LiDARPheno – A Low-Cost LiDAR-Based 3D Scanning System for Leaf Morphological Trait Extraction

The ever-growing world population brings the challenge for food security in the current world. The gene modification tools have opened a new era for fast-paced research on new crop identification and development. However, the bottleneck in the plant phenotyping technology restricts the alignment in geno–pheno development as phenotyping is the key for the identification of potential crop for improved yield and resistance to the changing environment. Various attempts to making the plant phenotyping a “high-throughput” have been made while utilizing the existing sensors and technology. However, the demand for ‘good’ phenotypic information for linkage to the genome in understanding the gene-environment interactions is still a bottleneck in the plant phenotyping technologies. Moreover, the available technologies and instruments are inaccessible, expensive, and sometimes bulky. This work attempts to address some of the critical problems, such as exploration and development of a low-cost LiDAR-based platform for phenotyping the plants in-lab and in-field. A low-cost LiDAR-based system design, LiDARPheno, is introduced in this work to assess the feasibility of the inexpensive LiDAR sensor in the leaf trait (length, width, and area) extraction. A detailed design of the LiDARPheno, based on low-cost and off-the-shelf components and modules, is presented. Moreover, the design of the firmware to control the hardware setup of the system and the user-level python-based script for data acquisition is proposed. The software part of the system utilizes the publicly available libraries and Application Programming Interfaces (APIs), making it easy to implement the system by a non-technical user. The LiDAR data analysis methods are presented, and algorithms for processing the data and extracting the leaf traits are developed. The processing includes conversion, cleaning/filtering, segmentation and trait extraction from the LiDAR data. Experiments on indoor plants and canola plants were performed for the development and validation of the methods for estimation of the leaf traits. The results of the LiDARPheno based trait extraction are compared with the SICK LMS400 (a commercial 2D LiDAR) to assess the performance of the developed system

Mathematical modelling and control of the evolution of dynamic systems interacting with medium

The article proposes a new method of mathematical modeling evolutional systems interacting with medium. A cutting process or tribo-space formed in the contact area of two conjugate mechanical subsystems is considered as medium. The features of the medium depend not only on state coordinates of systems but also on trajectories. It is obtained that the parameters of the medium are performed as integral operators of equations like Volterra equations of 2nd type. The problems of control of evolutional systems are being analyzed

Accumulation and distribution of zinc in the leaves and roots of the hyperaccumulator Noccaea caerulescens

Understanding the uptake mechanisms of heavy metals by hyperaccumulators is necessary for improving phytoextraction options to reduce metal toxicities in contaminated soils. In this study, the capacity of Zn uptake by the hyperaccumulator Noccaea caerulescens was investigated and compared to the non-hyperaccumulator Thlaspi arvense. The plants were grown under hydroponic conditions in a glasshouse. The distribution of Zn in the roots and leaves of these species was investigated by scanning electron microscopy with energy-dispersive X-ray analysis. Compared with the control with no Zn added, it was shown that prolonged Zn treatments decreased the biomass of both N. caerulescens and T. arvense. Since N. caerulescens requires Zn for growth, no Zn toxicity symptoms were observed, even when the Zn concentration in shoots reached 2.5% dry mass. T. arvense showed serious Zn toxicity only after two weeks of Zn treatment. Zn uptake by N. caerulescens was mainly translocated to the leaves while almost all of the Zn taken-up by T. arvense was retained in the roots. In N. caerulescens, increasing concentration of Zn in the supply decreased Ca and P concentrations in the shoots by up to 50 and 35%, respectively. Zn-containing crystals were abundant in both the upper and lower epidermal cells of the leaves and in the cortex of the roots during the later growth phase. Co-localization of Ca and Zn, P and S were found in leaf and root tissues. The results suggest that Zn-rich crystals with an abundance of the Zn ligand in the roots and shoots, and co-localization and interaction between Zn and other ions, may have functional significance with respect to conferring particular attributes to N. caerulescens that are not present in the non-hyperaccumulator counterpart. An understanding of these species-specific differences has relevance from the perspective of offering some insight into how particular species could contribute to a strategy for the detoxification of Zn-contaminated sites

Simple Transferability Estimation for Regression Tasks

We consider transferability estimation, the problem of estimating how well deep learning models transfer from a source to a target task. We focus on regression tasks, which received little previous attention, and propose two simple and computationally efficient approaches that estimate transferability based on the negative regularized mean squared error of a linear regression model. We prove novel theoretical results connecting our approaches to the actual transferability of the optimal target models obtained from the transfer learning process. Despite their simplicity, our approaches significantly outperform existing state-of-the-art regression transferability estimators in both accuracy and efficiency. On two large-scale keypoint regression benchmarks, our approaches yield 12% to 36% better results on average while being at least 27% faster than previous state-of-the-art methods.Comment: Paper published at The 39th Conference on Uncertainty in Artificial Intelligence (UAI) 202

Assessment of seasonal winter temperature forecast errors in the regcm model over northern Vietnam

This study verified the seasonal six-month forecasts for winter temperatures for northern Vietnam in 1998–2018 using a regional climate model (RegCM4) with the boundary conditions of the climate forecast system Version 2 (CFSv2) from the National Centers for Environmental Prediction (NCEP). First, different physical schemes (land-surface process, cumulus, and radiation parameterizations) in RegCM4 were applied to generate 12 single forecasts. Second, the simple ensemble forecasts were generated through the combinations of those different physical formulations. Three subclimate regions (R1, R2, R3) of northern Vietnam were separately tested with surface observations and a reanalysis dataset (Japanese 55-year reanalysis (JRA55)). The highest sensitivity to the mean monthly temperature forecasts was shown by the land-surface parameterizations (the biosphere−atmosphere transfer scheme (BATS) and community land model version 4.5 (CLM)). The BATS forecast groups tended to provide forecasts with lower temperatures than the actual observations, while the CLM forecast groups tended to overestimate the temperatures. The forecast errors from single forecasts could be clearly reduced with ensemble mean forecasts, but ensemble spreads were less than those root-mean-square errors (RMSEs). This indicated that the ensemble forecast was underdispersed and that the direct forecast from RegCM4 needed more postprocessing

Incommensurate antiferromagnetic order in weakly frustrated two-dimensional van der Waals insulator CrPSe3_3

Although the magnetic order is suppressed by a strong magnetic frustration, it is maintained but appears in complex order forms such as a cycloid or spin density wave in weakly frustrated systems. Herein, we report a weakly magnetic-frustrated two-dimensional van der Waals material CrPSe$_3$. Polycrystalline CrPSe$_3$ was synthesized at an optimized temperature of 700$^\circ$C to avoid the formation of any secondary phases (e.g., Cr$_2$Se$_3$). The antiferromagnetic transition appeared at $T_N\sim 126$ K with a large Curie-Weiss temperature $T_{\rm CW} \sim -371$ via magnetic susceptibility measurements, indicating weak frustration in CrPSe$_3$ with a frustration factor $f (|T_{\rm CW}|/T_N) \sim 3$. Evidently, the formation of long-range incommensurate spin-density wave antiferromagnetic order with the propagation vector $k = (0, 0.04, 0)$ was revealed by neutron diffraction measurements at low temperatures (below 120K). The monoclinic crystal structure of C2/m symmetry is preserved over the studied temperature range down to 20K, as confirmed by Raman spectroscopy measurements. Our findings on the spin density wave antiferromagnetic order in two-dimensional (2D) magnetic materials, not previously observed in the MPX$_3$ family, are expected to enrich the physics of magnetism at the 2D limit, thereby opening opportunities for their practical applications in spintronics and quantum devices.Comment: 23 pages, 4 figures, 2 table

20-Hydroxyecdysone from Dacrycarpus imbricatus bark inhibits the proliferation of acute myeloid leukemia cells

Abstract Objective To investigate the anti-proliferative effects of 20-hydroxyecdysone isolated from the bark of Dacrycarpus imbricatus (Blume) de Laub. Methods Column chromatography was used for isolation of compounds from plant material. The structure of the isolated compound was identified by mass spectrometry and nuclear magnetic resonance techniques, including HSQC, HMBC, NOE-difference experiments. The isolated compound was tested for its anti-proliferative activity in acute myeloid leukemia (AML) and OCI-AML cells. Results Compound 1 was isolated from the ethyl acetate fraction of Dacrycarpus imbricatus barks by column chromatography. Its chemical structure was identified as 20-hydroxyecdysone (20HE), a cholestane-type ecdysteroid, by a combination of mass spectrometry and nuclear magnetic resonance spectrometric analyses. Our goal was to test the anti-proliferative activity of 20HE using the OCI-AML cell line. 20HE significantly decreased OCI cell number at a concentration of 1 mg/mL, whereas lower concentrations were ineffective. Moreover, this decrease was due to partial blockage of the G 1 /S phase of the cell cycle, with a reduction of cells in the G 2 M phase, not due to increased apoptosis. Conclusions This indicates that 20HE significantly decreases the number of cells in the G 1 /S phase of the cell cycle in human AML cells. This is the first time that the anti-proliferative activity of 20HE against a human tumor cell line has been reported