Secure ECDSA SRAM-PUF Based on Universal Single/Double Scalar Multiplication Architecture.

Physically unclonable functions (PUFs) are crucial for enhancing cybersecurity by providing unique, intrinsic identifiers for electronic devices, thus ensuring their authenticity and preventing unauthorized cloning. The SRAM-PUF, characterized by its simple structure and ease of implementation in various scenarios, has gained widespread usage. The soft-decision Reed-Muller (RM) code, an error correction code, is commonly employed in these designs. This paper introduces the design of an RM code soft-decision attack algorithm to reveal its potential security risks. To address this problem, we propose a soft-decision SRAM-PUF structure based on the elliptic curve digital signature algorithm (ECDSA). To improve the processing speed of the proposed secure SRAM-PUF, we propose a custom ECDSA scheme. Further, we also propose a universal architecture for the critical operations in ECDSA, elliptic curve scalar multiplication (ECSM), and elliptic curve double scalar multiplication (ECDSM) based on the differential addition chain (DAC). For ECSMs, iterations can be performed directly; for ECDSMs, a two-dimensional DAC is constructed through precomputation, followed by iterations. Moreover, due to the high similarity of ECSM and ECDSM data paths, this universal architecture saves hardware resources. Our design is implemented on a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC) using a Xilinx Virtex-7 and an TSMC 40 nm process. Compared to existing research, our design exhibits a lower bit error rate (2.7×10-10) and better area-time performance (3902 slices, 6.615 µs ECDSM latency).

Lightweight Detection Method for X-ray Security Inspection with Occlusion.

Identifying the classes and locations of prohibited items is the target of security inspection. However, X-ray security inspection images with insufficient feature extraction, imbalance between easy and hard samples, and occlusion lead to poor detection accuracy. To address the above problems, an object-detection method based on YOLOv8 is proposed. Firstly, an ASFF (adaptive spatial feature fusion) and a weighted feature concatenation algorithm are introduced to fully extract the scale features from input images. In this way, the model can learn further details in training. Secondly, CoordAtt (coordinate attention module), which belongs to the hybrid attention mechanism, is embedded to enhance the learning of features of interest. Then, the slide loss function is introduced to balance the simple samples and the difficult samples. Finally, Soft-NMS (non-maximum suppression) is introduced to resist the conditions containing occlusion. The experimental result shows that mAP (mean average precision) achieves 90.2%, 90.5%, 79.1%, and 91.4% on the Easy, Hard, and Hidden sets of the PIDray and SIXray public test set, respectively. Contrasted with original model, the mAP of our proposed YOLOv8n model increased by 2.7%, 3.1%, 9.3%, and 2.4%, respectively. Furthermore, the parameter count of the modified YOLOv8n model is roughly only 3 million.

Robust and Wet Adhesive Self-Gelling Powders for Rapid Hemostasis and Efficient Wound Healing.

Healing traumatic wounds is arduous, leaving miscellaneous demands for ideal wound dressings, such as rapid hemostasis, superior wet tissue adhesion, strong mechanical properties, and excellent antibacterial activity. Herein, we report a self-gelling, wet adhesive, stretchable (polyethylenimine/poly(dimethylammonium chloride)/(poly(acrylic acid)/poly(sodium styrenesulfonate)/alkylated chitosan)) ((PEI/PDDA)/(PAA/PSS)/ACS) powder as a new option. The self-gel utilizes noncovalent interactions among in situ formed PDDA/PSS nanoparticles and PEI/PAA polymetric matrices to earn sensational mechanical properties and tensile strength while incorporating ACS to obtain fast hemostasis and therapeutic capacities. The powder can form a hydrogel patch in situ within 3 s upon liquid absorption, capable of resisting pressure higher than twice the blood pressure. Deposition of the self-gelling powders on various wounds, such as rat liver and femoral artery wounds, can stop bleeding in 10 s and lessen the amount of bleeding 6-fold plus in corresponding models. Furthermore, the self-gelling powders can significantly advance the chronic wound healing process by displaying a high wound healing rate and a low inflammatory response and promoting the formation of new blood vessels and tissue regeneration. The satisfactory mechanical properties, strong wet adhesion, sufficient antibacterial properties, ease of usage, adaptability to complex wounds, rapid hemostasis, and superior therapeutic capacities of (PEI/PDDA)/(PAA/PSS)/ACS self-gelling powders render them as a profound wound dressing biomaterial.

All-aqueous microfluidic printing of multifunctional bioactive microfibers promote whole-stage wound healing.

Wound healing involves multi-stages of physiological responses, including hemostasis, inflammation, cell proliferation, and tissue remodeling. Satisfying all demands throughout different stages remains a rarely addressed challenge. Here we introduce an innovative all-aqueous microfluidic printing technique for fabricating multifunctional bioactive microfibers, effectively contributing to all four phases of the healing process. The distinctive feature of the developed microfibers lies in their capacity to be printed in a free-form manner in the aqueous-two phase system (ATPS). This is achieved through interfacial coacervation between alkyl-chitosan and alginate, with enhanced structural integrity facilitated by simultaneous crosslinking with calcium ions and alginate. The all-aqueous printed microfibers exhibit exceptional performance in terms of cell recruitment, blood cell coagulation, and hemostasis. The inclusion of a dodecyl carbon chain and amino groups in alkyl-chitosan imparts remarkable antimicrobial properties by anchoring to bacteria, complemented by potent antibacterial effects of encapsulated silver nanoparticles. Moreover, microfibers can load bioactive drugs like epidermal growth factor (EGF), preserving their activity and enhancing therapeutic effects during cell proliferation and tissue remodeling. With these sequential functions to guide the whole-stage wound healing, this work offers a versatile and robust paradigm for comprehensive wound treatment, holding great potential for optimal healing outcomes.

Triboelectric Nanogenerators-Based Therapeutic Electrical Stimulation on Skin: from Fundamentals to Advanced Applications.

Discovery of the amazing and vital therapeutic roles of electrical stimulation (ES) on skin has sparked tremendous efforts to investigate ES suppliers. Among them, triboelectric nanogenerators (TENGs), as a self-sustainable bioelectronic system, can generate self-powered and biocompatible ES for achieving superior therapeutic effects on skin applications. Here, a brief review of the application of TENGs-based ES on skin is presented, with specific discussions of the fundamentals of TENGs-based ES and its feasibility to be applied for adjusting physiological and pathological processes of skin. Then, a comprehensive and in-depth depiction of emerging representative skin applications of TENGs-based ES is categorized and reviewed, with particular descriptions about its therapeutic effects on achieving antibacterial therapy, promoting wound healing, and facilitating transdermal drug delivery. Finally, the challenges and perspectives for further advancing TENGs-based ES toward a more powerful and versatile therapeutic strategy are discussed, particularly regarding opportunities in fundamental multidisciplinary research and biomedical applications.

Functional nano-systems for transdermal drug delivery and skin therapy.

Transdermal drug delivery is one of the least intrusive and patient-friendly ways for therapeutic agent administration. Recently, functional nano-systems have been demonstrated as one of the most promising strategies to treat skin diseases by improving drug penetration across the skin barrier and achieving therapeutically effective drug concentrations in the target cutaneous tissues. Here, a brief review of functional nano-systems for promoting transdermal drug delivery is presented. The fundamentals of transdermal delivery, including skin biology and penetration routes, are introduced. The characteristics of functional nano-systems for facilitating transdermal drug delivery are elucidated. Moreover, the fabrication of various types of functional transdermal nano-systems is systematically presented. Multiple techniques for evaluating the transdermal capacities of nano-systems are illustrated. Finally, the advances in the applications of functional transdermal nano-systems for treating different skin diseases are summarized.

All-Aqueous Microfluidics Fabrication of Multifunctional Bioactive Microcapsules Promotes Wound Healing.

Wound healing involves multiple stages of body responses, including hemostasis, inflammation, cell proliferation, and tissue remodeling. New material design satisfying all demands throughout different stages of wound healing is cherished but rarely discussed. Here we introduce all-aqueous multiphase microfluidics as a novel strategy to fabricate self-assembled, multifunctional alkylated chitosan/alginate microcapsules (SAAMs) as novel therapeutic materials for rapid blood coagulation and wound healing. SAAMs are structurally distinguished by their ultrathin shells with polycationic surface for rapid activation of clotting cascade and their internal porous dextran-rich cores for fast absorption of blood and exudate. These features endow SAAMs with excellent hemostatic properties for acute hemorrhage. Moreover, the alkylated chitosan within the microcapsules exhibits persistent antimicrobial activities against bactericidal infections due to their amphiphilic and cationic surfaces. Besides, cytokines can be safely loaded into the organic-solvent-free microcapsules and released precisely to promote the proliferation of epidermal cells, supporting the subsequent development of granulation tissue and suppression of inflammation in the last stages of wound healing. With the ability to fabricate size-tailored soft microcapsules and to realize time-sequential functions for tissue repairing, the presented "all-aqueous microfluidics generation of multifunctional bioactive SAAMs" create a versatile and robust paradigm for wound treatment.

Local and Context-Attention Adaptive LCA-Net for Thyroid Nodule Segmentation in Ultrasound Images.

The thyroid nodule segmentation of ultrasound images is a critical step for the early diagnosis of thyroid cancers in clinics. Due to the weak edge of ultrasound images and the complexity of thyroid tissue structure, it is still challenging to accurately segment the delicate contour of thyroid nodules. A local and context-attention adaptive network (LCA-Net) for thyroid nodule segmentation is proposed to address these shortcomings, which leverages both local feature information from convolution neural networks and global context information from transformers. Firstly, since most existing thyroid nodule segmentation models are skilled at local detail features and lose some context information, we propose a transformers-based context-attention module to capture more global associative information for the network and perceive the edge information of the nodule contour. Secondly, a backbone module with 7×1, 1×7 convolutions and the activation function Mish is designed, which enlarges the receptive field and extracts more feature details. Furthermore, a nodule adaptive convolution (NAC) module is introduced to adaptively deal with thyroid nodules of different sizes and positions, thereby improving the generalization performance of the model. Simultaneously, an optimized loss function is proposed to solve the pixels class imbalance problem in segmentation. The proposed LCA-Net, validated on the public TN-SCUI2020 and TN3K datasets, achieves Dice scores of 90.26% and 82.08% and PA scores of 98.87% and 96.97%, respectively, which outperforms other state-of-the-art thyroid nodule segmentation models. This paper demonstrates the superiority of the proposed LCA-Net for thyroid nodule segmentation, which possesses strong generalization performance and promising segmentation accuracy. Consequently, the proposed model has wide application prospects for thyroid nodule diagnosis in clinics.

The Effect of High CDC6 Levels on Predicting Poor Prognosis in Colorectal Cancer.

INTRODUCTION: We investigated the function of cell division cycle 6 (CDC6) on the prognosis in colorectal carcinoma (CRC). METHODS: CDC6 protein expression levels in 121 patients with colorectal cancer and adjacent normal mucosa were detected by immunohistochemistry. RESULTS: Compared to adjacent normal tissues, CDC6 mRNA level was overexpressed in CRC tissues. Moreover, CDC6 protein levels were expressed up to 93.39% (113/121) in CRC tissues in the cell nucleus or cytoplasm. However, there were only 5.79% (7/121) in normal mucosal tissues with nuclear expression. CDC6 expression was significantly correlated with TNM stage and tumor metastasis. The 5-year survival rate was lower in the high CDC6 expression group than the low group. After silencing of CDC6 expression in SW620 cells, cell proliferation was slowed, the tumor clones were decreased, and the cell cycle was arrested in G1 phase. In multivariate analysis, increased CDC6 protein expression levels in colon cancer tissues were associated with cancer metastasis, TNM stage, and patient survival time. CONCLUSION: CDC6 is highly expressed in CRC, and downregulation of CDC6 can slow the growth of CRC cells in vitro. It is also an independent predictor for poor prognosis and may be a useful biomarker for targeted therapy and prognostic evaluation.

Regulation of nitrogen configurations and content in 3D porous carbons for improved lithium storage.

The incorporation of active nitrogen species in carbon materials has been widely demonstrated as a viable means to produce superior lithium storage materials, while the precise regulation of nitrogen configurations as well as their content still remains a formidable challenge. Herein, nitrogen-free porous carbon frameworks were synthesized by a self-templating strategy from disodium citrate, and post-annealing yielded 10.4 at% N that was primarily pyrrolic-N and pyridinic-N with an atomic ratio of about 3 : 1, with negligible inactive graphitic-N. A gravimetric capacity of 570 mA h g-1 at a current density of 4 A g-1 was measured for a Li half-cell based on the as-prepared N-doped 3D carbon materials. Lithium-ion capacitors with this N-doped carbon as the anode and commercial AC as the cathode yielded energy densities of 58.9 and 142.6 W h kg-1 with the corresponding power densities of 7400 and 185 W kg-1, respectively. We suggest that the carbon materials with high content of pyrrolic-N and pyridinic-N especially pyrrolic-N have improved lithium storage.

An efficient algorithm for direction finding against unknown mutual coupling.

In this paper, an algorithm of direction finding is proposed in the presence of unknown mutual coupling. The preliminary direction of arrival (DOA) is estimated using the whole array for high resolution. Further refinement can then be conducted by estimating the angularly dependent coefficients (ADCs) with the subspace theory. The mutual coupling coefficients are finally determined by solving the least squares problem with all of the ADCs utilized without discarding any. Simulation results show that the proposed method can achieve better performance at a low signal-to-noise ratio (SNR) with a small-sized array and is more robust, compared with the similar processes employing the initial DOA estimation and further improvement iteratively.