Microbial communities associated with epilithic algal matrix with different morphological characters in Luhuitou fringing reef

The microbiota is an important component of the epilithic algal matrix (EAM) and plays a central role in the biogeochemical cycling of important nutrients in coral reef ecosystems. Insufficient studies on EAM microbiota diversity have led to a limited understanding of the ecological functions of EAMs in different states. To explore the microbial community of EAMs in the Luhuitou fringing reef in Sanya, China, which has undergone the incessant expansion and domination of algae over the past several decades, investigations were conducted in the reef’s intertidal zone. Five types of substrate habitats (dead branching coral, dead massive coral, dead flat coral, granite block, and concrete block) were selected, and their microbial communities were analyzed by high-throughput sequencing of EAM holobionts using the 16S rDNA V4 region. Proteobacteria was the most abundant group, accounting for more than 70% of reads of the microbial composition across all sites, followed by Cyanobacteria (15.89%) and Bacteroidetes (5.93%), respectively. Cluster analysis divided all microbial communities into three groups, namely short, medium, and long EAMs. Algal length was the most important morphological factor impacting the differences in the composition of the EAM microbiota. The three EAM groups had 52 common OTUs and 78.52% common sequences, among which the most abundant were Vibrio spp. and Photobacterium spp. The three types of EAM also had unique OTUs. The short EAMs had 238 unique OTUs and 48.61% unique sequences, mainly in the genera Shewanella and Cyanobacterium. The medium EAMs contained 130 unique OTUs and 4.36% unique sequences, mainly in the genera Pseudomonas and Bacillus. The long EAMs only had 27 unique OTUs and 4.13% unique sequences, mainly in the genus Marinobacter. Compared with short EAM, medium and long EAM had a lower proportion of autotrophic bacteria and higher proportion of potential pathogenic bacteria. It is suggested that EAMs with different phenotypes have different microbial compositions, and the ecological function of the EAM microbiota changes from autotrophic to pathogenic with an increase in algal length. As EAMs have expanded on coastal coral reefs worldwide, it is essential to comprehensively explore the community structure and ecological role of their microbial communities

NaCl-induced hot corrosion behaviors of NiSiAlY coatings

In the marine environments, NiCrAlY coatings with high content of Cr would suffer much severer corrosion due to the effect of NaCl. Thus, NiSiAlY coatings with different Si content were proposed and deposited on Ni-based superalloys by multi-arc ion plating. The as-deposited coating was mainly composed of γ’-Ni3Al phase with a small amount of β-NiAl phase. NaCl-induced hot corrosion tests were performed on the coatings at 500°C, 600°C, and 700°C, respectively. Compared with Ni-based alloy substrates, the NiSiAlY coatings exhibited a good corrosion resistance to NaCl at elevated temperatures. However, with an excessive amount of Si, the NiSiAlY coating showed a degradation in the hot corrosion resistance. In this work, the corrosion mechanisms of the tested coatings were discussed. Moreover, the role of Si was also investigated

A low-cost collaborative location scheme with GNSS and RFID for the Internet of Things

The emergence and development of the Internet of Things (IoT) has attracted growing attention to low-cost location systems when facing the dramatically increased number of public infrastructure assets in smart cities. Various radio frequency identification (RFID)-based locating systems have been developed. However, most of them are impractical for infrastructure asset inspection and management on a large scale due to their high cost, inefficient deployment, and complex environments such as emergencies or high-rise buildings. In this paper, we proposed a novel locating system by combing the Global Navigation Satellite System (GNSS) with RFID, in which a target tag was located with one RFID reader and one GNSS receiver with sufficient accuracy for infrastructure asset management. To overcome the cost challenge, one mobile RFID reader-mounted GNSS receiver is used to simulate multiple location known reference tags. A vast number of reference tags are necessary for current RFID-based locating systems, which means higher cost. To achieve fine-grained location accuracy, we utilize a distance-based power law weight algorithm to estimate the exact coordinates. Our experiment demonstrates the effectiveness and advantages of the proposed scheme with sufficient accuracy, low cost and easy deployment on a large scale. The proposed scheme has potential applications for location-based services in smart cities

Diagnosis and segmentation effect of the ME-NBI-based deep learning model on gastric neoplasms in patients with suspected superficial lesions - a multicenter study

BackgroundEndoscopically visible gastric neoplastic lesions (GNLs), including early gastric cancer and intraepithelial neoplasia, should be accurately diagnosed and promptly treated. However, a high rate of missed diagnosis of GNLs contributes to the potential risk of the progression of gastric cancer. The aim of this study was to develop a deep learning-based computer-aided diagnosis (CAD) system for the diagnosis and segmentation of GNLs under magnifying endoscopy with narrow-band imaging (ME-NBI) in patients with suspected superficial lesions.MethodsME-NBI images of patients with GNLs in two centers were retrospectively analysed. Two convolutional neural network (CNN) modules were developed and trained on these images. CNN1 was trained to diagnose GNLs, and CNN2 was trained for segmentation. An additional internal test set and an external test set from another center were used to evaluate the diagnosis and segmentation performance.ResultsCNN1 showed a diagnostic performance with an accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 90.8%, 92.5%, 89.0%, 89.4% and 92.2%, respectively, and an area under the curve (AUC) of 0.928 in the internal test set. With CNN1 assistance, all endoscopists had a higher accuracy than for an independent diagnosis. The average intersection over union (IOU) between CNN2 and the ground truth was 0.5837, with a precision, recall and the Dice coefficient of 0.776, 0.983 and 0.867, respectively.ConclusionsThis CAD system can be used as an auxiliary tool to diagnose and segment GNLs, assisting endoscopists in more accurately diagnosing GNLs and delineating their extent to improve the positive rate of lesion biopsy and ensure the integrity of endoscopic resection

Even-Odd Layer-Dependent Anomalous Hall Effect in Topological Magnet MnBi2Te4 Thin Films

A central theme in condensed matter physics is to create and understand the exotic states of matter by incorporating magnetism into topological materials. One prime example is the quantum anomalous Hall (QAH) state. Recently, MnBi2Te4 has been demonstrated to be an intrinsic magnetic topological insulator and the QAH effect was observed in exfoliated MnBi2Te4 flakes. Here, we used molecular beam epitaxy (MBE) to grow MnBi2Te4 films with thickness down to 1 septuple layer (SL) and performed thickness-dependent transport measurements. We observed a non-square hysteresis loop in the antiferromagnetic state for films with thickness greater than 2 SL. The hysteresis loop can be separated into two AH components. Through careful analysis, we demonstrated that one AH component with the larger coercive field is from the dominant MnBi2Te4 phase, while the other AH component with the smaller coercive field is from the minor Mn-doped Bi2Te3 phase in the samples. The extracted AH component of the MnBi2Te4 phase shows a clear even-odd layer-dependent behavior, a signature of antiferromagnetic thin films. Our studies reveal insights on how to optimize the MBE growth conditions to improve the quality of MnBi2Te4 films, in which the QAH and other exotic states are predicted.Comment: 23 pages, 4 figures, comments are welcom

Noema formIng Cluster survEy (NICE): Discovery of a starbursting galaxy group with a radio-luminous core at z=3.95

The study of distant galaxy groups and clusters at the peak epoch of star formation is limited by the lack of a statistically and homogeneously selected and spectroscopically confirmed sample. Recent discoveries of concentrated starburst activities in cluster cores have opened a new window to hunt for these structures based on their integrated IR luminosities. Hereby we carry out the large NOEMA (NOrthern Extended Millimeter Array) program targeting a statistical sample of infrared-luminous sources associated with overdensities of massive galaxies at z>2, the Noema formIng Cluster survEy (NICE). We present the first result from the ongoing NICE survey, a compact group at z=3.95 in the Lockman Hole field (LH-SBC3), confirmed via four massive (M_star>10^10.5M_sun) galaxies detected in CO(4-3) and [CI](1-0) lines. The four CO-detected members of LH-SBC3 are distributed over a 180 kpc physical scale, and the entire structure has an estimated halo mass of ~10^13Msun and total star formation rate (SFR) of ~4000Msun/yr. In addition, the most massive galaxy hosts a radio-loud AGN with L_1.4GHz, rest = 3.0*10^25W/Hz. The discovery of LH-SBC3 demonstrates the feasibility of our method to efficiently identify high-z compact groups or forming cluster cores. The existence of these starbursting cluster cores up to z~4 provides critical insights into the mass assembly history of the central massive galaxies in clusters.Comment: 7 pages, 7 figures, submitted to A&