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With the application of large-span building covers in high-speed railway stations, the issue of structural vibration comfort induced by crowd walking has aroused the attention of researchers. The randomness of the crowd flow on large-span building covers, combined with the conventional method adopting the worst load case to evaluate the human-induced structural vibration, leads to larger response results and a significant deviation from the actual scenario. In this study, a novel crowd-load model considering the inherent dual randomness associated with the trajectory of the crowd and walking load is proposed. It is developed by integrating the social force model with a random single person walking load. In addition, a corresponding framework for structural vibration calculation is proposed as well. Three crowd-loading models are established, accounting for randomness, by combining with the finite element model of the thin plate structure. The vibration response of the floor slab under crowd excitation was assessed in the waiting hall of Xiong'an high-speed railway station. Numerical simulation calculations were performed, comparing the results for three different types of crowd load. The findings indicate a significant reduction in the vibration response of the large-span waiting hall when employing the load model incorporating the social force model. This serves as a correction to the overly conservative nature of the conventional load model. [ABSTRACT FROM AUTHOR]

• Both maximum Lyapunov exponents and correlation dimensions were significantly greater during heigher sevoflurane anaesthesia. • Approximate entropy conversely decrease along with deepening of sevoflurane anesthesia. • Chaotic nature of EEG might increase as anaesthesia deepens, despite the decrease in randomness as reflected in entropy. In conscious states, the electrodynamics of the cortex are reported to work near a critical point or phase transition of chaotic dynamics, known as the edge-of-chaos, representing a boundary between stability and chaos. Transitions away from this boundary disrupt cortical information processing and induce a loss of consciousness. The entropy of the electroencephalogram (EEG) is known to decrease as the level of anesthesia deepens. However, whether the chaotic dynamics of electroencephalographic activity shift from this boundary to the side of stability or the side of chaotic enhancement during anesthesia-induced loss of consciousness remains poorly understood. We investigated the chaotic properties of EEGs at two different depths of clinical anesthesia using the maximum Lyapunov exponent, which is mathematically regarded as a formal measure of chaotic nature, using the Rosenstein algorithm. In 14 adult patients, 12 s of electroencephalographic signals were selected during two depths of clinical anesthesia (sevoflurane concentration 2% as relatively deep anesthesia, sevoflurane concentration 0.6% as relatively shallow anesthesia). Lyapunov exponents, correlation dimensions and approximate entropy were calculated from these electroencephalographic signals. As a result, maximum Lyapunov exponent was generally positive during sevoflurane anesthesia, and both maximum Lyapunov exponents and correlation dimensions were significantly greater during deep anesthesia than during shallow anesthesia despite reductions in approximate entropy. The chaotic nature of the EEG might be increased at clinically deeper inhalational anesthesia, despite the decrease in randomness as reflected in the decreased entropy, suggesting a shift to the side of chaotic enhancement under anesthesia. [ABSTRACT FROM AUTHOR]

Random meso‐scale defects within welded joints can affect the structural damage process and cause dispersion in the fatigue lifetime of welded joints. In this paper, a meso‐scale stochastic damage approach is used to investigate the effect of random, meso‐scale defects on the fatigue damage lifetime of welded joints under different loads. First, we established an elastic–plastic fatigue damage model considering meso‐defects in the weld metal. Secondly, the fatigue lifetimes for gas tungsten arc welding and gas metal arc welding welded joints were predicted, with most of the predictions within the twofold dispersion factor. Thirdly, the Monte Carlo simulation method was used to investigate the influence of meso‐defect size on the fatigue lifetime dispersion degree, and the fatigue lifetime distribution under different loads was statistically analyzed. Established a fatigue life prediction model considering random meso‐defects in welds.The dispersion effect of meso‐scale random defect size on fatigue life was analyzed.Fatigue life prediction of welded specimens of other materials is also possible. [ABSTRACT FROM AUTHOR]

Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is no consensus on how best to quantify the randomness of responses in human-generated sequences. Traditionally, psychologists have used measures of randomness that directly assess specific features of human behavior in RNG tasks, such as the tendency to avoid repetition or to systematically generate numbers that have not been generated in the recent choice history, a behavior known as cycling. Other disciplines have proposed measures of randomness that are based on a more rigorous mathematical foundation and are less restricted to specific features of randomness, such as algorithmic complexity. More recently, variants of these measures have been proposed to assess systematic patterns in short sequences. We report the first large-scale integrative study to compare measures of specific aspects of randomness with entropy-derived measures based on information theory and measures based on algorithmic complexity. We compare the ability of the different measures to discriminate between human-generated sequences and truly random sequences based on atmospheric noise, and provide a systematic analysis of how the usefulness of randomness measures is affected by sequence length. We conclude with recommendations that can guide the selection of appropriate measures of randomness in psychological research. [ABSTRACT FROM AUTHOR]

In this paper, we develop a Bayesian two-stage cure rate model whose biological destructive mechanism (immune system) of the competing risk factors of death is suitable for detecting the impact on the long-term survival function of three sources of variance well-known in accident theory: randomness, liability and proneness. From a survival analysis viewpoint, proneness means individual effect or destructive mechanism and liability corresponds to external effects or covariates. The flexibility of the generalized Waring frailty distribution in capturing these variance components separately enables one to understand the nature of overdispersion of the risk factors involved in studying risk of death after a long-term treatment of the patient. A new cure rate, involving covariate and destructive mechanism, is developed here under a competing cause scenario. A simulation study and an application to colorectal cancer data set are finally presented to demonstrate the usefulness of the proposed model and the inferential results developed here. [ABSTRACT FROM AUTHOR]

Background: In the excitement about genomics, it is easy to lose sight of one of the most important findings from behavioural genetics: At least half of the variance of psychopathology is caused by environmental effects that are not shared by children growing up in the same family, which includes error of measurement. However, a 30‐year search for the systematic causes of nonshared environment in a line‐up of the usual suspects, especially parenting, has not identified the culprits. Method: I briefly review this research, but primarily consider the conceptual framework of the search for 'missing' nonshared environmental effects. Results: The search has focused on exogenous events like parenting, but nonshared environment might not be caused by anything we would call an event. Instead, it might reflect endogenous processes such as noisy biological systems (such as somatic mutations and epigenetics) or, at a psychological level, idiosyncratic subjective perceptions of past and present experiences, which could be called nonshared environmental experience to distinguish it from exogenous events. Although real, nonshared environment might be random in the philosophy of science sense of being unpredictable, even though it can have stable effects that predict subsequent behaviour. Conclusion: I wade into the weeds of randomness and suggest that this so‐called 'gloomy prospect' might not be so gloomy. [ABSTRACT FROM AUTHOR]

Creating and testing a biometric key is a critical process used for security and identity verification .When using biometric traits such as fingerprints, facial features, iris patterns, earprints, and voice patterns, a unique key is created and linked to the individual's biometric identity. These biometrics provide inherent uniqueness, resulting in a higher level of security compared to traditional methods. In addition, biometric authentication eliminates the need for users to memorize complex passwords or carry physical tokens, thus enhancing convenience and user experience. Iris recognition systems have received significant attention in biometrics for their ability to provide robust criteria for identifying individuals, thanks to the rich texture of the iris. In this research, the key generation process was created by converting biometrics (the iris) into a digital representation (a set of binary numbers from the two iris) that can be used in the encryption process. This is done by using digital image processing algorithms to extract unique features from the two irises. After the key is generated, it is tested using random metrics. If the key meets the criteria, it is random otherwise the key will be generated again.

Hyperspectral images are crucial in various sensitive areas and applications, necessitating the utmost security measures. To balance safety and efficiency, this paper presents a novel encryption scheme for hyperspectral images using a 4D Lorenz hyperchaotic system, 3D Zigzag-like transformation, and brushing diffusion. Firstly, the scheme utilizes the 4D hyperchaotic Lorenz system to generate pseudo-random sequences for scrambling and diffusion. The initial values correlated with the plaintext are obtained using the SHA-256 algorithm to enhance resistance against differential and plaintext attacks. Secondly, the brushing diffusion algorithm is employed to enhance the avalanche effect without significantly compromising the speed of the encryption process. Thirdly, the 3D Zigzag-like transformation with two key parameters is proposed and applied to reduce intra-band and inter-band adjacent pixel correlations. Experimental evaluations and security analysis confirmed the effectiveness of the scheme. The scheme offers a large key space, quick process, high key sensitivity, acceptable randomness in the ciphertext, and excellent visual reconstruction quality. Furthermore, it demonstrates resistance against common attacks, including statistical, differential, and plaintext attacks. In conclusion, the proposed encryption scheme effectively protects hyperspectral images while maintaining acceptable computational efficiency. [ABSTRACT FROM AUTHOR]

To address the issue of randomness in the mechanical properties of the hydroxyl‐terminated polybutadiene (HTPB) propellant, a stochastic constitutive model (SCM) with a lognormally distributed random parameter Λ was proposed to describe their mechanical behaviors, and the structural integrity of a HTPB propellant grain was analyzed based on it. The results indicate that the stress‐strain curves predicted by the SCM have a good agreement with the experimental curves, and the experimental curves fall within a 95 % probability interval predicted by the SCM. The mechanical response of HTPB propellant grain under ignition pressurization is associated with the random parameters Λ. The maximum equivalent stress and safety factor increase approximately linearly with the increase of random parameters Λ, while the maximum equivalent strain and maximum damage coefficient decrease approximately linearly with the increase of random parameters Λ. The error in the mechanical response of the grain obtained based on the SCM and the experimental constitutive model is basically not more than 2 %, the SCM can effectively characterize the randomness in the mechanical response of propellant grain caused by the dispersion of HTPB propellant mechanical properties. [ABSTRACT FROM AUTHOR]

This paper presents a new nonlinear feedback shift register (NLFSR) in the Galois configuration to generate the pseudorandom number sequences (PRNS) for a lightweight encryption scheme. In the NLFSR, the feedback function is applied to each state, not only the last bit of NLFSR. In the proposed design the size of the feedback is reduced using Galois configuration. The NLFSR is tested with NIST Statistical Test Suite to evaluate its quality randomness. The new NLFSR is used as an pseudorandom number generator to design a new lightweight image encryption algorithm. The encryption process can be represent in two phases permutation and diffusion. In the first phase, two different PRNSs generated by the new NLFSR for permute the row and column pixels of the plain image (PI). Then convert the permuted image into a 1D binary vector. In the diffusion phase, DNA arithmetic is applied between the 1D and another PRNS generated by the same NLFSR with different key. Several security analysis tests are performed on the proposed scheme (like histogram analysis, entropy, correlation coefficient, NPCR, UACI, MSE, and PSNR) to test the security strength of the encryption method. It was found that the new NLFSR had passes all the tests in NIST Statistical Test Suite, and the test results of the encryption scheme are also acceptable and shows potential security strength. [ABSTRACT FROM AUTHOR]

Inundations in Amazonian black‐water river floodplain result in the selection of different tree lineages, thus promoting coexistence between species. We investigated whether Amazonian tree communities are phylogenetically structured and distributed along a flooding gradient from irregularly flooded forests along streams embedded within upland (terra‐firme) forest to seasonally flooded floodplains of large rivers (igapós). Floristic inventories and hydrological monitoring were performed along the Falsino River, a black‐water river in the eastern Amazon within the Amapá National Forest. We constructed a presence‐and‐absence matrix and generated a phylogeny using the vascular plant database available in GenBank. We calculated the standardized values of the metrics of phylogenetic diversity (ses.PD), average phylogenetic distance (ses.MPD), and average nearest‐neighbor distance (ses.MNTD) to test whether the history of relationships between species in the community is influenced by inundation. We used the phylogenetic endemism (PE) metric to verify the existence of taxa with restricted distribution. Linear regressions were used to test whether phylogenetic metrics have a significant relationship with the variables: maximum flood height, maximum water table depth, and maximum flood amplitude. The results show that forests subject to prolonged seasonal flooding have reduced taxon richness, low phylogenetic diversity, and random distribution of lineages within communities. On the other hand, terra‐firme riparian forests showed higher rates of taxon richness, diversity, and phylogenetic dispersion, in addition to greater phylogenetic endemism. These results indicate that seasonal and predictable soil flooding filters tree lineages along the hydrographic gradient. Different adaptations to root waterlogging are likely requirements for colonization in these environments and may represent an important factor in the diversification of tree lineages in the Amazon biome. [ABSTRACT FROM AUTHOR]

The hoisting safety and the difficulty of the main reinforcement connection are directly affected by stiffness of reinforcement parts. Quantifying the stiffness of reinforcement parts has become a key technology problem. Firstly, an independent mechanical solution model of three-dimensional rotational stiffness (Rx , Ry , and Rz) for the welded joints is proposed from the perspective of mechanical mechanism. Considering the influence of the rebar diameter, 105 sets of T-type welded reinforcement specimens and 2 types of loading devices were designed, and graded loading tests were performed. On this basis, considering the randomness of the rotational stiffness of the welded joints, a deformation calculation method for the welded reinforcement parts based on Monte Carlo random sampling is proposed, and six groups of two-dimensional (2D) reinforcement mats and six groups of three-dimensional (3D) reinforcement cages tests were performed. The results show that the rotational stiffness of the welded joints is random and has the Gaussian distribution characteristics. The rotational stiffness of the welded joints has a significant effect on the deformation of the welded reinforcement parts. Under the same welding conditions, the rotational stiffness of the welded joints increases with the increase of reinforcement diameter. Under the same reinforcement diameter, the three-dimensional rotational stiffness of the welded joints is in the order Rx>Rz>Ry. The cross-sectional area of the welded joint can better characterize the rotational stiffness. The verification test of welded reinforcement shows that the error of the calculation method proposed in this paper is within 10%, while the error of rigid connections and hinge connections are less than 30% and 130%, respectively. [ABSTRACT FROM AUTHOR]

The study of the dynamics of foreign exchange rates is of paramount importance to economic policy makers for developing countries like India that depend on foreign exchange to meet a large part of their import obligations. This paper uses the concepts of entropy to study the regularity/irregularity of the returns from the Indian Foreign exchange (forex) markets particularly during periods of economic instability. We use the Approximate Entropy and Sample Entropy statistics which measure the level of repeatability in the data are used to quantify the randomness in the forex returns for four major currencies namely the US Dollar, the British pound, the EURO and the Japanese Yen with respect to the Indian Rupee from the time period 2006 to 2021. These statistics are chosen as they are both statistical measures for assessing the randomness or regularity of time series data and enable researchers to objectively evaluate the degree of randomness present in the returns series and understand the crucial underlying patters or behaviors. In this research we look at two periods of major financial upheavals, the subprime crisis also known as the Global Financial Crisis (GFC) during 2006-2007 and the recent Covid-19 pandemic during 2020-2021. Our empirical results overwhelmingly confirm our working hypothesis that regularity in the returns of the major Indian foreign exchange rates increases during times of financial crisis. This is evidenced by a decrease in the values of the sample entropy and approximate entropy before and after/during the financial crisis period for the majority of the exchange rates. Our empirical results also show that Sample Entropy is a better measure of regularity than Approximate Entropy for the Indian forex rates which is in agreement with the theoretical predictions. Understanding the returns from foreign exchange rates during financial crises has important policy implications for various stakeholders, including market participants, policymakers, and regulators. It enables them to formulate better risk management and hedging strategies. It also helps policy makers in crisis management and contingency planning and safeguard the stability of the financial system. Exchange rate movements are interconnected across global markets, and crises often have cross-border implications. Collaborating on crisis management strategies across countries can help foster stability in international markets. [ABSTRACT FROM AUTHOR]

Due to the large size of image files and the high correlation between the numerical values of the pixels, various improved algorithms have been used for image encryption in recent years. In most cases improvement is obtained by taking into account the characteristics of chaotic and random processes in encryption algorithms. In this study, an algorithm is proposed that encrypts images based on a maze created by keys consisting of random numbers generated with Feigembaum's quadratic function. For the generation of the maze, deep first search (DFS) algorithm has been used. During the generation with this algorithm, numbers representing the walking paths and as well as the length of the used stack are included in the encryption process. Algorithm security verification was carried out according to key space and differential analysis, statistical analysis such as entropy estimation, and analysis of correlation between the histogram and neighboring pixels of the image. [ABSTRACT FROM AUTHOR]

Copyright of Artnodes is the property of Universitat Oberta de Catalunya and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a new pseudo-random sequence generator to improve the security of data. The method innovatively integrates a 2D Henon map into the evolutionary process of cellular automata to introduce chaotic features into selected dynamic neighbourhoods during evolution, boosting the generator's efficacy. The proposed generator outperforms static neighborhood-based pseudo-random generators and meets the criteria defined by the National Institute of Standards. To overcome the limitation of the one-time pad algorithm, where the key length must match the plaintext length, the proposed generator ensuring that the key length matches the length plain text. The encryption scheme achieves an average entropy information value of 7.99%, which indicates robustness against entropy attacks. Additionally, the Number of Pixels Change Rate (NPCR) was above 99% and the Unified Average Changing Intensity (UACI) was close to the ideal value of 33%, demonstrating its suitability for image encryption with enhanced security and minimal complexity. [ABSTRACT FROM AUTHOR]

A hypothesis is presented to explain how the ageing process might be influenced by optimizing mitochondrial efficiency to reduce intracellular entropy. Research-based quantifications of entropy are scarce. Non-equilibrium metabolic reactions and compartmentalization were found to contribute most to lowering entropy in the cells. Like the cells, mitochondria are thermodynamically open systems exchanging matter and energy with their surroundings—the rest of the cell. Based on the calculations from cancer cells, glycolysis was reported to produce less entropy than mitochondrial oxidative phosphorylation. However, these estimations depended on the CO2 concentration so that at slightly increased CO2, it was oxidative phosphorylation that produced less entropy. Also, the thermodynamic efficiency of mitochondrial respiratory complexes varies depending on the respiratory state and oxidant/antioxidant balance. Therefore, in spite of long-standing theoretical and practical efforts, more measurements, also in isolated mitochondria, with intact and suboptimal respiration, are needed to resolve the issue. Entropy increases in ageing while mitochondrial efficiency of energy conversion, quality control, and turnover mechanisms deteriorate. Optimally functioning mitochondria are necessary to meet energy demands for cellular defence and repair processes to attenuate ageing. The intuitive approach of simply supplying more metabolic fuels (more nutrients) often has the opposite effect, namely a decrease in energy production in the case of nutrient overload. Excessive nutrient intake and obesity accelerate ageing, while calorie restriction without malnutrition can prolong life. Balanced nutrient intake adapted to needs/activity-based high ATP requirement increases mitochondrial respiratory efficiency and leads to multiple alterations in gene expression and metabolic adaptations. Therefore, rather than overfeeding, it is necessary to fine-tune energy production by optimizing mitochondrial function and reducing oxidative stress; the evidence is discussed in this paper. [ABSTRACT FROM AUTHOR]

This paper introduces a design of ternary bistale ring physical unclonable function (BRPUF) based on carbon nanotube field effect transistors (CNTFETs). PUFs can extract unique chip features from process variations and assign every chip an inherent fingerprint to be used for identification or authentication of devices. As the main point of strength for PUF security, the size of challenge-response pairs (CRPs) can be increased by adopting multi-valued logic designs. The proposed ternary BRPUF blends higher entropy into CRPs and is tested to produce unbiased response digits, thus making them more unpredictable and more resistant against machine learning attacks. The instinctive features of CNTFETs, such as intensive process variations and high tolerance against temperature fluctuations and noises, enable our design to function robustly in a wide range of operating conditions. The proposed design has been implemented using standard 32-nm CNTFET model libraries and tested by HSPICE simulations. The results elaborate the superiority of our work compared with the traditional binary BRPUFs. [ABSTRACT FROM AUTHOR]

Since the introduction of the Kolmogorov complexity of binary sequences in the 1960s, there have been significant advancements on the topic of complexity measures for randomness assessment, which are of fundamental importance in theoretical computer science and of practical interest in cryptography. This survey reviews notable research from the past four decades on the linear, quadratic and maximum-order complexities of pseudo-random sequences, and their relations with Lempel–Ziv complexity, expansion complexity, 2-adic complexity and correlation measures. [ABSTRACT FROM AUTHOR]

Abstract Background In the excitement about genomics, it is easy to lose sight of one of the most important findings from behavioural genetics: At least half of the variance of psychopathology is caused by environmental effects that are not shared by children growing up in the same family, which includes error of measurement. However, a 30‐year search for the systematic causes of nonshared environment in a line‐up of the usual suspects, especially parenting, has not identified the culprits. Method I briefly review this research, but primarily consider the conceptual framework of the search for ‘missing’ nonshared environmental effects. Results The search has focused on exogenous events like parenting, but nonshared environment might not be caused by anything we would call an event. Instead, it might reflect endogenous processes such as noisy biological systems (such as somatic mutations and epigenetics) or, at a psychological level, idiosyncratic subjective perceptions of past and present experiences, which could be called nonshared environmental experience to distinguish it from exogenous events. Although real, nonshared environment might be random in the philosophy of science sense of being unpredictable, even though it can have stable effects that predict subsequent behaviour. Conclusion I wade into the weeds of randomness and suggest that this so‐called ‘gloomy prospect’ might not be so gloomy.

This study addresses the temporal variability and randomness of concrete's chloride diffusion coefficient by proposing an analysis using stochastic measures for the instantaneous chloride diffusion coefficient (Dins) alongside Kullback-Leibler (K-L) divergence and Hamming distance for similarity assessment. Examination of diverse concrete specimens subjected to both natural tidal environments (NE) and simulated environments (SE) indicated that the environmental factors, primarily exposure setting and duration, substantially influence the diffusion coefficient's temporal behavior. SE with elevated temperature and salinity accelerated chloride penetration, leading to higher diffusion rate means than those in NE. Concrete in NE exhibited a log-normal distribution for Dins, while under SE, a normal distribution was observed. Variability was mainly driven by the exposure environment, with minor contributions from material components. Similarity analysis suggested that the stochastic character of Dins in SE after 120 days resembled those in NE at 600 days, as per K-L divergence, whereas Hamming distance showed the closest resemblance at 240 days in SE. The Material make-up showed negligible impact on distribution similarity, and the extending simulation exposure time had a limited effect on enhancing similarity of stochastic diffusion behavior across environments.

This study is to investigate the effects of random interfacial debonded on the elastic constants of carbon fiber reinforced composites. The results reveal that the interfacial debonded fraction (IDF) significantly effects the elastic constants, and the randomness of interfacial debonded position significantly effects the stress distribution, but different interfacial debonded positions at the same IDF have a negligible effect on the elastic constants. The increase of IDF leads to a gradual increase in the disruption of tandem integrity between fibers and matrix, limiting the capability of the interface to transfer loads more significantly. [ABSTRACT FROM AUTHOR]

Objective To summarize the performance and implementation status of various randomization methods, and to provide clinical researchers with a guide for choosing an appropriate randomization method and executing it in a standardized manner. Methods The review elucidated the conceptual and implementation integrity of randomization, and illuminated the developmental history and application of major randomization methods, as well as their performance in the two competitive dimensions of group allocation randomness and group sample balance. Results Restricted randomization was frequently used to maintain an appropriate treatment balance in practice. Block randomization was the most widely used, but its allocation sequence lacked sufficient randomness and could be predicted, elevating the risk of selection bias, especially in open-label trials. Methods offering a superior trade-off between randomness and balance included MTI restricted randomization methods like the big stick design and maximal procedure, as well as combinations of multiple randomization methods such as the block urn design and sandwich mixed randomization. Many clinical researchers still had misconceptions about the randomization concept itself and often overlooked its critical methodological rigor and standardized implementation. Conclusion Researchers should meticulously choose a suitable randomization method and report implementation details in a standardized manner, allowing peer researchers to evaluate the internal validity and evidence strength of the study. Due to its high predictability, the widely used block randomization method should be substituted by alternative methods with better performance. Future randomization procedures can be explored and developed based on the MTI restrictive methods and the combinations of existing methods. [ABSTRACT FROM AUTHOR]

While nature loves symmetry inasmuch as many natural laws remain invariant under various transformations, description of the natural diversity warrants some kind of breakdown of symmetry. Such a breakdown of symmetry may be either explicit or spontaneous. Many significant developments have taken place in recent times in diverse fields of study. Algorithmic information theory has been formulated by Kolmogorov and others. Spontaneous breakdown of symmetry and its use in the standard model of particle physics, discovery of the Higgs Boson are all notable events. Work of Ilya Prigogine to accommodate biological self-organisation within the ambit of the second law of thermodynamics is also quite noteworthy. According to some, his principle of minimum entropy production has added a dynamic content to the second law of thermodynamics, which otherwise is viewed as a mere kinematic constraint. It appears that non-linear dynamics and the catastrophe theory of Rene Thom can play an important role to understand a sudden qualitative change of a dynamical system triggered by certain value of a parameter. Phase change of water subjected to external heating or change from a stable economy to one marked by trade cycles are examples of such sudden transitions. Advent of econophysics and behavioural finance has facilitated a new way of looking logically at the problems of finance and economics with the help of established physical laws as well as rigorous mathematical and statistical analyses. Importance of such an approach is evident from the sad plight of Louis Bachelier. In this article, it has been our effort to link up such apparently disjoint developments from diverse fields of study within the ambit of a single logically consistent framework. [ABSTRACT FROM AUTHOR]

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33–50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment. [ABSTRACT FROM AUTHOR]

Genome steganography has emerged as a promising field for transmitting large amounts of data over an untrusted channel in the last two decades. DNA has many advantages over other multimedia cover mediums. Substitution is the most common approach to developing a DNA-based steganography algorithm. Components of the secret message are converted to DNA letters, which replace nucleotides in the cover sequence. The conversion is conducted through predetermined tables like binary coding rules and lookup/dictionary tables. These tables are static, limited to specific alphanumeric characters, and may compromise the hidden message if discovered by intruders. Most previously proposed algorithms adopt a simple sequential and ordered hiding pattern. This leads to poor utilization of the available hiding spots and creates a region of interest for attackers to apply steganalysis. In this paper, a novel DNA-based algorithm is proposed. Using two DNA sequences, primary and secondary, is the basis for this algorithm. Both sequences are segmented, where the primary sequence segments are for hiding the data, and the secondary sequence segments are for conveying the required information to find and extract the hidden data. Three enhanced tables are proposed: a modified ASCII table, a 4-bit binary coding rule table, and a two-tier lookup encoding table to convert the message to DNA form. The segmentation ensures that the hiding spots are randomly scattered across the primary cover DNA sequence, addressing the region of interest issue. The data is hidden in the cover using the least significant base substitutions. The result is an all-rounded algorithm that fulfills the desired performance measurements such as zero payloads, blindness, preserving functionality, high hiding capacity, low modification rate, and low cracking probability. [ABSTRACT FROM AUTHOR]

The XOR operator is a simple yet crucial computation in computer science, especially in cryptography. In symmetric cryptographic schemes, particularly in block ciphers, the AddRoundKey transformation is commonly used to XOR an internal state with a round key. One method to enhance the security of block ciphers is to diversify this transformation. In this paper, we propose some straightforward yet highly effective techniques for generating t-bit random XOR tables. One approach is based on the Hadamard matrix, while another draws inspiration from the popular intellectual game Sudoku. Additionally, we introduce algorithms to animate the XOR transformation for generalized block ciphers. Specifically, we apply our findings to the AES encryption standard to present the key-dependent AES algorithm. Furthermore, we conduct a security analysis and assess the randomness of the proposed key-dependent AES algorithm using NIST SP 800-22, Shannon entropy based on the ENT tool, and min-entropy based on NIST SP 800-90B. Thanks to the key-dependent random XOR tables, the key-dependent AES algorithm have become much more secure than AES, and they also achieve better results in some statistical standards than AES. [ABSTRACT FROM AUTHOR]

Symmetric cryptography provides the best examples of cryptosystems to be applied in lightweight environments (e.g., IoT). A representative example is the cryptosystem TinyJambu, one of the ten finalists in the NIST Lightweight Cryptography Standardization Project. It is an authentication encryption with associated data scheme that is extremely lightweight and fast. In this work, we analyze the security of TinyJambu from two distinct and non-symmetric points of view: (1) the improvement of the best cryptanalytical attack found in the literature and (2) a randomness analysis of the generated sequences. Concerning item (1), we launched a differential forgery attack with probability 2−65.9487, which was improved considerably compared with previous numerical results. Concerning item (2), we analyzed the degree of randomness of the TinyJambu keystream sequences with a complete and powerful battery of statistical tests. This non-symmetric study shows the weakness of TinyJambu against cryptanalytic attacks as well as the strength of TinyJambu against statistical analysis. [ABSTRACT FROM AUTHOR]

We investigate whether it is possible to distinguish chaotic time series from random time series using network theory. In this perspective, we selected four methods to generate graphs from time series: the natural, the horizontal, the limited penetrable horizontal visibility graph, and the phase space reconstruction method. These methods claim that the distinction of chaos from randomness is possible by studying the degree distribution of the generated graphs. We evaluated these methods by computing the results for chaotic time series from the 2D Torus Automorphisms, the chaotic Lorenz system, and a random sequence derived from the normal distribution. Although the results confirm previous studies, we found that the distinction of chaos from randomness is not generally possible in the context of the above methodologies. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Among large-span bridges, arch bridges have relatively high stiffness, which may lead to large dynamic amplification factors (DAFs). The DAFs suggested by current codes mostly originate from common simply supported beam bridges. Previous DAF studies on dynamic vehicle–bridge solutions for arch bridges have mainly focused on one or two side-by-side vehicles. However, complex traffic flows with randomness rather than one or two vehicles act on bridges. DAFs that consider the effects of random traffic flows have not previously been reported. In this study, a random traffic–bridge vibration solution was established to explore the DAFs of arch bridge components. The randomness of the traffic parameters and road roughness was explored. The randomness of the external excitation, including traffic flow and road roughness, resulted in random dynamic responses and DAFs of the arch bridge components. Normal distributions could be used to fit the DAF distributions of each arch bridge component under random vehicle spacing, weight, speed, and road roughness. Under random traffic parameters, the coefficients of variation of the DAFs exceeded the 5% accepted level. The shortest suspenders were more sensitive to the randomness of the traffic flow parameters. Both the mean and coefficient of variation of the DAFs increased with worsening of the road conditions. The influence of the randomness of the road roughness on the DAFs of arch bridges must be considered, particularly for the shortest suspender. The 95% upper confidence limits of the DAFs for all components may be greater than the suggested values in the code. [ABSTRACT FROM AUTHOR]

There is still controversy surrounding the definition and mechanisms of consciousness. The constrained disorder principle (CDP) defines complex systems by their dynamic borders, limiting their inherent disorder. In line with the CDP, the brain exhibits a disorder bounded by dynamic borders essential for proper function, efficient energy use, and life support under continuous perturbations. The brain's inherent variability contributes to its adaptability and flexibility. Neuronal signal variability challenges the association of brain structures with consciousness and methods for assessing consciousness. The present paper discusses some theories about consciousness, emphasizing their failure to explain the brain's variability. This paper describes how the CDP accounts for consciousness's variability, complexity, entropy, and uncertainty. Using newly developed second-generation artificial intelligence systems, we describe how CDP-based platforms may improve disorders of consciousness (DoC) by accounting for consciousness variability, complexity, entropy, and uncertainty. This platform could be used to improve response to current interventions and develop new therapeutic regimens for patients with DoC in future studies. [ABSTRACT FROM AUTHOR]

Aquatic vegetation plays an important role in natural water environments by interacting with the flow and generating turbulence that affects the air‐water and sediment‐water interfacial transfer. Regular and staggered arrays are often set as simplified layouts for vegetation canopy to study both mean flow and turbulence statistics in vegetated flows, which creates uniform spacing between vegetation elements, resulting in preferential flow paths within the array. Such preferential paths can produce local high velocity and strong turbulence, which do not necessarily happen in natural environments where vegetation is randomly distributed. How the randomness of the canopy affects interfacial processes by altering spatial turbulence distribution, which can potentially lead to different turbulence feedback on the interfacial transfer process, remains an open question. This study conducted a series of laboratory experiments in a race‐track flume using rigid cylinders as plant surrogates. Mean and turbulent flow statistics were characterized by horizontal‐ and vertical‐sliced PIV. Based on the measured flow characteristics under different stem diameters and array configurations, we propose a method to quantify the randomness of the vegetation array and update a sediment‐water‐air interfacial gas transfer model with the randomness parameter to improve its accuracy. The updated model agrees well with the dissolved oxygen experimental data from our study and data from existing literature at various scales. The study provides critical insight into water quality management in vegetated channels with improved dissolved oxygen predictions considering vegetation layout as part of the interfacial transfer model. Plain Language Summary: Aquatic vegetation plays an important role in natural water environments by interacting with the flow and generating turbulence, which affects the interfacial gas transfer across the air‐water and sediment‐water interfaces. Researchers often used regular and staggered arrays as simplified vegetation layouts in laboratory experiments to study the flow hydrodynamics of vegetated channels. However, such regular vegetation pattern creates uniform spacing between stem elements, resulting in preferential flow paths within the canopy, which is unrealistic in nature where plants are randomly distributed. To understand the discrepancies between the idealized and the actual field cases, laboratory experiments were conducted in a race‐track flume using arrays of rigid cylinders as plant surrogates. We investigate the effects of randomly distributed vegetation on hydrodynamics and how spatial heterogeneity can alter turbulence feedback on interfacial transfer processes. A randomness index was proposed based on the measured flow characteristics under different stem diameters and array configurations to update previous interfacial transfer models. The study provides helpful insight into water quality management in vegetated channels, with improved dissolved oxygen predictions via a more accurate and universal interfacial transfer model with different vegetation distribution patterns. Key Points: An index based on lateral flow variations is proposed to quantify the randomness in the distribution of vegetation elements in a canopyLayout of emergent vegetation does not affect surface gas transfer rates, as the average of the horizontal‐shear turbulence remains the sameContributions from coherent structures by flow‐stem‐bed interaction need to be corrected by the randomness index for sediment‐water transfer [ABSTRACT FROM AUTHOR]

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Abstract Inundations in Amazonian black‐water river floodplain result in the selection of different tree lineages, thus promoting coexistence between species. We investigated whether Amazonian tree communities are phylogenetically structured and distributed along a flooding gradient from irregularly flooded forests along streams embedded within upland (terra‐firme) forest to seasonally flooded floodplains of large rivers (igapós). Floristic inventories and hydrological monitoring were performed along the Falsino River, a black‐water river in the eastern Amazon within the Amapá National Forest. We constructed a presence‐and‐absence matrix and generated a phylogeny using the vascular plant database available in GenBank. We calculated the standardized values of the metrics of phylogenetic diversity (ses.PD), average phylogenetic distance (ses.MPD), and average nearest‐neighbor distance (ses.MNTD) to test whether the history of relationships between species in the community is influenced by inundation. We used the phylogenetic endemism (PE) metric to verify the existence of taxa with restricted distribution. Linear regressions were used to test whether phylogenetic metrics have a significant relationship with the variables: maximum flood height, maximum water table depth, and maximum flood amplitude. The results show that forests subject to prolonged seasonal flooding have reduced taxon richness, low phylogenetic diversity, and random distribution of lineages within communities. On the other hand, terra‐firme riparian forests showed higher rates of taxon richness, diversity, and phylogenetic dispersion, in addition to greater phylogenetic endemism. These results indicate that seasonal and predictable soil flooding filters tree lineages along the hydrographic gradient. Different adaptations to root waterlogging are likely requirements for colonization in these environments and may represent an important factor in the diversification of tree lineages in the Amazon biome.

Association football (commonly known as football or soccer) in the modern era places a greater emphasis on collaborating and working together as a team instead of relying solely on individual skills to strategize winning performances. The low-scoring and unpredictable nature of association football makes evaluating team performances challenging. Space creation and space utilization have been discussed in the football world lately. Existing literature evaluates this with on and off-ball runs by players for deceiving defenders to create open spaces. However, the contribution of these team ball movements’ enhanced randomness or chaotic nature to winning performances has yet to be explored. This work proposes a novel entropy-based time-series performance evaluation metric, EDRan, for quantifying this enhanced random nature by analyzing the spatial distribution of game events at regular intervals. Additionally, an unexplored cumulative ball possession matrix is used to quantify randomness. The correlation between the match winner and spatial event distribution randomness at regular intervals was analyzed. The significance of the proposed metric was demonstrated using a generalized linear model (GLM), which achieved an average accuracy of 80% for match-winning performance classification. The GLM p-values and coefficients revealed statistically significant relationships between the extracted temporal features and match-winning performances. Findings further revealed dispersed, highly random event distribution by winning teams during the early phases of the game, implying attacking behavior, followed by a compact, cautious playing style toward the end, suggesting that the game’s first-half performances are more pivotal. Despite the unpredictability of actual scores in association football, the proposed approach effectively captured the differences in performances between stronger and weaker teams with temporal relationships, highlighting its significance as a time-series metric for performance evaluation.

Simulating the concrete fracture unlike other elastic and brittle materials quite different due to its quasibrittleness. The present research focussed on assess softening behavior by varying different fractions of aggregates and cement matrix in micro details. Extended Finite Element Method (XFEM) for crack modeling implemented for simulating and visualizing crack propagation through Cement matrix, Interfacial Transition Zone (ITZ) and Aggregates . This approach permits the initializing crack by from enrichment zone and propagation of crack through element by traction separation law .The crack formation initiates when the maximum principal tensile stress reaches the tensile strength. The work involves creating python script for iterative process of random distribution of aggregates with in the matrix using Monte Carlo method and creating Cohesive zone element for zero thickness ITZ. introduces a finite element modeling technique for investigating multiscale fracture characteristics. This approach encompasses multiple levels of analysis, including the generation of aggregate particles using a Monte Carlo method implemented via a Python script. Additionally, we replicate the Interfacial Transition Zone (ITZ) between aggregate and mortar in the model. The load-deflection curves can be used to assess the softening behavior of concrete and suggest the realistic fraction of coarse aggregate in mix proportion to impart more ductility to beams.