Trap-assisted transition between Schottky emission and Fowler-Nordheim tunneling in the interfacial-memristor based on Bi2S3 nano-networks

For the usage of the memristors in functional circuits, a predictive physical model is of great importance. However, other than the developments of the memristive models accounting bulky effects, the achievements on simulating the interfacial memristance are still insufficient. Here we provide a physical model to describe the electrical switching of the memristive interface. It considers the trap-assisted transition between Schottky emission and Fowler-Nordheim tunneling, and successfully reproduces the memristive behaviors occurring on the interface between Bi2S3 nano-networks and F-doped SnO2. Such success not only allows us uncover several features of the memristive interface including the distribution nature of the traps, barrier height/thickness and so on, but also provides a foundation from which we can quantitatively simulate the real interfacial memristor

Novel Features of Canopy Height Distribution for Aboveground Biomass Estimation Using Machine Learning: A Case Study in Natural Secondary Forests

Identifying important factors (e.g., features and prediction models) for forest aboveground biomass (AGB) estimation can provide a vital reference for accurate AGB estimation. This study proposed a novel feature of the canopy height distribution (CHD), a function of canopy height, that is useful for describing canopy structure for AGB estimation of natural secondary forests (NSFs) by fitting a bimodal Gaussian function. Three machine learning models (Support Vector Regression (SVR), Random Forest (RF), and eXtreme Gradient Boosting (Xgboost)) and three deep learning models (One-dimensional Convolutional Neural Network (1D-CNN4), 1D Visual Geometry Group Network (1D-VGG16), and 1D Residual Network (1D-Resnet34)) were applied. A completely randomized design was utilized to investigate the effects of four feature sets (original CHD features, original LiDAR features, the proposed CHD features fitted by the bimodal Gaussian function, and the LiDAR features selected by the recursive feature elimination algorithm) and models on estimating the AGB of NSFs. Results revealed that the models were the most important factor for AGB estimation, followed by the features. The fitted CHD features significantly outperformed the other three feature sets in most cases. When employing the fitted CHD features, the 1D-Renset34 model demonstrates optimal performance (R2 = 0.80, RMSE = 9.58 Mg/ha, rRMSE = 0.09), surpassing not only other deep learning models (e.g.,1D-VGG16: R2 = 0.65, RMSE = 18.55 Mg/ha, rRMSE = 0.17) but also the best machine learning model (RF: R2 = 0.50, RMSE = 19.42 Mg/ha, rRMSE = 0.16). This study highlights the significant role of the new CHD features fitting a bimodal Gaussian function and the effects between the models and the CHD features, which provide the sound foundations for effective estimation of AGB in NSFs

Near-Infrared Spectroscopy as an Analytical Process Technology for the On-Line Quantification of Water Precipitation Processes during Danhong Injection

This paper used near-infrared (NIR) spectroscopy for the on-line quantitative monitoring of water precipitation during Danhong injection. For these NIR measurements, two fiber optic probes designed to transmit NIR radiation through a 2 mm flow cell were used to collect spectra in real-time. Partial least squares regression (PLSR) was developed as the preferred chemometrics quantitative analysis of the critical intermediate qualities: the danshensu (DSS, (R)-3, 4-dihydroxyphenyllactic acid), protocatechuic aldehyde (PA), rosmarinic acid (RA), and salvianolic acid B (SAB) concentrations. Optimized PLSR models were successfully built and used for on-line detecting of the concentrations of DSS, PA, RA, and SAB of water precipitation during Danhong injection. Besides, the information of DSS, PA, RA, and SAB concentrations would be instantly fed back to site technical personnel for control and adjustment timely. The verification experiments determined that the predicted values agreed with the actual homologic value

Which of Plot Size, Feature, and Prediction Model is More Important and Has Stronger Impacts on Estimating Aboveground Biomass?

The Unmanned Aerial Vehicle laser scanning (UAV-LiDAR) data (csv file) for five plot sizes: five plots for each plot size. Note: 004ha represents 0.04 ha; 006ha represents 0.06 ha;  009ha represents 0.09 ha; 016ha represents 0.16 ha; 025ha represents 0.25 ha.</p

Donor-derived Anti-CD19 CAR T cells GC007g for relapsed or refractory B-cell acute lymphoblastic leukemia after allogeneic HSCT: a phase 1 trialResearch in context

Summary: Background: Although chimeric antigen receptor-modified T cells (CAR T) cell therapy has been widely reported in improving the outcomes of B-cell acute lymphoblastic leukemia (B-ALL), less research about the feasibility and safety of donor-derived CAR T after allogeneic hematopoietic stem cell transplantation (allo-HSCT) was reported. Methods: This phase 1 clinical trial aims to evaluate safety and efficacy of donor-derived anti-CD19 CAR T cells (GC007g) in B-ALL patients who relapsed after allo-HSCT. This trial is registered with ClinicalTrials.gov, NCT04516551. Findings: Between 15 March 2021 and 19 May 2022, fifteen patients were screened, three patients were excluded due to withdraw of consent, donor's reason, and death, respectively. Patients received donor-derived CAR T cells infusions at 6 × 105/kg (n = 3) or 2 × 106/kg (n = 6) dose level. The median time from HSCT to relapse was 185 days (range, 81–2063). The median age of patients was 31 years (range 21–48). Seven patients (77.8%) had BCR-ABL fusion gene. CAR T cells expanded in vivo and the median time to reach Cmax was 9 days (range, 7–11). One patient had hyperbilirubinemia after GC007g infusion which was defined as a dose-limiting toxicity. All patients experienced CRS and hematological adverse events. Three patients had acute graft-versus-host-disease (grade I, n = 1; grade II, n = 1; grade IV, n = 1) and all resolved after treatment. They received CAR T cells from matched sister, haploidentical matched father and sisiter, respectively. At 28 days after infusion, all patients achieved complete remission with/without incomplete hematologic recovery (CRi/CR) with undetectable MRD. At a median follow-up of 475 days (range 322–732), seven patients remained in CR/CRi while two had CD19-negative relapse. The overall response rates (ORR) were 100% (9/9), 88.9% (8/9), and 75% (6/8) at 3 month, 6 month, and 12 month, respectively. The 1-year progression-free and overall survival were 77.8% and 85.7%, respectively. Interpretation: GC007g expanded and induced durable remission in patients with B-ALL relapsed after allo-HSCT, with manageable safety profiles. Funding: Gracell Biotechnologies Inc