Search Results (254)

FAEST is a National Institute of Standards and Technology post-quantum signature candidate based on the Vector Oblivious Linear Evaluation-in-the-Head paradigm, whose signing performance is dominated by repeated Advanced Encryption Standard Counter-based Pseudorandom Generator calls. The reference implementation provides no FAEST-specialized acceleration for Advanced RISC Machine platforms. This paper proposes a three-layer Advanced Reduced Instruction Set Computer Machine NEON Single Instruction Multiple Data optimization: a register-resident 256-byte S-box with Table Lookup/Table Lookup with Extension-based SubBytes and four-way/eight-way parallel Advanced Encryption Standard processing; a fixed-length Pseudorandom Generator specialized for the FAEST tree structure; and Portable Operating System Interface for Unix thread-based parallelization of independent Vector Oblivious Linear Evaluation instances. Evaluated on all 12 parameter sets of FAEST v2 on Raspberry Pi 4 (without Advanced Reduced Instruction Set Computer Machine version 8 crypto-extensions) and Apple M2 (with hardware Advanced Encryption Standard support), the proposed method achieves signing speedups of up to 136.9x on Raspberry Pi 4 and 330.1x on Apple M2 over the pure-C reference. On Raspberry Pi 4, the NEON implementation outperforms OpenSSL; on Apple M2, the NEON-plus-Portable Operating System Interface for Unix thread configuration outperforms hardware-accelerated OpenSSL across all parameters, confirming that NEON SIMD combined with task-level parallelization can exceed hardware-accelerated single-thread throughput on Advanced Reduced Instruction Set Computer Machine-based platforms. Full article

This paper presents an ARMv8/NEON-oriented implementation of NCC-Sign targeting the NTT-friendly trinomial parameter sets (NCC-Sign-1/3/5), whose dominant cost arises from mixed-radix NTT computations with $n=2^a·3^b$. We design lane-local SIMD kernels—including a four-lane Montgomery multiply–reduce, a centered modular reduction pass, a fused stage-0 butterfly, and streamlined radix-2/radix-3 pipelines—and extend them with three further optimizations: (i) radix-2 multi-stage butterfly merging to halve intermediate load/store traffic, (ii) a stride-3 vectorization technique exploiting NEON structure load/store instructions (vld3q/vst3q) to fully vectorize small-len radix-3 stages that would otherwise fall back to scalar execution, and (iii) NEON-parallel pointwise Montgomery multiplication. Using cycle-accurate PMU measurements under identical toolchains for baseline and optimized builds on Apple M1 Pro, we observe geometric-mean speedups of 1.40× for key generation, 2.24× for signing, and 2.01× for verification across NCC-Sign-1/3/5, with per-kernel gains of up to 5–6× for NTT/INTT and 7.5× for pointwise multiplication. To contextualize these results, we provide a direct comparison with the NEON-optimized ML-DSA (Dilithium) implementation of Becker et al. on the same platform, a cross-platform evaluation on Arm Cortex-A72 (Raspberry Pi 4), a Montgomery-versus-Barrett microbenchmark supporting our design choice, and an empirical constant-time assessment via dudect confirming that no timing leakage is detected in any NEON kernel under 30 million measurements. Full article

Bulk metallic glasses (BMGs) are a type of amorphous metal with a high degree of mechanical strength, elasticity and corrosion resistance, properties that are highly influenced by composition and the processing of the material. BMGs can be applied in advanced engineering fields, such as aerospace, biomedical, MEMS, and industrial applications. Additive manufacturing (AM) is revolutionary in producing intricate BMG parts whilst maintaining the amorphous structure. The current review critically evaluates the recent development in AM of BMGs, such as the development of selective laser melting, electron beam melting, and directed energy deposition, and new classes of hybrid strategies. Enhancements in dimensional accuracy, amorphous retention, microstructural tailoring and functional performance are emphasized along with computational and real-time process optimization strategies to improve overall manufacturing efficiency and material quality. Subsequently, the challenges that still exist are addressed in the review, including crystallization during printing, the buildup of stress, printable thickness, complicated geometries, oxidation, contamination, and heterogeneous amorphous fractions. Lastly, multi-material printing, scalable AM approaches, and AI-assisted design solutions are key features of future perspectives to solve existing restrictions. The review provides an excellent guidance for the researcher and engineer interested in advancing additive manufacturing of BMGs with the best structure–property relations. Full article

Coloured and variegated leaves are common in shade-tolerant ornamentals. However, it remains unclear whether their photosynthetic performance is determined mainly by pigment abundance or by the organisation of chloroplasts and thylakoids. We tested this in three Epipremnum aureum phenotypes (‘Neon’, ‘Golden’ and ‘Jade’) that share a genetic background but contrast in leaf colour, chloroplast density and thylakoid membrane abundance. Plants were grown in a greenhouse and assessed by hyperspectral and thermal imaging, infrared gas exchange analysis, chlorophyll a fluorescence measurements, and structural, ultrastructural and biochemical analyses. Traits were integrated by principal component analysis, with the quantum yield of CO₂ assimilation per absorbed photon (αCO_2,abs) as the response variable. ‘Neon’ leaves had high specific leaf area and approximately 55% lower maximum Rubisco carboxylation (Vc_MAX) and electron transport capacity (J_MAX) than ‘Jade’, as well as reduced chloroplast and thylakoid abundance and warmer canopies, despite carotenoid enrichment. JIP-test parameters and fluorescence light–response curves showed high absorption and dissipation per PSII reaction centre, elevated excitation pressure, modest non-photochemical quenching (NPQ), low αCO_2,abs, small carbohydrate pools and low intrinsic water-use efficiency. ‘Jade’ leaves developed thick mesophyll with dense chloroplast populations, extensive thylakoid networks, highest NPQ, cool canopies and large carbohydrate reserves, whereas ‘Golden’ leaves combined thin laminae and intermediate chloroplast–thylakoid organisation with early light saturation of CO₂ assimilation and the highest intrinsic water-use efficiency. Principal component analysis revealed a structural axis of chloroplast and thylakoid organisation that better predicted αCO_2,abs, net carbon gain and canopy temperature than pigment abundance. In variegated E. aureum, ‘photon economy’ is therefore governed primarily by chloroplast and thylakoid membrane organisation and abundance rather than by carotenoid accumulation. Full article

Background: Niemann–Pick type C is a lysosomal storage disorder that results from pathogenic variants in the NPC1 gene or in some cases from NPC2 pathogenic alterations. The disease presents a remarkable clinical variability that in some cases resembles common diseases, often resulting in a diagnostic odyssey or at least delaying proper diagnosis. In addition, the NPC1 gene is highly polymorphic, and consequently, when missense variants are identified after gene sequencing, accurate classification of their pathogenicity is essential to ensure appropriate access to available therapies and to provide reliable genetic counseling. Objectives: To get insights into the pathogenicity of a novel variant in NPC1, p.Cys800Ser, we created stable cell lines expressing this variant, in parallel with cell lines expressing the NPC1 wild-type and NPC1 pathogenic variants. Methods: We leveraged an isogenic cell line in which the NPC1 gene was knocked down and subsequently infected it with retroviruses carrying NPC1-WT and NPC1 variants C-terminally fused with an mNeonGreen tag. Three different NPC1 variants were included in this study: two known pathogenic variants, p.Ala1035Val and p.Pro1007Ala, and the novel p.Cys800Ser, whose significance was unknown. Results: We observed in the stable cell line expressing NPC1 p.Cys800Ser that the mutated NPC1 protein is transported to the lysosome similarly to the p.Pro1007Ala variant and affects lysosomal distribution. Conclusions: Using this approach, we could analyze the pathogenicity of each variant separately and these cell lines could be used for personalized medicine-based approaches and multi-omic studies. Full article

High-temperature superconducting (HTS) technologies continue to advance as promising solutions for large-capacity rotating electrical machinery. However, the cryogenic architecture required to maintain superconducting states remains a critical design challenge, particularly for performance evaluation systems (PESs). Conventional helium–neon (He–Ne) circulation-based cooling enables stable low-temperature operation and has been experimentally validated in previous PES implementations, but it introduces substantial limitations due to installation complexity, flow-induced instability, and limited adaptability to different coil configurations. To address these constraints, this study proposes a conduction-cooled PES architecture optimized for HTS field coil testing and examines its thermal and structural characteristics through comprehensive design and finite element method (FEM)-based analysis. A multi-stage conduction cooling pathway using a cryocooler, thermal straps, and copper heat plates was designed to achieve uniform temperature distribution and reduce thermal gradients across the HTS winding. Three-dimensional FEM simulations were performed to evaluate the steady-state temperature distribution and heat-transfer characteristics of the proposed conduction-cooled PES under representative thermal load conditions, and the predicted cooling performance was comparatively assessed against the He–Ne cooled PES. The conduction-cooled PES was analyzed by comparing its predicted performance with previously obtained experimental results from the He–Ne cooled PES. The proposed conduction cooling architecture achieved a significant reduction in total heat load, decreasing from 177 W in the He–Ne system to approximately 78 W in the conduction-cooled configuration while also improving thermal efficiency and simplifying system integration. In addition, conduction cooling enhances compatibility with a wider range of HTS coil geometries by eliminating the constraints associated with fluid-based circulation. While the proposed conduction-cooled PES has not yet been physically fabricated, the numerical framework was established based on experimentally confirmed operating conditions of the previously implemented He–Ne-cooled PES, and future work will include fabrication and experimental validation of the conduction-cooled configuration. These findings demonstrate that conduction cooling represents a practical and scalable alternative for next-generation PES platforms and provide essential design guidelines for the development of high-field HTS coils and large-capacity superconducting rotating machines. Full article

Optokinetic nystagmus (OKN) is an involuntary sawtooth eye movement that occurs in the presence of a drifting stimulus. Our experience is that low-amplitude/short-duration OKN can challenge the limits of our commercially available Pupil Neon eye-tracker, leading to false negative OKN detection results. We sought to investigate whether such instances could be remediated. We compared automated OKN detection using: (1) the gaze signal from the Pupil Neon (OKN-G), (2) centroid tracking (OKN-C), and (3) an image-phase-based “motion microscopy” technique (OKN-MMIC). The OKN-C and OKN-MMIC methods were also tested as a remediated step after a negative OKN-G result (OKN-C-STEP, OKN-MMIC-STEP). To validate the approaches adults (n = 22) with normal visual acuity was measured whilst viewing trials of an OKN induction stimulus shown at four levels of visibility. Confusion matrices and performance measures were determined for a “main” dataset that included all methods, and a “retest” set, which contained instances where centroid tracking failed. For the main set, all tested methods improved upon OKN-G by Matthew’s correlation coefficient (0.80–0.85 vs. 0.76), sensitivity (0.89–0.95 vs. 0.85), and accuracy (0.91–0.93 vs. 0.88); but only OKN-C yielded better specificity (0.90–0.96 vs. 0.95). For the retest set, MMIC and MMIC-STEP methods consistently improved upon the performance of OKN-G across all measures. Full article

Background: Arthrographis spp. are environmental fungi commonly found in soil and compost. Infections caused by Arthrographis species remain an uncommon clinical occurrence. Although these infections are infrequent in the general population, their incidence appears to be elevated among immunocompromised patients or those with significant comorbidities. Objectives: This review seeks to examine all documented human cases of Arthrographis spp. infections, with particular focus on aspects such as epidemiology, microbiological features, resistance patterns, therapeutic approaches and associated mortality rates. Methods: A narrative review was performed based on data obtained from the PubMed/MedLine and Scopus databases. Results: A total of 21 articles reported Arthrographis spp. infections in 21 patients. The mean age of affected individuals was 43.62 years, with 66.6% being male. A history of trauma was the most common predisposing factor, present in 33.33% of cases. Fever and abscess formation were the predominant clinical manifestations (28.6%), followed by organ dysfunction in 19% of patients. In vitro, the yeast generally showed susceptibility to voriconazole and itraconazole, with a low rate of resistance to amphotericin B. Clinically, amphotericin B was the most frequently administered antifungal (55%), followed by voriconazole (40%) and itraconazole (30%). The overall mortality rate was 19%, while deaths directly attributable to the infection accounted for 14.3%. Conclusions: Due to the capacity of Arthrographis spp. to cause serious infections, it is important for healthcare providers to consider this organism when dimorphic yeast appears in biological specimens’ cultures, especially in patients with immunosuppression or significant underlying conditions, to facilitate timely and accurate diagnosis. Full article

We present the effective optical potential describing the interaction between an electron and a neon atom in a dense plasma. This potential accounts not only for the screening effect but also for the quantum non-locality and electronic correlation effects, which lead to an increase in the interaction energy between the electron and the neon atom. Within this framework, differential and momentum transport cross-sections for elastic electron–neon scattering are determined. The obtained results are compared with the available experimental data and theoretical predictions, showing exceptionally good agreement. Full article

We derive an explicit analytic expression for the first quantum correction to the second virial coefficient of a d-dimensional fluid whose particles interact via the generalized Lennard-Jones $(2n,n)$ potential. By introducing an appropriate change of variable, the correction term is reduced to a single integral that can be evaluated in closed form in terms of parabolic cylinder or generalized Hermite functions. The resulting expression compactly incorporates both dimensionality and stiffness, providing direct access to the low- and high-temperature asymptotic regimes. In the special case of the standard Lennard-Jones fluid ($d=3$, $n=6$), the formula obtained is considerably more compact than previously reported representations based on hypergeometric functions. The knowledge of this correction allows us to determine the first quantum contribution to the Boyle temperature, whose dependence on dimensionality and stiffness is explicitly analyzed, and enables quantitative assessment of quantum effects in noble gases such as helium, neon, and argon. Moreover, the same methodology can be systematically extended to obtain higher-order quantum corrections. Full article

This study investigates drivers’ visual attention strategies during naturalistic urban driving using mobile eye-tracking (Pupil Labs Neon). A sample of experienced drivers participated in a realistic traffic scenario to examine fixation behaviour under varying traffic conditions. Non-parametric analyses revealed substantial variability in fixation behaviour attributable to driver identity (H(9) = 286.06, p = 2.35 × 10⁻⁵⁶), stimulus relevance (H(7) = 182.64, p = 5.40 × 10⁻³⁶), and traffic density (H(4) = 76.49, p = 9.64 × 10⁻¹⁶). Vehicles and pedestrians elicited significantly longer fixations than lower-salience categories, reflecting adaptive allocation of visual attention to behaviourally critical elements of the scene. Compared with the fixed-rule method, which produced inflated anomaly rates of 7.23–14.84% (mean 12.06 ± 2.71%), the DSGP algorithm yielded substantially lower and more stable rates of 1.62–3.33% (mean 2.48 ± 0.53%). The fixed-rule approach over-classified anomalies by approximately 4–6×, whereas DSGP more accurately distinguished contextually appropriate fixations from genuine attentional deviations. These findings demonstrate that fixation behaviour in driving is strongly shaped by individual traits and environmental context, and that driver-specific modelling substantially improves the reliability of attention monitoring. Therefore DSGP framework offers a robust, personalised alternative evaluated at the proof-of-concept level to fixed thresholds and represents a promising direction for enhancing driver-state assessment in future ADAS. Full article

Stable attitude control of unmanned or autonomous operations of vehicles moving in three spatial dimensions is essential for safe and reliable operations. Rigid body attitude control is inherently a nonlinear control problem, as the Lie group of rigid body rotations is a compact manifold and not a linear (vector) space. Prior research has shown that the largest possible domain of convergence is provided by smooth attitude feedback control laws are obtained using a Morse function on $\mathrm{SO}\left(3\right)$ as a measure of the attitude stabilization or tracking error. A polar Morse function on $\mathrm{SO}\left(3\right)$ has four critical points, which precludes the possibility of global convergence of the attitude state. When used as part of a Lyapunov function on the state space (the tangent bundle $\mathrm{TSO}\left(3\right)$) of attitude and angular velocity, it gives a globally continuous state-dependent feedback control scheme with the minimum of the Morse function as the almost globally asymptotically stable (AGAS) attitude state. In this work, we explore the use of explicitly time-varying gains for Morse functions for rigid body attitude control. This strategy leads to discrete switching of the indices of the three non-minimum critical points that correspond to the unstable equilibria of the feedback system. The resulting time-varying feedback controller is proved to be AGAS, with the additional desirable property that the time-varying gains destabilize the (locally) stable manifolds of these unstable equilibria. Numerical simulations of the feedback system with appropriate time-varying gains show that a trajectory starting from an initial state close to the stable manifold of an unstable equilibrium, converges to the desired stable equilibrium faster than the corresponding feedback system with constant gains. Full article

Passive microwave remote sensing of soil moisture is crucial for monitoring the Earth’s water cycle and surface dynamics. The penetration depth during this process is significant, as it influences the accuracy of retrieved soil moisture data. Within L-band remote sensing, tools such as the τ-z model interpret microwave emissions to estimate soil moisture, taking into account the complex interactions between soil and radiation. However, in validating these models against high-temporal-resolution, ground-based measurements, especially from extensive networks like the Terrestrial National Ecological Observatory Network (NEON), further research and validation efforts are needed. This study comprehensively validates the τ-z model’s ability to estimate the soil temperature sensing depth (z_Teff) using data from the NEON and Soil Moisture Active Passive (SMAP) satellite missions. A harmonization process was conducted to align the spatial and temporal scales of the two datasets, enabling rigorous validation. We compared soil optical depth (τ)—a parameter capable of theoretically unifying sensing depth representations across wet soil (~0.05 m) to extreme dry/frozen conditions (e.g., up to ~1500 m in ice-equivalent scenarios)—and geometric depth (z) frameworks against outputs from the τ-z model and NEON’s in situ profiles. The results show that: (1) for the profiles that satisfy the monotonic assumption by the τ-z model, z_Teff fits the prediction well at about 0.2 τ for the average; (2) Combining SMAP’s soil moisture, the τ-z model achieves high accuracy in estimating z_Teff, with RMSD (0.05 m) and unRMSD (0.03 m), and correlations (0.67) between estimated and observed values. The findings are expected to advance remote sensing techniques in various fields, including agriculture, hydrology, and climate change research. Full article

The advancement of hyperspectral remote sensing technology has enhanced the ability to assess and characterize land cover in complex ecosystems. In this study, a linear spectral unmixing algorithm was applied to NEON hyperspectral imagery in 2018 and 2022 to quantify the fractional abundance of dominant land cover classes, namely herbaceous vegetation, mixed forbs, and bare soil, across the Marvin Klemme Experimental Rangeland in Oklahoma. UAV imagery acquired during the 2023 field campaign provided high resolution reference data for model training. The LSU results revealed a decline in herbaceous cover from 16.02 ha to 11.56 ha and an expansion of bare soil from 3.37 ha to 6.39 ha, while mixed forb cover remained relatively stable (12.38 ha to 13.82 ha). Accuracy assessment using the UAV-derived validation points yielded overall accuracy of 84% and 60% at fractional thresholds of 50% and 75%, respectively. Although statistical tests indicated no significant change in mean fractional abundance (p > 0.05), slope-based trend maps captured localized vegetation loss and regrowth patterns. These findings demonstrate the effectiveness of integrating LSU with UAV data for detecting subtle yet ecologically meaningful shifts in semi-arid grassland composition. Full article

Satellite Light Detection and Ranging (LiDAR) systems produce high-resolution data essential for confronting critical environmental challenges like climate change, disaster management, and ecological conservation. A HyperHeight Data Cube (HHDC) is a novel representation of LiDAR data. HHDCs are structured three-dimensional tensors, where each cell captures the number of photons detected at specific spatial and height coordinates. These data structures preserve the detailed vertical and horizontal information essential for ecological and topographical analyses, particularly Digital Terrain Models and canopy height profiles. In this paper, we investigate lossless compression techniques for large volumes of HHDCs to alleviate constraints on onboard storage, processing resources, and downlink bandwidth. We analyze several methods, including bit packing, Rice coding (RC), run-length encoding (RLE), and context-adaptive binary arithmetic coding (CABAC), as well as their combinations. We introduce the block-splitting framework, which is a simplified version of octrees. The combination of RC with RLE and CABAC within this framework achieves a median compression ratio greater than 24, which is confirmed by the results of processing two large sets of HHDCs simulated using the Smithsonian Environmental Research Center NEON data. Full article