading characteristics of wide size moist coal

ABSTRACT Through composite dry separation, effective precipitation and impurity removal can be achieved, improving the quality of raw coal. This paper mainly systematically analyzes the synergistic control mechanisms of airflow velocity, airflow transition layer height and control angle on the upgrading characteristics of moist coal. The results show that Zone I is a high airflow area, and when v = 2.12 m/s, it can effectively destroy the original static stable structure of low-density particles, increase the degree of freedom of particle accumulation volume, and achieve effective precipitation of particles. Zone II is a medium air volume area, and when v = 1.78 m/s, the high-density particle group in this area has the weakest obstruction effect on airflow, which can achieve efficient particle precipitation. Zone III is a low airflow area, where the dispersion of high-density particle groups increases at v = 1.36 m/s. The airflow can effectively act on the particles through the bed layer, reducing their surface water. When the height (H) of the gas transition layer is 49-52 mm and the regulatory perspective is 20–25, the distribution uniformity of the gas flow in the bed is the best. After separation and upgrading, the moist coal concentrate yield is 78.3%, ash content is 10.05%, as well as the possible deviation E value is 0.1 g/cm3.

Sinus rate and QRS duration on lead V1 predict major events in Brugada syndrome

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Ministère de la Santé Française Background Arrhythmic risk stratification remains a major challenge in asymptomatic Brugada patients. Many studies have evaluated risk stratification performance based on a single or a few ECG-derived parameters measured manually. We aimed to assess the predictive value of multi ECG parameters measured automatically in patients with Brugada syndrome. Materials and Methods We performed a prospective, multicenter cohort study including Brugada patients with at least one available type 1 ECG (either spontaneously or drug-induced) between January 2005 and November 2021. Paper ECG were first digitized and then automatically analyzed using the Glasgow and Bravo algorithms (included in the logiciel CalECG). Clinical data and Brugada related events at diagnosis and during follow-up were collected. Sudden cardiac death, aborted cardiac arrest and appropriate ICD therapy in the VF zone were considered as major events. The predictive value of clinical and ECG parameters for symptomatic status was assessed using uni- and multivariate Cox models. Results ECGs from 301 Brugada patients (77% male, mean age at diagnosis 43 years, follow-up 7±5.6 years) were analyzed. Brugada-related symptoms (cardiac syncope or major event) occurred in 23% of patients before diagnosis and 11% during follow-up (incidence: 1.57%/year). After multivariate Cox analysis, only 2 baseline ECG (without Ajmaline) parameters were significantly associated with major events: RR interval (HR=1.01 (95%CI [1-1.01]), p=0.002) and QRS duration in lead V1 (HR=1.04 (95%CI [1-1.07]), p=0.038). QRS prolongation in lead V1 >113 ms (AUROC 0.69 (95% CI [0.58-0.8])) was associated with a 3-fold increased risk of major event (HR =3.49 (95% CI [1.72-7.09]), p=0.001). Conclusion Many previously described ECG parameter were not associated with major event in Brugada patients after multi-parameter evaluation. Sinus rate and QRS duration on lead V1 were independent risk factor. These results need to be validated on an external cohort. The predictive value of ECG parameters in Brugada syndrome should be assessed using automated multiparametric quantification.

Multi-parameter adaptive online energy management strategy for concrete truck mixers with a novel hybrid powertrain considering vehicle mass

Given the characteristics of dynamic vehicle mass, multi-operation scenes, and multi-energy-source and multi-energy-consumption-source, the energy optimization problem of concrete truck mixers remains a challenge. To this end, in this paper, a novel hybrid powertrain with a single-shaft parallel for the upper-part system and extended-range for the driving system is utilized and an adaptive online energy management strategy with multi parameters including the driving cycle, vehicle mass, battery state of charge (SOC), and remaining mileage is presented. First, a driven-data clustering method with fuel consumption differentiation is adopted. Then, using the parallel computing genetic algorithm-optimized rule-based method, a driving condition knowledge base, including optimal control models of the various typical driving conditions under multi-parameter combinations, is built to realize the adaptability and robustness. Parameter identifiers are designed, including a sparrow search-optimized-based deep mixed kernel extreme-learning machine recognizer and a vehicle mass recognizer based on sensor and working scene fusion for obtaining corresponding information online. Finally, simulation experiments are conducted to validate the performance and robustness of the presented control strategy. Results indicate it can reduce fuel consumption by an average value of 15.17% and performs better in the convergence level of terminal SOC in five real composite driving conditions.

Sinus rate and QRS duration on lead V1 predict major events in Brugada syndrome

Arrhythmic risk stratification remains a major challenge in asymptomatic Brugada patients. Many studies have evaluated risk stratification performance based on a single or a few ECG-derived parameters measured manually. We aimed to assess the predictive value of multi ECG parameters measured automatically in patients with Brugada syndrome. We performed a prospective, multicenter cohort study including Brugada patients with at least one available type 1 ECG (either spontaneously or drug-induced) between January 2005 and November 2021. Paper ECG were first digitized and then automatically analyzed using the Glasgow and Bravo algorithms. Clinical data and Brugada related events at diagnosis and during follow-up were collected. Sudden cardiac death, aborted cardiac arrest and appropriate ICD therapy in the VF zone were considered as major events. The predictive value of clinical and ECG parameters for symptomatic status was assessed using uni- and multivariate Cox models. ECGs from 301 Brugada patients (77% male, mean age at diagnosis 43 years, follow-up 7 ± 5.6 years) were analyzed. Brugada-related symptoms (cardiac syncope or major event) occurred in 23% of patients before diagnosis and 11% during follow-up (incidence: 1.57%/year). After multivariate Cox analysis, only 2 baseline ECG (without Ajmaline) parameters were significantly associated with major events: RR interval (HR = 1.01 [95%CI 1–1.01], P = 0.002) and QRS duration in lead V1 (HR = 1.04 [95%CI 1–1.07], P = 0.038). QRS prolongation in lead V1 > 113 ms (AUROC 0.69 [95%CI 0.58–0.8], Fig. 1) was associated with a 3-fold increased risk of major event [Fig. 2] (HR = 3.49 (95% CI [1.72–7.09], P = 0.001). Many previously described ECG parameter were not associated with major event in Brugada patients after multi-parameter evaluation. Sinus rate and QRS duration on lead V1 were independent risk factor. These results need to be validated on an external cohort. The predictive value of ECG parameters in Brugada syndrome should be assessed using automated multiparametric quantification.

PD39-07 CAN WE STOP DOING SYSTEMATIC BIOPSIES IN MEN WITH PIRADS/LIKERT 5 LESIONS ON MULTI PARAMETRIC MAGNETIC RESONANCE IMAGING? AN ANALYSIS FROM A MULTICENTRE PROSPECTIVE DATASET OF OVER 800 PATIENTS

You have accessJournal of UrologyCME1 Apr 2023PD39-07 CAN WE STOP DOING SYSTEMATIC BIOPSIES IN MEN WITH PIRADS/LIKERT 5 LESIONS ON MULTI PARAMETRIC MAGNETIC RESONANCE IMAGING? AN ANALYSIS FROM A MULTICENTRE PROSPECTIVE DATASET OF OVER 800 PATIENTS Jonathan Aning, Adrian Andreou, Liam Blaney, Paul Burn, Jon Oxley, Sue Mahoney, Sarah-Jane Davies, Lucy Simmons, Neil Trent, Douglas Kopcke, Raj Persad, and Nick Burns-Cox Jonathan AningJonathan Aning More articles by this author , Adrian AndreouAdrian Andreou More articles by this author , Liam BlaneyLiam Blaney More articles by this author , Paul BurnPaul Burn More articles by this author , Jon OxleyJon Oxley More articles by this author , Sue MahoneySue Mahoney More articles by this author , Sarah-Jane DaviesSarah-Jane Davies More articles by this author , Lucy SimmonsLucy Simmons More articles by this author , Neil TrentNeil Trent More articles by this author , Douglas KopckeDouglas Kopcke More articles by this author , Raj PersadRaj Persad More articles by this author , and Nick Burns-CoxNick Burns-Cox More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003342.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: MRI-targeted biopsy has been demonstrated to be superior to systematic prostate biopsies in randomised studies. However there are few real-life multicentre prospective data evaluating cognitive targeted local anaesthetic transperineal prostate biopsy (CT-LATPB) outcomes and whether additional value is added by performing systematic biopsies. The South West Prostate Dashboard (SWPD) is largest prospective database of Local Anaesthetic Transperineal Prostate Biopsies in the United Kingdom. We investigated the outcomes of men with PIRADS/LIKERT 5 lesions on mpMRI who underwent CT-LATPB and systematic biopsies in the SWPD. METHODS: Using the SWPD, we identified all men between January 2021 and June 2022 with a PIRADS/LIKERT 5 index lesion on their diagnostic mpMRI at 5 hospitals. We then compared the biopsy outcomes for targeted and systematic prostate biopsies in these men. Data in the SWPD registry is input from hospitals in the region prospectively by trained data inputters. Standardised mpMRI and pathology reporting was implemented prior to commencement of data entry. RESULTS: A total of 3799 men underwent mpMRI prostate in the SWPD over the study period. Of these 808/3799 (21%) men, median age 69, were identified to have a PIRADS/LIKERT 5 lesion and 629/808 (78%) of the men with these lesions were under 75 years. The median PSA density of men with these lesions was over 0.21 in all centres and all men with a PIRADS/LIKERT 5 lesion underwent a prostate biopsy. The median number of prostate cores taken at targeted and systematic biopsy per individual was 15. No evidence of cancer was present in 5% of men biopsied. In the remainder of men the overall International Society of Urological Pathology (ISUP) Grade Group (GG) identified was GG1 (6%), GG2 (33%), GG3 (26%), GG4 (9%), GG5 (21%). Systematic core biopsies identified higher ISUP grade groups than the targeted core biopsies taken in the same men in 78/808 (9%). The upgrading effect would only have changed the clinical management of patients in 17/808 (2%). CONCLUSIONS: Prospective data collection supports the safe diagnosis of clinically significant prostate cancer in men with PIRADS/LIKERT 5 lesions with CT-LATP biopsy only with standardised reporting of mpMRI. Systematic biopsies need only be taken if non clinically significant disease is identified or focal therapy is being considered. This resource efficient patient focused approach is also more environmentally sustainable. Source of Funding: SWAG Cancer Alliance and Peninsula Cancer Alliance © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1047 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jonathan Aning More articles by this author Adrian Andreou More articles by this author Liam Blaney More articles by this author Paul Burn More articles by this author Jon Oxley More articles by this author Sue Mahoney More articles by this author Sarah-Jane Davies More articles by this author Lucy Simmons More articles by this author Neil Trent More articles by this author Douglas Kopcke More articles by this author Raj Persad More articles by this author Nick Burns-Cox More articles by this author Expand All Advertisement PDF downloadLoading ...

Evaluation of prostate multi parameter bone structures for martial arts practitioners based on magnetic resonance imaging

ObjectiveIn this paper, we studied the feasibility of automatic segmentation of bone structures for rehabilitation and disease prevention from diffusion-weighted and apparent diffusion coefficient images obtained from prostate multi-parameter magnetic resonance imaging (mpMRI) in the healthy promotion of Chinese Taijiquan martial arts. MethodsThe mpMRI images of 15 patients practicing Taijiquan martial arts were analyzed retrospectively. We manually annotate bone structures on DWI (b = 800 s/mm2), DWI (b = 0S/mm2), and ADC images. Then, we use different sequence combinations as input data to test the segmentation model, and evaluate the impact of six different sequence combinations on the region-based segmentation performance, such as the watershed model. The model evaluation indicators include quantitative indicators (DICE coefficient, label capacity) and qualitative indicators (subjective score). The model evaluation standard calculates the coincidence rate of all sequences in the test set, and more than 80% are considered to meet the clinical application requirements. ResultsThe DICE value of the watershed segmentation model was 0.75 (0.70–0.81) −0.81 (0.73–0.85) on DWI images, and the ADC value was 0.79 (0.78–0.81) −0.83 (0.80–0.85). However, there was no significant difference in DICE value between different models (HDWI = 2.978, PDWI>0.05; HADC = 1.140, PADC>0.05). There was no significant difference in the volume difference between model prediction and manual labeling among different models (HDWI = 2.900, PDWI>0.05; HADC = 2.236, PADC>0.05). Qualitative scoring models 1 and 3 achieved the highest standard rate in DWI and ADC image segmentation, both above 80%. ConclusionAfter Taijiquan martial arts exercise, it is found that the DWI segmentation model based on watershed region combined with ADC sequence can achieve high-performance segmentation of pelvic bone structure in prostate mpMRI, meet the needs of clinical application, and is conducive to healthy sports for all.

A Multi Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model

Financial data are a type of historical time series data that provide a large amount of information that is frequently employed in data analysis tasks. The question of how to forecast stock prices continues to be a topic of interest for both investors and financial professionals. Stock price forecasting is quite challenging because of the significant noise, non-linearity, and volatility of time series data on stock prices. The previous studies focus on a single stock parameter such as close price. A hybrid deep-learning, forecasting model is proposed. The model takes the input stock data and forecasts two stock parameters close price and high price for the next day. The experiments are conducted on the Shanghai Composite Index (000001), and the comparisons have been performed by existing methods. These existing methods are CNN, RNN, LSTM, CNN-RNN, and CNN-LSTM. The generated result shows that CNN performs worst, LSTM outperforms CNN-LSTM, CNN-RNN outperforms CNN-LSTM, CNN-RNN outperforms LSTM, and the suggested single Layer RNN model beats all other models. The proposed single Layer RNN model improves by 2.2%, 0.4%, 0.3%, 0.2%, and 0.1%. The experimental results validate the effectiveness of the proposed model, which will assist investors in increasing their profits by making good decisions.

Responses of well-aquifer system to four earthquakes and implication for contaminant transport in Changan landfill, China

Evaluation of aquifer response to earthquakes is important to understanding the evolution of aquifer properties and contaminant transport. In Changan Landfill, a multi parameter monitoring system was installed to collect data every 12 h. Principal Component Analysis (PCA), energy density and wavelet analysis, and tidal analysis were used to reveal the response mechanisms to four earthquakes, sensitivity of various parameters to seismic stimuli, and permeability evolution, respectively. The results showed that the chemical characteristics of two aquifers were distinct. The shallow aquifer was polluted by leachate, and the deep aquifer was less polluted. Coseismic responses were dominated by the deep aquifer and the relative contribution of each aquifer remained stable. Coseismic chemical changes were dominated by the opening and closing of fractures, and the long-term evolution was controlled by seasonality. The deep aquifer had a higher sensitivity to seismic stimuli than the shallow aquifer. Tidal analysis showed that a general permeability decrease during this monitoring period reduced contaminant transport, but some contaminants crossed the aquitard between the two aquifers after the Zizhong earthquake, due to an increase in vertical permeability.

Well head multi parameter data monitoring system based on LoRa

Oilfield wellhead data is an important indicator to reflect the normal operation of oil well equipment. This paper monitors the data of standpipe pressure, hanging weight, torque and other parameters, which is helpful to improve the safety and production efficiency of the entire oilfield. Therefore, this paper proposes a set of multi parameter monitoring system based on LoRa to further explore and study in order to reduce oilfield accidents.

Research on comprehensive optimization strategy of transformer thermal life in digital substation

With the national advocacy and vigorous promotion of new digital infrastructure, digital assessment of transformer operation state based on digital twin technology has become one of the hot issues in the power field. In this paper, taking an oil immersed transformer as an example, the magnetic, current and thermal multi field coupling numerical analysis method is used to simulate and analyze the operation state of the transformer, monitor the multi state characteristic parameters of the transformer through sensors, integrate the numerical simulation analysis results with the state monitoring results, and build a transformer thermal life loss evaluation system. This method can evaluate and analyze the operation status of transformers in real time, which is of great significance for power companies to formulate governance measures. It can effectively support the national new digital infrastructure strategy and contribute to the national strategy while satisfying the normal operation of power grid enterprises.

Optimization of induction heating parameters for improving Self-healing performance of asphalt mixture through partial least square model

The self-healing capacity of asphalt mixture based on induction heating, determined by induction heating parameters, has been the key issue regarding asphalt mixture’s self-healing. This study tried to investigate how induction heating parameters determine asphalt mixture’s self-healing concerning parameters’ coupling effect. AC-13 asphalt mixtures consisting of steel fiber and steel slag were prepared for induction heating. Dynamic stability, low-temperature cracking resistance, and moisture stability were studied. Single-parameter (SP) method and multi-parameter (MP) method considering the coupling effect were separately used to achieve the optimum parameter combinations for improving the healing ratio (HR). A functional relationship by the MP method between HR and induction heating parameters was established based on partial least square through Data Processing System software (DPS). Results verified the coupling effect among parameters. Asphalt mixture with 8 % steel fiber content showed optimum pavement performance. The optimum parameter combination of SP method for HR was: 8 % steel fiber content, 5 mm, 180 s, and 16 kW for induction distance, time, and power respectively, and the optimum HR based on SP method was 69 %. The optimum parameter combination of MP method was: 8.8 %, 5 mm, 107 s, and 24 kW, while its predicted HR was 77 % and the actual HR was 75 %. Therefore, the MP method based on partial least square showed a greater improvement of HR than SP method, which proved that coupling effects of induction heating parameters affect asphalt mixture’s self-healing capacity.

Multi structural parameter analysis based on the labyrinth valve design with high pressure drop and low noise

Labyrinth channel design is a key for achieving high pressure loss for the labyrinth valve in a thermal power plant. However, the labyrinth channel structures are relatively complex, with many influencing parameters. An unreasonable design generates high noise, adversely affecting personnel and equipment. In this paper, pressure drop is used as a typical parameter for evaluating pressure loss performance, while cavitation, flow velocity, and transmission loss are used as characteristic parameters for assessing noise performance. A comprehensive evaluation criteria of noise performance is constructed. The numerical models with various stage numbers, entrance widths, channel depths, transition part parameters, and expansion coefficients are established, the effects of different structural parameters on the labyrinth channel pressure loss and noise performance are systematically studied to achieve a labyrinth valve design with high pressure loss and low noise. The results show that the influence of different structural parameters on the labyrinth channel pressure loss and noise performance is not the same. The parameter selection of multi-stage, small entrance width, medium channel depth, large transition part parameters, and high expansion coefficient is important way for realizing the design of high pressure loss and low noise labyrinth valve.