Estimation Of Rate Research Articles

External Validation of a Novel Multimarker GFR Estimating Equation.

Using multiple markers may improve accuracy in glomerular filtration rate (GFR) estimation. We sought to externally validate and compare the performance a novel multi-marker estimated GFR (panel eGFR) among Black and White persons using the Genetic Epidemiology Network of Arteriopathy cohort. We included 224 sex, race/ethnicity, and measured GFR (mGFR)-category-matched persons, with GFR measured using urinary clearance of iothalamate. We calculated panel eGFR using serum creatinine, valine, myo-inositol, cystatin C, age, and sex. We compared its reliability with current eGFR equations (2021 CKD-EPI creatinine [eGFR-Cr] and creatinine with cystatin C [eGFR-Cr-CysC]) using median bias, precision, and accuracy metrics. We evaluated each equation's performance in age, sex, and race subgroups. In the overall cohort, 49% were Black individuals and mean mGFR was 79 ml/min/1.73m2. Panel eGFR overestimated mGFR (bias: -2.4 ml/min/1.73m2; 95% confidence interval [CI]: -4.4, -0.7), eGFR-Cr-CysC underestimated mGFR (bias: 4.8 ml/min/1.73m2; 95% CI: 2.1, 6.7), while eGFR-Cr was unbiased (bias: 2.0 ml/min/1.73m2; 95% CI: -1.1, 4.6). All equations had comparable accuracy. Among Black males age <65 years, both eGFR-Cr (bias: 17.0 ml/min/1.73m2; 95% CI: 8.6, 23.5) and eGFR-Cr-CysC (bias: 14.5 ml/min/1.73m2; 95% CI: 6.0, 19.7) underestimated mGFR whereas panel eGFR was unbiased (bias: 1.7 ml/min/1.73m2; 95% CI: -3.4, 10.0). Metrics of accuracy for all eGFRs were acceptable in all subgroups except for panel eGFR in Black females <65 years (P30: 73.3%). Panel eGFR can be used to estimate mGFR and may have utility among Black males age <65 years where current CKD-EPI equations are biased.

Automated Counting of Tobacco Plants Using Multispectral UAV Data

Plant counting is an important part in precision agriculture (PA). The Unmanned Aerial Vehicle (UAV) becomes popular in agriculture because it can capture data with higher spatiotemporal resolution. When it is equipped with multispectral sensors, more meaningful multispectral data is obtained for plants’ analysis. After tobacco seedlings are raised, they are transplanted into the field. The counting of tobacco plant stands in the field is important for monitoring the transplant survival rate, growth situation, and yield estimation. In this work, we adopt the object detection (OD) method of deep learning to automatically count the plants with multispectral images. For utilizing the advanced YOLOv8 network, we modified the architecture of the network to adapt to the different band combinations and conducted extensive data pre-processing work. The Red + Green + NIR combination obtains the best detection results, which reveal that using a specific band or band combinations can obtain better results than using the traditional RGB images. For making our method more practical, we designed an algorithm that can handling the image of a whole plot, which is required to be watched. The counting accuracy is as high as 99.53%. The UAV, multispectral data combined with the powerful deep learning methods show promising prospective in PA.

Monitoring drought induced photosynthetic and fluorescent variations of potatoes by visible and thermal imaging analysis

Accurate determination of photosynthetic parameters is critical to evaluate crop physiological and growth processes. This study aimed to estimate photosynthetic and fluorescence variables of potatoes by visible and thermal imaging fusion analysis. Two-years pot experiments were conducted in a climate chamber with different irrigation treatments. Multi-modal image features of crop canopy were extracted from both visible and thermal images by color component extraction, discrete wavelet transformation, gray level co-occurrence matrix, and local binary pattern algorithms. Extracted features were subsequently employed to build partial least squares regression (PLSR) models for estimation of transpiration rate (Tr), net photosynthetic rate (An), stomatal conductance (GSW), electron transport rate (ETR), and maximum photochemical efficiency under Photosystem II (Fv'/Fm'). Results showed that Mask Region-Convolutional Neural Network (Mask R-CNN) performed satisfactorily on canopy segmentation with intersection over union of 87.29 % and 86.93 % in visible and thermal images, respectively. Three different types of models that either using only visible image features (PLSRRGB), or only thermal image features (PLSRT) or both visible and thermal image features (PLSRRGB+T) as inputs were compared. Results showed that PLSRRGB+T had superior estimation performance in terms of R2 and RMSE. It achieved the highest R2 of 0.85 with An and the lowest R2 of 0.66 with GSW for Zhongshu 5, while it had the highest R2 of 0.86 with Fv'/Fm', and the lowest R2 of 0.71 with Tr and An for D681. This implied the potential of visible and thermal image-driven method for quick and accurate estimation of photosynthetic traits of crops grown in controlled environment.

Projected incidence trends of need for long-term care in German men and women from 2011 to 2021.

The German Federal Statistical Office routinely collects and reports aggregated numbers of people in need of long-term care (NLTC) stratified by age and sex. Age- and sex-specific prevalence of NLTC from 2011 to 2021 is reported as well. One estimation of the incidence rate of NLTC based on the age- and sex-specific prevalence exists that did not explore possible trends in incidence [based on MRR (mortality rate ratio)], which is important for an adequate projection of the future number of people with NLTC. We aim to explore possible trends in age-specific incidence of NLTC in German men and women from 2011 to 2021 based on different scenarios about excess mortality (in terms of MRR). The incidence of NLTC was calculated based on an illness-death model and a related partial differential equation based on data from the Federal Statistical Office. Estimation of annual percent change (APC) of the incidence rate was conducted in eight scenarios. There are consistent indications for trends in incidence for men and women aged 50-79 years with APC in incidence rate of more than +9% per year (up to nearly 19%). For ages 80+ the APC is between +0.4% and +12.5%. In all scenarios, women had higher age-specific APCs than men. We performed the first analysis of APC in the age- and sex-specific incidence rate of NLTC in Germany and revealed an increasing trend in the incidences. With these findings, a future prevalence of NLTC can be estimated which may exceed current prognoses.

A machine learning approach and numerical investigation for intelligent forecasting of entropy generation rate inside a turbulator-inserted solar collector tube

The irreversibility rate analysis on the solar thermal collectors can be used to determine the regions in the geometry with high intensification of the thermal and viscous entropy generation rates (S˙th and S˙fr), thereby improving the geometry. Although the numerical analysis of the hydrothermal characteristics of the solar thermal collector has been widely studied, the entropy generation rate inside a turbulator insert absorber tube is less understood. In addition, there is still the lack of an accurate predictive model for the estimation of the total entropy generation rate inside the turbulator insert absorber tube. This study deals with the determination of S˙th and S˙fr of water flow inside a tube considering three twisted tape inserts with pitch distances (H) of 50 mm, 100 mm, and 150 mm as well as the Re numbers of 500, 1000, and 1500. The results showed that the escalation of H from 50 mm to 150 mm at Re numbers of 500, 1000, and 1500, S˙fr reduces by 15.40%, 24.50%, and 29.67%, respectively. Also, a 90% increase in S˙fr was observed as Re intensified from 500 to 1500. In addition, the increment in Re from 500 to 1500 reduces by 43%, 41%, and 34% at H values of 50 mm, 100 mm, and 150 mm, respectively. Besides, the increase in H from 50 mm to 150 mm escalates S˙th b by 55%, 63%, and 60%, respectively, for Res of 500, 1000, and 1500. Meanwhile, the entropy generation contour plots revealed that the rate of irreversibilities near the blade and tube wall is high indicating a turbulator geometry modification is needed for the lower entropy generation rates. Moreover, the results of the artificial neural network model showed the high accuracy of the introduced correlation for the estimation of the total entropy generation rate in terms of Re and H.

Estimation of heart rate and respiratory rate by monitoring cardiopulmonary signals with flexible sensor.

Monitoring of cardiopulmonary signals plays an important role in many clinical applications. A portable magnetic induction cardiopulmonary signal monitoring system with the flexible sensor of double micro-coils is presented in this paper. The detection of cardiopulmonary signals is realized with double micro-coils. The proposed system is safe, non-invasive, simple, and portable compared with traditional direct contact methods. The Hilbert-Huang transform (HHT) based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is applied to cardiopulmonary signal processing, decomposing cardiopulmonary signal effectively. The sensor to monitor respiration rate and heart rate is validated and demonstrated with healthy volunteers. The root mean squared errors (RMSE) of heart rate, respiration rate under deep breathing and normal breathing are 3.8 beats/min, 0.61 times/min, and 0.98 times/min respectively. The flexible sensor of double micro-coils has little influence on the measurement results at the bending curvature of 33.9 m-1. Therefore, a suggested solution for monitoring and decomposition of cardiopulmonary signals is easy-to-use, and quick, which can be applied as a respected analytical device on mobile occasions in this study.

Factors affecting diffusion of polar organic compounds in agarose hydrogel applied to control mass transfer in passive samplers.

Diffusive hydrogel-based passive sampler (HPS) based on diffusive gradients in thin films (DGT) is designed for monitoring polar organic contaminants in the aquatic environment. DGT technique controls the compound's overall uptake rate by adding a hydrogel layer of known thickness, which minimizes the importance of the resistive water boundary layer in the compound uptake process. In this work, we investigated several factors which may influence the diffusion of a range of aquatic contaminants in 1.5% agarose hydrogel. Diffusion in hydrogel was tested using the sheet stacking method. We demonstrated that a thin nylon netting incorporated into the diffusive hydrogel for mechanical strengthening does not significantly affect the diffusion of 11 perfluoroalkyl compounds. Further, we investigated the effect of pH in the range from 3 to 11 on the diffusion of a range of 39 aromatic amines (AAs)-36 aromatic, 2 aliphatic, and azobenzene in hydrogel. AAs were chosen as representatives of compounds with pH-dependent dissociation in water. Analysis of variance showed no significant difference in meandiffusion coefficient log D value at five pH values. The demonstration that the diffusion coefficient D and thus the sampling rate Rs are independent on pH simplifies the interpretation of data from field studies because we can neglect the influence of pH on the Rs. log D values (m2 s-1) of tested AAs ranged from to - 9.77 for 3,3'-dimethylbenzidine to - 9.19 for azobenzene. A negative correlation of log D with molar mass (log M) and molecular volume (log Vm) was observed (R = - 0.57 and - 0.56, respectively). The diffusion coefficient presents a critical parameter for the sampling rate estimation of HPS. Theoretical sampling rates Rs of AAs were calculated for a HPS using the average D values. TheoreticalRs values calculated for AAs at 22°C ranged from 29 mL day-1 for 3,3'-dimethylbenzidine to 106 mL day-1 for 2-aminopyridine. Our calculated values of Rs are in the same range as those already published for a range of low-molecular polar organic contaminants, which supports the possibility of deriving sampler performance parameters in the field from laboratory-derived diffusivity of analytes in hydrogel.

Revisiting incidence rates comparison under right censorship.

Data description is the first step for understanding the nature of the problem at hand. Usually, it is a simple task that does not require any particular assumption. However, the interpretation of the used descriptive measures can be a source of confusion and misunderstanding. The incidence rate is the quotient between the number of observed events and the sum of time that the studied population was at risk of having this event (person-time). Despite this apparently simple definition, its interpretation is not free of complexity. In this piece of research, we revisit the incidence rate estimator under right-censorship. We analyze the effect that the censoring time distribution can have on the observed results, and its relevance in the comparison of two or more incidence rates. We propose a solution for limiting the impact that the data collection process can have on the results of the hypothesis testing. We explore the finite-sample behavior of the considered estimators from Monte Carlo simulations. Two examples based on synthetic data illustrate the considered problem. The R code and data used are provided as Supplementary Material.

An Improved Model of Single-Event Transients Based on Effective Space Charge for Metal-Oxide-Semiconductor Field-Effect Transistor.

In this paper, a single-event transient model based on the effective space charge for MOSFETs is proposed. The physical process of deposited and moving charges is analyzed in detail. The influence of deposited charges on the electric field in the depletion region is investigated. The electric field decreases in a short time period due to the neutralization of the space charge. After that, the electric field increases first and then decreases when the deposited charge is moved out. The movement of the deposited charge in the body mainly occurs through ambipolar diffusion because of its high-density electrons and holes. The derivation of the variation in electric field in the depletion region is modeled in the physical process according to the analysis. In combination with the ambipolar diffusion model of excessive charge in the body, a physics-based model is built to describe the current pulse in the drain terminal. The proposed model takes into account the influence of multiple factors, like linear-energy transfer (LET), drain bias, and the doping concentration of the well. The model results are validated with the simulation results from TCAD. Through calculation, the root-mean-square error (RMSE) between the simulation and model is less than 3.7 × 10-4, which means that the model matches well with the TCAD results. Moreover, a CMOS inverter is simulated using TCAD and SPICE to validate the applicability of the proposed model in a circuit-level simulation. The proposed model captures the variation in net voltage in the inverter. The simulation result obviously shows the current plateau effect, while the relative error of the pulse width is 23.5%, much better than that in the classic model. In comparison with the classic model, the proposed model provides an RMSE of 7.59 × 10-5 for the output current curve and an RMSE of 0.158 for the output voltage curve, which are significantly better than those of the classic model. In the meantime, the proposed model does not produce extra simulation time compared with the classic double exponential model. So, the model has potential for application to flow estimation of the soft error rate (SER) at the circuit level to improve the accuracy of the results.

Modelling faecal microbe dynamics within stormwater constructed wetlands

Modelling faecal microbe levels is performed widely in natural and wastewater wetlands, yet these predictions can be challening due to highly stochastic storm events. In our study, a coupled hydrodynamic and microorganism model was developed and tested to predict the long-term faecal microbial removal in stormwater constructed wetlands. The microorganism model simulates the fate and transport of the faecal indicator organism Escherichia coli (E. coli), resolving advection-dispersion, sedimentation, resuspension and die-off based on temperature and UV exposure. The model was tested using a two-year monitoring dataset collected from Troups Creek wetland, a multiple-inflow stormwater wetland in Melbourne, Australia. The model parameter values applied in the coupled model were based on a mixture of site-specific data and values obtained from literature. The only adjusted parameter in our microorganism model was the die-off rate in dark conditions in the stormwater wetlands. An urban stormwater microorganism model, MOPUS, was used to generate continuous catchment E. coli loading rates as input to the wetland. The hydrodynamic model was evaluated using flow rate monitored at the outlet weir, achieving Nash- Sutcliffe Efficiency (E) values of 0.86 over the two-year monitoring period. The E. coli model was tested using outflow E. coli concentration data and achieved an overall E of 0.37. The performance of the microbial model was variable across the 22 monitored events, with E ranging from <0 to 0.8. Sensitivity tests were performed to evaluate the model outputs and the results indicated that (a) the importance of collecting high-quality data for stormwater inputs into wetlands and (b) the importance of accurate estimation of the die-off rate in wetland microbial removal models. Our research showed that this model can be used to help design and rectify stormwater constructed wetlands for better faecal microbial removal, vegetation maintenance and support future real-time decision-making.

Application of DCF Model in Enterprise Valuation

The home appliances industry is an important manufacturing industry that reflects the consumption level of Chinese residents. Midea Group is the leading enterprise in the household appliances industry and one of the enterprises with high brand value in China. For Midea Group in the home appliance industry, this paper will apply the DCF model for enterprise valuation. This paper mainly uses the financial information of Midea Group and the discounted cash flow model for enterprise valuation. Then, the advantages and disadvantages of the DCF valuation model are analyzed through practical cases, and the overall valuation process is summarized. The company value of Media that valued by the DCF model is 384,922.89 million RMB. The analysis results show that the DCF model can better reflect the status quo of enterprise value, but in the process of DCF valuation model, it is not easy to predict the accurate amount of future cash flow. It also has limitations in industry and product selection, and its estimation of the risk rate is not accurate enough.

Research on multi-source remote sensing image registration technology based on Baker mapping

ABSTRACT To address the issues of inaccurate estimation of registration parameters and high mismatch rate in feature based remote sensing image registration, a registration method based on global feature triangle similarity is proposed. This method utilizes the similarity principle of feature triangles to evaluate the global geometric similarity of matching feature points to eliminate mismatched points. In addition, due to the sensitivity of phase information in the frequency domain to spatial transformations and structural differences, as well as its robustness to lighting and noise, a phase structure consistency measurement method is proposed for developing feature point position adjustment strategies. The results indicate that the registration method proposed by the research institute achieved the lowest RMSE with a size of 1.51. In terms of IRMSE indicators, compared to the RANSAC measurement model, the PH SSIM measurement model has a mean decrease of 0.253. This indicates that the improved registration model proposed in the study has advantages in improving registration accuracy. The innovation of this study lies in constructing a matching feature point evaluation model to eliminate mismatched points, and proposing a remote sensing image registration method based on mismatch point removal and feature point position adjustment.

Abstract 16967: Effect of Catheter Ablation of Persistent Atrial Fibrillation on Surface Atrial ECG Dominant Frequency

Background: There are no standard techniques to track effects of catheter ablation (CA) of persistent atrial fibrillation (PeAF). The Atrial ECG (A-ECG) derived from the standard ECG provides the atrial dominant frequency (DF), an estimation of atrial rate. Research Question: Does CA for PeAF diminish A-ECG DF? Aims: To evaluate change in A-ECG peak DF pre- and post-CA. Methods: We obtained 1-minute epochs of surface ECG pre- and post-CA in 32 patients (age 63±9 years; 71% males) undergoing CA for PeAF. A-ECG was derived by QRST subtraction and independent component analysis filtering, and divided into overlapping10-second windows, each subjected to Fast Fourier Transform. DF was calculated for each lead as the average DF for all 10-sec segments. Peak A-ECG DF was assessed by regional lead group and among all leads. 10 patients were excluded for significant artifact. Of the 22 analyzed patients, all had pulmonary vein isolation and 3 had posterior wall isolation. Two-year outcomes were available in 20 patients (13 were free from recurrent AF). Results: The figure shows the change in the time-frequency plot (left panel) of DF for one subject and the shift in the spectra (right panel) with CA. A-ECG peak DF was significantly lower post- versus pre-CA: 5.96±0.63 vs 6.16±0.64 Hz, p=0.0009. By lead group, peak DFs were all lower post CA - Anterior (V1-3): 5.94±0.62 vs 6.13±0.64 Hz, p=0.0015; Inferior (II, III, aVF): 5.82±0.63 vs 6.01±0.66 Hz, p=0.0040; Lateral (I, aVL, V5-6): 5.82±0.64 vs 5.99±0.63 Hz, p=0.0015. In this small cohort, there was no significant difference in change of peak DF in those free from AF versus with recurrent AF (-2.4±4.3% vs -4.6±3.7%, p=0.26). Conclusion: The A-ECG provides physiologic information of activation rate in PeAF, but despite current, advanced signal processing techniques is analyzable in only 69% of patients. CA results in a significant reduction in DF. Clinical implications of these CA induced changes require further study.

CHARACTERIZATION AND SCREENING PARAMETERS OF SPRAY FILM-FORMING SYSTEMS: A COMPREHENSIVE STUDY ON DOSAGE FORMS AND QUALITY INDICATORS

Objective: The objective of this study is to present the main screening parameters for the development of Spray Film-Forming Systems (SFFSs) using the design space. The focus is on characterizing the different phase states of SFFSs during application and establishing appropriate methods for determining the range of parameters. Methods: In this study, various methods were used to determine the range of SFFS parameters. These include contact angle determination, pH test, viscosity measurement, drying rate estimation, spray pattern determination, tensile strength test, and washability. The methods used were evaluated and found to be effective in assessing the quality parameters of liquid concentrates, aerosols, and films of commercially available SFFS samples. Results: Three states (liquid, aerosol, and solid) of commercially available SPSFs were evaluated using the techniques mentioned above. The applicability of the techniques and variability was discussed in comparison with similar studies. The results showed that the mean pH ranged from 5.43±0.02 to 6.63±0.05, the bioadhesion of liquid concentrates was in a narrow range of 4.49±0.52, the highest index of dynamic viscosity was 0.33±0.04, values of the spray pattern ranged from 6.19±1.97 to 17.46±2.72 cm2, bioadhesion values of the films ranged from 3.87 to 4.06 N, average values of film formation time were in the range of 65.55±12.65) s. 3 of the 4 samples had resistance to skin cracking, the tensile load of the commercial SFFS films varied from 2.91±0.3 to 5.11±0.65 N, and the tensile strength from 1.07±0.11 to 1.20±0.3 mPa. All films were not washed off with water. Conclusion: The findings of this study demonstrate the successful application of tested methods in determining the range of parameters for SFFSs. The established values for indicators of liquid concentrates can serve as a basis for the further development of SFFSs. Overall, this research contributes to the understanding and standardization of Spray Film-Forming Systems for wounds, enabling their effective development and application in local skin treatments.

Local false discovery rate estimation with competition-based procedures for variable selection.

Multiple hypothesis testing has been widely applied to problems dealing with high-dimensional data, for example, the selection of important variables or features from a large number of candidates while controlling the error rate. The most prevailing measure of error rate used in multiple hypothesis testing is the false discovery rate (FDR). In recent years, the local false discovery rate (fdr) has drawn much attention, due to its advantage of accessing the confidence of individual hypotheses. However, most methods estimate fdr through -values or statistics with known null distributions, which are sometimes unavailable or unreliable. Adopting the innovative methodology of competition-based procedures, for example, the knockoff filter, this paper proposes a new approach, named TDfdr, to fdr estimation, which is free of -values or known null distributions. Extensive simulation studies demonstrate that TDfdr can accurately estimate the fdr with two competition-based procedures. We applied the TDfdr method to two real biomedical tasks. One is to identify significantly differentially expressed proteins related to the COVID-19 disease, and the other is to detect mutations in the genotypes of HIV-1 that are associated with drug resistance. Higher discovery power was observed compared to existing popular methods.

Experimental Estimation of Heat Release Rate of Burning Luggage

Experimental Estimation of Heat Release Rate of Burning Luggage

A fluvial record of late Quaternary climate changes and tectonic uplift along the Marche Piedmont Zone of the Apennines: New insights from the Tesino River (Italy)

Fluvial terraces are a pre-eminent continental record of climate changes and tectonics. Although the use of fill terraces for incision rate derivation is complicated due to their cyclical nature relative to strath terraces, they remain a relatively complete record of incision and deposition, thus allowing one to derive interpretations about both tectonics and climate. The Adriatic piedmont of the Apennines (central Italy) offers a well-preserved staircase of such terraces, caused by the cyclical alternation of fluvial aggradation and incision over the Middle and Late Pleistocene in response to a combination of low-rate tectonic uplift and climate changes. Although the staircase has been already widely described with examples from several valleys of the Adriatic Piedmont, its geochronological constraints are limited and must be enhanced to extract reliable climatic and tectonic signals from terrace deposits—especially for the older terrace levels.This research provides new Optically Stimulated Luminescence (OSL) data on the terrace chronology in combination with new semi-automatically extracted data on the altimetric and along-valley terrace distributions, as well as the sedimentological characteristics of fill terraces within the Tesino River basin in the Marche piedmont zone of the Apennines. The semi-automatic extraction of the terrace tread allowed a preliminary level classification as a function of the terrace height above the modern channel thalweg. The results demonstrate that, within the slowly uplifting Adriatic piedmont of the Apennines, the main phases of fluvial aggradation occurred during cold and full-glacial conditions followed by river incision and floodplain-channel abandonment during warmer periods. This finding confirms previous results from the last fluvial aggradation-incision cycle (Late Pleistocene). The results also show that the same formation mechanism is valid for the older (Middle Pleistocene) terraces. Indeed, this study provides new geochronological constraints for the regional-scale paradigm of cyclical formation and development of Quaternary fill terrace staircases along this sector of the Apennines. The use of a dated fill terrace staircase allowed estimation of a Middle Pleistocene long-term bedrock incision rate ranging from 0.3 to 0.5 mm yr−1 in agreement with previous studies in the central-northern sector of the Adriatic Apennines. The resulting uplift rate supports the presence of differently uplifted blocks due to the fragmentation of the peri-Adriatic region caused by the activity of left-lateral faults.

Machine learning framework for Inter-Beat Interval estimation using wearable Photoplethysmography sensors

Accurate estimation of Heart Rate (HR) is crucial for various health and fitness tracking applications in wearable devices. Among the existing techniques, those based on Photoplethysmography (PPG) signals have been extensively explored for continuous HR monitoring. In this paper, we introduce a new framework that utilizes machine learning methods to estimate Inter-Beat Interval (IBI) from wrist PPG signals. The primary objective of the proposed methods is to enhance the accuracy of IBI estimates while ensuring their feasibility for wearable devices, considering typical computational power, and memory constraints. This is achieved through two combined approaches. The first method involves optimizing a set of parameters associated with the interpolation of the systolic peaks. During the training stage of this method, we optimize the weights applied to the neighboring samples of the systolic peaks while minimizing the error between the fine-tuned peak positions and their corresponding ground truth. The second method is related to a supervised machine learning approach that handles the R-peak detection as a classification task. This allows us to accurately detect systolic peaks in PPG signals by classifying candidate peaks as true or false systolic peaks. To evaluate the effectiveness of our proposed methods, we conducted experiments on a dataset collected and carefully organized to this end. It consists of PPG and Electrocardiogram (ECG) signals obtained from 46 volunteers, including individuals with normal sinus rhythm, atrial fibrillation, and other non-specified cardiac arrhythmias. Comparing our framework with other state-of-the-art methods, we observed excellent performance, with lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) in IBI estimation. The proposed approach also achieved higher levels of Precision and Recall in terms of the detection of systolic peaks.

C-CAR039, a Novel Anti-CD20/CD19 Bi-Specific CAR T-Cell Therapy Shows Deep and Durable Clinical Benefits in Patients with Relapsed or Refractory (r/r) B-Cell Non-Hodgkin Lymphoma (B-NHL) in Long Term Follow up

Background: We previously reported that C-CAR039, an autologous anti-CD20/CD19 bispecific chimeric antigen receptor (CAR) T-cell therapy, demonstrated a favorable safety profile and promising efficacy in patients (pts) with r/r B-NHL. Of the initial 28 pts treated with C-CAR039 with a median of 3 prior lines of therapy. Only 1 patient experienced grade ≥3 cytokine release syndrome (CRS), and no patient reported grade ≥2 immune effector cell-associated neurotoxicity syndrome (ICANS). The overall response rate (ORR) was at 92.6%, with 85.2% complete response (CR). After a median follow-up of 7 months, 74.1% of pts remained in CR, and the Kaplan-Meier (KM) estimation of progression-free survival (PFS) at 6 months was 83.2%. (Liang et al. ASCO 2021. #2507). Here we present the updated results to include more pts (48 pts) and a longer duration of follow-up (median 23.9 months). Methods: This is an open-label, dose escalation and expansion investigator-initiated trial (IIT) of C-CAR039. This trial was conducted at 4 sites to determine the safety and efficacy of C-CAR039 in pts with r/r B-NHL. Pts with r/r diffuse large B cell lymphoma (DLBCL), primary mediastinal large B cell lymphoma (PMBCL), follicular lymphoma (FL) or mantle cell lymphoma (MCL) were enrolled and received a single C-CAR039 infusion at a dose of 1.0-5.0x10 6 CAR-T cells/kg after a 3-day conditioning chemotherapy. The primary objective was to assess the safety and tolerability. CRS and ICANS were graded according to ASTCT 2019 criteria. The secondary objectives were to evaluate C-CAR039 efficacy and pharmacokinetics. Response was assessed per Lugano 2014 criteria. Results: Between Nov 5, 2019, and Jan 11, 2022, 48 pts received C-CAR039 manufactured using Miltenyi Biotec CliniMACS Prodigy® System. Of the 48 pts, 44 pts had large B-Cell Lymphoma (LBCL) (DLBCL, n = 37; PMBCL, n = 3; tFL, n=4), 3 pts had FL and 1 patient had MCL. The median age was 55 (range, 25-71) years, and 11 (22.9%) pts were ≥ 65 years. Thirty-six (75%) pts were in Ann Arbor Stage III/IV with 3 median prior lines of therapy (range, 1-7). All pts received anti-CD20 antibody and alkylating agents. Eight (16.7%) pts had prior ASCT, 32 (66.7%) pts were refractory to their last treatment, and 22 (45.8%) pts never achieved CR to their prior therapies. Prior to C-CAR039 infusion, 12 (25%) pts received bridging therapy. As of Jan 15, 2023, 45 pts (93.8%) experienced CRS, of which 44 (91.7%) pts reported grade 1 or 2, only 1 (2.1%) patient experienced grade 3 CRS. Median time to CRS onset was 3 days (range, 1-12), with median duration of 5 days (range, 2-78). Three pts had ICANS at a dose of 5.0x10 6 CAR-T cells/kg, of which 2 were grade 1 and 1 was grade 2. The median time to onset of ICANS was 6 days (range, 5-29), with a median duration of 12 days (range, 3-53). All CRS and ICANS were resolved. Grade ≥3 neutropenia, anemia, thrombocytopenia and infection were reported in 83.3%, 14.6%, 27.1% and 10.4% of pts, respectively. Second primary malignancy after C-CAR039 infusion were observed in 3 pts; 2 acute myeloid leukemia (AML) occurred at 2 and 10 months, and 1 Epstein-Barr virus-positive cytotoxic T-cell lymphoma was at 8 months, the tumor biopsy was tested with qPCR and CAR transgene was negative and none were related to C-CAR039. Twelve deaths occurred, 9 due to disease progression, 2 due to AE of AML, and 1 due to unknown cause. Of the 48 pts, 47 pts were evaluable for efficacy (1 patient with DLBCL had no measurable disease at baseline). The ORR and CR rate among evaluable pts were 91.5% and 85.1% respectively. Median time to first response and CR was 1.0 month (range, 0.9-1.9) and 1.1 month (range, 0.9-8.9), respectively. Of the 43 LBCL pts, the ORR was 90.7%, with 86.0% CR. Median DOR, PFS and OS were not reached. The KM estimation of PFS and OS rate at 24 months was 66.0% (95%CI 53.2%-81.9%) and 77.9% (95% CI, 66.6%-91.1%) respectively. C-CAR039 showed cellular kinetic profile consistent with commercial CAR-T therapies. In 48 evaluable pts, the median T max was 11.5 day (range, 7-31), the median C max was 139,416 copies/g gDNA (range, 708-962,445), and the median AUC 0-28day was 1,513,442 copies/ug∙day (range, 3,818-11,594,912.5). Conclusions: At a longer median follow-up of 23.9 months, C-CAR039 demonstrated a favorable safety profile with deep and durable response in pts with r/r B-NHL, especially in LBCL pts.

Urban Heat Variation and Temperature Lapse Rate in the Kathmandu Valley

The rate of urbanization growth has accelerated and made urban areas comparatively warmer than surroundings which are the main issues of urban heat worldwide. The Kathmandu Valley is one of the million plus cities with the fastest rate of urbanization and consequent extreme heat. In this study, urban heat was analyzed using both in-situ and satellite-based observation and estimated temperature lapse rate. The Mann Kendell test, Sen’s slope, raster image analysis and lapse rate estimation methods were used. The results showed that average temperature difference in between urban core and surrounding was 4.07°C from 1990 to 2020. Likewise, the summer day temperature in Putalisadak was 8.8°C higher than the Nagarkot. The maximum temperature has increased in all stations where Godavari station has increased significantly (0.073°Cyr−1, p&lt;0.0001). During all seasons, the daytime temperature is higher than the nighttime temperature. The maximum 32.86°C daytime temperature was recorded on August 4, 1pm and the minimum temperature was 3.67°C on Jan 20, 6am, 2020 at the city core. Similarly, the highest temperature was recorded at 31°C in Bagbazar and 33°C in Patan on July 10 and July 11, 2022 respectively when the humidity was lower. Satellite-based observation also shows that the urban heat scenario of the Kathmandu Valley was higher in the urban core which was ranges from 21.06 to 26.09 during 2000-2020. The temperature of the city has increased. However, temperature lapse rate in response to Nagarkot (reference station) is normal i.e decreased temperature in response to increased height. The higher lapse rate is generally found in the Godavari and lower was observed in the Machhegaoun. Overall, the Kathmandu Valley is getting more warmer compared to the surroundings. This comprehensive study is useful to explore the understanding of urban heat islands and temperature lapse rate in the major cities in compared to the surroundings in Nepal.