Search Results (242)

LiDAR–camera fusion is widely used for 3D perception in intelligent connected vehicles, but a clean camera branch does not necessarily compensate for structured LiDAR corruption. We propose CMS-Attack, a cross-modal search framework in which only the LiDAR point cloud is perturbed while the camera input remains unchanged; here, “cross-modal” denotes that a single-modality LiDAR perturbation propagates through the LiDAR–camera fusion process and disrupts the multimodal detector, rather than simultaneous perturbation of both modalities. The framework has the following two access-dependent routes: the gray-box route contains FB-CMS, which uses camera-BEV, LiDAR-BEV, fused-BEV, and detection-head responses to construct a target-aware prior and prune an over-complete candidate pool, and Adaptive CMS, which substitutes architecture-specific intermediate responses; the decision-only black-box route contains FC-CMS, which refines candidates solely from display-level target states. On the nuScenes validation split, FB-CMS reduced matched target confidence from 0.80 to 0.03 under 140 injected points, corresponding to a 96.1% relative drop and 100% ASR@0.3. The ten-query FC-CMS achieved 58.97% ASR@0.3, compared with 6.17% for random frustum spoofing. On the query-based FUTR3D detector, Adaptive CMS reduced the mean matched-target score from 0.642 to 0.058, corresponding to a 90.97% relative reduction and 93.42% ASR@0.3. Intermediate camera-, LiDAR-, and fused-BEV region energies changed by less than 0.8% despite target suppression, indicating disruption at the fusion-decision stage (defined here as the decoder/detection-head and post-processing path from fused representations to final object predictions) rather than a collapse of BEV feature magnitude. These results show that structured LiDAR fabrication is substantially more disruptive than information removal and that generic outlier filtering incurs a robustness–accuracy tradeoff. Full article

This study aimed to optimize the spray-drying (SD) process for aquafaba and compare the physical and techno-functional properties of the resulting powder with those of its freeze-dried (FD) counterpart. A Box–Behnken design was employed to evaluate the effects of inlet air temperature (150–190 °C), air speed (3.5–4.3 m/s), and feed flow rate (0.3–0.5 L/h) on 14 quality responses. The optimized SD conditions were determined to be an inlet air temperature of 189 °C, an air speed of 4.2 m/s, and a feed flow rate of 0.3 L/h. Validation experiments demonstrated that the developed models had high predictive capacity, with only a small discrepancy (0.56–5.88%) between the predicted and experimental values. Comparative analysis showed that the optimized SD powder had significantly lower moisture content (2.47%) and water activity (0.18) than the FD powder (3.51% and 0.34, respectively), indicating superior storage stability. In addition, the SD powder exhibited greater whiteness (82.37), higher water solubility (88.44%), and substantially greater foaming capacity (266.67%) than the FD sample (243.33%). Although the FD powder demonstrated better wettability and water absorption capacity because of its porous structure, FTIR spectroscopy and protein secondary structure analysis confirmed that SD preserved the functional integrity of aquafaba. Specifically, SD induced a transition from disordered random-coil structures to more ordered β-sheet and β-turn configurations, thereby improving foaming performance. Overall, these findings indicate that optimized spray-drying is a highly efficient and industrially scalable alternative to freeze-drying for producing functional aquafaba powder for use as a plant-based egg substitute. Full article

The MAT1-1-1 and MAT1-2-1 proteins perform essential DNA-binding activities and regulation of the transcription of genes governing sexual reproduction in Ophiocordyceps sinensis. Previous studies have documented differential occurrence, alternative splicing, and transcriptional divergence of MAT1-1-1, MAT1-2-1, and pheromone receptor genes in Hirsutella sinensis (Genotype #1 among 17 genome-independent genotypes of O. sinensis fungi). In the present study, we analyzed the natural pairing patterns of structurally variant MAT1-1-1 and MAT1-2-1 proteins simultaneously produced by each of 20 purportedly homogenous O. sinensis strains, based on AlphaFold-predicted 3D structural models and pairwise structural superposition analyses. The differentially naturally paired mating proteins exhibited distinct heteromorphic stereostructures across strains. Specifically, the MATα_HMGbox domain of MAT1-1-1 and the HMG-box_ROX1-like domain of MAT1-2-1 displayed variable N- and/or C-terminal truncations, 1–4 amino acid substitutions at distinct sites, and concomitant alterations in hydrophobic properties and secondary/tertiary structural configurations. Thus, the differentially naturally paired but structurally divergent mating proteins support heterogeneous fungal origins within the analyzed O. sinensis strains and are inconsistent with a strictly self-fertilization reproductive model. Our findings suggest that O. sinensis adopts a self-sterile reproductive strategy, potentially involving heterothallic mating or hybrid reproduction during the lifecycle of the LEVEL-II protected Cordyceps sinensis insect–fungal complex endemic to the Qinghai-Tibet Plateau. Full article

Sugarcane bagasse (SCB) represents an abundant lignocellulosic residue with significant potential for integrated biorefinery applications. In this study, an alkaline extraction process was optimized for lignin recovery from SCB using a Box–Behnken Design (BBD) to evaluate the effects of extraction temperature (70–110 °C), NaOH concentration (3–9%, w/v), solid-to-liquid ratio (1:10–1:50, g mL⁻¹), and extraction time (30–90 min). Total phenolic content (TPC) and pure lignin content (PLC) were employed as response variables to identify optimal extraction conditions. Under the optimized parameters, a lignin yield of 17.7% and a TPC of 52.7 mg GAE g⁻¹ were achieved. Structural and thermal characterization by Fourier-transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA) confirmed the preservation of characteristic lignin functionalities and adequate thermal stability for downstream applications. To demonstrate its valorization potential, the recovered lignin was successfully incorporated as a partial substitute for petroleum-derived phenol in the formulation of a lignin-based resin, providing a proof of concept for its utilization in sustainable polymeric materials. In parallel, the cellulose-enriched residual solid (RS) obtained after lignin extraction was subjected to fermentation, yielding 10.3 g L⁻¹ ethanol. This integrated strategy enabled the sequential production of lignin-derived materials and bioethanol from a single biomass feedstock, maximizing resource utilization while minimizing waste generation. The findings highlight the feasibility of coupling lignin recovery with biofuel production and support the development of SCB-based biorefineries for the generation of renewable chemicals, bio-based materials, and sustainable energy carriers. Full article

Resource-constrained Internet-of-Things (IoT) terminals require encryption engines that combine low silicon cost with adequate throughput, a balance that is hard to reach with general-purpose software alone. This paper presents an LBlock lightweight block cipher coprocessor tightly coupled to an open-source RISC-V (Hummingbird E203) core through the NICE custom-instruction interface. LBlock serves here as a compact Feistel-cipher benchmark targeting legacy and low-volume IoT deployments rather than as a substitute for newer standards such as ASCON. We exploit two structural properties of LBlock: first, its 4-bit S-boxes map naturally onto the six-input look-up tables (LUTs) of modern FPGAs, so the entire substitution layer is realized as eight parallel single-LUT-depth tables instead of multi-cycle table lookups. Second, the LBlock key schedule is a one-way feedback-free recurrence, which lets us refactor key expansion from an independent multi-cycle sequential module into a pure combinational function that is fused with the round function and executed in the same clock cycle. The resulting encryption core performs one round per cycle, reducing core-only single-block latency from 226 cycles in the baseline implementation to 34 cycles, while the complete NICE coprocessor operation requires 85 cycles including data movement, instruction issue, computation, and write-back. The design is described in Chisel and integrated as a coprocessor with three custom instructions. On an FPGA-based SoC, the coprocessor produces outputs identical to the LBlock test vectors and accelerates encryption by 121.45× over a software baseline on the same core, while the encryption core reaches 321.7 MHz (643 Mbps) on Artix-7 and up to 472.2 MHz (944 Mbps) on Virtex-7 while occupying only 187 LUTs, as validated across three FPGA families. These results show that matching the algorithmic symmetry of LBlock to the underlying hardware fabric yields a lightweight and low-overhead cryptographic accelerator suitable for RISC-V IoT endpoints. Full article

We present Dipper, a lightweight 64-bit block cipher with 96-bit and 128-bit key variants, built on a 28-round hybrid SPN–ARX structure. Each round applies a full-state key addition, sixteen parallel 4-bit GIFT S-boxes, four word-wise rotations, two 16-bit modular additions over half of the state, and the GIFT-64 bit permutation, combining the compact substitution layer of GIFT-style designs with the diffusion efficiency of ARX operations. We evaluate Dipper from both hardware and cryptanalytic perspectives under a single, fully open-source methodology. Round-based Verilog implementations were synthesized alongside PRESENT, GIFT, and SIMON variants using an identical Yosys + ABC + Nangate45 flow. Under this flow, Dipper-64/96 and Dipper-64/128 require 2498 and 2824 gate equivalents (GE), respectively, both falling between GIFT-64-128 (2191 GE) and PRESENT-128 (2963 GE); notably, Dipper-64/128 is more compact than PRESENT-128 at the same key size, despite incorporating an additional ARX diffusion layer. A broader comparison re-implements eleven established lightweight ciphers under the same flow, and post-place-and-route FPGA results on Lattice ECP5, measured software timings, and Cortex-M memory footprints support deployment across RFID, sensor-node, and edge-gateway scenarios. For differential resistance, we develop a mixed-integer linear programming (MILP) model that couples the exact GIFT differential distribution table with a Lipmaa–Moriai encoding of modular addition. Predicted and empirical differential probabilities agree tightly for reduced-round variants, while five-round trails reveal differential clustering. The security evaluation further includes proven-optimal linear trail bounds up to ten rounds, an exhaustive impossible-differential search bounding the longest distinguisher at five rounds, and experimental integral distinguishers of at most five rounds, leaving the 28-round cipher a margin close to 3× against the longest identified distinguisher. All RTL, synthesis scripts, reference implementations, and MILP models are released for full reproducibility. Full article

Pulmonary nodules are circular or irregular lesions visible on chest computed tomography (CT), and their early detection is critical for lung cancer screening. Deep learning detection algorithms have been widely adopted for pulmonary nodule diagnosis; existing lightweight models suffer from redundant network parameters and low detection accuracy for tiny lesions. To address these limitations, this study proposes an improved detection model based on YOLOv8n. First, Omni-Dimensional Dynamic Convolution (ODConv) replaces static convolution in the backbone to enhance multi-morphology nodule feature extraction. Second, the Convolutional Block Attention Module (CBAM) is embedded at multiple positions of the neck network to suppress background interference from blood vessels and normal lung parenchyma. Third, Complete Intersection over Union (CIoU) loss is substituted by Wise Intersection over Union (W-IoU) to optimize bounding box regression for hard samples with blurred boundaries. Experiments on the LUNA16 dataset show that compared with the original YOLOv8n, the proposed model improves Precision by 6.3%, Recall by 8.6%, mAP50 by 3.4%, and mAP50-95% by 2.7% while maintaining high inference speed. Additional generalization verification on the LIDC-IDRI multi-center dataset further proves the robustness of the proposed lightweight architecture, which achieves balanced accuracy and real-time performance compared with mainstream detection models. Full article

This paper presents TALOS, a unified reusable 6G CryptoProcessor architecture for high-assurance symmetric security services under a 256-bit private-key baseline. The design addresses a core hardware challenge in future mobile systems: supporting heterogeneous strong symmetric primitives without duplicating complete cipher cores. TALOS combines a Hierarchical Common Data Path (HCDP) with a three-tier cryptographic encapsulation model spanning AES-256, Snow 5G/SNOW-V-class, and ZUC-256. Tier-1 captures native nonlinear substitutions, Tier-2 compiles bounded arithmetic nonlinearities into exact micro-S-boxes, and Tier-3 consolidates shared permutation, XOR, affine, diffusion, and state-transport fabrics. This decomposition preserves cipher correctness while exposing realistic sharing opportunities across substitution, arithmetic, and linear transport layers. The architecture also supports confidentiality processing and integration with integrity- and authentication-oriented service logic through a common control/resource framework. Compared with monolithic universal-box or loosely aggregated multi-core approaches, TALOS provides a disciplined, RTL-oriented taxonomy for crypto-agile symmetric-core hardware. The proposed framework advances 6G cryptographic hardware design by combining operator-exact reuse, architectural scalability, and implementation-oriented efficiency within a single CryptoProcessor paradigm. Full article

Background: Mutations in the FBXO7 gene (PARK15) cause an autosomal recessive, early-onset neurodegenerative disorder typically presenting as Parkinsonian-Pyramidal Syndrome (PPS). Despite its recognition, the high phenotypic variability often delays diagnosis. Here, we report a novel Italian family and synthesize data from all published cases to date, offering an updated clinical and molecular overview of the disease. Methods: We performed clinical and molecular characterization of a newly identified family. Furthermore, we conducted a systematic literature review (from 2008 to 2026) to aggregate clinical, genetic, and geographic data of all reported PARK15 cases. Results: Two siblings presented with a complex phenotype including early-onset parkinsonism, cognitive decline, psychiatric symptoms, and aphasia-type speech disorders. Genetic analyses identified two novel likely pathogenic variants: a missense substitution in the UBL domain (p.Ile74Met) and a frameshift indel (p.Val233GlufsTer8). The literature review (incorporating clinical data from Europe, Asia, and South America) confirms a high prevalence of postural instability (87.5%), bradykinesia (83.3%), and pyramidal signs (~60%). We observed a distinct distribution of variants: missense mutations cluster in the N-terminal UBL and F-box domains, while truncating variants are more common in the C-terminal region. Discussion: Our findings expand the FBXO7 mutational landscape and underscore the “atypical” clinical markers, such as pyramidal signs and cognitive decline, that distinguish PARK15 from other recessive forms of parkinsonism like PARK2 and PARK6. The dual role of FBXO7 in mitochondrial quality control and proteasomal assembly suggests a broad disruption of cellular homeostasis. These observations refine genotype–phenotype correlations and may guide variant interpretation in routine diagnostic settings. Full article

Repetitive head impacts (RHIs) in combat and contact sports are associated with long-term neuropsychological consequences. The present study explores episodic memory performance, with a focus on pattern separation, a memory process associated with hippocampal function, in athletes characterized by different exposure profiles to RHIs. The study included 26 fighters (boxing, Mixed Martial Arts, Muay Thai), 20 rugby players, and 26 age-matched controls. Participants completed the Mnemonic Similarity Task (MST) and additional cognitive measures (Digit Span, Digit Symbol Substitution Test, Attentional Matrices, and N-back tasks). Group differences were assessed using ANCOVAs. Results indicated that fighters exhibited significantly poorer pattern separation performance compared to both rugby players and controls. Rugby players also performed worse than controls on the pattern separation measure, revealing a graded pattern of performance across groups. Additionally, fighters demonstrated slower reaction times during the MST and lower performance on the N-back tasks relative to both comparison groups. Overall, athletes participating in sports characterized by different exposure profiles to RHIs showed distinct patterns of cognitive performance, with the most pronounced differences observed in fighters. These findings highlight pattern separation as a potentially sensitive cognitive marker in athletes participating in combat and contact sports and underscore the need for longitudinal studies incorporating objective measures of head-impact exposure. Full article

Most remote sensing extraction studies utilizing vegetation indices typically classify and extract land cover features based on the phenological characteristics of the study area or rely on a single vegetation index. When attempting to extract multiple land cover types simultaneously, classification accuracy often declines significantly because a single vegetation index is unsuitable for all features. While some recent studies employ deep learning and neural networks for classification and extraction, their complex mechanisms and “black-box effect” hinder clear explanations for accuracy outcomes. In response to the issues outlined above, this paper proposes a simpler and more intuitive method for the hierarchical extraction of typical land cover features. This approach analyzes the difficulty of separating these features based on spectral reflectance data to determine the following extraction order: first water bodies, followed by reed, then Suaeda salsa, and finally tidal flat. Furthermore, by selecting appropriate parameters and substituting vegetation indices for bands that perform better, high extraction accuracy is achieved. The classification and interpretation results were validated using a combination of field survey data and Google imagery, together with a validation sample. Accuracy assessments using overall accuracy and Kappa coefficient demonstrate the following optimal results for the hierarchical approach: NDWI for water, S2REP for reeds, and MSAVI for Suaeda salsa. Overall accuracy reached 98.5% with a Kappa coefficient of 0.9796, validating the effectiveness of this spectral-feature-based hierarchical extraction method using diverse vegetation indices. Using a hierarchical extraction approach to classify typical land cover features in the study area from 2020 to 2025, accuracy rates exceeded 98% in all cases. Based on these classification results, the INVEST model was employed to simulate carbon stock trends in the Liaohe Estuary region over the past five years. The study found that, although factors such as tides and the date of image acquisition had a certain impact on the study area compared with the problems caused by historical development, the ecological environment in the study area is gradually stabilizing at the present stage. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects 25–30% of adults globally. Dietary sugar reduction is one of the key therapeutic targets, but elimination of sugar-sweetened foods may compromise adherence to calorie-restricted diets. Brazzein, a natural sweet protein that is 500–2000 times sweeter than sucrose, offers a promising substitute, yet clinical data in patients with MASLD are lacking. In a double-blind, randomized, two-period crossover trial, 103 adults with MASLD tasted iso-sweet vanilla ice cream sweetened with either brazzein or sucrose on two consecutive days. Overall impression and sensory attributes (appearance, color, aroma, taste, and texture) were rated on 5-point hedonic scales, and the percentage of the 100 g portion consumed was recorded. Brazzein-sweetened ice cream met the prespecified criteria for both non-inferiority and equivalence versus sucrose for overall impression. Top-2 box acceptance (ratings ≥ 4) was extremely high and nearly identical (96.1% for brazzein and 98.1% for sucrose). Mean consumption exceeded 98% of the portion for both products, with no significant difference between sweeteners. Secondary sensory ratings were closely similar, and multivariate analyses indicated highly overlapping sensory profiles. Exploratory subgroup analyses suggested consistent findings across most demographic and clinical characteristics, although participants with advanced liver fibrosis (LSM ≥ 9.6 kPa) showed numerically higher ratings for sucrose. In exploratory analyses, liver stiffness was associated with slightly lower intake at higher stiffness values. This study provides the first evidence that brazzein-sweetened ice cream maintains short-term sensory acceptability comparable to a conventional sucrose-sweetened product in adults with MASLD. These findings support further development and evaluation of brazzein-containing sugar-reduced foods, including repeated-exposure sensory studies and separate metabolic investigations. Full article

Existing chaos-based color image encryption algorithms still face several challenges, including insufficient dynamical complexity of low-dimensional chaotic maps, residual boundary regularity caused by fixed block partitioning, and limited diffusion among RGB channels. To address these issues, this paper proposes a color image encryption algorithm based on a three-dimensional sine-bilinear fully coupled chaotic map (3D-SBFCM). The proposed map integrates sinusoidal modulation, linear coupling, and bilinear cross-coupling within a mod-1 mapping framework, thereby improving the complexity and pseudorandomness of the generated chaotic sequences. In addition, a residual-feasibility-constrained dynamic rectangular partitioning mechanism is developed to generate reversible non-uniform image blocks and reduce the structural regularity associated with fixed-size partitioning. Based on this partitioning structure, inter-block permutation among same-size blocks and intra-block two-dimensional permutation are performed to weaken both global and local spatial correlations. Plaintext-related initialization, dynamic S-box substitution, and forward-backward cross-channel diffusion are further incorporated into the overall permutation-diffusion framework to enhance plaintext sensitivity, nonlinear confusion, and perturbation propagation across RGB channels. Experimental results demonstrate that the proposed algorithm effectively conceals the statistical characteristics of plaintext images, with information entropy values higher than 7.999 for all color channels and NPCR/UACI values close to their theoretical expectations. The algorithm also shows satisfactory robustness against cropping and noise attacks. These results indicate that the proposed method provides an effective and secure solution for color image encryption. Full article

PPV5 NS1 is a nonstructural and multifunctional protein comprising helicase and nuclease domains. The helicase domain contains conserved motifs from superfamily 3 helicases, including Walker A, Walker B, Motif B’, Motif C, and Box VII, whereas the nuclease domain consists of glutamate, a HUH motif, lysine, and tyrosine. In Mexico, the reported prevalence of PPV5 is higher than in other countries, with notable amino acid differences compared with pathogenic PPVs. This study compares the helicase and nuclease domains from a full-length PPV5 NS1 sequence with porcine parvovirus 1 (PPV1) and canine parvovirus (CPV) to characterize the protein further and perform three-dimensional (3D) modeling using bioinformatic tools, including solvent-accessible surface area (SASA) and electrostatic potential assessments. The main findings highlight the ATP-binding pocket, showing electrostatic values in PPV5 that contrast with PPV1 and CPV. The electrostatic potential 3D models suggest those differences involve non-conserved regions. In particular, the PPV5 Box VII surface is predominantly negative due to a glutamate substitution at position 7. In the nuclease domain, the interaction with Mg²⁺ differs between PPV5 and pathogenic PPV. The electrostatic findings suggest that these differences may have functional implications for both domains, but confirmation must be completed with functional assays. Full article

Background and Objectives: Sjögren’s disease (SjD) is a chronic autoimmune disorder in which the immune system attacks the glands that produce tears and saliva, leading to symptoms such as dry eyes and dry mouth. If left untreated, SjD can also cause inflammation and damage to other parts of the body, including the skin, lungs, kidneys, and nervous system, and increase the risk of developing lymphoma. The human leukocyte antigen (HLA) class II molecule HLA-DR3 is strongly associated with SjD. Materials and Methods: To investigate how post-translational modifications (PTMs) influence the presentation of SjD-associated autoantigens by HLA-DR3, we employed a computational framework to determine the binding of PTM-mimic peptides to HLA-DR3. We further supported the in-silico results with in-vitro experiments. Results: Our analysis revealed that PTM-mimic substitutions at canonical anchor positions rarely improved predicted binding affinity using the Stabilized Matrix Method, with most modifications resulting in reduced affinity. However, a comprehensive analysis of full-length SjD-associated autoantigen sequences (Ro60, Ro52, La) identified discrete regions with high densities of PTM-eligible anchor sites, specifically, the Ro60 HEAT solenoid, Ro52 RING/B-box/PRY-SPRY modules, and the La motif-RRM1 region, suggesting that PTMs may alter epitope presentation in a sequence-dependent manner. Experimental validation of selected PTM-mimic peptides showed enhanced T cell responses, which were associated with increased binding affinity to HLA-DR3. Structural modeling of a representative complex revealed that PTM-mimic peptides adopt a slightly shifted backbone orientation and altered side-chain positioning, leading to a larger peptide–DR3 interaction interface. Conclusions: These findings provide new insights into the role of PTMs in shaping the immunogenicity of SjD-associated autoantigens and highlight the potential for PTM-mimic peptides to modulate T cell responses in SjD. Full article