Classical Maps Research Articles

Constructing Surrogate Lung Ventilation Maps from 4DCT-derived Subregional Respiratory Dynamics

PurposeTo present a two-stage framework that robustly extracts and maps reliable lung ventilation surrogates based on subregional respiratory dynamics (SRD) measured from four-dimensional computed tomography (4DCT) images, with comprehensive consideration of spatial and temporal heterogeneity in the ventilation process over the respiratory cycle. Materials and MethodsWe retrospectively analyzed three subject cohorts from the VAMPIRE challenge containing 4DCT and reference ventilation imaging (RefVI) scans. Lung subregions were partitioned on the 4DCT end-of-exhale base phase using anatomically constrained simple linear iterative clustering, while sliding-preserved interphase image registrations were performed between the base and other phases. SRDs of breathing-induced volume and intensity changes were tracked across phases utilizing the displacement fields. Voxel-level representations integrating mechanical collapsibility and physiological tissue density (VSRD) were accordingly constructed from SRDs. Imaging performance of VSRD as the proposed surrogate ventilation map was studied against RefVI scans and compared to classical biphasic Jacobian maps. The dosimetric performance evaluation was also conducted to assess the clinical benefits of incorporating VSRD maps into functional lung avoidance radiotherapy (FLA-RT) planning. ResultsThe extracted SRD highlighted temporally varying subregional volume and CT intensity changes related to underlying functional physiology and pathologies. For imaging performance, the median Spearman correlation coefficients between VSRD and RefVI scans were 0.600, 0.582, and 0.561 for the three cohorts, while median Dice similarity coefficients against RefVI scans showing the high(low)-functioning lung regions’ concordances, were 0.611(0.626), 0.592(0.620), and 0.601(0.611), superior to biphasic Jacobian maps for both metrics. For dosimetric performance, VSRD-guided FLA-RT plans achieved significantly better dose sparing of high-functioning lung regions compared to FLA-RT plans based on biphasic Jacobian maps. ConclusionsVSRD maps captured spatial and temporal heterogeneity in the ventilation process, providing improved ventilation representations compared to classical algorithms. The capability to extract multidimensional ventilation-correlated image information from widely available 4DCT images showed promise in enhancing personalized FLA-RT implementations.

Assessment of planar array accuracy for 3D sound source reconstruction with Bayesian Focusing

As planar microphone arrays were initially designed for bidimensional sound source localisation, their use for three-dimensional acoustic imaging consistently suffers from a poor resolution along the normal axis. Such a statement is already well documented for beamforming approaches and their declensions. Bearing this in mind, this paper delves into the possibilities offered by inverse methods and especially iterative Bayesian Focusing to tackle this issue and deliver accurate source positions in three dimensions based on planar array measurements only. To this end, an experimental set up is designed: omnidirectional sources are mounted in a wooden mock-up featuring faces at different distances from an 81 MEMs planar array. Based on this measurements, a benchmark study of sound source reconstruction on a 3D mesh of the mock-up is conducted and compared to classical 2D acoustic maps set at different depths. The latter process is declined for various source correlation values and at extended frequency ranges. By doing so, the current paper delivers an overview of the ability to discriminate acoustic sources along the normal axis of a planar array, on a simple and well controlled test case, with a view to provide guidelines for further applications of 3D acoustic imaging on complex geometries.

Assessment of earthquake location uncertainties for the design of local seismic networks

The ability to estimate earthquake source locations, along with the appraisal of relevant uncertainties, is paramount in monitoring both natural and human-induced micro-seismicity. For this purpose, a monitoring network must be designed to minimize the location errors introduced by geometrically unbalanced networks. In this study, we first review different sources of errors relevant to the localization of seismic events, how they propagate through localization algorithms, and their impact on outcomes. We then propose a quantitative method, based on a Monte Carlo approach, to estimate the uncertainty in earthquake locations that is suited to the design, optimization, and assessment of the performance of a local seismic monitoring network. To illustrate the performance of the proposed approach, we analyzed the distribution of the localization uncertainties and their related dispersion for a highly dense grid of theoretical hypocenters in both the horizontal and vertical directions using an actual monitoring network layout. The results expand, quantitatively, the qualitative indications derived from purely geometrical parameters (azimuthal gap (AG)) and classical detectability maps. The proposed method enables the systematic design, optimization, and evaluation of local seismic monitoring networks, enhancing monitoring accuracy in areas proximal to hydrocarbon production, geothermal fields, underground natural gas storage, and other subsurface activities. This approach aids in the accurate estimation of earthquake source locations and their associated uncertainties, which are crucial for assessing and mitigating seismic risks, thereby enabling the implementation of proactive measures to minimize potential hazards. From an operational perspective, reliably estimating location accuracy is crucial for evaluating the position of seismogenic sources and assessing possible links between well activities and the onset of seismicity.

Identifying Editions of the Ptolemy of Rome Maps (1478/90–1507/08) by Copper Plates Changes

Traditionally, it has been considered that the Ptolemaic or classical maps from the four editions of Ptolemy’s Geography published in Rome (1478, 1490, 1507, and 1508) are apparently indistinguishable at first glance because they have been printed from the same plates. This poses a problem for antiquarians, collectors, and curators who wish to accurately date their copies. Recently, two very comprehensive articles have been published on the different paper watermarks associated with each edition, which would allow for the correct identification of each one. However, there are occasions when the maps do not display watermarks. This article aims to provide some keys to distinguish between the incunabula editions (1478, 1490) and those of 1507–1508 in cases of the absence of watermarks. In this process of detecting differences, we have used digitized images of the maps. The results show small modifications in the copper plates made between the editions of 1490 and 1507/08. Our findings reveal that seven previously unknown reworked maps have been identified.

Constructing a non-degeneracy nD chaotic map model and counteracting dynamic degradation through adaptive impulsive perturbation

The characteristics of state point trajectory in phase space of a chaotic map, such as ergodicity, aperiodicity, broadband and noise-like, have been proved to be suitable for cryptography. However, some weaknesses, such as small key space, multiple bifurcations and dense windows that exist in some classic 1D and 2D chaotic maps, effect their practical application. To solve these problems, we constructed a non-degeneracy nD chaotic model, and instantiated it to obtain a 3D chaotic map (3D-NDCM), the dynamics analysis results demonstrated that the 3D-NDCM has a sufficiently large chaotic range, its state point trajectories has ergodicity in phase space. To counteract dynamic degradation and extend the aperiodic length of state time sequences, we further constructed a 6D-NDCM based on the model. Experimental analysis results demonstrated that, a state time sequence with longer aperiodicity can be obtained, through both dimension expansion and adaptive impulsive perturbation.

The superior frontal sulcus in the human brain: Morphology and probability maps.

The superior frontal sulcus (SFS) is the major sulcus on the dorsolateral frontal cortex that defines the lateral limit of the superior frontal gyrus. Caudally, it originates near the superior precentral sulcus (SPRS) and, rostrally, it terminates near the frontal pole. The advent of structural neuroimaging has demonstrated significant variability in this sulcus that is not captured by the classic sulcal maps. The present investigation examined the morphological variability of the SFS in 50 individual magnetic resonance imaging (MRI) scans of the human brain that were registered to the Montreal Neurological Institute (MNI) standard stereotaxic space. Two primary morphological patterns were identified: (i) the SFS was classified as a continuous sulcus or (ii) the SFS was a complex of sulcal segments. The SFS showed a high probability of merging with neighbouring sulci on the superior and middle frontal gyri and these patterns were documented. In addition, the morphological variability and spatial extent of the SFS were quantified using volumetric and surface spatial probability maps. The results from the current investigation provide an anatomical framework for understanding the morphology of the SFS, which is critical for the interpretation of structural and functional neuroimaging data in the dorsolateral frontal region, as well as for improving the accuracy of neurosurgical interventions.

Thermalization universality-class transition induced by Anderson localization

We study the disorder-induced crossover between the two recently discovered thermalization slowing-down universality classes, characterized by long- and short-range coupling, in classical unitary-circuit maps close to integrability. We compute Lyapunov spectra, which display qualitatively distinct features depending on whether the proximity to the integrable limit is short or long range. For sufficiently small nonlinearity, translationally invariant systems fall into the long-range class. Adding disorder to such a system triggers a transition to the short-range class, implying a breaking of this invariance, and in the very limit of vanishing nonlinearity Anderson localization emerges. The crossover from the long- to the short-range class is attained by tuning the localization length ξ from ξ≈N to ξ≪N, where N is the system size. As a consequence, the Lyapunov spectrum becomes exponentially suppressed, depending on the extent to which its translational invariance is destroyed. We expect that this disorder-induced crossover will lead to prethermalized phases and, following quantization, to many-body localization. Published by the American Physical Society 2024

Color watermarking algorithm combining the quantum discrete cosine transform with the sinusoidal–tent map

To overcome the drawbacks of the existing sinusoidal map and tent map, this paper proposes the design of a sinusoidal–tent (ST) map. The test results indicate that the new chaotic system exhibits more significant advantages in chaos control. Compared with the sinusoidal map and tent map, the proposed sinusoidal–tent map performs better in terms of bifurcation diagram and Lyapunov exponents. The trajectories of the sinusoidal–tent map can occupy all the phase planes over (0,4), while those of the two classic maps only occupy a small phase space, and the Lyapunov exponents of the ST map are all positive within the range of control parameters, higher than those of seed maps. Simultaneously, a novel quantum scrambling operation is devised based on the sinusoidal–tent map to avoid the periodicity of the quantum Arnold scrambling method. Initially, two chaotic sequences are generated to scramble the pixel positions of the watermark image, further enhancing the security of the watermarking algorithm. Subsequently, the host image is processed by the quantum discrete cosine transform, and finally, the scrambled watermark image is inserted into the medium-frequency band of the transformed host image, ensuring the invisibility of the watermarking. According to the simulation results, the quantum watermarking algorithm has excellent invisibility and robustness.

3D Visualization of geological structures using Python: the case study of the Palomeque sheets (SE, Spain)

ABSTRACT The goal of this paper is the construction of computerized 3D visualization of geological structures. Several Python applications have been used to adapt the paper map-based geological classical information to numerical geological maps represented in HTML files. The models include a map with the stratigraphic and structural contacts and symbols, five serial vertical sections, and a geological block diagram, all with real topography. This block diagram made with 2D figures allows a 3D visualization. Palomeque area (Murcia region, southeastern Spain) has been used as a key-case. This area consists of a deformed Upper Cretaceous to Oligocene succession belonging to the Internal Zone Malaguide Complex. The main structure consists of two thrust-fold sheets forming an imbricate system, also affected by a set of strike-slip faults with a sinistral regime. The constructed maps show a good agreement with the published classical geological maps and cross-sections demonstrating the benefits of using these Python applications.

Beyond flood hazard. Mapping the loss probability of pedestrians to improve risk estimation and communication

The effective communication of flood hazard and risk is a necessary step to foster preparedness and resilience, hence reducing the detrimental impacts of flooding events. Classical flood maps, which show flow depth and velocity, have often proved to be incomprehensible to the majority of people. Some recent studies used color maps to convey the spatial distribution of diverse hazard indexes that, accounting for both water depth and velocity, are intended to communicate the hazard degree in a more intelligible way. It is first shown that these hazard indexes have some inherent limitations, as for example the implicit assumption of a linear relationship between flood hazard and flow velocity. As an alternative, we propose to map the loss probability (LP) of pedestrians exposed to floodwaters, which is a physics-based and data-consistent risk index accounting for both hazard and vulnerability. LP can be easily computed and allows for a sounder estimation and a more effective communication of flood risk to the general public.

Mind the Map: Redesigning the London Underground Map

ABSTRACT In May 2022, ahead of the 90th anniversary of Beck’s original London Underground map, Transport for London opened the new Elizabeth Line, and added it to the already-congested map. But is the map still fit for purpose? This paper references critiques of the recent iterations of the map, and undertakes a cartographic review that assesses its form and function. It includes new designs of the map, created by the author, that attempt to deal with the issues identified, as well as providing a wider critique. In exploring why cartographers and designers offer alternative, often unrequested, new designs of such classic maps, the paper will reflect upon the issue of whether holding on to an iconic map, with its flaws, is preferable to letting go of the past and designing a completely new map. Changing the map would be a brave move, but is one that this author, among others, feels is too pertinent an issue to continue to ignore.

Rational homogeneous spaces as geometric realizations of birational transformations

In this paper we study geometric realizations of some classic birational maps, such as inversion maps, special Cremona transformations, special birational transformations of type (2, 1), by considering {{mathbb {C}}}^*-actions on rational homogeneous spaces and their subvarieties.

A novel chaos-based permutation for image encryption

Image encryption is an essential method for ensuring confidentiality during transmission on open channels. Digital images have a high correlation with large redundant data, requiring alternative spatial handling during encryption. Digital chaos offers shared properties of randomness and sensitivity that can provide secure image encryption. The security and performance of chaotic image ciphers depend on the underlying digital chaotic map. Therefore, classical chaotic maps must improve security while maintaining implementation time. The main objective of this paper is to propose a new image encryption algorithm based on an enhanced chaotic map that offers high security and low time consumption. A new perturbed logistic chaotic map based on hybridizing backward and forward perturbation methods is introduced, which exhibits better chaotic features than other existing chaotic systems such as a large chaotic range, higher sensitivity, and randomness. Based on this, a new image encryption algorithm is proposed, employing a novel permutation operation and two substitution operations to achieve superior encryption speed and efficiency. The novel permutation operation based on a chaotic data sequence utilizes all chaotic states to generate 8-bit numbers. Each index of the resulting 8-bit number is compiled into one block. The plain image is then scanned in accordance with the randomized indices of each block. The two substitution operations involve an XORing operation for each pixel and a hashing process for each block. The newly proposed encryption algorithm can effectively encrypt images of varying sizes and types, transforming them into indecipherable cipher images that successfully pass through rigorous security tests, including differential attack analysis with a score of 28/28 and local Shannon entropy with a score of 25/28. The experimental findings showcase the superior performance of the proposed cipher over existing chaotic image ciphers, creating a cipher image that resembles noise and has the ability to resist a diverse range of cyber-attacks.

Analysis of Cyber Security Threats of the Printing Enterprise

The topic of scientific works on the implementation of modern technologies and systems of automated management of the enterprise, its resources and technical means is analyzed, and the insufficient completeness of research on the features of the integrated approach to the design and deployment of innovative means of production order support. Based on the determined factors of the operation of the enterprise in the latest conditions of the fourth industrial revolution, directions for the formation of strategies for the introduction of the elements of Industry 4.0 in modern printing enterprises, as well as information protection systems, are determined with electronic document circulation. The mechanisms of decision of tasks of management informative risks considered in complex control system by printeries in the conditions of vagueness and at co-operation of elements of control system between itself. The necessity of using a web portal for the formation of printing orders is substantiate, the main components are define and the levels of access to them described. The paper examines the use of classic and gray fuzzy cognitive maps to solve the problem of cyber security risk assessment of the intelligent management system of a printing enterprise. It is demonstrate that the average estimate of local risk, which is formed using an ensemble of two heterogeneous fuzzy cognitive maps, decreases compared to the use of individual cognitive maps. In order tî better, highlight the results of the research, an example of the application of the proposed methodology for assessing the risks of ensuring the integrity of telemetric information in the industrial network of the intelligent technological process management system of a printing enterprise given, with the continuity of the technological process of manufacturing printing products. In addition to the classic FCM, the paradigms of two variants of the FCM extension were also use in the study, namely, the gray FCM, which used to solve the problem of assessing cyber security risks of intelligent management systems of printing enterprises. An analysis of the possibility of building FCM ensembles to increase the effectiveness of risk assessment using several options for formalizing the expert’s knowledge and experience performed. A fragment of the enterprise management system was consider and an analysis of possible directions of attacks on the printing enterprise by malicious software was perform. These are attacks such as replacing the executable files of server and ARM software, overwriting PLC projects during system operation, and refusing to service the equipment. Based on the formed list of attack vectors and the consequences of their implementation, the task of analyzing the risks of cyber security of a printing enterprise, taking into account the impact on the system of possible internal threats, was considered, using the cognitive modeling apparatus as a modeling tool. The scenario of cognitive modeling of the influence of an internal criminal who exploits the vulnerabilities of the software and hardware components of the control system using the given variants of FCM construction is considered. The average assessment of local risks, which formed using an ensemble of cognitive maps, is better from the point of view of dispersion of assessments of the state of target concepts than the use of individual FCMs. The spread of estimates of the state of ensemble concepts is smaller than the spread of estimates of their gray values using the GFCM, on average by 1.4–1.8 times, which indicates a decrease in the influence of the subjectivity factor on the results of risk assessment. The performed scenario modeling showed that the use of the specified means of protection and organizational measures allows reducing the assessment of local risks by 12–18%, which is a significant indicator. This technique allows obtaining a qualitative and quantitative assessment of risk indicators, taking into account the entire set of objective and subjective factors of uncertainty.

Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection

Cancer is a highly heterogeneous condition that can occur almost anywhere in the human body. [<sup>18</sup>F]fluorodeoxyglucose Positron Emission Tomography (<sup>18</sup>F-FDG PET) is a imaging modality commonly used to detect cancer due to its high sensitivity and clear visualisation of the pattern of metabolic activity. Nonetheless, as cancer is highly heterogeneous, it is challenging to train general-purpose discriminative cancer detection models, with data availability and disease complexity often cited as a limiting factor. Unsupervised learning methods, more specifically anomaly detection models, have been suggested as a putative solution. These models learn a healthy representation of tissue and detect cancer by predicting deviations from the healthy norm, which requires models capable of accurately learning long-range interactions between organs, their imaging patterns, and other abstract features with high levels of expressivity. Such characteristics are suitably satisfied by transformers, which have been shown to generate state-of-the-art results in unsupervised anomaly detection by training on normal data. This work expands upon such approaches by introducing multi-modal conditioning of the transformer via cross-attention i.e. supplying anatomical reference information from paired CT images to aid the PET anomaly detection task. Furthermore, we show the importance and impact of codebook sizing within a Vector Quantized Variational Autoencoder, on the ability of the transformer network to fulfill the task of anomaly detection. Using 294 whole-body PET/CT samples containing various cancer types, we show that our anomaly detection method is robust and capable of achieving accurate cancer localization results even in cases where normal training data is unavailable. In addition, we show the efficacy of this approach on out-of-sample data showcasing the generalizability of this approach even with limited training data. Lastly, we propose to combine model uncertainty with a new kernel density estimation approach, and show that it provides clinically and statistically significant improvements in accuracy and robustness, when compared to the classic residual-based anomaly maps. Overall, a superior performance is demonstrated against leading state-of-the-art alternatives, drawing attention to the potential of these approaches.

Are the EEG microstates correlated with motor and non-motor parameters in patients with Parkinson's disease?

ObjectivesThis study compared electroencephalography microstates (EEG-MS) of patients with Parkinson's disease (PD) to healthy controls and correlated EEG-MS with motor and non-motor aspects of PD. MethodsThis cross-sectional exploratory study was conducted with patients with PD (n = 10) and healthy controls (n = 10) matched by sex and age. We recorded EEG-MS using 32 channels during eyes‐closed and eyes‐open conditions and analyzed the four classic EEG-MS maps (A, B, C, D). Clinical information (e.g., disease duration, medications, levodopa equivalent daily dose), motor (Movement Disorder Society - Unified Parkinson Disease Rating Scale II and III, Timed Up and Go simple and dual-task, and Mini-Balance Evaluation Systems Test) and non-motor aspects (Mini-Mental State Exam [MMSE], verbal fluency, Hospital Anxiety and Depression Scale, and Parkinson's Disease Questionnaire-39 [PDQ-39]) were assessed in the PD group. Mann-Whitney U test was used to compare groups, and Spearman's correlation coefficient to analyze the correlations between coverage of EEG-MS and clinical aspects of PD. ResultsThe PD group showed a shorter duration of EEG-MS C in the eyes-closed condition than the control group. We observed correlations (rho = 0.64 to 0.82) between EEG-MS B, C, and D and non-motor aspects of PD (MMSE, verbal fluency, PDQ-39, and levodopa equivalent daily dose). ConclusionAlterations in EEG-MS and correlations between topographies and cognitive aspects, quality of life, and medication dose indicate that EEG could be used as a PD biomarker. Future studies should investigate these associations using a longitudinal design.

Chaotic Image Encryption Using Piecewise-Logistic-Sine Map

The classical one-dimension chaotic maps are not adequately secure, and some improved maps usually have a high time complexity. To address these problems, this paper presents a new Piecewise-Logistic-Sine map (PLSM). The bifurcation diagrams, Lyapunov exponent, and running time of the proposed PLSM are analyzed, and the outcomes show that it has better chaotic behavior with low time complexity. Furthermore, diffusion by certain rules is vulnerable to attack, so a PLSM-based image encryption scheme with random exclusive OR diffusion is proposed. Using a 256-bit secret key, the initial value and parameters of PLSM are calculated by the key distribution method. Then four chaotic sequences are generated by PLSM, they are used in three rounds of random exclusive OR diffusion. This scheme can spread a small change in the original image to all pixels, and the performance evaluation shows the security of this image encryption scheme.

Finite-time Lyapunov fluctuations and the upper bound of classical and quantum out-of-time-ordered expansion rate exponents.

This Letter demonstrates for chaotic maps [logistic, classical, and quantum standard maps (SMs)] that the exponential growth rate (Λ) of the out-of-time-ordered four-point correlator is equal to the classical Lyapunov exponent (λ) plus fluctuations (Δ^{(fluc)}) of the one-step finite-time Lyapunov exponents (FTLEs). Jensen's inequality provides the upper bound λ≤Λ for the considered systems. Equality is restored with Λ=λ+Δ^{(fluc)}, where Δ^{(fluc)} is quantified by k-higher-order cumulants of the (covariant) FTLEs. Exact expressions for Λ are derived and numerical results using k=20 furnish Δ^{(fluc)}∼ln(sqrt[2]) for all maps (large kicking intensities in the SMs).

A Low Complexity and Long Period Digital Random Sequence Generator Based on Residue Number System and Permutation Polynomial

Long period digital random sequence plays an important role in reliable communications and high security scenarios. This paper improved the method of generating long period digital random sequences based on the Residue Number System (RNS) and the Chinese Remainder Theorem (CRT), and a sequence mapping method after CRT extension. This paper proves that the period of sequence after mapping will not degenerate if the modulus used in the mapping stage is coprime with the period of the original sequence. By using the parallelism of RNS, the proposed method can generate sequences at high speed with fewer hardware resources. The NIST test results show that the pass rate of each test item is above 98.40%, which meets the NIST test confidence requirements, confirming the randomness of the generated sequences. An image encryption test is given as one of the example applications of the generated sequences. On the theoretical basis, by jointly optimizing the sequence mapping and iteration procedure, a hardware implementation architecture is also presented in this paper. The implementation is based on Xilinx XC7Z020CLG484-3 FPGA and compared with the implementations of classical chaotic maps. The results show that the proposed architecture has longer sequence period with less hardware resource consumption and higher generation speed and is more general. Meanwhile, the proposed architecture has fast phase switching ability, which is about 10 clock periods. This is one of the key attributes when the sequence is used in communication systems.

Global patterns of vascular plant alpha diversity

Global patterns of regional (gamma) plant diversity are relatively well known, but whether these patterns hold for local communities, and the dependence on spatial grain, remain controversial. Using data on 170,272 georeferenced local plant assemblages, we created global maps of alpha diversity (local species richness) for vascular plants at three different spatial grains, for forests and non-forests. We show that alpha diversity is consistently high across grains in some regions (for example, Andean-Amazonian foothills), but regional ‘scaling anomalies’ (deviations from the positive correlation) exist elsewhere, particularly in Eurasian temperate forests with disproportionally higher fine-grained richness and many African tropical forests with disproportionally higher coarse-grained richness. The influence of different climatic, topographic and biogeographical variables on alpha diversity also varies across grains. Our multi-grain maps return a nuanced understanding of vascular plant biodiversity patterns that complements classic maps of biodiversity hotspots and will improve predictions of global change effects on biodiversity.