Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

Broadband amplifier and high performance tunable laser with an extinction ratio of higher than 60 dB using bismuth oxide-based erbium-doped fiber

A Bi₂O₃-based erbium-doped fiber (Bi-EDF) ring laser with a 70?nm tunable range is demonstrated with a 49?cm long Bi-EDF in which tuning range can be extended to larger than 100?nm using an optical switch to alter the length of Bi-EDF in the laser cavity. With an extinction ratio of better than 60?dB throughout the entire tuning range, the measured FWHM of laser lines are measured to be 0.09?nm. In addition, the common amplification parameters are measured and studied in detail for various pumping configurations.     

New Beta-lactamases in Candidate Phyla Radiation: Owning Pleiotropic Enzymes Is a Smart Paradigm for Microorganisms with a Reduced Genome

The increased exploitation of microbial sequencing methods has shed light on the high diversity of new microorganisms named Candidate Phyla Radiation (CPR). CPR are mainly detected via 16S rRNA/metabarcoding analyses or metagenomics and are found to be abundant in all environments and present in different human microbiomes. These microbes, characterized by their symbiotic/epiparasitic lifestyle with bacteria, are directly exposed to competition with other microorganisms sharing the same ecological niche. Recently, a rich repertoire of enzymes with antibiotic resistance activity has been found in CPR genomes by using an in silico adapted screening strategy. This reservoir has shown a high prevalence of putative beta-lactamase-encoding genes. We expressed and purified five putative beta-lactamase sequences having the essential domains and functional motifs from class A and class B beta-lactamase. Their enzymatic activities were tested against various beta-lactam substrates using liquid chromatography-mass spectrometry (LC-MS) and showed some beta-lactamase activity even in the presence of a beta-lactamase inhibitor. In addition, ribonuclease activity was demonstrated against RNA that was not inhibited by sulbactam and EDTA. None of these proteins could degrade single- and double-stranded-DNA. This study is the first to express and test putative CPR beta-lactamase protein sequences in vitro. Our findings highlight that the reduced genomes of CPR members harbor sequences encoding for beta-lactamases known to be multifunction hydrolase enzymes.     

Social impact assessment of investment activities in the China–Pakistan economic corridor

In order to analyze potential social risks, and achieve smooth implementation of investment activities in the China–Pakistan economic corridor (CPEC), we attempt to establish social impact and risk indicators. Both the impacts on the projects and the impacts of the projects are used to develop risk indicators in accordance with the literature review, reality and international standard principles. Using an analytic hierarchy process (AHP) and average value to analyze questionnaires of both Chinese and Pakistani respondents, we identify the importance of various risk indicators. The primary social risks of the western high mountain region include tribal obstacles and religious extremism. The social risks to the southeast coastal plains include preserving the historical and cultural heritage of the area and international protection of national parks. The social risks in north Kashmir include disputes, extremist threats, religious and cultural differences, and the protection of natural reserves. The social risks of the Xinjiang region primarily involve social issues faced by ethnic minorities and environmental pressures.     

High-feed turning of AISI D2 tool steel using multi-radii tool inserts: Tool life,material removed,and workpiece surface integrity evaluation

Multi-radii tool inserts offer novel configuration that comprises of multiple radii at tool nose. A review of the available literature indicates that there exists a need for experimental investigation on certain key machining characteristics of such tools. This paper reports on tool wear/life, material removed, and workpiece surface roughness when multi-radii mixed alumina TiN coated tool inserts are employed for turning D2 steel. Inserts of three different nose radii (0.40, 0.80, 1.20?mm) at six levels of feed rates (ranging from 0.157 to 0.562?mm/rev) are used. Results show that flank wear is the dominant wear mode with catastrophic tool failure occurring at highest nose radius (1.20?mm) and feed rate (0.562?mm/rev) combination. Also, there is ～59% reduction in tool life accompanied by ～62% increase in quantity of material removed as the feed rate increases from 0.157 to 0.562?mm/rev at maximum nose radius (1.20?mm). Feed rate is found to be statistically significant factor for all three responses considered herein at 95% confidence level. Surface integrity assessment at maximum feed rate reveals presence of a strain hardened layer extending to the depth of 150?µm below the machined surface without any observance of white layer for all the tool conditions and nose radius.     

Design of dual‐band microstrip patch antenna with right‐angle triangular aperture slot for energy transfer application

This work focusing on the dual‐band antenna design with rectifying circuit for energy transfer system technology for enhancement gain performance. The air gap technique is applied on this microstrip antenna design work to enhance the antenna gain. The work begins with designing and analyzing the antenna via the CST Microwave Studio software. After validation on acceptable performance in simulation side is obtained, the return loss, S₁₁ of the antenna is measured using vector network analyzer equipment. The rectifier circuit is used to convert the captured signal to DC voltage. This projected dual‐band antenna has successfully accomplished the target on return loss of ?44.707 dB and ?32.163 dB at dual resonant frequencies for 1.8 GHz and 2.4 GHz, respectively. This proposed antenna design benefits in low cost fabrication and has achieved high gain of 6.31 dBi and 7.82 dBi for dual‐band functioning frequencies.     

Regulation of Cell Signaling Pathways and Non-Coding RNAs by Baicalein in Different Cancers

Landmark discoveries in molecular oncology have provided a wide-angle overview of the heterogenous and therapeutically challenging nature of cancer. The power of modern ‘omics’ technologies has enabled researchers to deeply and comprehensively characterize molecular mechanisms underlying cellular functions. Interestingly, high-throughput technologies have opened new horizons for the design and scientific fool-proof evaluation of the pharmacological properties of targeted chemical compounds to tactfully control the activities of the oncogenic protein networks. Groundbreaking discoveries have galvanized the expansion of the repertoire of available pharmacopoeia to therapeutically target a myriad of deregulated oncogenic pathways. Natural product research has undergone substantial broadening, and many of the drugs which constitute the backbone of modern pharmaceuticals have been derived from the natural cornucopia. Baicalein has gradually gained attention because of its unique ability to target different oncogenic signal transduction cascades in various cancers. We have partitioned this review into different sub-sections to provide a broader snapshot of the oncogenic pathways regulated by baicalein. In this review, we summarize baicalein-mediated targeting of WNT/β-catenin, AKT/mTOR, JAK/STAT, MAPK, and NOTCH pathways. We also critically analyze how baicalein regulates non-coding RNAs (microRNAs and long non-coding RNAs) in different cancers. Finally, we conceptually interpret baicalein-mediated inhibition of primary and secondary growths in xenografted mice.     

A Multistage In Silico Study of Natural Potential Inhibitors Targeting SARS-CoV-2 Main Protease

Among a group of 310 natural antiviral natural metabolites, our team identified three compounds as the most potent natural inhibitors against the SARS-CoV-2 main protease (PDB ID: 5R84), M^pro. The identified compounds are sattazolin and caprolactin A and B. A validated multistage in silico study was conducted using several techniques. First, the molecular structures of the selected metabolites were compared with that of GWS, the co-crystallized ligand of M^pro, in a structural similarity study. The aim of this study was to determine the thirty most similar metabolites (10%) that may bind to the M^pro similar to GWS. Then, molecular docking against M^pro and pharmacophore studies led to the choice of five metabolites that exhibited good binding modes against the M^pro and good fit values against the generated pharmacophore model. Among them, three metabolites were chosen according to ADMET studies. The most promising M^pro inhibitor was determined by toxicity and DFT studies to be caprolactin A (292). Finally, molecular dynamics (MD) simulation studies were performed for caprolactin A to confirm the obtained results and understand the thermodynamic characteristics of the binding. It is hoped that the accomplished results could represent a positive step in the battle against COVID-19 through further in vitro and in vivo studies on the selected compounds.     

Pivotal Role of Phytohormones and Their Responsive Genes in Plant Growth and Their Signaling and Transduction Pathway under Salt Stress in Cotton

The presence of phyto-hormones in plants at relatively low concentrations plays an indispensable role in regulating crop growth and yield. Salt stress is one of the major abiotic stresses limiting cotton production. It has been reported that exogenous phyto-hormones are involved in various plant defense systems against salt stress. Recently, different studies revealed the pivotal performance of hormones in regulating cotton growth and yield. However, a comprehensive understanding of these exogenous hormones, which regulate cotton growth and yield under salt stress, is lacking. In this review, we focused on new advances in elucidating the roles of exogenous hormones (gibberellin (GA) and salicylic acid (SA)) and their signaling and transduction pathways and the cross-talk between GA and SA in regulating crop growth and development under salt stress. In this review, we not only focused on the role of phyto-hormones but also identified the roles of GA and SA responsive genes to salt stress. Our aim is to provide a comprehensive review of the performance of GA and SA and their responsive genes under salt stress, assisting in the further elucidation of the mechanism that plant hormones use to regulate growth and yield under salt stress.     

Mitochondrial Dysfunction Plays Central Role in Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is a global pandemic that affects one-quarter of the world’s population. NAFLD includes a spectrum of progressive liver disease from steatosis to nonalcoholic steatohepatitis (NASH), fibrosis, and cirrhosis and can be complicated by hepatocellular carcinoma. It is strongly associated with metabolic syndromes, obesity, and type 2 diabetes, and it has been shown that metabolic dysregulation is central to its pathogenesis. Recently, it has been suggested that metabolic- (dysfunction) associated fatty liver disease (MAFLD) is a more appropriate term to describe the disease than NAFLD, which puts increased emphasis on the important role of metabolic dysfunction in its pathogenesis. There is strong evidence that mitochondrial dysfunction plays a significant role in the development and progression of NAFLD. Impaired mitochondrial fatty acid oxidation and, more recently, a reduction in mitochondrial quality, have been suggested to play a major role in NAFLD development and progression. In this review, we provide an overview of our current understanding of NAFLD and highlight how mitochondrial dysfunction contributes to its pathogenesis in both animal models and human subjects. Further we discuss evidence that the modification of mitochondrial function modulates NAFLD and that targeting mitochondria is a promising new avenue for drug development to treat NAFLD/NASH.