Miracle-dz/UniFAR-FTUs huggingface dataset:
Context-Aware 3D Point Cloud Semantic Segmentation With Plane Guidance

Point cloud segmentation is fundamental in under- standing 3D environments. However, most existing methods usually perform poorly on identifying boundaries of touching objects and large surfaces of objects. Planes in a scene usually act as supporting surfaces to separate touching objects and provide geometry priors to group points on a large surface as shown in Fig. 1. Besides, planes can roughly represent the structure of a scene, and are more efficient to encode holistic scene contexts than large scale point clouds. In light of the above advantages, we advise a plane-assisted module, coined <italic>3D-PAM</italic>, to enhance semantic segmentation of touching objects and large surface objects. <italic>3D-PAM</italic> consists of a plane separation network (<italic>PS-Net</italic>) and a plane relation network (<italic>PR-Net</italic>). <italic>PS-Net</italic> focuses on learning features that can robustly separate touching objects, e.g., a chair on a floor, as well as capture plane-based geometry priors to group points on a large plane, e.g., points of a desk. <italic>PR-Net</italic> encodes mutual plane relations as a proxy of a scene structure to capture holistic contexts. <italic>3D-PAM</italic> is designed as a plug-and-play module so that it can be easily plugged into any off-the-shelf semantic segmentation network. Extensive experiments demonstrate that the method achieves large segmentation improvements on several backbones, and accomplishes superior results on most categories when using a RandLA-Net backbone (<inline-formula><tex-math notation="LaTeX">$11/13$</tex-math></inline-formula> categories on S3DIS dataset and <inline-formula><tex-math notation="LaTeX">$15/20$</tex-math></inline-formula> categories on ScanNetv2 dataset). The project is available at GitHub <uri>https://github.com/windmillknight/Context-Aware-3D-Point-Cloud-Semantic-Segmentation-With-Plane-Guidance</uri>
Genipa americana L. GEOGRAPHIC OCCURRENCE IN BRAZIL

Genipa americana is a well-recommended tree species for the restoration of degraded areas, and it is necessary to understand which soil and climate variables determine its occurrence and in which environments it would become better adapted. The objective of this work was to survey the occurrence of Genipa americana in Brazil and the edaphoclimatic and vegetation variables' influence on its distribution. For this, the survey was carried out using the NeoTropTree database, using 19 environmental variables for the study. The data were submitted to principal component analysis in RStudio, with the factoextra and ggplot2 packages. The main variables from this analysis were applied in the map elaboration with the ArcMap 10.5 program. In the geographic occurrence analysis of 3,916 site results for Brazil, the species G. americana was present in 20.9% of the sites. The predominant biome in the species occurrence in the country was the Amazon, concentrating 38.9% of the sites. Regarding environmental limits, it is clear that the lower the temperature, the lower the chance of the species occurrence. The species is well adapted to high temperatures, annual rainfall ranging from 1,000 to 2,500 mm, and low reliefs. With climate change imminent, it could be used to restore warm regions. However, sites currently dry or threatened with becoming more arid over the years are unsuitable for the species.
THE MERGER ENVIRONMENT OF THE WIDE ANGLE TAIL HOSTING CLUSTER A562

We present a Chandra X-ray observation and Very Large Array radio observations of the nearby (z = 0.11) galaxy cluster A562 and the wide angle tail (WAT) radio source 0647+693. The cluster displays signatures of an ongoing merger leading to the bending of the WAT source including an elongation of the X-ray surface brightness distribution along the line that bisects the WAT, an excess of displaced gas found between the radio lobes, and anisotropies within the intracluster medium projected temperature and abundance distributions. The most likely geometry of the ongoing interaction is a head-on merger occurring along the WAT bending axis. By combining observable properties of A562 and 0647+693 with common values for the conditions within merging clusters at the time of core crossing, we constrain the internal density (ρj = 0.001 ρICM) of the jets and plasma flow velocity within the lobes (vr = 0.02c–0.03c) of the WAT source.
Is it possible to reveal the lost siblings of the Sun

We present the results of our numerical experiments on stellar scattering in the Galactic disc under the influence of the perturbed Galactic gravitational field associated with spiral density waves. We show that the view according to which stars do not migrate far from their birthplace is, in general, incorrect. Despite close initial locations and the same velocities, after 4.6 Gyr the members of an open cluster are scattered over a very large portion of the Galactic disc. If we assume that the parental solar cluster had ∼103 stars, solar siblings are unlikely to be found within 100 pc of the Sun. They have a good chance of being found, however, if the cluster had ∼104 stars. We also demonstrate that unbound open clusters disperse in a short period of time under the influence of the spiral gravitational field. Their stars became part of the Galactic disc. We estimate typical times of cluster disruption in the radial and azimuthal directions and the corresponding diffusion coefficients.
PEMANFAATAN YOLOV4 UNTUK DETEKSI PELANGGARAN HELM DAN MASKER SERTA IDENTIFIKASI PELAT NOMOR MENGGUNAKAN TESSERACT-OCR

transfer dataset sejumlah 600 gambar menghasilkan 8 model, model dengan Mean Average Precision (mAP) tertinggi 93.38% dan F1-Score 0.77. model dengan F1-Score tertinggi 0.86 mAP 88.78%. disimpulkan model F1-Score pelatihan model Tesseract ABSTRACT The world is being hit by a pandemic that requires humans to wear masks when outdoors. In order to prevent the spread of the virus and ensure orderliness for motorcyclists, it is important for motorcyclists to wear helmets and masks at the same time. Therefore, a program was created that can detect helmet and mask violations and get the violator's plate number automatically. This study uses the YOLOv4 transfer learning method and utilizes Tesseract-OCR. YOLOv4 is able to detect helmets, masks, motorcycles and license plates in one image. Using a dataset of 600 images resulted in 8 models, the model with the highest Mean Average Precision (mAP) 93.38% and F1-Score 0.77. the model with the highest F1-Score of 0.86 with an mAP of 88.78%. It can be concluded that the model with the highest F1-Score is better at detecting and classifying objects. While training the Tesseract model helps improve the identification of number plate characters.
Heralded-qubit amplifiers for practical device-independent quantum key distribution

Device-independent quantum key distribution does not need a precise quantum mechanical model of employed devices to guarantee security. Despite its beauty, it is still a very challenging experimental task. We compare a recent proposal by Gisin et al. [Phys. Rev. Lett. 105, 070501 (2010)] to close the detection loophole problem with that of a simpler quantum relay based on entanglement swapping with linear optics. Our full-mode analysis for both schemes confirms that, in contrast to recent beliefs, the second scheme can indeed provide a positive key rate which is even considerably higher than that of the first alternative. The resulting key rates and required detection efficiencies of approximately 95% for both schemes, however, strongly depend on the underlying security proof.
Bioinformatics analysis of the clinical significance of HLA class II in breast cancer

Human leukocyte antigen (HLA) class II plays critical roles in antigen presentation and the initiation of immune responses. However, the correlation between the HLA class II gene expression level and the survival of patients with breast cancer is still under investigation. We analyzed microarray and RNA-Seq data of breast cancer from the cancer genome atlas (TCGA), genotype-tissue expression (GTEx) and Oncomine databases by using bioinformatics tools. The expression of the HLA-DQA1, HLA-DQA2, and HLA-DQB2 genes was significantly upregulated in breast cancer. Higher expression levels of HLA class II genes in breast cancer, especially HLA-DOB and HLA-DQB2, were significantly associated with better overall survival. Furthermore, the expression of HLA class II genes was more closely associated with survival in breast cancer than in other cancer types. CD48 coexpressed with both HLA-DOB and HLA-DQB2 was also positively associated with the overall survival of breast cancer patients. The results indicated that HLA class II and CD48 may enhance antitumor immunity, and their expression patterns may serve as potential prognostic biomarkers and therapeutic targets in breast cancer.
On the Performance of Cache-Free/Cache-Aided STBC-NOMA in Cognitive Hybrid Satellite-Terrestrial Networks

Future wireless networks pose several challenges such as high spectral efficiency, wide coverage, massive connectivity, low receiver complexity, etc. To this end, this letter investigates an overlay-based cognitive hybrid satellite-terrestrial network (CHSTN) combining non-orthogonal multiple access (NOMA) and conventional Alamouti space-time block coding (STBC) techniques. Herein, a decode-and-forward based secondary terrestrial network cooperates with a primary satellite network for dynamic spectrum access. Further, for reliable content delivery and low latency requirements, wireless caching is employed, whereby the secondary network can store the most popular contents of the primary network. Considering the relevant heterogeneous fading channel models and the NOMA-based imperfect successive interference cancellation, we examine the performance of CHSTN for the cache-free (CF) STBC-NOMA and the cache-aided (CA) STBC-NOMA schemes. We assess the outage probability expressions for primary and secondary networks and further, highlight the corresponding achievable diversity orders. Indicatively, the proposed CF/CA STBC-NOMA schemes for CHSTN perform significantly better than the benchmark standalone NOMA and OMA schemes.
Muti-Frame Point Cloud Feature Fusion Based on Attention Mechanisms for 3D Object Detection

Continuous frames of point-cloud-based object detection is a new research direction. Currently, most research studies fuse multi-frame point clouds using concatenation-based methods. The method aligns different frames by using information on GPS, IMU, etc. However, this fusion method can only align static objects and not moving objects. In this paper, we proposed a non-local-based multi-scale feature fusion method, which can handle both moving and static objects without GPS- and IMU-based registrations. Considering that non-local methods are resource-consuming, we proposed a novel simplified non-local block based on the sparsity of the point cloud. By filtering out empty units, memory consumption decreased by 99.93%. In addition, triple attention is adopted to enhance the key information on the object and suppresses background noise, further benefiting non-local-based feature fusion methods. Finally, we verify the method based on PointPillars and CenterPoint. Experimental results show that the mAP of the proposed method improved by 3.9% and 4.1% in mAP compared with concatenation-based fusion modules, PointPillars-2 and CenterPoint-2, respectively. In addition, the proposed network outperforms powerful 3D-VID by 1.2% in mAP.
Influence of the Accuracy of Chlorophyll-Retrieval Algorithms on the Estimation of Solar Radiation Absorbed in the Barents Sea

The aim of this work is to study the influence of errors on the accuracy of estimation of absorbed solar energy in the visible spectral range in the water column of the Barents Sea occurring due to the use of various satellite ocean color chlorophyll-retrieval algorithms. The estimates of absorbed energy are based on data obtained during field experiments conducted in various parts of the Barents Sea in June-August 2021, as well as on modeling results. A new regional algorithm for evaluation of chlorophyll concentration in the Barents Sea (B22) is presented as a data source. This algorithm provides more accurate estimates compared to the standard MODIS algorithm under conditions of coccolithophore bloom. Comparing of the results of hydro-optical modeling to the data of shipboard hydro-optical measurements made it possible to validate the obtained data and confirmed the correctness of the selected models. Furthermore, we calculate the parameters of underwater light fields and the absorbed thermal energy in the visible spectral range in the seawater column, showing that differences in the chlorophyll concentration due to the accuracy of satellite bio-optical algorithms (30–50%) have little effect on the vertical distribution of solar energy absorbed in the seawater column.
CRISPR-Cas: A continuously evolving technology

The discovery of the CRISPR/Cas microbial adaptive immune system and its ongoing development as a genome editing tool represents the work of many scientists around the world. The time line of CRISPR/Cas system shows that this technology is improving continuously to remove the demerits of preceding one with the aim of development of highly efficient, specific with low off target effect and ultimately transgene free technology in light of ethical and environmental issues related with transgenic technology. Initially, CRISPR/Cas9 was developed as method of choice as it provides targeted mutagenesis under in vivo condition and all the homeoalleles of a gene can be targeted in same plant, especially in case of polyploid species efficiently which is difficult through other existing technology. No residual or foreign gene insertion is required and modification is permanent. Now, CRISPR/Cpf1 has been developed as more potent, efficient and simpler than CRISPR/Cas9. Different forms of Cas enzymes provide new avenues for regulation of genomic component. In view of the present devastating COVID-19 disaster the scientists used this novel technology for detection of virus in humans at an early stage of infection thus saving human lives. The evolution of CRISPR/Cas technology, their advantages, apprehensions and solution, experimental design and updates of this technology is discussed in the present review.
Multimodal Cross-registration and Quantification of Metric Distortions in Whole Brain Histology of Marmoset using Diffeomorphic Mappings

Whole brain neuroanatomy using tera-voxel light-microscopic data sets is of much current interest. A fundamental problem in this field is the mapping of individual brain data sets to a reference space. Previous work has not rigorously quantified the distortions in brain geometry from in-vivo to ex-vivo brains due to the tissue processing, which will be important when computing properties such as local cell and process densities at the voxel level in creating reference brain maps. Further, existing approaches focus on registering uni-modal volumetric data; however, given the increasing interest in the marmoset model for neuroscience research, it is necessary to cross-register multi-modal data sets including MRIs and multiple histological series that can help address individual variations in brain architecture. Here we present a computational approach for same-subject multimodal MRI guided reconstruction of a histological series, jointly with diffeomorphic mapping to a reference atlas. We quantify the scale change during the different stages of histological processing of the brains using the Jacobian determinant of the diffeomorphic transformations involved. There are two major steps in the histology process with associated scale distortions (a) brain perfusion (b) histological sectioning and reassembly. By mapping the final image stacks to the ex-vivo post fixation MRI, we show that tape-transfer histology can be reassembled accurately into 3D volumes with a local scale change of 2.0 $\pm$ 0.4% per axis dimension. In contrast, the perfusion step, as assessed by mapping the in-vivo MRIs to the ex-vivo post fixation MRIs, shows a larger local scale change of 6.9 $\pm$ 2.1% per axis dimension. This is the first systematic quantification of the local metric distortions associated with whole-brain histological processing, and we expect that the results will generalize to other species.
Tamarix hispida NAC Transcription Factor ThNAC4 Confers Salt and Drought Stress Tolerance to Transgenic Tamarix and Arabidopsis

Salt and drought are considered two major abiotic stresses that have a significant impact on plants. Plant NAC (NAM, ATAF1/2, and CUC2) transcription factors (TFs) have been shown to play vital roles in plant development and responses to various abiotic stresses. ThNAC4, a NAC gene from Tamarix hispida involved in salt and osmotic stress tolerance, was identified and characterized in this study. According to a phylogenetic study, ThNAC4 is a member of NAC subfamily II. Subcellular localization analysis showed that ThNAC4 is located in the nucleus, and transcriptional activation experiments demonstrated that ThNAC4 is a transcriptional activator. Transgenic Arabidopsis plants overexpressing ThNAC4 exhibited improved salt and osmotic tolerance, as demonstrated by improved physiological traits. ThNAC4-overexpressing and ThNAC4-silenced T. hispida plants were generated using the transient transformation method and selected for gain- and loss-of-function analysis. The results showed that overexpression of ThNAC4 in transgenic Tamarix and Arabidopsis plants increased the activities of antioxidant enzymes (SOD, POD, and GST) and osmoprotectant (proline and trehalose) contents under stress conditions. These findings suggest that ThNAC4 plays an important physiological role in plant abiotic stress tolerance by increasing ROS scavenging ability and improving osmotic potential.
Radar Sensor-Based Estimation of Vehicle Orientation for Autonomous Driving

Automotive sensors are essential to autonomous driving, which performs various functions to perceive the surrounding environment. Among the various functions of the automotive sensors, the estimation of vehicle orientation is considered significant in responding to unpredictable situations in a dynamic driving environment. In this article, we propose a method of estimating the vehicle orientation using a cascaded multiple-input multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radar system. The radar signal is collected by varying the orientation angle of the vehicle, and the point cloud data corresponding to the vehicle are extracted through signal preprocessing. Because the processed point cloud data are distributed along the axis of vehicle orientation, the orientation angle can be estimated by applying regression algorithms. We used the principal component analysis (PCA), decision tree, and convolutional neural network (CNN) algorithms for regression and compared their performances. The comparison of various estimation methods showed that the proposed method of using the CNN framework can accurately estimate the orientation angle of a vehicle within a root mean square error (RMSE) of 4°.
Single Stage Single Switch Quadruple Output Power Supply for Electric Vehicle Applications

The article explains the single stage AC-DC switched mode isolated constant voltage four outputs product design approach. It works on primary sensing though magnetics and soft switching. The input voltage can change from extended universal input voltage range from 85V to 300V AC. The output voltage and current of outputs are 24V/1A, 12V/1A, 5V/0.5A, 3.3V/0.33A. The overall power output is up to 40W. The primary sensing helps low overall cost and circuit complexity. The input low voltage protection as well as overload protection is inbuilt in this powerful converter. The overall efficiency is more than 85% and power factor more than 0.95 at nominal input and full load. This power supply can be used for multi-output constant voltage requirement of electric vehicles, relay operations, constant voltage LED and other consumer electronics.
Galaxy clustering in the CFHTLS-Wide: the changing relationship between galaxies and haloes since z ~ 1.2

It has become increasingly apparent that studying how dark matter haloes are populated by galaxies can provide new insights into galaxy formation and evolution. In this paper, we present a detailed investigation of the changing relationship between galaxies and the dark matter haloes they inhabit from z similar to 1.2 to the present day. We do this by comparing precise galaxy clustering measurements over 133 deg(2) of the “Wide” component of the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) with predictions of an analytic halo occupation distribution (HOD) model where the number of galaxies in each halo depends only on the halo mass. Starting from a parent catalogue of similar to 3 x 10(6) galaxies at i(AB)' \textless 22.5 we use accurate photometric redshifts calibrated using similar to 10(4) spectroscopic redshifts to create a series of type-selected volume-limited samples covering 0.2 \textless z \textless 1.2. Our principal result, based on clustering measurements in these samples, is a robust determination of the luminosity-to-halo mass ratio and its dependence on redshift and galaxy type. For the full sample, this reaches a peak at low redshifts of M-h(peak) = 4.5 x 10(11) h(-1) M-circle dot and moves towards higher halo masses at higher redshifts. For redder galaxies the peak is at higher halo masses and does not evolve significantly over the entire redshift range of our survey. We also consider the evolution of bias, average halo mass and the fraction of satellites as a function of redshift and luminosity. Our observed growth of a factor of similar to 2 in satellite fraction between z similar to 1 and z similar to 0 is testament to the limited role that galaxy merging plays in galaxy evolution for similar to 10(12) h(-1) M-circle dot mass haloes at z \textless 1. Qualitatively, our observations are consistent with a picture in which red galaxies in massive haloes have already accumulated most of their stellar mass by z similar to 1 and subsequently undergo little evolution until the present day. The observed movement of the peak location for the full galaxy population is consistent with the bulk of star-formation activity migrating from higher mass haloes at high redshifts to lower mass haloes at lower redshifts.