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"Nikolaev, Dmitry"
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No Reproducibility, No Progress: Rethinking CT Benchmarking
Reproducibility is a cornerstone of scientific progress, yet in X-ray computed tomography (CT) reconstruction, it remains a critical and unresolved challenge. Current benchmarking practices in CT are hampered by the scarcity of openly available datasets, the incomplete or task-specific nature of existing resources, and the lack of transparent implementations of widely used methods and evaluation metrics. As a result, even the fundamental property of reproducibility is frequently violated, undermining objective comparison and slowing methodological progress. In this work, we analyze the systemic limitations of current CT benchmarking, drawing parallels with broader reproducibility issues across scientific domains. We propose an extended data model and formalized schemes for data preparation and quality assessment, designed to improve reproducibility and broaden the applicability of CT datasets across multiple tasks. Building on these schemes, we introduce checklists for dataset construction and quality assessment, offering a foundation for reliable and reproducible benchmarking pipelines. A key aspect of our recommendations is the integration of virtual CT (vCT), which provides highly realistic data and analytically computable phantoms, yet remains underutilized despite its potential to overcome many current barriers. Our work represents a first step toward a methodological framework for reproducible benchmarking in CT. This framework aims to enable transparent, rigorous, and comparable evaluation of reconstruction methods, ultimately supporting their reliable adoption in clinical and industrial applications.
Journal Article
Fast Gaussian Filter Approximations Comparison on SIMD Computing Platforms
Gaussian filtering, being a convolution with a Gaussian kernel, is a widespread technique in image analysis and computer vision applications. It is the traditional approach for noise reduction. In some cases, performing the exact convolution can be computationally expensive and time-consuming. To address this problem, approximations of the convolution are often used to achieve a balance between accuracy and computational efficiency, such as with running sums, Bell blur, Deriche approximation, etc. At the same time, modern computing devices support data parallelism (vectorization) via Single Instruction Multiple Data (SIMD) and can process integer numbers faster than floating-point approaches. In this paper, we describe several methods for approximating a Gaussian filter, implement the SIMD and quantized versions, and compare them in terms of speed and accuracy. The experiments were performed on central processing units with a x86_64 architecture using a family of SSE SIMD extensions and an ARMv8 architecture using the NEON SIMD extension. All the optimized approximations demonstrated 10–20× speedup while maintaining the accuracy in the range of 1 × 10−5 or higher. The fastest method is a trivial Stack blur with a relatively high error, so we recommend using the second-order Vliet–Young–Verbeek filter and quantized Bell blur and running sums as more accurate and still computationally efficient alternatives.
Journal Article
UAV Control on the Basis of 3D Landmark Bearing-Only Observations
The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks’ position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.
Journal Article
Russian agricultural innovations prospects in the context of global challenges: Agriculture 4.0
For the last 10–15 years, Russia has become the key player in the world agricultural market. Increasing export volume up to $45 billion by 2025 is the ambitious plan of the Russian Government. Windows of opportunity that create fundamentally new prospects for increasing competitiveness are opened mainly during the period of changing technological patterns, such as the current transition of the world’s agriculture towards Agriculture 4.0 paradigm. This is crucial for further economic growth. Information for this article was prepared based on “desk research” methods and then all data and hypotheses obtained were tested by conducting detailed in-depth interviews with key industry decision makers. According to the results of research there has been a huge interest on the part of business to implement innovative solutions in agriculture. Yet significant institutional constraints, problems in the legislative and regulatory sectors, the absence of a system of transfer or commercialization of technology from research center to the final manufacturer are still present. At the same time, all the instruments of state support are currently configured only for conventional, as opposed to innovative agriculture.
Journal Article
Talking About Temperature and Social Thermoregulation in the Languages of the World
The last decade saw rapid growth of the body of work devoted to relations between social thermoregulation and various other domains, with a particular focus on the connection between prosociality and physical warmth. This paper reports on a first systematic cross-linguistic study of the exponents of conceptual metaphor AFFECTION IS WARMTH (Lakoff & Johnson, 1980; Grady, 1997), which provides the motivation for the large share of research in this area. Assumed to be universal, it ebles researchers, mostly speakers of major European languages, to treat words like warm and cold as self-evident and easily translatable between languages – both in their concrete uses (to feel warm/cold) and as applied to interpersol relationships (a cold/warm person, warm feelings, etc.). Based on a sample of 94 languages from all around the world and using methodology borrowed from typological linguistics and mixed-effects regression modelling, we show that the relevant expressions show a remarkably skewed distribution and seem to be absent or extremely margil in the majority of language families and linguistic macro-areas. The study demonstrates once again the dramatic influence of the Anglocentric, Standard Average European, and WEIRD perspectives on many of the central concepts and conclusions in linguistics, psychology, and cognitive research and discusses how changing this perspective can impact research in social psychology in general and in social thermoregulation in particular.
Journal Article
Modeling DECT-2020 as a Tandem Queueing System and Its Application to the Peak Age of Information Analysis
The Peak Age of Information (PAoI) quantifies the freshness of updates used in cyber-physical systems (CPSs), realized within the Internet of Things (IoT) paradigm, encompassing devices, networks, and control algorithms. Consequently, PAoI is a critical metric for real-time applications enabled by Ultra-Reliable Low Latency Communication (URLLC). While highly useful for system evaluation, the direct analysis of this metric is complicated by the correlation between the random variables constituting the PAoI. Thus, it is often evaluated using only the mean value rather than the full distribution. Furthermore, since CPS communication technologies like Wi-Fi or DECT-2020 involve multiple processing stages, modeling them as tandem queueing systems is essential for accurate PAoI analysis. In this paper, we develop an analytical model for a DECT-2020 network segment represented as a two-phase tandem queueing system, enabling detailed PAoI analysis via Laplace–Stieltjes transforms (LST). We circumvent the dependence between generation and sojourn times by classifying updates into four mutually exclusive groups. This approach allows us to derive the LST of the PAoI and determine the exact Probability Density Function (PDF) for M|M|1→M|M|1 system. We also calculate the mean and variance of the PAoIs and validate our results through numerical experiments. Additionally, we evaluate the impact of different service time distributions on PAoI variability. These findings contribute to the theoretical understanding of PAoI in tandem queueing systems and provide practical insights for optimizing DECT-2020-based communication systems.
Journal Article
HyperHazeOff: Hyperspectral Remote Sensing Image Dehazing Benchmark
Hyperspectral remote sensing images (HSIs) provide invaluable information for environmental and agricultural monitoring, yet they are often degraded by atmospheric haze, which distorts spatial and spectral content and hinders downstream analysis. Progress in hyperspectral dehazing has been limited by the absence of paired real-haze benchmarks; most prior studies rely on synthetic haze or unpaired data, restricting fair evaluation and generalization. We present HyperHazeOff, the first comprehensive benchmark for hyperspectral dehazing that unifies data, tasks, and evaluation protocols. It comprises (i) RRealHyperPDID, 110 scenes with paired real-haze and haze-free HSIs (plus RGB images), and (ii) RSyntHyperPDID, 2616 paired samples generated using a physically grounded haze formation model. The benchmark also provides agricultural field delineation and land classification annotations for downstream task quality assessment, standardized train/validation/test splits, preprocessing pipelines, baseline implementations, pretrained weights, and evaluation tools. Across six state-of-the-art methods (three RGB-based and three HSI-specific), we find that hyperspectral models trained on the widely used HyperDehazing dataset fail to generalize to real haze, while training on RSyntHyperPDID enables significant real-haze restoration by AACNet. HyperHazeOff establishes reproducible baselines and is openly available to advance research in hyperspectral dehazing.
Journal Article
Fabrication of poly (-caprolactone) 3D scaffolds with controllable porosity using ultrasound
3D printing has progressed significantly, allowing objects to be produced using a wide variety of materials. Recent advances have employed focused ultrasound in 3D printing, to allow printing inside acoustically transparent materials. Here we introduce a selective ultrasonic melting (SUM) method for 3D printing of poly (
-caprolactone) powder mixed with water. The printing was done by mechanically moving a focused ultrasound transducer. The microstructure and porosity of the prints were analyzed with micro-computed tomography. The open porosity of the printed samples was determined using the water intrusion method and by passing fluorescent microspheres through the structure. The cytocompatibility of the printed structures was confirmed by seeding NIH-3T3 fibroblast cells on the scaffolds, followed by analysis using live/dead fluorescent assay and visualization using scanning electron microscopy. We demonstrated that SUM is a viable technique to print structures with active control of their porosity. This method provides an alternative to methods such as fused deposition modelling and material jetting.
Journal Article
Leveraging Achromatic Component for Trichromat-Friendly Daltonization
Color vision deficiency (CVD) affects around 300 million people globally due to issues with cone cells, highlighting the need for effective daltonization methods. These methods modify color palettes to enhance detail visibility for individuals with CVD. However, they can also distort the natural appearance of images. This study presents a novel daltonization method that focuses on preserving image naturalness for both normal trichromats and individuals with CVD. Our approach modifies only the achromatic component while enhancing detail visibility for individuals with CVD. To compare our approach with the previously known anisotropic daltonization method, we utilize objective and subjective evaluations that separately assess visibility enhancement and naturalness preservation. Our findings indicate that the proposed method outperforms the anisotropic method in naturalness by over 10 times according to objective criteria. Subjective evaluations revealed that more than 90% of CVD individuals and 95% of trichromats preferred our method for its natural appearance. Although objective contrast metrics suggest inferior visibility enhancement, subjective evaluation indicates comparable performance: contrast improvement was observed in 65% of protan cases for our method versus 70% for the anisotropic method, with contrast deterioration in 18% versus 7%, respectively. Overall, our method offers superior naturalness while maintaining comparable detail discrimination.
Journal Article