The design complexity of the new generation of civil aero-engines results in higher demands on engines’ components, higher component temperature, higher heat generation, and, finally, critical thermal management issues. This paper will propose a methodological approach to create physics-based models for heat loads developed by sources as well as a systematic sensitivity analysis to identify the effects of design parameters on the thermal behaviour of civil aero-engines. The ranges and levels of heat loads generated by heat sources (e.g., accessory gearbox, bearing, pumps, etc.) and heat absorption capacity of heat sinks (e.g., engine fuel, oil, and air) are discussed systematically. The practical research challenges for thermal management system design and development for the new and next generation of turbofan engines will then be addressed through a sensitivity analysis of the heat load values as well as the heat sinks flow rates. The potential solutions for thermal performance enhancements of propulsion systems will be proposed and discussed accordingly.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

The objective of this research is to establish a better understanding of the current landscape of digital learning research and sustainable development by using CiteSpace. First, we retrieved published publications from the Web of Science (2004–2022). Following that, we examined the primary research strengths and important subjects of digital learning from two perspectives: collaboration networks (including collaborative networks across countries, institutions, and authors) and co-citation networks. We examined the co-citation network from three perspectives: cluster analysis, the most active citers, top references. Furthermore, referenced journals, popular themes, and rising trends were examined. These findings indicate the primary study subjects in the field of digital learning, the most intriguing research literature, and each period's emerging research hotspots. Finally, we proposed further study ideas for future paths.

Cholangiocellular carcinoma (CCA) is the second most common primary liver cancer, with increasing incidence worldwide and inadequate therapeutic options. Intra- and extrahepatic bile ducts have distinctly different embryonic origins and developmental behavior, and accordingly intra- and extrahepatic CCAs (ICC vs. ECC) are molecularly different. A promising strategy in oncotherapy is targeted therapy, targeting proteins that regulate cell survival and proliferation; such as the MAPK/ERK and PI3K/AKT/mTOR signaling pathways. Inhibitors of these pathways have been tested previously in CCA cell lines. However, these cell lines could not be clearly assigned to ICC or ECC, and results indicated apoptosis induction by targeted therapeutics. We tested targeted therapeutics (selumetinib, MK2206) in three defined ICC cell lines (HuH28, RBE, SSP25). We observed cooperative effects of dual inhibition of the two pathways, in accordance with inhibition of phospho-AKT and phospho-ERK1/2 expression. Proliferation was blocked more effectively with dual inhibition than with each single inhibition, but cell numbers did not drop below baseline. Accordingly, we observed G1-phase arrest, but not apoptosis (cleaved caspase-3, AIFM1 regulation, subG1-phase) or necroptosis (phospho-MLKL). We conclude that dual inhibition of MAPK/ERK and PI3K/AKT/mTOR pathways is highly effective to block proliferation of ICC cell lines, but therapy must certainly be supplemented with standard therapies.

Historical maps constitute unique sources of retrospective geographic information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geographic information contained in such data archives allows extending geospatial analysis retrospectively beyond the era of digital cartography. However, given the large data volumes of such archives and the low graphical quality of older map sheets, the processes to extract geographic information need to be automated to the highest degree possible. In order to understand the salient characteristics, data quality variation, and potential challenges in large-scale information extraction tasks, preparatory analytical steps are required to efficiently assess spatio-temporal coverage, approximate map content, and spatial accuracy of such georeferenced map archives across different cartographic scales. Such preparatory steps are often neglected or ignored in the map processing literature but represent highly critical phases that lay the foundation for any subsequent computational analysis and recognition. In this contribution we demonstrate how such preparatory analyses can be conducted using classical analytical and cartographic techniques as well as visual-analytical data mining tools originating from machine learning and data science, exemplified for the United States Geological Survey topographic map and Sanborn fire insurance map archives.

This work intends to present a study on relations between a Lie algebra called dispersion operators algebra, linear canonical transformation and a phase space representation of quantum mechanics that we have introduced and studied in previous works. The paper begins with a brief recall of our previous works followed by the description of the dispersion operators algebra which is performed in the framework of the phase space representation. Then, linear canonical transformations are introduced and linked with this algebra. A multidimensional generalization of the obtained results is given.

In any region of a space, the gravitational field cannot be eliminated. The speed of light in a vacuum has never been observed and cannot be observed with current technology. Till now, only the speed of light in a gravitational field has been observed. It results in that all the observed speed of light are always being varied by the gravity. Here, it is presented that light could be dispersion in a gravitational field analogous to the dispersion of light in the Newtonian prism experiment. The relativistic mass density on the surface of a neutron star is on the level of 10¹⁷kg/m³ while on the surface of the Earth is only 10^-7kg/m³, the effect of the gravitational field acting on the speed of light by a neutron star is much larger than that by the Earth. Therefore, the dispersion of light in strong gravitational field could be generally observed from the image of a star and it should have been observed through the double-image gravitational lensing and the spectroscopic binary system. And, it should affect the observed numbers, spectrogram, size and distance of the celestial objects.

Fast Field-Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry is a powerful non-destructive magnetic resonance technique that enables, among other things, the investigation of slow molecular dynamics at low magnetic field intensities. FFC-NMR relaxometry measurements provide insight into molecular motion across various timescales within a single experiment. This study focuses on a \textit{model-free} approach, representing the NMRD profile $R_1$ as a linear combination of Lorentzian functions, thereby addressing the challenges of fitting data within an ill-conditioned linear least-squares framework. Tackling this problem, we present a comprehensive review and experimental validation of three regularization approaches to implement the model-free approach to analysing NMRD profiles. These include: (1) \nameUpe, utilizing locally adapted $L_2$ regularization; (2) \nameL, based on $L_1$ penalties; and (3) a hybrid approach combining locally adapted $L_2$ and global $L_1$ penalties. Each method's regularization parameters are determined automatically, according to the Balancing and Uniform Penalty principles. % Our contributions include the implementation and experimental validation of the \nameUpe{} and \nameUp{} algorithms, and the development of a "dispersion analysis" technique to assess the existence range of the estimated parameters. The objective of this work is to delineate the variance in fit quality and correlation time distribution yielded by each algorithm, thus broadening the set of software tools for the analysis of sample structures in FFC-NMR studies. The findings underline the efficacy and applicability of these algorithms in the analysis of NMRD profiles from samples representing different potential scenarios. 1

Recently we have seen a relaxation of the historic restrictions on the use and subsequent research on the Cannabis plants, generally classified as Cannabis sativa and Cannabis indica. What research has been performed to date has centered on chemical analysis of plant flower products, namely cannabinoids and various terpenes that directly contribute to phenotypic characteristics of the female flowers. In addition, we have seen many groups recently completing genetic profiles of various plants of commercial value. To date, no comprehensive attempt has been made to profile the proteomes of these plants. We report herein our progress on constructing a comprehensive draft map of the Cannabis proteome. To date we have identified over 17,000 potential protein sequences. Unfortunately, no annotated genome of Cannabis plants currently exists. We present a method by which “next generation” DNA sequencing output and shotgun proteomics data can be combined to produce annotated FASTA files, bypassing the need for annotated genetic information altogether in traditional proteomics workflows. The resulting material represents the first comprehensive annotated protein FASTA for any Cannabis plant. Using this annotated database as reference we can refine our protein identifications, resulting in the confident identification of 13,000 proteins with putative function. Furthermore, we demonstrate that post-translational modifications play an important role in the proteomes of Cannabis flower, particularly lysine acetylation and protein glycosylation. To facilitate the evolution of analytical investigations into these plant materials, we have created a portal to host resources we have developed from proteomic and metabolomic analysis of Cannabis plant material as well as our results integrating these resources. All data for this project is available to view or download at www.CannabisDraftMap.Org

Abstract: The air pollution dispersion modelling via spatial analyses (Land Use Regression – LUR) is an alternative approach to the air quality assessment to the standard air pollution dispersion modelling techniques. Its advantages are mainly much simpler mathematical apparatus, quicker and simpler calculations and a possibility to incorporate other factors affecting pollutant’s concentration. The goal of the study was to model the PM10 particles dispersion modelling via spatial analyses v in Czech-Polish border area of Upper Silesian industrial agglomeration and compare results with results of the standard Gaussian dispersion model SYMOS’97. Results show that standard Gaussian model with the same data as the LUR model gives better results (determination coefficient 71% for Gaussian model to 48% for LUR model). When factors of the land cover and were included into the LUR model, the LUR model results were significantly improved (65% determination coefficient) to the level comparable with Gaussian model. The hybrid approach combining the Gaussian model with the LUR gives superior quality of results (65% determination coefficient).

Local air quality is a major concern for the population regularly exposed to high levels of air pollution. The airport, mainly due to its aircraft engines activities during taxiing and take off, is often submitted to heterogeneous but important concentrations of NOx and PM. The study suggests an innovative approach to determine the air traffic impact on air quality at the scale of the airport, its runways and terminals, in order to be able to locate the persistent high concentrations spots. The pollutants concentrations at 10 m resolution and 1 s time step are calculated in order to identify the most affected areas of an airport platform. A real day of air traffic on a regional airport is simulated, using real data as aircraft trajectories (from radar streams). In order to estimate the aircraft emissions, the Air Transport Systems Evaluation Infrastructure (IESTA) is used. Regarding local air quality, IESTA relies on the non-hydrostatic meso-scale atmospheric model Meso-NH using grid-nesting capabilities with 3 domains, for this study. The detailed cartography of the airport distinguishes between grassland, parking and terminals, allowing to compute exchanges of heat, water and momentum between the different types of surfaces and the atmosphere as well as the interactions with the building using a drag force. The dynamic parameters like wind, temperature, turbulent kinetic energy and pollutants concentration are computed at 10 m resolution over the 2 × 4 km airport domain. The pollutants are considered in this preliminary study as passive tracers, without chemical reactions. This preliminary study aims at proving the feasibility of high scale modelling over an airport with state of the art physical models.

Image encryption based on chaotic maps is an important way to ensure the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed by employing a compound chaotic map and random cyclic shift. Firstly, an improved Hybrid chaotic system is designed by coupling Logistic, ICMIC, Tent, and Chebyshev maps (HLITC). Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and Kolmogorov entropy illustrate the new hybrid chaotic map has better chaotic performance. Then the proposed HLITC chaotic system is used to develop a new chaotic image encryption scheme with the double cyclic shift. The improved HLITC chaotic system is performed to generate key sequences used in the image scrambling and diffusion stage. The spiral transformation controlled by chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments of statistical analysis, key sensitivity, and keyspace analysis are conducted. Experimental results show the proposed encryption scheme has good robustness against brute force attacks, statistical attacks, and differential attacks, and is more effective than many existing chaotic image encryption algorithms.

Cyberspace map, as one of the important tools to describe cyberspace, gives an image to the unpredictable and illusory cyberspace, and has become a research hotspot in the fields of cartography, cyberspace security. Clarifying the concept of cyberspace map and constructing the conceptual model of cyberspace map can promote people's unified cognition of cyberspace. Based on the view of cartography, this paper compares and analyzes some related concepts of cyberspace map, discusses the characteristics of cyberspace map，and gives its concept. After that, it analyzes people's cognition of cyberspace composition. On this basis, it caters to this cognition mode and proposes the conceptual model of cyberspace map. Then, the connotation of the model is elaborated from three aspects: element-space association dimension, element mapping dimension and the map representation dimension. Finally, the specific composition and symbolization of various elements are analyzed. The model provides the top-level framework and theoretical guidance for the research of cyberspace map. This paper aims to adapt to the development trend of Cartography in ternary space, clarify the basic concept of cyberspace map, promote the development of cyberspace mapping theory, and lay the foundation for subsequent research.

We describe a vision for a national-scale heavy mineral (HM) map generated through automated mineralogical identification and quantification of HMs contained in floodplain sediments from large catchments covering most of Australia. The composition of the sediments reflects the dominant rock types in each catchment, with the generally resistant HMs largely preserving the mineralogical fingerprint of their host protoliths through the weathering-transport-deposition cycle. Heavy mineral presence/absence, absolute and relative abundance, and co-occurrence are metrics useful to map, discover and interpret catchment lithotype(s), geodynamic setting, magmatism, metamorphic grade, alteration or mineralization. Underpinning this vision is a pilot project, focusing on a subset of the national sediment sample archive, which is used to demonstrate the feasibility of the larger, national-scale project. We preview a bespoke, cloud-based mineral network analysis (MNA) tool to visualize, explore and discover relationships between HMs as well as between them and geological setting or mineral deposits. We envisage that the Heavy Mineral Map of Australia and MNA tool will contribute significantly to mineral prospectivity analysis and modeling here, particularly for technology critical elements and their host minerals, which are central to the global economy transitioning to a more sustainable, decarbonized paradigm.

In this paper the D 3 dihedral logistic map of fractional order is introduced. The map 1 presents a dihedral symmetry D 3 . It is numerically shown that the construction and interpretation 2 of the bifurcation diagram versus the fractional order require special attention. The system stability 3 is determined and the problem of hidden attractors is analyzed. Also, analytical and numerical 4 results show that the chaotic attractor of integer order, with D 3 symmetries, looses its symmetry 5 in the fractional-order variant.

The statistical properties of a good estimator include robustness, unbiasedness, efficiency, and consistency. However, the commonly used estimators of dispersion have lack or are weak in one or more of these properties. In this paper, I proposed statistical mirroring as a good alternative estimator of dispersion around defined location estimates or points. In the main part of the paper, attention is restricted to Gaussian distribution and only estimators of dispersion around the mean that functionalize with all the observations of a dataset were considered at this time. The different estimators were compared with the proposed estimators in terms of alternativeness, scale and sample size robustness, outlier biasedness, and efficiency. Monte Carlo simulation was used to generate artificial datasets for application. The proposed estimators (of statistical meanic mirroring) turn out to be suitable alternative estimators of dispersion that is less biased (more resistant) to contaminations, robust to scale and sample size, and more efficient to a random distribution of variable than the standard deviation, variance, and coefficient of variation. However, statistical meanic mirroring is not suitable with a mean (of a normal distribution) close to zero, and on a scale below ratio level.

Purpose: To investigate the effect of pigment dispersion on trabecular meshwork (TM) cells. Methods: Porcine TM cells from ab interno trabeculectomy specimens were exposed to pigment dispersion, then analyzed for changes in morphology, immunostaining, and ultrastructure. Their abilities to phagocytose, migrate, and contract were quantified. An expression microarray, using 23,937 probes, and a pathway analysis were performed. Results: TM cells readily phagocytosed pigment granules. Pigment induced stress fiber formation (pigment (P): 60.1 ± 0.3%, n = 10, control (C): 38.4 ± 2.5%, n = 11, P < 0.001) and contraction at 24 hours onward (P < 0.01). Phagocytosis declined (P: 68.7 ± 1.3%, C: 37.0 ± 1.1%, n = 3, P < 0.001) and migration was reduced after 6 hours (P: 28.0.1 ± 2.3, n = 12, C: 40.6 ± 3.3, n = 13, P < 0.01). Microarray analysis revealed that Rho, IGF-1, and TGFβ signaling cascades were central to these responses. Conclusions: TM cell exposure to pigment dispersion resulted in reduced phagocytosis and migration, as well as increased stress fiber formation and cell contraction. The Rho signaling pathway played a central and early role, suggesting that its inhibitors could be used as a specific intervention in treatment of pigmentary glaucoma.

In the past few decades, the transmission of data over an unsecure channel resulted in an increased rate of hacking. Therefore, the requirement to make multimedia data more secure is increasing day by day. Numerous algorithms are developed to improve efficiency and robustness. In this article, a novel and secure image encryption algorithm is presented. It is based on a modified chaotic logistic map (CLM) that provides the advantage of having less computational time to encrypt an input image. The encryption algorithm is based on Shannon’s idea of using substitution-permutation and one-time-pad network to achieve ideal secrecy. The CLM is used for substitution and permutation to improve randomness and increase dependency on the encryption key. Various statistical tests are conducted, such as Key Space Analysis, Complexity Analysis, Sensitivity Analysis, Strict Avalanche Criteria (SAC), Histogram Analysis, Entropy Analysis, Mean of Absolute Deviation (MAD) Analysis, Correlation Analysis, Contrast Analysis, and Homogeneity to give a comparative analysis of the proposed algorithm and verify its security. As a result of various statistical tests, it is evident that the proposed algorithm is more efficient and robust as compared to previous ones.

By constructing a static map, the library robot can navigate and access documents autonomously, which greatly improves efficiency; however, for libraries where shelves can be moved, map changes do not allow for direct navigation, and also sensors such as radar and camera are relatively expensive, so we propose a low-cost navigation algorithm based on real-time ranging data and map matrices, and designed a mobile archive access robot. In order to obtain real-time distance data, nine near/long range sensors were mounted on the chassis and a composite digital filtering algorithm was designed based on different moving area characteristics; then the access task matrix and map matrix were designed based on the archive access task and the location characteristics of the archive shelf placement, the robot can rely on the range data to update the map matrix during the moving process, complete its own positioning, and use the task matrix The robot can use the task matrix to complete autonomous navigation and access to multiple files. Experiments show that the filtered positioning accuracy can reach 1cm, while the robot can move to the target shelf autonomously, which is more practical and less costly.

Quantum tunneling in a two-dimensional integrable map is studied. The orbits of the map are all confined to the curves specified by the one-dimensional Hamiltonian. It is found that the behavior of tunneling splitting for the integrable map and the associated Hamiltonian system is qualitatively the same, with only a slight difference in magnitude. However, the tunneling tails of the wave functions, obtained by superposing the eigenfunctions that form the doublet, exhibit significant difference. To explore the origin of the difference, we observe the classical dynamics in the complex plane and find that the existence of branch points appearing in the potential function of the integrable map could play the role for yielding non-trivial behavior in the tunneling tail. The result highlights the subtlety of quantum tunneling, which cannot be captured in nature only by the dynamics in the real plane.

Many studies in the field of robot navigation have focused on environment representation and localization. The goal of map representation is to summarize spatial information in topological and geometrical abstracts. By providing strong priors, maps improve the performance and reliability of automated robots. Due to the transition to fully automated driving in recent years, there has been a constant effort to design methods and technologies to improve the precision of road participants and the environment's information. Among these efforts is the High Definition (HD) Map concept. Making HD maps requires accuracy, completeness, verifiability, and extensibility. Because of the complexity of HD mapping, it is currently expensive and difficult to implement, particularly in an urban environment. In an urban traffic system, the road model is at least a map with sets of roads, lanes, and lane markers. While more research is being dedicated to mapping and localization, a comprehensive review of the various types of map representation is still required. This paper presents a brief overview of map representation, followed by a detailed literature review of HD Map for automated vehicles. The current state of AV mapping is encouraging, the field has matured to a point where detailed maps of complex environments are built in real-time and have been proved useful. Many existing techniques are robust to noise and can cope with a large range of environments. Nevertheless, there are still open problems for future research. AV mapping will continue to be a highly active research area essential to the goal of achieving full autonomy.

Landscapes evolve due to climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics. These processes link geological processes at depth to surface features. Consequently, the study of landscapes can reveal essential information about the geochemical footprint of ore deposits at depth. Advances in satellite imaging and computing power have enabled the creation of large geospatial datasets, the sheer size of which necessitates automated processing. We describe a methodology to enable the automated mapping of landscape pattern domains using machine learning (ML) algorithms. From a freely available Digital Elevation Model, derived data, and sample landclass boundaries provided by domain experts, our algorithm produces a dense map of the model region in Western Australia. Both random forest and support vector machine classification achieve about 98\% classification accuracy with reasonable runtime of 48 minutes on a single core. We discuss computational resources and study the effect of grid resolution. Larger tiles result in a more contiguous map, while smaller tiles result in a more detailed, and at some point, noisy map. Diversity and distribution of landscapes mapped in this study support previous results. In addition, our results are consistent with the geological trends and main basement features in the region.

Some of the most promising small molecule toxins used to generate antibody drug conjugates (ADCs) include anti-mitotic agents (e.g auristatin and its derivatives) which are designed to attack cancerous cells at their most vulnerable state during mitosis. We were interested to identify a human cystostatic protein eventually showing comparable activities and allowing the generation of corresponding targeted fully human cytolytic fusion proteins. Recently, we identified the human microtubule associated protein tau (MAP tau) which binds specifically to tubulin and modulates the stability of microtubules thereby blocking mitosis and presumably vesicular transport. By binding and stabilizing polymerized microtubule filaments, MAP tau-based fusion proteins skew microtubule dynamics towards cell cycle arrest and apoptosis. This biological activity makes rapidly proliferating cells (e.g cancer and inflammatory cells) an excellent target for MAP tau-based targeted treatments. Their superior selectivity for proliferating cells confers additional selectivity towards upregulated tumor-associated antigens at their surface, thereby preventing off-target related toxicity against normal cells bearing tumor-associated antigens at physiologically normal to low levels. In this review, we highlight recent findings on MAP tau-based targeted cytolytic fusion proteins reported in preclinical immunotherapeutic studies.

Refractive index measurements have been an important task for a long time because that index plays an essential role in describing the optical properties of a material. Many methods have been developed to perform that task. Some of them use interferometry to achieve high precision, however these configurations are complicated. Some measure the critical angle using simple structures, but the accuracy is not satisfactory because it is difficult to judge the exact critical angle with intensity variations. Here we propose several new schemes based on measuring the polarization change in the total internal reflection. The proposed method has the merits of simple structure and easy incident angle determination that gives the maximum phase change. Additionally, it is possible to find the material dispersion by measuring the wavelength dependence of the polarization ellipticity. Some useful formulas relating the refractive index with the maximum phase change are obtained. This work can provide valuable alternatives for index measurement.

The present study was designed to develop a self-micellizing solid dispersion (SMSD) containing Thymoquinone (TQM), a phytonutrient obtained from Nigella sativa seeds, aiming to improve its biopharmaceutical and nephroprotective functions. The apparent solubility of TQM in polymer solutions was used to choose an appropriate amphiphilic polymer that could be used to make an SMSD system. Based on the apparent solubility, Soluplus® was chosen as an appropriate carrier, and mixing with TQM, SMSD-TQM with different loadings of TQM (5–15%) was made by solvent evaporation and freeze-drying techniques, respectively, and the formulations were optimized. The optimized SMSD-TQM was evaluated in terms of particle size distribution, morphology, release characteristics, pharmacokinetic behavior, and nephroprotective effects in a rat model of acute kidney injury. SMSD-TQM significantly improved the dissolution characteristics (97.8%) of TQM in water within 60 min. Oral administration of SMSD-TQM in rats exhibited a 4.9-fold higher systemic exposure than crystalline TQM. In a cisplatin-induced (6 mg/kg, i.p.) acute kidney-damaged rat model, oral SMSD-TQM (10 mg/kg) improved the nephroprotective effects of TQM based on the results of kidney biomarkers and histological abnormalities. These findings suggest that SMSD-TQM might be efficacious in enhancing the nephroprotective effect of TQM by overcoming biopharmaceutical limitations.

Nigella sativa's thymoquinone (TQM), a water-insoluble phytonutrient exhibits nephroprotective effects. This study intends to develop a self-micellizing solid dispersion (SMSD) of TQM for better biopharmaceutical and nephroprotective performance. Soluplus®-based SMSD of TQM was created and tested for physicochemical properties, solubility, and pharmacokinetics in rats. Plasma creatinine, blood urea nitrogen (BUN), nephrotoxic indicators, and oxidative stress biomarkers were also tested. During SMSD preparation, TQM was found amorphous, boosting solubility. Minimal band changes between TQM and Soluplus® indicate insignificant drug-carrier interactions. SMSD-TQM generated fine micelles in water, improving TQM's solubility by 97.8% in 60 min. SMSD-TQM was 4.9 times more bioavailable orally in rats than crystalline TQM. In a rat model of acute renal damage by cisplatin (6 mg/kg, i.p.), SMSD-TQM (10 mg-TQM/kg, p.o.) reduced blood creatinine and BUN by 56% and 63.2%, respectively. These findings imply that SMSD-TQM may be a potent dosage option for enhancing TQM's nutrient value.

The systems ESTE are running in nuclear crisis centers at various levels of emergency preparedness and response in Slovakia, the Czech Republic, Austria, Bulgaria, and Iran (at NPP monitored by International Atomic Energy Agency, IAEA). ESTE is a decision support system, running 24/7, and serves the crisis staff to propose actions to protect inhabitants against radiation in case of a nuclear accident. ESTE is also applicable as decision support system in case of a malicious act with radioactive dispersal device in an urban or industrial environment. Dispersion models implemented in ESTE are Lagrangean particle model (LPM) and Puff trajectory model (PTM). Described are models approaches as implemented in ESTE. PTM is applied in ESTE for the dispersion calculation near the point of release, up to 100 km from the point of nuclear accident. LPM for general atmospheric transport is applied for short-range, meso-scale and large-scale dispersion, up to dispersion on the global scale. Additionally, a specific micro-scale implementation of LPM is applied for urban scale dispersion modelling too. Dispersion models of ESTE are joined with radiological consequences models to calculate a complete spectrum of radiological parameters - effective doses, committed doses and dose rates by various irradiation pathways and by various radionuclides. Finally, radiation protective measures, like sheltering, iodine prophylaxis, or evacuation, evaluated on the base of predicted radiological impacts are proposed. Dispersion and radiological models of the state-of-the-art ESTE systems are described. Results of specific analyses, like number of particles applied, initial spatial distribution of the source, height of the bottom reference layer, are presented and discussed.

We calculate the sound velocity and the damping rate of the collective excitations of a 2D fermionic superfluid in a non-perturbative manner. Specifically, we focus on the Anderson-Bogoliubov excitations in the BEC-BCS crossover regime, as these modes have a soundlike dispersion at low momenta. The calculation is performed within the path integral formalism and the Gaussian pair fluctuation approximation. From the action functional, we obtain the propagator of the collective excitations and determine their dispersion relation by locating the poles of this propagator. We find that there is only one kind of collective excitation, which is stable at $T=0$ and has a sound velocity of $v_{F}/\sqrt{2}$ for all binding energies, i.e. throughout the BEC-BCS crossover. As the temperature is raised, the sound velocity decreases and the damping rate shows a non-monotonous behavior: after an initial increase, close to the critical temperature $T_{C}$ the damping rate decreases again. In general, higher binding energies provide higher damping rates. Finally, we calculate the response functions and propose that they can be used as another way to determine the sound velocity.

Dispersion tests based on the second order component of smooth test statistics are related to Fisher’s Index of Dispersion test, used for testing for the Poisson distribution when there are no covariates present. Such tests have been recommended in [1] to test for the Poisson distribution when covariates are present. The modified Borel-Tanner (MBT) distribution seems suited to data with extra zeroes, a monotonic decline in counts and longer tails. Here we recommend a dispersion test for the MBT distribution for both when covariates are absent and when they are present.

Ensuring safe and continuous autonomous navigation in long-term mobile robot applications is still challenging. To ensure a reliable representation of the current environment without the need for periodic re-mapping, updating the map is recommended. However, in case of incorrect estimation of robot pose, updating the map can lead to errors that prevent the robot localisation and jeopardize map accuracy. In this paper, we propose a safe LIDAR-based occupancy grid map updating algorithm for dynamic environments taking into account the uncertainties in the estimation of the robot’s pose. The proposed approach allows robust long-term operations as it can recover the robot’s pose, even when it gets lost, to continue the map update process providing a coherent map. Moreover, the approach is robust also to temporary changes in the map due to the presence of dynamic obstacles such as humans and other robots. Results highlighting map quality, localisation performance, and pose recovery, both in simulation and experiments, are reported.

Since its original publication 1 in 1978, Lozi’s chaotic map has been thoroughly explored and continues to be. Hundreds of publications analyze its particular structure or apply its properties in many fields (electronic devices like memristor, A.I. with swarm intelligence, etc.). Several generalizations have been proposed, transforming the initial two-dimensional map into multidimensional one. However, they do not respect the original constraint that allows this map to be one of the few strictly hyperbolic: a constant Jacobian. In this paper we introduce a three-dimensional piece-wise linear extension respecting this constraint and we explore a special property never highlighted for chaotic mappings: the coexistence of thread-chaotic attractors (i.e., attractors which are formed by collection of lines) and sheet-chaotic attractors (i.e., attractors which are formed by collection of planes). This new 3-dimensional mapping can generate a large variety of chaotic and hyperchaotic attractors. We give five examples of such behavior in this article. In the first three examples, there is coexistence of thread and sheet-chaotic attractors. However, their shape are different and they are constituted by a different number of pieces. In the two last examples, the blow up of the attractors with respect to parameter a and b is highlighted.

Memristors were proposed in the early ’70s of the XXth century by Leon Chua as a new electrical element linking the charge and the flux. Since that first introduction, these devices have positioned themselves to be considered as possibly fundamental for the new generations of electronic devices. It has to be mentioned that actual memristors have only been recognized to exist as physical elements. In this paper, we apply a modeling framework to generate a model describing experimental measurements performed on a ReRAM. We show how to apply the Dynamic Route Map technique in the general case to obtain an approximation to the differential equation that determines the behaviour of the device.

The world tsunami hazard map is developed to understand the pattern of occurrence of tsunami across the globe and for using this database for preparing effective evacuation plan and rescue operations. It has been developed by using Web GIS tools. HTML, CSS, Java Script, JQuery, IIS and Maps API are utilized to develop hazard map. These data can be even used by government authorities as well as by other nodal agencies.

The paper presents an analysis of the latest developments in the field of stereo vision in the low-cost segment, both for prototypes and for industrial designs. We described the theory of stereo vision and presented information about cameras and data transfer protocols and their compatibility with various devices. The theory in the field of image processing for stereo vision processes is considered and the calibration process is described in detail. Ultimately, we presented the developed stereo vision system and provided the main points that need to be considered when developing such systems. The final, we presented software for adjusting stereo vision parameters in real-time in the python language in the Windows operating system.

In today's world it is very much important to maintain the security of information and its risks. The biometric-based techniques are very much useful in these problems. Among the several kinds of biometric-based technique, face detection is much complex and much more important. Due to the age and several other problems, a human face structure changes over time, again a human has lots of expressions. Sometimes due to the lighting condition or the variation of the angle of an input device, the pattern of a human face structure also changed. As a result, the face cannot be detected properly. In this paper, a method is proposed that can detect the human faces both automatically and manually very efficiently. In manual mode, a user can select the input faces referred by the system according to their choice. In automated mode, the system detected all possible face areas using the Kohonen Self-Organizing Feature Map technique. This method reduced the complex color image into a vector quantized image with desired colors. Then a color segmentation technique is used to detect the possible face skin areas from the vector quantized image. Then the Histogram Oriented Gradient technique used to detect the feature from the faces and K-Nearest Neighbour Classifier is used to compare both face images detected by the two modes. The automated method prosed better accuracy than the manual method.

Background: Human papillomavirus (HPV) infection plays a key role in the development of cervical cancer that ranks as the third most common gynecological cancer in China. We attempt to investigate the age and genotype-specific prevalence of HPV DNA in western Chinese females. Methods: A total of 301,880 woman were recruited from 4 different regions of western China. Routine cervical samples were collected and HPV screening was performed using 21 HPV Genotyping test (Hybribio). The overall prevalence, age-specific prevalence, and genotype distribution were analyzed. Results: The overall prevalence of HPV was 18.01%. The high-risk HPV infection rate was 79.14%, the low-risk HPV infection rate was 12.56%, and the mixed HPV infection rate was 8.30%. The most common 4 HR HPV subtypes were HPV-52, 16, 58 and 53, which accounted for 20.49 %, 19.93 %, 14.54 % and 10.01 %. In LR HPV genotype, HPV-6 ranked the highest (28.17 %), followed by HPV-81 (9.09 %), HPV-11 (3.78 %). HPV genotype subgroup analysis also showed that single-type infections had the highest prevalence rate (77.26%) among HPV positive individuals. Among muti-infection genotype, double infection was most common with frequencies of 76.04%. Conclusion: This large report shows that the overall prevalence of HPV was high in China, whose distribution exhibits different patterns across different particular age and regions. Viral genotypes HPV53, 6 were are frequently detected in this population, which is worth of significant clinical attention.

Magnesium is one of the lightest structural metal used in different industrial sector and many works are present in literature about the study of its reinforcement by fillers addition. Basalt fibres are natural fillers with good mechanical properties, excellent resistance to high temperature and lower cost than carbon fibres. For these aspects, in the last years they are increasingly used in the production of composite materials with polymeric matrices. However, very few information are presents in literature about the use of basalt fibres as reinforcement in metal matrix composite materials. It is well known that the impregnation of fibres reinforcement affects the mechanical behavior of composites materials. The aim of this study is to investigate the impregnation and the behavior of basalt fibres in a magnesium alloy composite material manufactured by a centrifugal casting technique.

The discovery of a growing number of exoplanets and even extrasolar systems supports the scientific consensus that it is possible to find other signs of life in the universe. The present work proposes for the first time, an explicit mechanism inspired by the dynamics of biological dispersion, widely used in ecology and epidemiology, to study the dispersion of biogenic units, interpreted as complex organic molecules, between rocky or water exoplanets (habitats) located inside star clusters. The results of the dynamic simulation suggest that for clusters with populations lower than 4 M+/ly³ it is not possible to obtain biogenic worlds after 5 Gyr. Above this population size, biogenic dispersion seems to follow a power law, the larger the density of worlds lesser will be the impact rate (β ) value to obtain at least one viable biogenic Carrier habitat after 5 Gyr. Finally, when we investigate scenarios by varying β, a well-defined set of density intervals can be defined in accordance to its characteristic β value, suggesting that biogenic dispersion has a behavior of “minimal infective dose” of “minimal biogenic effective” events by interval i.e. once this dose has been achieved, doesn’t matter if additional biogenic impact events occur on the habitat.

The influence of distant London dispersion forces on the docking preference of alcohols of different size between the two lone electron pairs of the carbonyl group in pinacolone is explored by infrared spectroscopy of the OH stretching fundamental in supersonic jet expansions of 1:1 solvate complexes. Experimentally, no pronounced tendency of the alcohol to switch from the methyl to the bulkier tert-butyl side with increasing size is found. In all cases, methyl docking dominates by at least a factor of two, whereas DFT-optimized structures suggest a very close balance for the larger alcohols, once corrected by CCSD(T) relative electronic energies. Together with inconsistencies when switching from a C4 to a C5 alcohol, this points at deficiencies of the investigated B3LYP and in particular TPSS functionals even after dispersion correction, which cannot be blamed on zero point energy effects. The search for density functionals which describe the harmonic frequency shift, the structural change and the energy difference between the docking isomers of larger alcohols to unsymmetric ketones in a satisfactory way is open.

The laser differential equations are used to transform them into identical coupled maps. Valuable results are deduced during analytical and numerical studies on cavity loss. Phase and spatiotemporal synchronized attractors are observed via quasi-chaos under a certain range of controlling parameters, and symmetry breaking of chaotic attractors due to collision with their basin boundaries, and transpire differently from the previous attractors. During the numerical simulation, it is found that the sequence of repeated strange attractors if the coupling strength further increases, which are orthogonal mirror images (the dynamics of the system is the same at different values of controlling parameters). Moreover, it can help us to predict future problems and their solutions based on current issues, if we develop this model in more general.

A number of studies have been conducted to improve the accessibility of images using touchscreen devices for screen reader users. In this study, we conducted a systematic review of 33 papers to get a holistic understanding of existing approaches and to suggest a research road map given identified gaps. As a result, we identified types of images, visual information, input device and feedback modalities that were studied for improving image accessibility using touchscreen devices. Findings also revealed that little has studied how to automate the generation of image-related information, and that screen reader users play important roles during the evaluation but the design process. Then we introduce two of our recent studies on the accessibility of artwork and comics, AccessArt and AccessComics respectively. Based on the identified key challenges, we suggest a research agenda for improving image accessibility for screen reader users.

This study explores the near-surface dispersion mechanisms of contaminants in coastal waters, leveraging a comprehensive method that includes using dye and drifters as tracers, coupled with diverse observational platforms like drones, satellites, in-situ sampling, and HF radar. The aim is to deepen our understanding of surface currents' impact on contaminant dispersion, thereby improving predictive models for environmental incident management, including pollutant releases. Rhodamine WT dye, chosen for its significant fluorescent properties and detectability, along with drifter data, allowed us to investigate the dynamics of near-surface physical phenomena such as the Ekman current, Stokes drift, and wind-driven currents. Our research emphasizes the importance of integrating scalar tracers and Lagrangian markers in experimental designs, revealing differential dispersion behaviors due to near-surface vertical shear caused by the Ekman current and Stokes drift. The elongation direction of the dye patch aligns with the Ekman current direction during slow current conditions. Analytical calculations of vertical shear, based on the Ekman current and Stokes drift, closely matched those derived from tracer observations. Over a 7-hour experiment, the vertical diffusivity of near-surface water was observed at 2×10-4 m2/s, and the horizontal eddy diffusivity of the dye patch and drifters reached the order of 1 m2/s and at a 1000m length scale. Particle tracking models demonstrate that while HF radar currents can effectively predict the trajectories of tracers near the surface, incorporating near-surface currents, including Ekman current, Stokes drift, and windage, is essential for a more accurate prediction of the fate of surface floats.

Significant amounts of anthropogenic radionuclides were introduced in ocean waters following nuclear atmospheric tests and development of the nuclear industry. Dispersion of artificial dissolved radionuclides has been extensively measured for decades over the European continental shelf. The radionuclide measurement and release fluxes databases provided here represent an exceptional opportunity to validate dispersion hydrodynamic models. MARS hydrodynamic model have been applied at different scales to reproduce in realistic conditions the measured dispersion. Specific methods have been developed to obtain qualitative and quantitative results and perform model/measurement comparisons. Model validation concerns short to large scales with dedicated surveys following the dispersion: it was performed within two and three dimensions framework and from minutes and hours following a release up to several years. Results are presented concerning the dispersion of radionuclides in marine systems deduced from standalone measurements, or according to model comparisons. It allows characterising dispersion over the continental shelf, pathways, transit times, budgets and source terms. This review exhibits the main features retained from the point of view of radiotracers, hydrodynamic models and model/measurement methods with perspectives of applications in other areas or oceanographic domains.

A finite-type immersion or smooth map is a nice tool to classify submanifolds of Euclidean space, which comes from eigenvalue problem of immersion. The notion of generalized 1-type is a natural generalization of those of 1-type in the usual sense and pointwise 1-type. We classify ruled surfaces with generalized 1-type Gauss map as part of a plane, a circular cylinder, a cylinder over a base curve of an infinite type, a helicoid, a right cone and a conical surface of $G$-type.

Coal-fired thermal plants (CTPP) are known to pollute the atmosphere with emission of many greenhouse gases and particulate matter. The power generation from these thermal plants cannot be stopped completely because it forms the backbone of the grid power supply. It is necessary to study the dispersion patterns of pollutants that affect the health of the people. The dispersion patterns are location specific since they depend on local meteorological conditions. In this study, the dispersion of particulate matter (PM) and sulphur dioxide (SO₂) from a CTPP with 275 m high stack are studied under different atmospheric boundary layer (ABL) of neutral, stable and unstable conditions up to a distance of 30 km from the stack. The plume of the PM spreads under all conditions. During some parts of the day, PM settles around the stack while at other times PM keeps suspending in the air for the full distance under study. Sulphur dioxide dilutes to concentrations below the detection limits in about 12-13 km from the stack for neutral and unstable ABL whereas for the stable ABL, the dispersion is up to 30 km. The 24 h weighted average concentration of sulphur dioxide, at 10 m height from the ground, is 14.2 mg/m³ at a distance of 25 kms from the CTPP, which is comparable with the value of 9.2 mg/m³ measured at the Air Quality Stations located around the same distance. Based on the results policy changes that need to be implemented are suggested.

Longitudinal dispersion coefficient (LDC) plays an essential role in modeling the transport of pollution and sediment in the natural rivers. As a result of transportation processes, the concentration of pollution changes along the river. Different studies have been conducted to provide simple equations for estimating LDC. In this study, Support Vector Regression (SVR), Gaussian Process Regression (GPR), M5P and Random Forest (RF) examined to predict the LDC in the natural streams. The hydraulic and geometric features of different rivers gathered for developing the mentioned models for LDC estimation and various statistical criteria were utilized to scrutinize of the models. Furthermore, the Taylor chart was used to evaluate the models and achieved results showed that among machine learning models, M5P displayed the superior performance with CC of 0.823, SI of 0.812, NS of 0.577 and WI of 0.879. As well, S-D model with CC of 0.795 SI of 0.827, NS of 0.558 and WI of 0.890 had more precise results than other empirical models. The results indicates that the developed M5P model with simple formulations was superior to other machine learning models and empirical models and therefore, it can be used as a proper tool for estimating LDC in natural rivers.

Despite increased protection globally, climate change and other anthropogenic factors have caused a significant decline in seagrass cover. Identifying the specific causes of this decline is paramount if they are to be addressed. Therefore, we identified the causes of long-term change in seagrass/submerged aquatic vegetation (SAV) percentage cover and extent in the Bluefields Bay Special Fish Conservation Area (BBSFCA), a marine protected area on Jamaica’s southern coast. We used two random forest regression (RFr) models that included 2013 hydroacoustic survey SAV percentage cover data (dependent variable), and auxiliary data, reflectance data from level 2 processed 2013 Landsat 7 and 8 images and image band texture statistics maps (mean and variance) as predictors to generate 24 SAV percentage cover maps for the period 1984 – 2021 (37 years) using data from Landsat 4-5, 7 and 8 images., from which benthic features maps (SAV present, absent and coral reef) were created. Rainfall and map data were used to determine if SAV extent/area (km2) and average percentage cover and annual rainfall changed significantly over time and to evaluate the influence of rainfall. Rainfall impact on the overall spatial patterns of SAV loss, gain, and percentage cover change was assessed using a pixel-based regression. Finally, the most important spatial pattern predictors (two rainfall proxies (distance and direction from river mouth), benthic topography, depth, and hurricane exposure (a measure of hurricane disturbance)) of SAV loss, gain, and percentage cover change during 23 successive 1-to-4-year periods were identified using spatial Bayesian INLA generalized linear mixed models. SAV area/extent was largely stable with &gt; 70% mean percentage cover for multiple years. However, Hurricane Ivan (in 2004) caused a significant decline in SAV area/extent (by 1.62 km2, or a 13%) during 2002 – 2006 and a second hurricane (Dean) in 2007 delayed recovery until 2015. Additionally, rainfall declined significantly by &gt;1000 mm since 1901, and mean monthly rainfall positively influenced SAV percentage cover change. The pixel-based regression highlighted areas where mean monthly rainfall had a positive overall effect on SAV cover percentage change (across the entire bay) and gain (closer to the mouth of a river). The most frequently selected important spatial pattern predictors were the two rainfall proxies (areas closer to the river mouth were more likely to experience SAV loss and gain) and depth, with shallow areas generally having a higher probability of SAV loss and gain. Three hurricanes had significant but different impacts depending on their distance from the southern coastline. Hurricane Gilbert, which made landfall in 1988, resulted in higher SAV percentage cover loss in 1987 - 1988. Benthic locations with a northwestern/northern facing aspect (the predominant direction of Ivan’s leading edge wind bands) experienced higher SAV losses during 2002 – 2006. Although some locations impacted by Ivan and not by Dean recovered during 2006 – 2008, exposure to Ivan explained percentage cover loss during 2006 – 2008 and average exposure to (the cumulative impact of) Ivan and Dean (both with tracks close to the southern coastline) explained SAV loss during 2013 – 2015. Therefore, despite historic lows in annual rainfall, overall, higher rainfall was beneficial, multiple hurricanes impacted the site, and despite two hurricanes in three years SAV recovered within a decade. Hurricanes and a further reduction in rainfall may pose a serious threat to SAV persistence in the future.

Keywords: liquid alloys, microstratification, dispersed particles, spontaneous dispersion, criteria for true (entropic) spontaneous dispersion, mechanisms of quasi-spontaneous dispersion, methods and results for assessing size of dispersed particles.

This manuscript investigates the dispersion of cetyltrimethylammonium bromide (CTAB) treated cellulose nanocrystals (CNCs) in polypropylene (PP) by melt mixing. FTIR spectra of CTAB-modified CNCs and unmodified CNCs in a PP matrix were used to evaluate the surface treatments. The surface energies and morphologies of CTAB surface modified CNCs in polypropylene (PP) were used to interpret the effects of nanoparticle dispersion on the crystallization and rheological and mechanical properties of the PP matrix.

Alumina dispersion-strengthened copper, Glidcop, is used widely in high-heat-load ultra-high-vacuum components for synchrotron light sources (absorbers), accelerator components (beam intercepting devices) and in nuclear power plants. Glidcop has similar thermal and electrical properties to OFE (oxygen free electrical) copper, but has superior mechanical properties, thus making it a feasible structural material; its yield and ultimate strength are equivalent to those of mild-carbon steel. The purpose of this work has been to develop a brazing technique to join Glidcop to Mo, using a commercial Cu-based alloy. The effects of the excessive diffusion of the braze along the grain boundaries on the interfacial chemistry and joint microstructure, as well as on the mechanical performance of the brazed joints, has been investigated. In order to prevent the diffusion of the braze into the Glidcop alloy, a copper barrier layer has been deposited on Glidcop by means of RF-sputtering.

The objective was to conduct a scoping review and produce a publicly available database characterizing the design and reporting elements of the literature on dietary added sugars and select health outcomes. Relevant studies published from 1990 – 2021 were identified to create a database containing information on study and population characteristics, reported added sugars source and concentrations, diet energy balance, total energy intake, and outcome measures related to body composition, obesity, cardiovascular disease, and diabetes mellitus. There were 245 publications identified, 22% of which describe interventions and 78% describe observational studies. Publications pertaining to added sugars have risen dramatically since 2010, led by studies primarily assessing body composition (36%) or cardiovascular health (32%), including adults (65%), measuring liquid-only sources of added sugars (56%). Over 65% of studies reported total energy intake, 61% controlled for total energy intake in the design and analysis, and fewer than 5% of studies reported the energy balance of subjects. There has been a significant increase in research on added sugars since 2010, with substantial heterogeneity across all facets of methodology – study designs, exposures and outcomes of interest, terminology, and reporting of dietary intake data – thus limiting the ability to synthesize evidence in this scope of literature. This evidence map highlights gaps and important areas for improvement to strengthen the state of research to better inform future policies and dietary recommendations on added sugars.

In present paper, spatial Minkowski Pythagorean Hodograph (MPH) curves are characterized with Rational Rotation Minimizing Frames (RRMFs). We define Euler-Rodrigues Frame (ERF) for MPH curves and by means of this concept, we reach the definition of MPH curves of type (n, m). Expressing the conditions provided by these curves in the form of Minkowski-Hopf map that we define, it is aimed to establish a connection with the Lorentz force which occurs during the process of Computer Numerical Control (CNC) type sinker Electronic Discharge Machines (EDMs). This approach is reinforced by split quaternion polynomials. Finally, we give conditons satisfied by MPH curves of low degree to be type (n, m) and construct illustrative examples.

The flow behavior of Fe-6.5wt.%Si alloys during hot compression was investigated at temperatures 650–950 °C and strain rates 0.01–10 s^-1. The results showed that the flow stress depended distinctly on the deformation temperatures and strain rates. The flow stress and work hardening rate increased with the decrease of temperature and the increase of strain rate. The activation energy under all the deformation conditions was calculated to be 410 kJ/mol. The constitutive equation with hyperbolic sine function and Zener–Hollomon parameter was developed. The peak stress, critical stress, and steady-state stress could be represented as σ=A+Bln(Z/A). Dynamic recrystallization occurred under the deformation conditions where the values of Z were lower than 10²⁰. Processing maps were established to optimize the processing parameters. The power dissipation efficiency decreased in the high temperature and low strain rate region, increased in the high temperature and high strain rate region, and remained unchanged in other regions with the increase of true strain. Furthermore, the unstable area expanded. The true strain of 0.7 was the optimum reduction according to the processing map. Based on the analysis of surface quality, microstructures, and ordered structures, the optimized processing parameters for the Fe-6.5wt.%Si alloys were the temperature and strain rate of higher than 900 °C and 0.01–10 s^-1, respectively, or 800–900 °C and lower than 0.4 s^-1, respectively.

The application of machine learning techniques to satellite imagery has been the subject of interest in recent years. The increase in quality and quantity of images, made available by Earth observation programs, such as the Copernicus program, led to the generation of large amounts of data. Among the various applications of this data is the creation of land cover maps. The present work aimed to create machine learning models capable of accurately segment and classify satellite images, to automatically generate a land cover map of the Portuguese territory. Several experiments were carried out with the spectral bands of the Sentinel-2 satellite, with vegetation indices, and with several sets of land cover classes. Three machine learning architectures were evaluated, which adopt two different techniques for image classification. One of the classification techniques follows an object-oriented approach, and in this case the architecture adopted in our models was a U-Net artificial neural network. The other classification technique is pixel-oriented, and the machine learning models tested were random forest and support vector machine. The overall accuracy of the results obtained ranged from 68.6% to 94.75%, depending strongly on the number of classes into which the land cover is classified. The result of 94.75% was obtained when classifying the land cover only into 5 classes. However, a very interesting accuracy of 92.37% was achieved by the model when trained to classify 8 classes. These results are superior to those reported in the related bibliography.

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To this end, we exploit a neural network metric in the output of a biologically inspired Self-Organizing Map, the Quantization Error (SOM-QE). Shape pairs with perfect geometric mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, longer choice RT for ‘yes’ responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data.

This study employs the FLACS code to analyze hydrogen leakage, vapor dispersion, and subsequent explosions. Utilizing pseudo-source models, a liquid pool model, and a hybrid model combining both, we investigate dispersion processes for varying leak mass flow rates (0.225 kg/s and 0.73 kg/s) in a large open space. We also evaluate explosion hazards based on overpressure and impulse effects on humans. The computational results, compared with experimental data, demonstrated reasonable hydrogen vapor cloud concentration predictions, especially aligned with the wind direction. For higher mass flow rate of 0.73 kg/s, the pseudo-source model and hybrid model proved appropriate, while the liquid pool model was more suitable for lower mass flow rate of 0.225 kg/s. Regarding explosion analyses using overpressure-impulse diagram, higher mass flow rates leaded to potentially fatal overpressure and impulse effects on humans. However, lower mass flow rates may cause severe eardrum damage at the maximum overpressure point.

Road vehicles are a large contributor to Nitrogen Oxides (NOx) pollution. The routine road-side monitoring stations, however, may underrepresent the severity of personal exposure in urban areas, because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at local level. This study deploys a 10 cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic, by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at constant speed may generate momentary road-side concentrations of NOx as high as 1.25 mg/m3, with 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

Solving environmental odor issues can be confounded by many analytical, technological, and socioeconomic factors. Considerable know-how and technologies can fail to properly identify odorants responsible for the downwind nuisance odor and mitigate it for the affected citizenry. We propose enabling solutions to environmental odor issues by utilizing troubleshooting techniques developed for the food, beverage, and consumer products industries. We showed that the downwind odorant impact-priority ranking process can be definable and relatively simple. The initial challenge is the prioritization of environmental odor character from the perspective of the impacted citizenry downwind. In this research, we aim at summarizing three natural models of the rolling unmasking effect (RUE) and discuss them more systematically in the context of the proposed downwind environmental odor prioritization approach. Regardless of the size and reach of an odor source, a simplification of odor character and composition typically develops with downwind dilution. The extreme odor simplification-upon-dilution was demonstrated for two plant varieties, prairie verbena and Virginia pepperweed. Their downwind odor frontal boundaries were dominated by single, character-defining odorants; p-cresol-dominated ‘barnyard’ odor, and benzyl mercaptan-dominated ‘burnt match’ odor, respectively. The P.T. porcupine downwind odor frontal boundary was dominated by two potent, character-defining odorants: (1) ‘onion’/‘body odor’ odorant #1 and (2) ‘onion’/‘grilled’ odorant #2. In contrast with their downwind boundary simplicities, each odor source presented considerable compositional complexity and composite character difference near the source. The proposed RUE approach’s ultimate significance is the illustration of naturally occurring phenomena that explain why some environmental odors and their sources can be challenging to identify and mitigate using the analytical only approach (focused on compound identities and concentrations). These approaches rarely move beyond comprehensive lists of compounds being emitted by the source.

Ornamental kale (Brassica oleracea var. acephala) is an attractive ornamental plant with a range of leaf colors and shapes. Breeding new varieties of ornamental kale has proven challenging due to its lengthy breeding cycle and the limited availability of genetic markers. Microspore culture is an effective approach to generate new materials and genetic maps are a prerequisite for quantitative trait loci analysis, MAS, fine gene mapping, and genome sequence assembly. In this study, a F1DH ornamental kale population comprising 300 DH lines was constructed using microspore culture. A high-density genetic map was developed by conducting whole-genome sequencing on 150 individuals from the F1DH population. The genetic map contained 1,696 bin-markers with 982,642 single-nucleotide polymorphisms (SNPs) spanning a total distance of 775.81 cM on all nine chromosomes with an average distance between markers of 0.46 cM. The ornamental kale genetic map contained substantially more SNP markers compared with published genetic maps for other B. oleracea crops. The F1DH progenies provide an excellent resource for germplasm innovation and breeding new varieties of ornamental kale. The high-density genetic map provides crucial insights for gene mapping and unraveling the molecular mechanisms behind important agronomic traits in ornamental kale.

Due to its time effective, joint friendly and highly customizable character whole-body-electromyostimulation (WB-EMS) is regarded as a feasible solution for a large variety of training issues particularly in the area of non-athletic application. To identify gaps in research and summarize prevalent evidence we conducted an evidence map on outcomes addressed by WB-EMS trials in middle-aged to older, non-athletic adults. Based on a comprehensive systematic search in five databases and two study registers according to PRISMA, 54 projects published in 80 articles were included. More than 90% of the studies reported outcomes related to the physical fitness or function domain. Body composition parameters were addressed by two thirds of the projects. Health-related outcomes addressed by WB-EMS included cancer/neoplasm (n=7), endocrine regulation (n=8), glucose metabolism (15), nervous system diseases (n=2), cardiovascular system diseases (n=22), non-specific chronic low back pain (n=4), osteopenia (n=5) and diseases of the renal system (n=12). Outcomes related to inflammation were addressed 18 times. Of importance, no studies reported clinically relevant adverse effects related to the WB-EMS intervention. In summary, while considerable evidence on outcomes related to fitness/function and body composition is prevalent, evidence gaps of WB-EMS research were particular evident for diseases of the nervous and cerebrovascular system.

There is a need to develop enriched milk drinks with healthy and natural additives. A consumer test was conducted to compare milk (cow and camel) flavored with date syrup (Khlass and Sukkary varieties) at different percentage. The objective of the present work was to study consumers liking patterns for flavored milk drinks from dates syrup (from Khlass and Sukkary dates), at different percentages, added to milk (cow and camel) utilizing preference mapping analysis. A total of sixteen trained panelists took part in the test. The obtained data were used to develop an internal preference map for these samples. Principal component analysis (PCA) and Agglomerative hierarchical clustering (AHC) algorithms were used to construct the preference map. The first component signifies overall acceptance of taste and color, while the second focuses on texture and flavor. Consumers were grouped into five clusters based on preferences. Cluster two favored both components positively, while cluster four leaned negatively on both. A factorial ANOVA was performed and the results showed a significant effect of the main factors as well as the interactions. Panelists preferred cow's milk over Camel’s milk in all aspects. For taste, cow’s milk with 20% Khlass syrup or 10% Sukkary syrup was favored, while in flavor, it was cow’s milk with 5% Khlass syrup and Camel’s milk with 10% Sukkary syrup. Texture-wise, Camel’s milk with 5% Khlass syrup and 15% Sukkary syrup, along with cow’s milk with 10% Khlass syrup, received top marks. In color evaluation, cow’s milk with 15% Sukkary syrup was the preferred choice. Finally, for overall color score, cow’s milk with 10% Sukkary syrup led, followed by cow’s milk with 5% Sukkary syrup. This research suggests that dairy companies may have more impact if they use date syrup as a natural and healthy flavor. The preference map includes two main dimensions; the first represents overall acceptance, taste, and color while the second is related to flavor and texture attributes. The preference map can be used in product optimization and development.

The demand for efficient processes through a comprehensive understanding and optimization of welding conditions continues to grow in the manufacturing industry. This study involves heat-resistant 2.25 Cr-1 Mo V-groove steel welding using the square-waveform alternating cur-rent. Experiments were conducted to build the relationship between input variables—such as current, frequency, electrode negativity ratio, and welding speed—and process performance, such as penetration, bay area, deposition rate, melting efficiency, percentage dilution, flux–wire ratio, and heat input. The process was analyzed in light of the defect-free high-deposition weld groove weld, the sensitivity to process parameters, and the optimization and development of the process map. The study proposes an innovative approach to reducing the cost and time of optimizing the one-pass-each-layer V-groove welding process using bead-on-plate welds. Square waveform welding creates a metallurgical notch in the form of a bay at the fusion boundary that can be minimized by selecting appropriate welding conditions. The square waveform submerged arc welding is more sensitive towards changes in current and welding speed than the frequency and electrode negativity ratio; however, the electrode negativity ratio and frequency are minor but helpful parameters to achieve optimal results. The proximity of the planned and experimental results to within 3% confirms the validity of the proposed approach. The investigation shows that 90% of the maximum deposition rate is possible for one-pass-each-layer V-groove welds within heat input and weld width constraints.

We present an exact expression for the upscaled dynamic dispersion coefficient (D) for one-dimensional transport by Hagen-Poiseuille flow which is the basis for modeling transport in porous media idealized as capillary tubes. The theoretical model is validated by comparing the breakthrough curves (BTCs) from a 1D advection-dispersion model with dynamic D to that from direct numerical solutions utilizing a 2D advection-diffusion model. Both Taylor dispersion theory and our new theory are good predictors of D at lower Peclet Number (Pe) regime, but gradually fail to capture most parts of BTCs as Pe increases. However, our model generally predicts the mixing and spreading of solutes better than Taylor’s theory since it covers all transport regimes from molecular diffusion, through anomalous transport, and to Taylor dispersion. The model accurately predicts D based on the early part of BTCs even at relatively high Pe regime (~62) where the Taylor’s theory fails. Furthermore, the model allows for calculation of the time scale that separates Fickian from non-Fickian transport. Therefore, our model can readily be used to calculate dispersion through short tubes of arbitrary radii such as the pore throats in a pore network model.

In this article, we investigate two types of double dispersion equations in two dierent dimensions. Double dispersion equation were derived to describe long nonlinear wave evolution in a thin hyperelastic rod. Conservation laws are obtained for these equations by the application of the multiplier method. Finally, travelling waves and line travelling waves are respectively considered for these two equations.

Daniel Yergin’s “The New Map: Energy, Climate, and the Clash of Nations” is a remarkable and groundbreaking work that addresses the ever-changing global energy landscape and its profound geopolitical implications. In this modest book review, we aim to offer a fresh perspective by re-examining the core issues from the standpoint of political geography. The aim of this article is twofold: to enrich the existing literature on political geography and to provide valuable insights to students of geography to broaden their knowledge in this field.

This paper offers a novel geometric and visual approach to the renowned Four Color Map Theorem and K5 non-planarity problem while unveiling their profound connection to the "kissing number" problem in 2D. We represent planar graphs through circles and tangents, simplifying complex structures and shedding light on these classic problems. Our proofs by contradiction, rooted in the kissing number concept, reveal that both the Four Color Map Theorem and K5 non-planarity are fundamentally linked, as they pivot around the concept of coloring. This study bridges the realms of geometry and graph theory, providing fresh insights and emphasizing the significance of the kissing number problem in various fields.

Hashimoto’s thyroiditis (HT) is a common autoimmune disease, with its prevalence rapidly increasing. Both genetic and environmental risk factors contribute to the development of HT. Recently, viral infection has been suggested to act as a trigger of HT by eliciting the host immune response and subsequent autoreactivity. We analyzed features of HT through bioinformatics analysis so as to identify markers of HT development. We accessed public microarray data of HT patients from the Gene Expression Omnibus (GEO) and obtained differentially expressed genes (DEGs) under HT. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed for functional clustering of our protein-protein interaction (PPI) network. Utilizing ranked gene lists, we performed Gene Set Enrichment Analysis (GSEA) using the clusterprofiler R package. By comparing the expression signatures of the huge perturbation database with the queried rank-ordered gene list, connectivity map (CMap) analysis was performed to screen potential therapeutic targets and agents. The gene expression profile of the HT group was in line with general characteristics of HT. Biological processes related to the immune response and viral infection pathways were obtained for the upregulated DEGs. GSEA results revealed activation of autoimmune disease-related pathways and several viral infection pathways. Autoimmune disease and viral infection pathways were highly interconnected by common genes, while the HLA genes which are shared by both were significantly upregulated. CMap analysis suggested that perturbagens, including SRRM1, NLK, and CCDC92, have the potential to reverse the HT expression profile. Several lines of evidence suggested that viral infection and the host immune response are activated during HT. Viral infection is suspected to act as a key trigger of HT by causing autoimmunity. SRRM1, an alternative splicing factor, which responds to viral activity, might serve as potential marker of HT.

Empirical equations representing, interpolating and smoothing groups of measurement results by regression methods are in widespread use in metrology and other fields of science and engineering. Standard equations for the propagation of measurement uncertainties to values computed from such equations are available but suffer from a lack of general acceptance and are only infrequently applied in practice. One reason for the slow uptake is the lack of clear methods to account for systematic error. In this paper, uncertainty propagation equations in terms of covariance matrices are generalized to allow for systematic errors in least-squares regression, and effects of the resulting uncertainties are investigated analytically. A stochastic ensemble model of systematic error is proposed for the computation of the non-diagonal elements of the weight matrix of the Generalized Least-Squares method (GLS) from the measurement uncertainty. A GLS projector formalism is described which separates the effects of measurement scatter on values calculated by the equation from those on the related “residuals”, i.e., the residual errors in the fitted data. The same projectors act similarly on the associated uncertainties and covariance matrices and permit the effects of systematic errors on the simulation covariance to be quantified. It is demonstrated that, in order to include systematic errors in the uncertainty estimates of GLS, covariance matrices may be substituted by novel, specifically defined dispersion matrices that are not specified yet by the GUM[1]. Systematic measurement errors may be estimated from various sources; a particularly easy way suggested here involves analyzing the structure in the regression residuals. It is demonstrated that GLS projectors exhibit inherent features of “error blindness” also with respect to systematic errors. [1] GUM: Guide to the Expression of Uncertainty in Measurement, http://www.bipm.org/en/publications/guides

We evaluated the change in water dispersibility of lactic acid bacteria (LAB, Enterococcus faecalis KH2) upon powderization and its influence on their efficacy. When cultured LAB are washed, heat-killed, and powdered, adhesion between LAB occurs and they form aggregation (non-treated LAB, n-LAB). However, a dispersed LAB (d-LAB) powder with less aggregates can be prepared by treating them with a high-pressure homogenizer and adding an excipient during powdering. n-LAB or d-LAB was administered to mice and the Peyer's patches in the small intestine were observed. n-LAB administration showed a high amount of aggregated LAB drifting in the intestinal mucosa, whereas d-LAB reached the Peyer's patches and was taken up into the Peyer's patches. Evaluation in a mouse influenza virus infection model showed that d-LAB was more effective than n-LAB in influenza yield of bronchoalveolar lavage fluids (BALFs) on day 3 post-infection, neutralizing antibody titers of sera and influenza virus-specific IgA in the feces on day 14 post-infection. Thus, the physical properties of LAB affect their efficacy; controlling their water dispersibility can improve their effectiveness.

A critical discussion on the computation of the dispersion diagram in periodic one-dimensional guiding structures is carried out. In particular, an analysis is presented of the pros and cons of combined methods that make use of full-wave simulations done with commercial software packages with further analytical post-processing based on simplifications brought by an equivalent circuit model of the structure. Some of the most common methods reported in the literature are reviewed and their advantanges and limitations highlighted. Our discussion is complemented with several selected numerical examples in order to discuss the most relevant aspects that a potential user of these methods should be aware of. Special attention is paid to the relevant role played by the high-order coupling between the two halves of a symmetric unit cell of the periodic structure.

Melt mixing is a convenient method to prepare polymer nanocomposites, but the extent of the dispersion of the solid filler reached is often limited, and may compromise the anticipated performance of these materials during service. Since the efficiency of extensional flows on dispersion is now well recognized, several mixers were designed with the aim of inducing both shear and extensional flow components. This work combines experimental and numerical data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with equal outer diameter and alternating larger and smaller inner diameters, thus creating a series of converging/diverging flows. Numerical simulation of the flow using the opensource OpenFOAM software assuming both inelastic and viscoelastic responses predicted the velocity, streamlines, flow type and shear and normal stress fields for the mixer. Experimental and computed data were combined to determine the trade-off between the local degree of dispersion of the PP/GnP nanocomposite, measured as Area ratio, and the absolute average value of the hydrodynamic stresses multiplied by the local cumulative residence time. From considerations based on a theoretical approach to dispersion, the cohesive strength of the GnP agglomerates studied was estimated to be in the range 3 - 10kPa.

It is currently difficult to obtain accurate fine dust information in residential areas due to the insufficient number of air quality monitoring systems and spatial imbalances. Therefore, a detailed particulate matter dispersion model including factors such as land use and meteorological information was developed in this study and used to create fine dust concentration distribution maps. The fine dust concentration distribution maps currently available to citizens were compared with those obtained by dispersion modeling, and population distribution data were employed to compare the populations exposed to fine dust according to the two methods. The results of the existing method and the developed particulate matter dispersion model differed significantly. For instance, the PM2.5 concentrations in Daejeon, South Korea, on February 17, 2018, were 56% “Good” and 44% “Moderate,” according to the existing method, while they were 31% “Good,” 26% “Moderate,” 28% “Unhealthy,” and 15% “Very Unhealthy,” according to the dispersion model. Furthermore, the existing method indicated that no portion of the population was exposed to poor fine dust concentrations, while the proposed model revealed that over 170 thousand people were exposed to such concentrations. These results on fine dust distributions will contribute to sustainable urban and environmental planning.

The precise prediction of air contaminant dispersion is essential to the air quality monitoring and the emergency management of the contaminant gases leakage incidents in the chemical industry park. The conventional atmospheric dispersion models can seldom give precise prediction due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion model, two data assimilation methods (i.e. one is merely based on the typical particle filter while the other is a combination of particle filter and expectation-maximization algorithm) are proposed to assimilate the UAV observations into the atmospheric dispersion model. Two emission cases are taken into consideration, the difference between which is the different dimensions of state variables. To test the performances of the proposed methods, experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model prediction when the dimension of state variables is low. In contrast, when the dimension of state variables becomes higher, the method of particle filter combining expectation-maximization algorithm performs better in the parameter estimation accuracy and warm-up time. Therefore, the data assimilation methods are able to effectively support the air quality monitoring and emergency management in chemical industry parks.

Whole-body electromyostimulation (WB-EMS) can be considered as a time-efficient, joint-friendly and highly customizable training technology that attracts a wide range of users. The present evidence map aimed to provide an overview of different non-athletic cohorts addressed by WB-EMS research. Based on a comprehensive systematic search according to PRISMA, eighty-six eligible longitudinal trials were identified that correspond with our eligibility criteria. In summary, WB-EMS research sufficiently covers all adult age categories in males and females. Most cohorts addressed (58%) were predominately or exclusively overweight/obese and in about 60% of them, diseases or conditions were inclusion criteria for the trials. Cohorts specifically addressed by WB-EMS trials suffer from cancer/neoplasm (n=7), obesity (n=6), diabetes mellitus (n=5), the metabolic syndrome (n=2), nervous system diseases (n=2), chronic heart failure (n=4), stroke (n=1), peripheral arterial diseases (n=2), knee arthrosis (n=1), sarcopenia (n=3), chronic unspecific low back pain (n=4), and osteopenia (n=3). Chronic kidney disease was an eligibility criterion in five WB-EMS trials. Finally, three studies included only critically ill patients, two further studies considered frailty as an inclusion criterion. Of importance, no adverse effects of the WB-EMS intervention were reported. In summary, evidence gaps of WB-EMS research were particular evident for cohorts with diseases of the nervous and cerebrovascular system.

Despite several decades of research, the physics underlying translation – protein synthesis at the ribosome – remains poorly studied. For instance, the mechanism coordinating various events occurring in distant parts of the ribosome is unknown. Very recently, we have suggested that this allosteric mechanism could be based on the transport of electric charges (electron holes) along RNA molecules and localization of these charges in the functionally important areas; this assumption was justified using tRNA as an example. In this study, we turn to the ribosome and show computationally that holes can also efficiently migrate within the whole ribosomal small subunit (SSU). The potential sites of charge localization in SSU are revealed, and it is shown that most of them are located in the functionally important areas of the ribosome – intersubunit bridges, Fe4S4 cluster and the pivot linking the SSU head to the body. As a result, we suppose that hole localization within the SSU can affect intersubunit rotation (ratcheting) and SSU head swiveling, in agreement with the scenario of electronic coordination of ribosome operation. We anticipate that our findings will improve the understanding of the translation process and advance the molecular biology and medicine.

In mitosis, faithful chromosome segregation is orchestrated by the dynamic interactions between the spindle microtubules (MTs) emanating from the opposite poles and the kinetochores of chromosomes. However, the precise mechanism that coordinates the coupling of kinetochore components to dynamic MTs has been a long-standing question. Microtubule (MT) associated proteins (MAPs) regulate MT nucleation, dynamics, MT-mediated transport and MT cross-linking in cells. Especially during mitosis, MAPs play an essential role not only in determining the spindle length, position and orientation but also in facilitating robust kinetochore-microtubule (kMT) attachments by linking the kinetochores to spindle MTs efficiently. MT-stability imparted by the MAPs is critical to ensure accurate chromosome segregation. This review primarily focuses on the specific function of non-motor kinetochore MAPs, their recruitment to kinetochores and their MT-binding properties. We also attempt to synthesize and strengthen our understanding of how these MAPs work in coordination with the kinetochore-bound Ndc80 complex (the key component of the MT-binding interface in metaphase and anaphase) to establish stable kMT attachments and control accurate chromosome segregation during mitosis.

The Computational theoretical techniques using first principle which make use of the density functional theory as implemented by quantum expresso as well as inter – atomic force constant (IFC) techniques (Born-von Jarman) were used to investigate the phonon dispersion curves of Silver (Ag) and Gold (Au) The results obtained show that for Au, the extension to 1 – 6^th neighbour gave slightly close agreement with the experimental phonon dispersions when compared to the 1 – 5^th neighbor at W_T and L_L symmetry points. The percentage error for Au at W_T are 2.5% and 2.9% ; at point L_L we obtained 0.6% and 0.7% respectively. The Local density Approximation (LDA) results for Ag underestimates the lattice with about 1.6% while the Generalized Gradient Approximation (GGA) overestimates it by 1.9%.

Chaotic theory is commonly being researched for application in image encryption scheme (IES). In this paper, a novel two-dimensional cross hyperchaotic Sine-modulation-Logistic map (2D-CHSLM) based on the famous Sine and Logistic maps. The hyperchaotic behaviors of 2D-CHSLM is testified with the help of their bifurcation diagrams, trajectory plots, Lyapunov exponents, sample entropy, C0 complexity, permutation entropy and 0-1 test. A new bit-level IES with traditional encryption structure is proposed utilizing 2D-CHSLM. The 2D-CHSLM-IES performs a 2D-CHSLM-based bit-level confusion using zig-zag transform and a 2D-CHSLM-based cross coupled diffusion operations for generating a highly secure cipher-image. Then the simulations and security analyses are further carried out with the help of key space, key sensitivity, histogram, correlation, information entropy, differential attack, noise and data loss attacks, prove that the security of the proposed 2D-CHSLM-IES

Image encryption is increasingly becoming an important area of research in information security and network communications, as digital images are widely used in various applications and are vulnerable to various types of attacks. In this research work, a color image cryptosystem that is based on a 3-layer permutation-substitution network (PSN) is proposed. For every layer, an encryption key and an S-box are generated and utilized. Those are based on a four-dimensional (4D) dynamical Chen system of a fractional-order, the Mersenne Twister, OpenSLL, Rule 30 Cellular Automata and Intel’s MKL. The sequential application of Shannon’s ideas of diffusion and confusion for 3 times guarantees a total distortion of any input plain image, resulting in a totally encrypted one. Apart from the excellent and comparable performance to counterpart algorithms from the literature, showcasing resistance to visual, statistical, entropy, differential, known plaintext and brute-force attacks, the proposed image cryptosystem provides an exceptionally superior performance in 2 aspects: a vast key space of 2^1658 and an average encryption rate of 3.34 Mbps. Furthermore, the proposed image cryptosystem is shown to successfully pass all the tests of the NIST SP 800 suite.

The diagnosis of Cardio-Vascular diseases (CVD) is highly dependent on analysis of ECG signals. ECG analysis can be helpful in estimating the underlying cause and condition of heart in cardiac abnormality. The effectiveness of ECG signal analysis in detection of CVDs is widely accepted by professional healthcare service provider. Many algorithms have been proposed but almost all of them have some kind of limitations, and these limitations largely influence the effectiveness of ECG analysis. The performed research work is dedicated for design of unique self-organizing maps (SOMs) based neural network for classification of arrhythmia according to a particular ECG signal, the generation of SOMs is based on the certain unique signatures of ECG signals and have potential to classify different cardiac conditions. For extraction of unique features from ECG signals, we have proposed to use Fast Discrete Stockwell Transform (FDST). Since the proposed technique is a result of combining two different techniques hence called as hybrid technology. The purpose of using FDST is to identify unique signatures of ECG signals in a more improved manner than existing one, the term improved is used because it has several advantages over existing techniques such as wavelet and Fourier Transform based methods. Results obtained from the implementation of the technique are capable in visualizing the ECG sinus rhythm and arrhythmia conditions in form of unique SOM for each associated arrhythmia condition. This unique SOM based classification makes them ideal for being used as a diagnostic tool. This ability of arrhythmia classification using FDST and SOMs makes the technique unique and useful providing valuable information about patient condition. Using proposed technology a portable diagnosis tool for monitoring of patient at their site may be facilitated later, that will improve the quality of life of the patient by diagnosing cardiac condition.

Resveratrol, because of its low solubility in water and its high membrane permeability, is collocated in the second class of the biopharmaceutical classification system, with limited bioavailability due to its dissolution rate. Solid dispersion of resveratrol supported on magnesium dihydroxide (RESV@MDH) was evaluated to improve solubility and increase bioavailability of resveratrol. Fluorimetric microscopy and granulometric analysis display three types of microparticles with similar size: type 1 that emitted preferably fluorescence at 463 nm (λ_ecc 358 nm), type 2 that emitted preferably fluorescence at 605 nm (λ_ecc 550 nm) andtype 3 that are non-fluorescent. Micronized pure resveratrol display only microparticles type 1 whereas type 3 are associated to pure magnesium dihydroxide. Dissolution test in simulated gastric environment resveratrol derived from RESV@MDH in comparison to resveratrol alone displayed better solubility. According to the biopharmaceutical classification, an increase of 3 fold of resveratrol bioavailabilitywas observed after oral administration of 50 mg/Kg of resveratrol of RESV@MDH in rabbits. We hypothesize that type 2 microparticles represent magnesium dihydroxide microparticles with a resveratrol shell and that they are responsible for the improved resveratrol solubility and bioavailability of RESV@MDH.

Air pollution poses a significant risk to public health and ecosystems. The use of sophisticated models to simulate the transformation and dispersion of pollutants in the atmosphere is a recognized method to assess air pollution levels and its sources and inform policy decisions for effective mitigation strategies in urban and industrial environments. The reliability of models depends, in part, on the sensitivity to the variance of input parameters, which can introduce uncertainty into the model's predictions. This uncertainty is especially challenging when the input parameters exhibit inherent variability. In this study, we analyse the uncertainty of an integrated emission/dispersion model by evaluating the relationship between input parameters and model outcomes. We uncover new aspects of this relationship while clarifying some previously known dependencies. Wind speed was found to have the most significant effect on calculated concentrations, with small differences leading to substantial concentration variations. The time of day, which reflects prevailing vertical turbulence conditions, was also found to have a notable impact on concentrations, whereas ambient temperature can also significantly influence model’s results. Based on these findings, we offer specific recommendations for regulators and scientists involved in environmental impact assessment to improve the accuracy and reliability of air pollution modelling.

The properties of rubber are strongly influenced by the distribution of filler within the polymer matrix. Here we introduce a Monte Carlo-based morphology generator. The basic elements of our model are cubic cells, which, in the current version, can be either silica filler particles or rubber volume elements in adjustable proportion. The model allows the assignment of surface free energies to the particles according to whether a surface represents, for instance, 'naked' silica or silanised silica. The amount of silanisation is variable. We use a nearest-neighbour site-exchange Monte Carlo algorithm to generate filler morphologies, mimicking flocculation. Transmission electron micrographs (TEM) as well as small angle scattering (SAS) intensities can be calculated along the Monte Carlo trajectory. In this work we demonstrate the application of our morphology generator in terms of selected examples. We illustrate its potential as a tool for screening studies, relating interface tensions between the components to filler network structure as characterized by TEM and SAS.

At present, indoor localization is one of the core technologies of location-based services (LBS), and there exist numerous scenario-oriented application solutions. Visual features, as the main semantic information to help people understand the environment and thus occupy the dominant part, many techniques about indoor scene recognition are widely adopted. However, the engineering application problem of cell phone indoor scene recognition and localization has not been well solved due to insufficient semantic constraint information of building map and the immaturity of building map location anchors (MLA) matching positioning technology. To address the above problems, this paper proposes a cell phone indoor scene recognition and localization method with building map semantic constraints. Firstly, we build a library of geocoded entities for building map location anchors (MLA), which can provide users with "immersive" real-world building maps on the one hand and semantic anchor point constraints for cell phone positioning on the other. Secondly, using the improved YOLOv5s deep learning model carried on the mobile terminal, we recognize the universal map location anchors (MLA) elements in building scenes by cell phone camera video in real-time. Lastly, the spatial location of the scene elements obtained from the cell phone video recognition is matched with the building MLA to achieve real-time positioning and navigation. The experimental results show that the model recognition accuracy of this method is above 97.2%, and the maximum localization error is within the range of 0.775 m, and minimized to 0.5 m after applying the BIMPN road network walking node constraint, which can effectively achieve high positioning accuracy in the building scenes with rich MLA element information. In addition, the building map location anchors (MLA) has universal characteristics, and the positioning algorithm based on scene element recognition is compatible with the extension of indoor map data types, so this method has good prospects for engineering applications.

An extension of the models used to generate fractal traffic flows is presented by means of the formulation of a model that considers the use of one-dimensional chaotic maps. Based on the disaggregation of the temporal series generated by the model, a valid explanation of behavior of the values of Hurst exponent is proposed and the feasibility of their control from the parameters of the proposed model is shown.

Canopy characteristics are crucial for accurately and safely determining the pesticide quantity and volume of water used for spray applications in vineyards. The inevitably high degree of intra-plot variability makes it difficult to develop a global solution for the optimal volume application rate. Here, the design procedure of, and the results obtained from, a variable rate application (VRA) sprayer are presented. Prescription maps were generated after detailed canopy characterization, using a multispectral camera embedded on an unmanned aerial vehicle, throughout the entire growing season in Torrelavit (Barcelona) in four vineyard plots of Chardonnay (2.35 ha), Merlot (2.97 ha), and Cabernet Sauvignonn (4.67 ha). The maps were obtained by merging multispectral images with information provided by DOSAVIÑA®, a decision support system, to determine the optimal volume rate. They were then uploaded to the VRA prototype, obtaining actual variable application maps after the application processes were complete. The prototype had an adequate spray distribution quality and exhibited similar results in terms of biological efficacy on powdery mildew compared to conventional (and constant) application volumes. The VRA results demonstrated an accurate and reasonable pesticide distribution, with potential for reduced disease damage even in cases with reduced amounts of plant protection products and water.

Due to low culturing costs and high seed protein contents, legumes represent the main global source of food protein. Pea (Pisum sativum L.) is one of the major economically important legume crops, impacting both animal feed and human nutrition. Therefore, the quality of pea seeds needs to be ensured in the context of sustainable crop production and nutritional efficiency. Obviously, changes in seed protein patterns might directly affect both of these aspects. Thus, here we address the pea seed proteome in more detail and provide, to the best of our knowledge, the most comprehensive annotation of the functions and intracellular localization of pea seed proteins. Accordingly, 1938 and 1989 non-redundant proteins were identified in yellow and green pea seeds, in total. Only 35 and 44 proteins, respectively, could be additionally identified after protamine sulfate precipitation (PSP) potentially indicating the high efficiency of our experimental workflow. In total 981 protein groups could be assigned to 34 functional classes, which were to a large extent differentially represented in yellow and green seeds. Closer analysis of these differences by processing of the data in KEGG and String databases revealed their possible relation to a higher metabolic status and reduced longevity of green seeds.

Predictive studies are essential to establish fundamental data for monitoring and controlling Xylella fastidiosa infections in our country. Limited knowledge exists about how Xylella fastidiosa interacts with the plant host's immune system, leaving numerous unanswered questions regarding Xylella fastidiosa biology and its interactions with national plant hosts. Key inquiries include understanding of how the plant immune system interfaces with Xylella fastidiosa in the xylem and identifying the specific or shared mechanisms underlying the susceptibility of different hosts. Factors such as the presence of insect vectors, abundance of host plants, and climate suitability play pivotal roles in Xylella fastidiosa dispersal. We recommend that countries identified with relatively high risk, like Portugal, undertake thorough individual risk analyses. The implementation of preventive measures and, if necessary, the enhancement of surveillance systems for early detection of Xylella fastidiosa in plants and insect vectors are crucial steps. Additionally, raising awareness is of equal importance to mitigate socioeconomic and ecological impacts on their ecosystems.

The weakness of the dispersion-managed link combined with optical phase conjugation to compensate for optical signal distortion caused by chromatic dispersion and nonlinear Kerr effect of standard single mode fiber is its limited structural flexibility. We propose dispersion map that can simultaneously compensate for the distorted wavelength division multiplexed signal while increasing the configurational flexibility. Each residual dispersion per span (RDPS) in the former half of the proposed link is randomly determined, and in the latter half, the arrangement order of RDPS is the same as or inverted in the former half. We confirm that the dispersion maps in which the RDPS distribution pattern in the latter half is opposite to the arrangement order in the former half are more effective in compensation, and rather, the compensation effect is better than in the dispersion map of the conventional scheme. The notable result of this paper is that the increase of flexibility can be achieved through random arrangement of RDPS in the former half, and the compensation improvement can be achieved by through inverse arrangement in the latter half which make the distribution profile of each half link roughly symmetric with respect to the midway optical phase conjugator.

This article reveals a best possible design for hybrid dispersion compensating fiber (HyDCF) with high birefringence established on modified broadband compensating structure through S, C and L telecommunication bands. The simulation outcome exhibits relatively higher birefringence of 3.76×10-2 at wavelength of 1550 nm. The suggested fiber also has dispersion compensation characteristics in an inclusive series of wavelengths which covers 1400-1625 nm. The reported design can achieve dispersion quantity of – 606 ps/ (nm.km) at 1550 nm effective wavelength. The reported fiber design matches the relative dispersion slope (RDS) 0.003694 nm-1 similar to single mode fiber at 1550 nm operating wavelength. This fiber demonstrates negatively flattened effective dispersion of – 2.703 ± 0.734 ps/ (nm.km) within 180 nm flat band ranging from 1460-1640 nm wavelength. It is also convenient to optical high bit rate communication systems. The low confinement loss is found 3.756×10-10 dB/m at the operating wavelength. This design also achieves highly nonlinear coefficient of 50.34 W-1km-1. In some cases, it can also be used in sensing applications.

A controlled ammonia (NH₃) release experiment was performed at a grassland site to quantify the effect of dry deposition, at the field scale between the source and the receptors (NH₃ measurement locations), on the estimates of emission rates by means of inverse dispersion modelling. NH₃ was released for 3 hours at a constant rate of Q = 6.29 mg s⁻¹ from a grid of 36 orifices spread over an area of 250 m². The increase in line-integrated NH₃ concentration was measured with open-path optical miniDOAS devices at different locations downwind of the artificial source. Using a backward Lagrangian stochastic (bLS) dispersion model (bLSmodelR), the fraction of the modelled release rate to the emitted NH₃ (Q_bLS/Q) was calculated from the measurements of the individual instruments. Q_bLS/Q was found to be systematically lower than 1, on average between 0.69 and 0.91, depending on the location of the receptor. We hypothesized that NH₃ dry deposition to grass and soil surfaces was the main factor responsible for the observed depletion of NH₃ between source and receptor. A dry deposition algorithm based on a deposition velocity approach was included in the bLS modelling. Model deposition velocities were evaluated from a ‘big‑leaf’ canopy resistance analogy. Canopy resistances (generally termed Rc) that provided Q_bLS/Q = 1 ranged from 75 to 290 s m⁻¹, showing that surface removal of NH₃ by dry deposition can plausibly explain the original underestimation of Q_bLS/Q. The inclusion of a dry deposition process in dispersion modelling is crucial for emission estimates, which are based on concentration measurements of depositing tracers downwind of homogeneous area sources or heterogeneously distributed hot spots, such as e.g. urine patches on pastures in the case of NH₃.

Since late December, the underwater Hunga Tonga-Hunga Ha'apai volcano has been erupting for weeks and has seen sporadic activities in a series of pretty big eruptions. On Friday 15th January 2022, an explosion shot a massive cloud of ash high into the atmosphere and generated a tsunami that impacted much of the Pacific Rim, which makes it one of the most energetic explosions of the entire 21st century so far. Thus, the need to determine the significant impact of these generated volcanic aerosols on the environment is a prominent task. This study depicts the modeling of the volcanic ash dispersion from the 2022 Hunga Tonga-Hunga Ha'apai volcanic eruption while investigating the effects of incorporating radiative feedback effects within the inline Weather Research and Forecasting model coupled with chemistry (WRF-Chem). Results for 4-day averaged values have proven that the basic run (No Feedback) produced higher ash concentrations than the one with aerosol radiative feedback effects (Feedback). The simulations highlighted also the significant volcanic ash biases concentrated around the ash cloud. Additionally, our data analysis from meteorological stations and Copernicus TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI-S5P) mission indicates that total sulfur dioxide () emissions traveled west. We show also that the huge plume of on January 18 reached Australia, more than 7000 km west of the eruption. With the enormous ash cloud produced, its impact on the environment and global climate change would be considered an excellent exercise for atmospheric dispersion modelers, volcanologists, and the environmental scientists' community.

Conventional mechanical Fourier Transform Spectrometers (FTS) are able to simultaneously measure absorption and dispersion spectra of gas-phase samples. However, they usually need very long measurement times to achieve time-resolved spectra with a good spectral and temporal resolution. Here, we present a mid-infrared dual-comb-based FTS in an asymmetric configuration, providing broadband absorption and dispersion spectra with a spectral resolution of 5 GHz, a temporal resolution of 20 μs, and a total measurement time of a few minutes. We used the dual-comb spectrometer to monitor the reaction dynamics of methane and ethane in an electrical plasma discharge. We observed ethane/methane formation as a recombination reaction of hydrocarbon radicals in the discharge in various static and dynamic conditions. The results demonstrate a new analytical approach for measuring fast molecular absorption and dispersion changes and monitoring fast dynamics of chemical reactions, which can be interesting for chemical kinetic research and particularly for the combustion and plasma analysis community.

The central nervous system (CNS) controls movements and regulates joint stiffness with muscle coactivation, but until now few studies have examined muscle pairs during running. This study aims to investigate differences in lower limb muscle coactivation during gait at different speeds from walking to running. Nineteen healthy runners walked and ran at speeds ranging from 0.8 km/h to 9.3 km/h. Twelve lower limb muscles' coactivation was calculated using the time-varying multi-muscle coactivation function (TMCf) with global, flexor-extension, and rostro-caudal approaches. Spatiotemporal and kinematic parameters were also measured. We found that TMCf, spatiotemporal and kinematic parameters were significantly affected by gait speed for all approaches. Significant differences were observed in the main parameters of each coactivation approach, and in the spatiotemporal, and kinematic parameters at the transition between walking and running. Positive and negative strong correlations were found between global coactivation parameters and center of mass displacements, as well as some spatiotemporal parameters, regardless of gait speed. Our findings suggest that walking and running have different coactivation patterns and kinematic characteristics, with the whole-limb stiffness exerted more synchronously and stably in running. The coactivation indexes and kinematic parameters could be the result of global coactivation, which is a sensory-control integration process used by the CNS to deal with more demanding and potentially unstable tasks like running.

(1) Background: Stereological estimations significantly contributed to our anatomical and physiological understanding of the lung by providing an average distribution of measured parameters over the entire lung parenchyma. However, most structural lung diseases show a very inhomogeneous pattern of alterations. (2) Methods: We developed a novel protocol for the analysis of all pulmonary airspaces. Our pipeline starts with high-resolution synchrotron radiation-based X-ray tomographic microscopy (SRXTM) and consists of (i) image segmentation with the combination of the free machine-learning tool Ilastik and ImageJ and (ii) calculation of the airspace diameter distribution of an entire lung using a diameter map function. To evaluate the new pipeline, lungs from adult mice with cystic fibrosis (CF)-like lung disease (ENaC-transgenic mice) or mice with elastase-induced emphysema were compared to healthy controls. (3) Results: We were able to show the distribution of airspace diameters throughout the entire lung, as well as separately for the conducting airways and the gas-exchange area. In the pathobiological context, we observed an irregular widening of parenchymal airspaces in mice with CF-like lung disease and elastase-induced emphysema. Comparable results were obtained when analyzing lungs imaged with μCT, suggesting that our pipeline is applicable to different kinds of imaging modalities. (4) Conclusions: We conclude that the airspace diameter map is well suited for a detailed analysis of unevenly distributed structural alterations in chronic muco-obstructive lung diseases such as cystic fibrosis and COPD.

Currently it was theoritized that cave paintings have meaning more than human and animal interactions. Based on an example from Lascaux cave, a figure of a bull is believed representing Taurus constellation together with the Pleiades. In here this study aims to assess the connections of paleolithic art works in the forms of cave paintings and zoomorphic figures resemble to bovid with possible ancient astronomy and constellation depictions in South East Asia. The study caves were Jeriji Saleh in Kalimantan and Leang Leang and Sumpang Bita caves in Sulawesi where ancient cave paintings and zoomorphic figures date to 40000 years old have been found. The results show that cave paintings in Jeriji Saleh, Leang Leang and Sumpang Bita caves were comparable to the current findings. Those paintings were having bovid like figures with Leang Leang has figure identified as extant Bubalus depressicornis. In Sumpang Bita, this species was depicted in pregnant condition similar to pregnant horse figure in Lascaux cave. Depiction of pregnant figures in cave paintings indicates the use of ancient calendar to determine season based on the animal mating season. Bovid figure in Jeriji Saleh was illustrated in the same posture like auroch bovid in Lascaux cave and this indicates that cave paintings in Jeriji Saleh have been used to visualize Taurus constellation. The postures of bovid paintings in Leang Leang were different and it is interpreted to visualize Capricorn constellation. Another significant similarity between Lascaux and Leang Leang caves can be seen in paintings depicting a shaft scene with the presences of 3 similar figures include dying man, speared bovid and small zoomorphic figures. This concludes that the caves with their wall painting were not merely functioned as media for ancient art works, whereas it has functioned as paleolithic planetarium and this knowledge was globally widespread.

Integrating nanomaterials like carbon nanotubes (CNTs) and iron oxide (Fe₃O₄) into epoxy composites has significant interest due to their potential to enhance mechanical properties. This study evaluates the impact of dispersion quality on the mechanical performance of CNT/Fe₃O₄/Epoxy composites, comparing stirring and sonication methods at three different loadings: 0.1, 0.3, and 0.5 wt.%. Tensile testing revealed that sonicated composites consistently outperformed stirred composites, with a significant increase in elastic modulus and ultimate tensile strength (UTS). However, fracture strain decreased in both composite types compared to pure epoxy, with sonicated composites experiencing a more significant reduction than stirred composites. These results underscore the importance of high-quality dispersion for optimizing mechanical properties.

In the land use planning framework in the neighbourhood of industrial facilities, the current approach to predicting the consequences of massive toxic gas releases is generally based on Gaussian or integral models. For many years, CFD models have been more and more used in this context, in accordance with the development of High-Performance Computing (HPC). The present paper focuses on harmonizing input data for Atmospheric Transport and Dispersion (AT&amp;D) modelling between the widely used approaches. First, a synthesis of the practice’s harmonization for atmospheric dispersion modelling within the framework of risk assessment is presented. Then, these practices are applied to a large-scale INERIS ammonia experimental release. For illustration purposes, the impact of the proposed harmonization will be evaluated using different approaches: the SLAB model, the FDS model and the Code_Saturne model. The two main focuses of this paper are the adaptation of the source term dealing with a massive release and the wind flow modelling performance using an experimental signal for CFD models inflow. Finally, comparisons between the modelling and experimental results enable checking the consistency of these approaches and reinforce the importance of the input data harmonization for each AT&amp;D modelling approach.

Conventional method for monitoring the IgG levels suffered from some apparent problems such as long assay time, multistep processing, and high overall cost. An effective and suitable optical platform for label-free biosensing has been investigated by the implementation of antibody/antigen immunoassays. Thus, the ultrasensitive detection of IgG levels can be achieved by exploiting the dispersion turning point (DTP) existed in the tapered two-mode fibers (TTMFs) due to the sensitivity will reach ±∞ on either side of the DTP. Tracking the resonant wavelength shift it was found that the fabricated TTMF device exhibited limits of detection (LOD) down up to concentrations of 10 fg/mL of IgG in PBS solution. Such immunosensors based on the DTP have great significance on trace detection of IgG due to simple detection scheme, quick response time, and miniaturation.

The article describes the results of comparison of occurence of buildings (and address points) in Poland with delimitations of land use belonging to particular classes in the CORINE Land Cover (CLC) 2018 dataset. Large discrepancies have been identified, which reach on average approx. 34% of addresses and 35% of buildings located outside class 1 (artificial surfaces), mainly on terrains of class 2 (agricultural areas). Among single-family buildings it was 37% and among new addresses (forecasted or ‘under construction’ buildings) – as much as 50%. This puts a question mark over the possibility of using CLC data with resolution of 25 ha for monitoring of spatial planning and development in Poland for purposes of the diagnosis and assessment of the scale of dispersion of built-up areas. It is worth carrying out similar analyses in other countries, known for the deconcentration processes and a relatively large share of dispersed settlement e.g. other CEE countries, Spain, Portugal, Italy.