In this paper, we designed an end-to-end spectral-spatial residual network (SSRN) that takes raw 3-D cubes as input data without feature engineering for hyperspectral image classification. In this ...network, the spectral and spatial residual blocks consecutively learn discriminative features from abundant spectral signatures and spatial contexts in hyperspectral imagery (HSI). The proposed SSRN is a supervised deep learning framework that alleviates the declining-accuracy phenomenon of other deep learning models. Specifically, the residual blocks connect every other 3-D convolutional layer through identity mapping, which facilitates the backpropagation of gradients. Furthermore, we impose batch normalization on every convolutional layer to regularize the learning process and improve the classification performance of trained models. Quantitative and qualitative results demonstrate that the SSRN achieved the state-of-the-art HSI classification accuracy in agricultural, rural-urban, and urban data sets: Indian Pines, Kennedy Space Center, and University of Pavia.
Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D LiDAR data has led to rapid development in the field of autonomous driving. However, automated processing ...uneven, unstructured, noisy, and massive 3-D point clouds are a challenging and tedious task. In this article, we provide a systematic review of existing compelling DL architectures applied in LiDAR point clouds, detailing for specific tasks in autonomous driving, such as segmentation, detection, and classification. Although several published research articles focus on specific topics in computer vision for autonomous vehicles, to date, no general survey on DL applied in LiDAR point clouds for autonomous vehicles exists. Thus, the goal of this article is to narrow the gap in this topic. More than 140 key contributions in the recent five years are summarized in this survey, including the milestone 3-D deep architectures, the remarkable DL applications in 3-D semantic segmentation, object detection, and classification; specific data sets, evaluation metrics, and the state-of-the-art performance. Finally, we conclude the remaining challenges and future researches.
The mobile laser scanning (MLS) technique has attracted considerable attention for providing high-density, high-accuracy, unstructured, three-dimensional (3D) geo-referenced point-cloud coverage of ...the road environment. Recently, there has been an increasing number of applications of MLS in the detection and extraction of urban objects. This paper presents a systematic review of existing MLS related literature. This paper consists of three parts. Part 1 presents a brief overview of the state-of-the-art commercial MLS systems. Part 2 provides a detailed analysis of on-road and off-road information inventory methods, including the detection and extraction of on-road objects (e.g., road surface, road markings, driving lines, and road crack) and off-road objects (e.g., pole-like objects and power lines). Part 3 presents a refined integrated analysis of challenges and future trends. Our review shows that MLS technology is well proven in urban object detection and extraction, since the improvement of hardware and software accelerate the efficiency and accuracy of data collection and processing. When compared to other review papers focusing on MLS applications, we review the state-of-the-art road object detection and extraction methods using MLS data and discuss their performance and applicability. The main contribution of this review demonstrates that the MLS systems are suitable for supporting road asset inventory, ITS-related applications, high-definition maps, and other highly accurate localization services.
Adeno-associated virus (AAV) is the leading vector in emerging treatments of inherited diseases. Higher transduction efficiencies and cellular specificity are required for broader clinical ...application, motivating investigations of virus–host molecular interactions during cell entry. High-throughput methods are identifying host proteins more comprehensively, with subsequent molecular studies revealing unanticipated complexity and serotype specificity. Cryogenic electron microscopy (cryo-EM) provides a path towards structural details of these sometimes heterogeneous virus–host complexes, and is poised to illuminate more fully the steps in entry. Here presented, is progress in understanding the distinct steps of glycan attachment, and receptor-mediated entry/trafficking. Comparison with structures of antibody complexes provides new insights on immune neutralization with implications for the design of improved gene therapy vectors.
High-resolution cryogenic electron microscopy (cryo-EM) structures detail adeno-associated virus (AAV) receptor protein binding interactions.AAV’s glycan 'primary receptors' are recharacterized as 'attachment factors'.AAV5-like viruses interact with a different domain of the receptor using a binding site that is distinct from that of other AAVs.The epitopes of many AAV-neutralizing antibodies overlap with receptor-binding sites on the capsid.Future structural focus will be on AAV receptor-independent pathways and additional steps in entry and trafficking.
Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as ...potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become increasingly popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road maintenance. However, current smartphone sensors operate at a low frequency, and undersampled sensor signals cause low detection accuracy. In this study, current approaches for using smartphones for road surface anomaly detection are reviewed and compared. In addition, further opportunities for research using smartphones in road surface anomaly detection are highlighted.
We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations and discovered ...putative tumor suppressor genes by determining homozygous deletions and loss of heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53, and DIS3 (particularly in nonhyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of nonmutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions.
•Deep sequencing reveals significant genetic events in multiple myeloma•Intratumor genetic heterogeneity is common in multiple myeloma•Recurrent mutations can occur either early or late in the evolution of a tumor•Genetic heterogeneity in cancer may limit effectiveness of targeted therapy
Intimate Lightning, by Dan Wylie, presents a detailed account and evaluation of Sydney Clouts’s poetry as phenomenologically driven: a poetry that invites readers to look inwards to the “speck and ...the fleck” of things in the natural world. At the same time, Wylie posits that Clouts is the finest poet of his generation in South Africa of the 1960s. In this article, I acknowledge Wylie’s engagement with the poetry while I question whether the somewhat relentless focus inwards is not too neglectful of those poems in which Clouts looks outwards to human interaction in the world. Such poems of abbreviated narrative, some of which I analyse in the course of my argument, suggest that looking outwards is necessary, at least, to consider Wylie’s claim that Clouts’s poetry is yet to receive its wider and just recognition. Given that Wylie offers little, if any, substantiation of Clouts’s standing as a poet among his peers, I move to a ‘summary’ perspective on Clouts in relation to what, I contend, is a rich and various poetry scene in 1960s South Africa. This leads me to the conclusion that the question of whether Clouts is the finest poet of his generation is not perhaps the question best pursued in Intimate Lightning. Where Wylie’s study succeeds is in reminding us that Clouts is a poet quite unlike any other we will encounter.
ABSTRACT
We present the cosmological analysis of the configuration-space anisotropic clustering in the completed Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) ...Data Release 16 galaxy sample. This sample consists of luminous red galaxies (LRGs) spanning the redshift range 0.6 < $z$ < 1, at an effective redshift of $z$eff = 0.698. It combines 174 816 eBOSS and 202 642 BOSS LRGs. We extract and model the baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) features from the galaxy two-point correlation function to infer geometrical and dynamical cosmological constraints. The adopted methodology is extensively tested on a set of realistic simulations. The correlations between the inferred parameters from the BAO and full-shape correlation function analyses are estimated. This allows us to derive joint constraints on the three cosmological parameter combinations: DM($z$)/rd, DH($z$)/rd, and fσ8($z$), where DM is the comoving angular diameter distance, DH is the Hubble distance, rd is the comoving BAO scale, f is the linear growth rate of structure, and σ8 is the amplitude of linear matter perturbations. After combining the results with those from the parallel power spectrum analysis of Gil-Marin et al., we obtain the constraints: DM/rd = 17.65 ± 0.30, DH/rd = 19.77 ± 0.47, and fσ8 = 0.473 ± 0.044. These measurements are consistent with a flat Lambda cold dark matter model with standard gravity.
Primary biliary cholangitis (formerly known as primary biliary cirrhosis, PBC) is an autoimmune liver disease in which a cycle of immune mediated biliary epithelial cell injury, cholestasis and ...progressive fibrosis can culminate over time in an end-stage biliary cirrhosis. Both genetic and environmental influences are presumed relevant to disease initiation. PBC is most prevalent in women and those over the age of 50, but a spectrum of disease is recognised in adult patients globally; male sex, younger age at onset (<45) and advanced disease at presentation are baseline predictors of poorer outcome. As the disease is increasingly diagnosed through the combination of cholestatic serum liver tests and the presence of antimitochondrial antibodies, most presenting patients are not cirrhotic and the term cholangitis is more accurate. Disease course is frequently accompanied by symptoms that can be burdensome for patients, and management of patients with PBC must address, in a life-long manner, both disease progression and symptom burden. Licensed therapies include ursodeoxycholic acid (UDCA) and obeticholic acid (OCA), alongside experimental new and re-purposed agents. Disease management focuses on initiation of UDCA for all patients and risk stratification based on baseline and on-treatment factors, including in particular the response to treatment. Those intolerant of treatment with UDCA or those with high-risk disease as evidenced by UDCA treatment failure (frequently reflected in trial and clinical practice as an alkaline phosphatase >1.67 × upper limit of normal and/or elevated bilirubin) should be considered for second-line therapy, of which OCA is the only currently licensed National Institute for Health and Care Excellence recommended agent. Follow-up of patients is life-long and must address treatment of the disease and management of associated symptoms.
PDF
