Securing Signal-free Intersections against Strategic Jamming Attacks: A Macroscopic Approach

We consider the security-by-design of a signal-free intersection for connected and autonomous vehicles in the face of strategic jamming attacks. We use a fluid model to characterize macroscopic traffic flow through the intersection, where the saturation rate is derived from a vehicle coordination algorithm. We model jamming attacks as sudden increase in communication latency induced on vehicle-to-infrastructure connectivity; such latency triggers the safety mode for vehicle coordination and thus reduces the intersection saturation rate. A strategic attacker selects the attacking rate, while a system operator selects key design parameters, either the saturation rate or the recovery rate. Both players' actions induce technological costs and jointly determine the mean travel delay. By analyzing the equilibrium of the security game, we study the preferable level of investment in the intersection's nominal discharging capability or recovery capability, for balance between hardware/infrastructure cost and security-by-design.Comment: Submitted to 61st IEEE Conference on Decision and Contro

Lossy and Lossless (L2^2) Post-training Model Size Compression

Deep neural networks have delivered remarkable performance and have been widely used in various visual tasks. However, their huge size causes significant inconvenience for transmission and storage. Many previous studies have explored model size compression. However, these studies often approach various lossy and lossless compression methods in isolation, leading to challenges in achieving high compression ratios efficiently. This work proposes a post-training model size compression method that combines lossy and lossless compression in a unified way. We first propose a unified parametric weight transformation, which ensures different lossy compression methods can be performed jointly in a post-training manner. Then, a dedicated differentiable counter is introduced to guide the optimization of lossy compression to arrive at a more suitable point for later lossless compression. Additionally, our method can easily control a desired global compression ratio and allocate adaptive ratios for different layers. Finally, our method can achieve a stable $10\times$ compression ratio without sacrificing accuracy and a $20\times$ compression ratio with minor accuracy loss in a short time. Our code is available at https://github.com/ModelTC/L2_Compression

Advances in the application of co-culture strategies in organoids

As a good in vitro research model, organoids are more and more widely used in the biomedical field. By developing self-assembled 3D structures using various tissue culture techniques, organoids can rebuild the high complexity of cells in the inherent structure of the organ, and are therefore unanimously used to study mechanisms regulating body development and disease, high-throughput drug screening, and personalized treatment and so on. To better recapitulate cell-to-cell interactions within the microenvironment, co-culture strategies have been extended to more cell types, and their rapid development offers broader prospects for organoids and paves the way for the treatment of human diseases and regenerative medicine. This review discussed the role of co-culture strategies in organoid generation, and focused on the application of various cellular components and microorganisms in organoid construction, thereby providing reference and help for scholars to construct and develop organoids with a higher degree of in vivo simulation

Susceptibilities of Yersinia pestis to Twelve Antimicrobial Agents in China

Streptomycin is the preferred choice for therapy of plague in China and other countries. However, Yersinia pestis exhibiting plasmid-mediated antimicrobial agent–resistant traits had been reported in Madagascar. In this study, we evaluated the susceptibility of traditional or newer antimicrobial agents used for treatment and/or prophylaxis of plague. Following Clinical and Laboratory Standards Institute (CLSI) recommendations, the susceptibility of 12 antimicrobial agents was evaluated by the agar microdilution method in 1,012 strains of Y. pestis isolated from 1943 to 2017 in 12 natural plague foci in China. One clinical Y. pestis isolate (S19960127) was found to be highly resistant to streptomycin, while the strain was still sensitive to other 11 antibiotics, that is, ciprofloxacin, ofloxacin, kanamycin, chloramphenicol, ampicillin, ceftriaxone, cefuroxime, trimethoprim-sulfamethoxazole, tetracycline, spectinomycin and moxifloxacin. The remaining 1,011 Y. pestis strains in this study demonstrated susceptibility to the above-mentioned 12 antimicrobial agents. Antimicrobial sensitivity surveillance of Y. pestis isolates, including dynamic monitoring of streptomycin resistance during various clinical plague treatments, should be carried out routinely

Rosebengal-Loaded Nanoporous Structure Based on Rare Earth Metal-Organic-Framework: Synthesis, Characterization and Photophysical Performance

A rosebengal-modified nanoporous structure was designed and constructed. This composite structure consisted of an organic sensitizer based on rosebengal and a supporting host of rare earth metal-organic-framework (MOF). It was identified by means of its x-ray diffraction (XRD) pattern, Infrared (IR) spectra, thermal stability and photophysical measurements. Its absorption was increased by 2,4,6-trinitrophenol. Its rosebengal emission was proportionally increased. But its rare earth emission was well-preserved, offering ratiometric signals. These two sensing modes exhibited linear response and good selectivity with a limit of detection (LOD) of 1.9 μM. Its sensing nature was confirmed as the combination of increased rosebengal emission and rare earth emission quenching effect triggered electron-deficient molecules. This nanoporous structure was superior to traditional ones owing to its double sensing modes

Phylogenetic relationship and comparative analysis of the main Bupleuri Radix species in China

Background Bupleuri Radix (Chaihu) is a famous traditional Chinese medicine derived from Bupleurum, Apiaceae. The origin of cultivated Chaihu germplasm in China is unclear, which has led to unstable Chaihu quality. In this study, we reconstructed the phylogeny of the main Chaihu germplasm species in China and identified potential molecular markers to authenticate its origin. Methods Three Bupleurum species (eight individuals), B. bicaule, B. chinense, and B. scorzonerifolium, were selected for genome skimming. Published genomes from B. falcatum and B. marginatum var. stenophyllum were used for comparative analysis. Results Sequences of the complete plastid genomes were conserved with 113 identical genes ranging from 155,540 to 155,866 bp in length. Phylogenetic reconstruction based on complete plastid genomes resolved intrageneric relationships of the five Bupleurum species with high support. Conflicts between the plastid and nuclear phylogenies were observed, which were mainly ascribed to introgressive hybridization. Comparative analysis showed that noncoding regions of the plastomes had most of the variable sequences. Eight regions (atpF-atpH, petN-psbM, rps16-psbK, petA-psbJ, ndhC-trnV/UAC and ycf1) had high divergence values in Bupleurum species and could be promising DNA barcodes for Chaihu authentication. A total of seven polymorphic cpSSRs and 438 polymorphic nSSRs were detected across the five Chaihu germplasms. Three photosynthesis-related genes were under positive selection, of which accD reflected the adaptation fingerprint of B. chinense to different ecological habitats. Our study provides valuable genetic information for phylogenetic investigation, germplasm authentication, and molecular breeding of Chaihu species

Characterization of the chloroplast genome of the family Lauraceae plant species, Cinnamomum cassia

The fruit of Cinnamomum cassia is an important spice material and its branch is a common Chinese herbal medicine as the family Lauraceae. In this study, we reported the complete chloroplast genome of C. cassia. The chloroplast genome of C. cassia with length of 152,675 bp is a characteristic quadripartite structure. The length of the inverted-repeats regions (IRs), large single-copy (LSC) region, and small single-copy (SSC) region of C. cassia was 20,068 bp, 93,663 and 18,876 bp. The chloroplast genome of C. cassia contains 124 genes, which includes 80 protein-coding genes (PCGs), 36 transfer RNA genes (tRNAs) and 8 ribosomal RNA genes (rRNAs). The overall nucleotide content of the chloroplast genome: 30.0% A (Adenine), 30.8% T (Thymine), 19.7% C (Cytosine), 19.5% G (Guanine), and 39.2% GC content. Evolutionary relationship result showed that Cinnamomum cassia was most closely related to Cinnamomum parthenoxylon in the family Lauraceae by the Neighbor-Joining (NJ) method

Exosomes in Glioma: Unraveling Their Roles in Progression, Diagnosis, and Therapy

Gliomas, the most prevalent primary malignant brain tumors, present a challenging prognosis even after undergoing surgery, radiation, and chemotherapy. Exosomes, nano-sized extracellular vesicles secreted by various cells, play a pivotal role in glioma progression and contribute to resistance against chemotherapy and radiotherapy by facilitating the transportation of biological molecules and promoting intercellular communication within the tumor microenvironment. Moreover, exosomes exhibit the remarkable ability to traverse the blood–brain barrier, positioning them as potent carriers for therapeutic delivery. These attributes hold promise for enhancing glioma diagnosis, prognosis, and treatment. Recent years have witnessed significant advancements in exosome research within the realm of tumors. In this article, we primarily focus on elucidating the role of exosomes in glioma development, highlighting the latest breakthroughs in therapeutic and diagnostic approaches, and outlining prospective directions for future research

Multi-Focus Image Fusion Based on Convolution Neural Network for Parkinson’s Disease Image Classification

Parkinson’s disease (PD) is a common neurodegenerative disease that has a significant impact on people’s lives. Early diagnosis is imperative since proper treatment stops the disease’s progression. With the rapid development of CAD techniques, there have been numerous applications of computer-aided diagnostic (CAD) techniques in the diagnosis of PD. In recent years, image fusion has been applied in various fields and is valuable in medical diagnosis. This paper mainly adopts a multi-focus image fusion method primarily based on deep convolutional neural networks to fuse magnetic resonance images (MRI) and positron emission tomography (PET) neural photographs into multi-modal images. Additionally, the study selected Alexnet, Densenet, ResNeSt, and Efficientnet neural networks to classify the single-modal MRI dataset and the multi-modal dataset. The test accuracy rates of the single-modal MRI dataset are 83.31%, 87.76%, 86.37%, and 86.44% on the Alexnet, Densenet, ResNeSt, and Efficientnet, respectively. Moreover, the test accuracy rates of the multi-modal fusion dataset on the Alexnet, Densenet, ResNeSt, and Efficientnet are 90.52%, 97.19%, 94.15%, and 93.39%. As per all four networks discussed above, it can be concluded that the test results for the multi-modal dataset are better than those for the single-modal MRI dataset. The experimental results showed that the multi-focus image fusion method according to deep learning can enhance the accuracy of PD image classification

Engineering Polarization in the Ferroelectric Electrocatalysts to Boost Water Electrolysis

Water splitting is the most important process for making green hydrogen. The positive effects of ferroelectric polarization in various kinds of water splitting are well recognized, but the study of electrocatalytic water splitting is still in its infancy. Herein, a family of intrinsic ferroelectrics with a flexible tetragonal tungsten bronze structure is chosen to accommodate oxygen evolution reaction (OER) active sites together with its freedom for tuning the ferroelectric polarization. It is found that the OER performance is positively correlated with the ferroelectric polarization, with a significant reduction in the overpotential of ≈40 mV at 10 mA cm−2, coming from two trade-off effects, i.e., enhancement of the surface adsorption and band tilting for fast electron transfer. This study not only fills the gap between electrocatalytic water splitting and the band structure but also proposes ferroelectric polarization as a powerful tool to enhance water splitting for clean hydrogen in several ways