Search Results (41,169)

The Controller Area Network (CAN) remains the backbone of in-vehicle communication, but its lack of built-in security exposes safety-critical systems to cyberattacks. This paper presents a real-time, reconfigurable, specification-driven intrusion detection system (IDS) implemented on a custom test bench that emulates an EV powertrain. The CAN traffic captured from the four-ECU setup formed the dataset used in this study. The IDS enforces a compact, reconfigurable ruleset covering timing bounds, jitter envelopes, identifier whitelists, frame format, data length code (DLC) compliance, bus-load thresholds, application-level CRC, and alive-counter verification. The IDS achieves detection times below 2 ms with false positive rates under 1% for injection, denial of service (DoS), and fuzzy attacks, even at CAN bus loads up to 70%, while microcontroller resource usage remains within the constraints of automotive-grade devices, supporting deployment in embedded environments. The main contributions of this study are as follows: (i) a validated and reproducible EV powertrain test bench with millisecond-level timing, (ii) a deployable and easily reconfigurable ruleset with deterministic runtime, and (iii) a latency-oriented evaluation framework that is portable across automotive microcontroller platforms. The EV powertrain dataset v1.0 was released in a public GitHub repository to facilitate reproducible research and enable future benchmarking studies. Full article

Partial discharge (PD) measurements are crucial for evaluating the condition of the insulation systems of medium-voltage (MV) cables and their accessories. However, identifying PD defect types from phase-resolved partial discharge (PRPD) patterns still largely relies on expert knowledge. In this paper, the authors critically evaluate lightweight deep neural network architectures for automated classification of insulation defects from PRPD patterns: YOLOv8n, the MobileNetV2–YOLO hybrid network, and a compact SqueezeNet-based model. PD measurements were performed in a controlled environment in a factory laboratory for MV power cables in order to better evaluate the capability of the investigated models. The results demonstrate that lightweight deep neural architectures can effectively classify PRPD patterns and be deployed in a real measurement environment. The proposed approach has been integrated with the OMICRON MPD Suite measurement system, enabling automated defect recognition and visualisation during routine testing of MV cable. Full article

Ti-6Al-4V parts fabricated via selective laser melting (SLM) often exhibit severe surface irregularities that limit their direct engineering application. This study proposes a top-hat beam laser polishing method to improve surface quality. The results show that surface roughness (Sa) is reduced to 0.48 μm, a 95.3% decrease from the as-built condition. The uniform energy distribution of the top-hat beam stabilizes melt pool behavior, enabling effective surface leveling through valley filling and lateral melt flow. In contrast, Gaussian beam polishing induces strong Marangoni convection and wake effects, resulting in higher residual roughness. Microstructural analysis indicates an increased fraction of equiaxed α grains and a β-phase content of ~6% after top-hat polishing. The heat-affected zone likely exhibits a subcritical heat-treatment-like effect, promoting fine secondary α precipitation. Additionally, localized stresses induced by steep thermal gradients during SLM are effectively relieved. Overall, top-hat laser polishing is a promising post-processing technique for enhancing the surface quality of Ti-6Al-4V components. Full article

We report a curious numerical observation: If atomic nuclei are modelled as connect-sums of threefoil knots with alternating chirality, the ropelength of the composite knot—a purely geometric quantity requiring no quantum mechanics—tracks the experimental binding-energy curve from hydrogen to uranium. A two-parameter fit to 50 nuclei gives $R^2=0.9998$ (coefficient of determination; 1 = perfect fit) and $\mathrm{RMS}=6.9\mathrm{MeV}$ (root-mean-square deviation between model and experiment), comparable to the five-parameter Bethe–Weizsäcker formula ($\mathrm{RMS}=8.3\mathrm{MeV}$) at less than half the parameter count. Out-of-sample predictions for ${}^{244}\mathrm{Pu}$ and ${}^{252}\mathrm{Cf}$, not used in the fit, are accurate to $0.4\mathrm{MeV}$ and $8.4\mathrm{MeV}$, respectively. What makes the observation worth reporting is not the fit itself, but the range of nuclear phenomenology that emerges uninstructed from the topology: saturation, surface energy, isospin pairing, odd-even staggering, and geometric analogues of nuclear isomers all appear as consequences of the connect-sum construction, without additional assumptions. We catalogue these correspondences, assess which are structural and which may be coincidental, and identify concrete numerical tests that would distinguish the two possibilities. Full article

Background/Objectives: Cancer remains one of the leading causes of mortality worldwide, with lung and colon cancers among the most prevalent. Conventional histopathological diagnosis is time-consuming, requires expert pathologists, and is susceptible to human error. Methods: To address these limitations, this study proposes an automated classification framework for lung and colon cancer using histopathological images. The proposed method employs a lightweight pretrained deep learning model, MobileNetV3-Small, through transfer learning. Training is performed on an enhanced version of the LC25000 dataset, in which redundant image patches are removed to improve robustness and clinical generalizability. The images were initially available in multiple resolutions, which are resized to 224 × 224 × 3 to match the canonical input size of MobileNetV3-Small. Deep features are extracted from the dropout layer as it provides regularized representation of high-level features by reducing the overfitting (dimension N × 1024), which are optimized using a differential evolution algorithm, reducing the feature space to N × 60. These optimized features are evaluated using multiple classifiers. Results: Experimental results demonstrate a maximum classification accuracy of 98.14% using a Quadratic Support Vector Machine (SVM) and a 21.3× speed-up achieved with bagged trees, outperforming several state-of-the-art approaches representing a 3.34% improvement over the baseline study on the enhanced dataset. Conclusions: The results confirm that the proposed framework effectively balances high accuracy with computational efficiency. The use of a lightweight deep model combined with feature optimization makes the approach well-suited for practical clinical environments. Full article

Pt–transition metal intermetallic compounds have been recognized as promising catalysts for oxygen reduction reaction (ORR). However, further enhancing the activity and durability of this kind of catalyst is still necessary. Herein, we report a novel L1₀-type PtFe intermetallic nanoalloy with the partial substitution of Fe sites by La as a highly active and stable catalyst towards ORR. This new intermetallic nanoalloy retains an ordered structure after the incorporation of La confirmed by XRD, XPS and TEM results and the ordered PtFe_0.5La_0.5 nanoparticles are embedded in porous carbon (L1₀-PtFe_0.5La_0.5@C) in very uniform particle size of around 2 nm. This L1₀-PtFe_0.5La_0.5@C catalyst exhibits a half-wave potential of 933 mV, which is about 12 mV and 70 mV higher than those of L1₀-PtFe@C and commercial Pt/C catalysts, respectively. Moreover, it also achieves an enhanced mass activity of 0.79 A mg_Pt⁻¹ at 0.90 V, which outperforms the performance of commercial Pt/C (0.10 A mg_Pt⁻¹). In addition, it also shows excellent stability with only 3 mV negative shift in half-wave potential after 20k CV cycles of accelerated durability testing. This high activity and stability may be attributed to the incorporation of La in the PtFe lattice, which induces the formation of a compressively strained Pt overlayer in acidic media which not only tunes the surface strain of Pt sites but also possesses robust resistance to the dissolution of Fe and La. This work also provides a new direction for the development of Pt-based intermetallic catalysts for efficient catalysis applications. Full article

This paper presents a nanowatt-scale operational transconductance amplifier (OTA) and an electronically tunable third-order low-pass filter (LPF) designed for energy-constrained biomedical signal conditioning. The circuits are implemented in a 65 nm CMOS process and verified through comprehensive schematic-level simulations. Biased in the deep subthreshold region at 1 nA, the OTA achieves a 50 dB low-frequency gain, a 225 Hz unity-gain bandwidth at 10 pF load capacitance and an input-referred noise floor of 1.55 μV/√Hz, with a total power consumption of only 1.75 nW. The integrated third-order LPF provides a wide tuning range (37–668 Hz) via bias current modulation, exhibiting excellent linearity with a THD of 0.059% and a 65.3 dB dynamic range. Monte Carlo and PVT corner analyses demonstrate the design’s theoretical robustness against process variations and environmental fluctuations. ECG signal simulations validate the circuit’s effectiveness in suppressing high-frequency artifacts while preserving morphological integrity, providing a proof-of-concept for ultra-low-power wearable healthcare architectures. Full article

Ti alloys are widely used in aerospace and biomedical fields due to their high mechanical properties under severe loading. Interest in additively manufactured Ti6Al4V has increased, but further research is needed to fully characterize their properties. This work compares the effects of surface properties, internal defects, microstructure, hardness, and Hot Isostatic Pressing (HIP) or Vacuum Heat Treatment (VHT) on the fatigue behavior of Ti6Al4V produced by Selective Laser Melting (SLM) and Electron Beam Melting (EBM). Printing parameters and post-processing were optimized to achieve high density and minimal porosity, providing a solid basis for realistic fatigue comparisons. Samples were characterized in terms of microstructure (optical microscopy and SEM), mechanical properties (hardness mapping), surface texture (confocal microscopy), and internal defects (image-based analysis). Uniaxial fatigue limits were determined by a Dixon-Mood staircase method, and failed specimens were analyzed for fracture surfaces and defect areas. Applied load on flaws was evaluated to identify root causes of fatigue failure. Results showed that fatigue of as-printed samples is governed by surface roughness, while machined specimens are controlled by internal defect size. Machining increased the fatigue limit roughly threefold, and HIP further improved it by 10–20% by reducing internal porosity. In conclusion, with properly optimized melting parameters, both EBM and SLM produce similar mechanical performance at comparable roughness, supporting their use for structural components. Full article

We investigate the effects of post-annealing in oxygen (O₂) and nitrogen (N₂) on tin-doped vanadium oxide (V_xSn_yO_z) films for microbolometer applications. The films were deposited using magnetron sputtering in an Ar:O₂ environment. We demonstrate that low Sn doping combined with N₂ post-annealing provides an effective approach to optimize the temperature coefficient of resistance (TCR), resistivity, and 1/f-noise. Compared to undoped VO_x, V_xSn_yO_z films exhibit an enhanced TCR, moderate resistivity, and reduced 1/f-noise. The 135 nm thick V_0.46Sn_0.03O_0.51 film after post-annealing in N₂ shows a TCR of −4.08%/K and a resistivity of 7.3 × 10⁻² Ω⋅cm at 300 K, an absorptance of 63–68% in the 900–2500 nm wavelength range, and low noise voltage power spectral density (1.77 × 10⁻¹⁶ V²/Hz at 100 Hz under 0.3μA bias current). These results indicate that Sn-doped VO_x films are promising sensing materials for microbolometer applications. Full article

Organic redox-active molecules are promising catholyte materials for aqueous organic redox flow batteries (AORFBs), yet they often suffer from low solubility and poor cycling stability. Herein, we report a series of water-soluble phenothiazine derivatives functionalized with quaternary ammonium groups. The optimized compound, N,N,N-trimethyl-1-(10H-phenothiazin-10-yl) propan-2-aminium chloride (TMiPrPTCl), exhibits exceptional solubility (2.69 M in water) and a high redox potential (0.902 V vs. SHE). A comparative study of four derivatives reveals that side-chain length and branching critically modulate both solubility and degradation pathways: while three-carbon-linked analogs N,N,N-trimethyl-3-(10H-phenothiazin-10-yl)propan-1-aminium chloride (TMPrPTCl) degrade primarily via irreversible oxidation to sulfoxide, two-carbon-linked species (TMiPrPTCl) undergo additional side-chain cleavage, leading to rapid capacity fade. Although the quaternization strategy successfully achieves record solubility, the electrochemical stability remains a key challenge. Post-cycling analysis confirms the loss of redox activity and the formation of inert products. This work highlights the delicate balance between solubility enhancement and molecular stability, providing clear design guidelines for future phenothiazine-based catholytes. Full article

Background/Objectives: SARS-CoV-2 is the causative agent of COVID-19, an infectious viral respiratory disease with human-to-human transmission. Current molecular understanding of how hosts respond to infection by respiratory viral pathogens in general and to SARS-CoV-2 in particular is still a research field under development. The activation levels of various host pathways are dependent on several variables, including the host tissue compartment. Methods: In this work, Illumina RNA sequencing was performed to assess the transcriptional host response to SARS-CoV-2 infection using COVID-19 PCR testing nasopharyngeal (NP) swab remnants from twenty infected and nine non-infected individuals. Results: Differential gene expression (DGE) analysis identified 182 overexpressed genes, with strong enrichment in innate immune and viral response genes. This included a significant induction of IFIH1/MDA5, a pattern recognition receptor (PRR) gene participating in the initial sensing of viral RNAs and subsequent cascade activation of interferon (IFN) and IFN-stimulated genes (ISGs). Interestingly, we observed different levels of concordance with previous similar studies and a significant induction of RIG1 and TLR3, two PRR genes encoding proteins that function to upregulate IFN and ISGs, but which are not normally identified as differentially expressed genes (DEGs). Finally, the overexpression of MX1, a well-characterized biomarker of viral infection; IFIT1, one of the top upregulated genes; and OAS1, OAS2 and OAS3, genes with a molecular function, 2-5-oligoadenylate synthase activity, identified as enriched in the DGE analyses, was confirmed by RT-qPCR. Conclusions: This study provides insights into upper respiratory tract responses to SARS-CoV-2 infections and identifies a set of differentially expressed genes (DEGs) with potential as candidates for further investigations as viral infection biomarkers. Full article

Background: Hematological patients have a high risk of developing severe COVID-19 (37%). Most mRNA vaccine trials in hematological patients showed a low immunogenicity after two doses, while long-term data are scarce. Methods: In this monocentric retrospective observational study, we evaluated humoral and T cell-mediated immune responses in 230 hematological patients after three doses of the Pfizer-BioNTech mRNA COVID-19 vaccine. Patients were stratified by age, disease type/state, prior COVID-19 infection, and treatment status and regimens (anti-CD20 monoclonal antibodies, BTK and BCL-2 inhibitors, and treatment line). Antibody titer to SARS-CoV-2 was assessed by electrochemiluminescence immunoassay and T cell response by QuantiFERON interferon-γ release assay (IGRA). Data were analyzed using univariate (Fisher’s exact test) and Firth’s bias-reduced penalized-likelihood logistic regression. Results: A robust humoral response was observed with 91.55% of patients developing anti-spike antibodies (GMT 988.83 U/mL). Anti-CD20-bendamustine treatment was associated with a significantly lower antibody positivity compared to untreated subjects. Prior COVID-19 infection significantly boosted both antibody positivity (95.9% vs. 85.2%) and GMT (847.02 U/mL vs. 258.79 U/mL). Conversely, T cell response was suboptimal (36.1% positive), particularly in anti-CD20-bendamustine-treated and multi-treated patients (27.1%), but highest in those treated with BTK inhibitors (50%). Multivariable logistic regression analysis linked multiple treatments to lower T cell response. Following vaccination, 29.1% of patients contracted SARS-CoV-2, but only 0.89% developed severe COVID-19. Conclusions: Three doses of mRNA vaccine elicit a strong humoral but a low T cell response, as detected by IGRA, in hematological patients. These findings underscore the importance of completing vaccination before initiating immunosuppressive therapies. Full article

There is a risk of wire breakage and falls when constructing high-voltage transmission lines. If this occurs, it seriously endangers the safety of crossing objects. As key structures commonly used in power construction to protect crossing facilities from wire breakage, the scientific design and accurate calculation of the safety margins for suspension-crossing frames are particularly important. However, the existing energy transfer mathematical model for impact-bearing cables after conductor fracture cannot accurately describe the physical process, and the value of the fixed break impact coefficient (e.g., 2.89 for the double circuit) adopted in the design specification is not sufficiently accurate. Thus, there is a large deviation in the bearing cable safety factor, which can cause the safety margin to be either too large or insufficient, in turn seriously affecting the safe and efficient completion of cross-line construction. To this end, in this study, we first constructed a mathematical model of impact energy conversion based on the law of conservation of energy; then, we proposed an accurate method for calculating the safety factor of the bearing cable. To verify the method’s accuracy, a full-scale true wire breakage impact test was conducted. The results show that the error between the impact coefficient calculated by this method and the test result is only 6.7%, significantly better than the 38.3% error, found when the traditional design specification is used to fix the value. This method is applied to a 220 kV crossing project case. The analysis shows that, to meet the same safety requirements, the model recommends the use of Φ12 Dyneema rope, while the traditional method requires Φ16 Dyneema rope; simultaneously, for the Φ18 Dyneema rope, the maximum allowable span calculated by this method is 450 m, which is greater than the 400 m calculated using the traditional method. Thus, this method can calculate a more accurate impact coefficient based on actual working conditions, thereby significantly optimizing the selection of load-bearing cables and increasing the upper limit of span design while ensuring construction safety. Overall, the research conclusions provide important theoretical and technical support for optimizing the design and safety check of the suspension-crossing frame. Full article

Genetic diversity and antifungal susceptibility profiles of Aspergillus fumigatus are critical for understanding the evolution of resistance in clinical and environmental settings. We performed comprehensive genomic characterization of A. fumigatus isolates using whole-genome sequencing combined with phenotypic susceptibility assays. SnpEff-based variant annotation identified 76,079 single-nucleotide polymorphisms, revealing a high proportion of mutations (78.8%) in upstream and downstream regulatory regions, whereas high-impact coding variants remained rare (0.083%). Several key mutations were identified, including the well-established cyp51A M220V and HMG1 S212P/Y564H mutations. Moreover, a diverse array of peripheral cyp51A polymorphisms (M39I, E402D, N248K, and K372N) was detected, although these variants did not correlate with the resistant phenotypes. Our comparative genomic analysis identified a novel A586T substitution in the FKS1 gene in an isolate with an elevated minimum effective concentration of caspofungin, suggesting its possible association with reduced susceptibility, although functional validation is required. In isolates lacking canonical target-site mutations, the high frequency of regulatory-region variants indicated the involvement of non–target-site mechanisms. This study provides a detailed map of the genomic landscape of A. fumigatus and identifies candidate loci for future functional validation. Our results demonstrate the utility of high-throughput genomic surveillance for monitoring emerging resistance trends and characterizing the genetic background of clinical fungal pathogens. Full article

Licania tomentosa leaf extract was used to synthesize zinc oxide nanoparticles (ZnO NPs) which were systematically analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-Visible (UV-Vis) and Fourier transform infrared (FT-IR) spectroscopies and energy-dispersion X-ray spectroscopy (EDS) methods. Based on XRD scans, the green NPs have an average crystallite size of 15.9 nm as estimated using the Scherrer equation and have a roughly spherical shape with an average diameter of 25.15 ± 1.2 nm as calculated from SEM data. As estimated from the Tauc plot based on UV-Vis absorption spectra, ZnO NPs have a small band gap of 3.0 eV. The biosynthesized ZnO NPs were effectively utilized for the photodegradation of methylene blue (MB) and crystal violet (CV) dyes under UV illumination with resulting MB and CV degradation efficiencies of ~94% and ~81% after 60 min and 70 min, with pH = 12 and pH = 10, respectively. Different experimental parameters such as NPs quantity, experimental pH, light intensity and initial concentration of dyes were varied to test the performance of the catalyst. Furthermore, efficient recycling of the catalyst was demonstrated. We also undertook antimicrobial studies of the green ZnO NPs. The ZnO NPs demonstrated broad-spectrum antimicrobial efficacy against Escherichia coli ATCC 35218, Enterococcus faecalis ATCC 29737, Klebsiella pneumoniae ATCC 700603, Pseudomonas aeruginosa ATCC 27853, P. aeruginosa B3, Staphylococcus aureus ATCC 29213, and S. aureus SA01, with the minimum inhibitory concentration (MIC) and the inhibitory concentrations associated with 50% effect (IC50) values ranging from 250 to 2000 µg/mL and 7.74 to 283.14 µg/mL, respectively. The nanoparticles also significantly inhibited biofilm formation by E. faecalis ATCC 29737, P. aeruginosa ATCC 27856, and S. aureus SA03. The antimicrobial efficiency of the ZnO NPs against Escherichia coli ATCC 25922 and Staphylococcus aureus SA03 isolates was also assessed using the disk diffusion assays. Taken together, our results reveal that the biosynthesized ZnO NPs are promising multifunctional materials with potential applications in antimicrobial treatments, biofilm control, and photocatalytic remediation. Full article