New setting is introduced to study the global powerful alliance. Global powerful alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global powerful alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs excluding empty, path, star, and wheel and containing complete, cycle and r-regular-strong are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is used in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-powerful-alliance number and minimal-global-powerful-alliance-neutrosophic number. Two different types of sets namely global-powerful alliance and minimal-global-powerful alliance are defined. Global-powerful alliance identifies the sets in general vision but minimal-global-powerful alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-powerful-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-powerful alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs has an open avenue, in the way that, the family only contains same classes of neutrosophic graphs. The results are about minimal-global-powerful alliance, minimal-global-powerful-alliance number and its corresponded sets, minimal-global-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-powerful alliances, minimal-t-powerful alliance, minimal-t-powerful-alliance number and its corresponded sets, minimal-t-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-t-powerful alliances. The connections amid t-powerful-alliances are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications and closing remarks. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global powerful alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set and reversely for non-members of set with less members in the way that the set is simultaneously t-offensive and(t-2)-defensive. A set is global if t=0. It leads us to the notion of global powerful alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

In this paper we provide some important and significant observations on invo-regular rings appeared in Ann. Univ. Mariae Curie-Sklodowska Sect. A Mathematica (2018). In addition we exhibit that strongly invo-regular rings, invo-regular rings and quasi invo-regular rings all coincide with the well known and well characterized tripotent rings and all these rings further coincide with the well known unit regular rings.

We review the basics of nuclear binding energy scheme assumed to be associated with the existence of a new strong elementary charge associated with square root of reciprocal of the strong coupling constant.

Abstract: Bulgaria is famous for its oil-bearing rose. R. damascena Mill. and R. alba L. are mainly cultivated in the country, but a recent survey of industrial plantations in 2020 revealed that R. centifolia L. and hybrids of R. damascena Mill. x R. gallica L. are also common in the rose valley. Although their essential oil cannot be compared in quality with the classic, they are preferred by farmers with high yields of flowers and resistance to diseases and pests. All these roses are also used to produce rose water and extracts. The aim of this investigation was to compare the yield and chromatographic fingerprints of seven rose oils and hydrosols produced in Bulgaria. The quantitative composition of the main components of the oils was compared with the norms of the world standard. Our study showed that the yield of essential oil from these roses was in the range of 0.015 - 0.048%. The main group in the chemical composition is terpene alcohols, which vary in the range: geraniol (17.60 - 34.02 %), citronellol (8.38 - 28.7 %), and nerol (4.8 - 11.90 %), but with a different ratio. Hydrocarbons are represented by saturated aliphatic homologs with an odd number of carbon atoms, the main ones being: nonadecane (8.10 - 22.67 %), heneicosane (4.37 - 10.21 %), heptadecane (1.07 - 2.98 %) and triclosan (0.81 - 5.90 %). In contrast, the chemical profile of the hydrosols was performed by phenyl ethyl alcohol (27.45 - 69.88 %), geraniol (13.72 - 28.67 %), and citronelol+nerol (4.56 - 17.37 %). The results show that the presence of plantations with a genotype different from that of R. damascena implies differences in the quality of rose oils and hydrosols. This predetermines their properties of use.

BACE1 is involved in the production of beta-amyloid peptides, and inhibiting its activity is a potential therapeutic strategy for managing Alzheimer's disease, as excessive beta-amyloid accumulation is a characteristic feature of the disease.Computational results suggest that hypericin has the potential to act as an inhibitor of BACE1. The Molecular Docking results indicate a high binding affinity between hypericin and BACE1, with a notable binding energy score of -10.3 kcal/mol. Additionally, the formation of various chemical bonds, including hydrogen bonds and hydrophobic bonds, further supports the idea that hypericin may effectively interact with the active site of BACE1. It's important to note that while the in silico Molecular Docking results are promising, further in vitro and in vivo studies would be necessary to validate and better understand the inhibitory potential of hypericin against BACE1. Additionally, the practical application of hypericin as a BACE1 inhibitor in a therapeutic context would require careful consideration of factors such as bioavailability, safety, and efficacy.

Enhancing traffic safety is one of the fundamental objectives of Intelligent Transport Systems (ITS), and it aligns closely with the principles of sustainable transport. Due to specific differences in infrastructure, vehicles, and users’ behaviour, places where different modes of traffic intersect are recognized as critical points of the traffic system, making them crucial aspects of Sustainable Urban Mobility Plans (SUMPs) implementation. The SUMPs aim to create urban mobility that is not only environmentally friendly and efficient but also safe for all users. The continuous development and widespread adoption of innovative ITS technologies have paved the way for a system that could provide drivers with real-time information about both immediate and potential dangers at these critical points. This paper provides an overview of previous research in the field, investigating the impact of information systems on drivers’ behaviour, various detection and communication solutions that can be effectively integrated into such a system, as well as a brief overview of models and solutions that have been developed to warn drivers in a similar context. The reviewed literature offered valuable insights on which a novel driver information system architecture framework is proposed. This framework can contribute to the ongoing safety improvement in multimodal transport networks within the context of sustainable transport.

Constructing new graph from the graph's parameters and related notions in the way that, the study on the new graph and old graph in their parameters could be facilitated. As graph, new graph has some characteristics and results which are related to the structure of this graph. For this purpose, regular graph is considered so the internal relation and external relation on this new graph are studied. The kind of having same number of edges when this number is originated by common number of graphs like maximum degree, minimum degree, domination number, coloring number and clique number, is founded in the word of having regular graph

To ensure the safety in aircraft flying, we aim use of the deep learning methods of nondestructive examination with multiple defect detection paradigms for X-ray image detection posed. The use of the Fast Region-based Convolutional Neural Networks (Fast R-CNN) driven model seeks to augment and improve existing automated Non-Destructive Testing (NDT) diagnosis. Within the context of X-ray screening, limited numbers insufficient types of X-ray aeronautics engine defect data samples can thus pose another problem in training model tackling multiple detections perform accuracy. To overcome this issue, we employ a deep learning paradigm of transfer learning tackling both single and multiple detection. Overall the achieve result get more then 90% accuracy based on the AE-RTISNet retrained with 8 types of defect detection. Caffe structure software to make networks tracking detection over multiples Fast R-CNN. We consider the AE-RTISNet provide best results to the more traditional multiple Fast R-CNN approaches simpler translate to C++ code and installed in the Jetson™ TX2 embedded computer. With the use of LMDB format, all images using input images of size 640 × 480 pixel. The results scope achieves 0.9 mean average precision (mAP) on 8 types of material defect classifiers problem and requires approximately 100 microseconds.

Molecular docking, a computational method predicting how molecules bind to target proteins, is employed in this study to explore Polydatin's interactions with Ras-related protein Rab (Rab) proteins using the Mcule Database. This database validates the docking results and offers insights into the pharmacological properties of Polydatin. Notably, specific Rab proteins like Rab-5A, HRas, and Rab-18 exhibit robust interactions with Polydatin, indicated by favorable binding energies.These findings illuminate the potential roles of Polydatin in therapeutic and biological contexts, emphasizing its interaction with Rab proteins. The Mcule Database enhances the credibility of the study, providing additional perspectives on Polydatin's applications. The observed interactions, particularly with key proteins like HRas, present a promising avenue for modulating cellular signaling pathways. This modulation holds therapeutic potential, potentially addressing conditions associated with pathway overactivity, including specific cancer types.

The assessment of Histone deacetylases in conjunction with Curcumin, conducted through the Mcule Database employing the Autodock Vina algorithm, involves an examination of molecular interactions. This analysis includes the calculation of binding energies, revealing the strength and stability of the interactions between Curcumin and various Histone deacetylase targets. The comparison encompasses diverse aspects such as binding energies, specific binding sites, interactions across different targets, structural details, and potential implications for biological activity. The results imply that Curcumin shows heightened affinity for Histone deacetylase 4 in comparison to other investigated histone deacetylases.

Climate change will pose a challenge for the winemaking sector worldwide, bringing progressively drier and warmer conditions and increasing the frequency and intensity of weather extremes. The short-term adaptation strategy of applying biostimulants through foliar application serves as a crucial measure in mitigating the detrimental effects of environmental stresses on grapevine yield and berry quality. The aim of this study was to evaluate the effect of foliar application of a seaweed based biostimulant (A. nodosum – ANE) and glycine betaine (GB) on berry quality, bioactive compounds, antioxidant activity, and elucidated their action on the secondary metabolism. A trial was installed in a commercial vineyard (cv. ‘Touriga Franca’) in the Cima Corgo (Upper Corgo) sub-region of the Douro Demarcated Region. A total of four foliar sprayings were performed during the growing season: at flowering, pea size, bunch closer, and veraison. There was a positive effect of GB in the berry quality traits. Both ANE and GB increased the synthesis of anthocyanins and other phenolics in berries and influenced the expression of genes related to the synthesis and transport of anthocyanins (CHS, F3H, UFGT, MATE1 and GST). So, they have the potential to act as elicitors of secondary metabolism, leading to improved grape quality, but also sets the foundation for sustainable agricultural practices in the long run.

With reference to our 4G model of final unification, strong coupling constant and strong interaction charge of magnitude $e_s\cong 2.95e$, it is possible to understand the nuclear stability range with a simple power law of the form, $A_s\cong \left(Z+2.95\right)^{1.2\pm0.015}$

The study examines n-balls, regular n-simplices, and n-orthoplices in real dimensions using novel recurrence relations that removed indefiniteness present in known formulas. They show that in the negative, integer dimensions volumes of n-balls are zero if n is even, positive if n = -4k - 1, and negative if n = -4k - 3, for natural k. Volumes and surfaces of n-cubes inscribed in n-balls in negative dimensions are complex, wherein for negative, integer dimensions they are associated with integral powers of the imaginary unit. The relations are continuous for n Î ℝ and show that the constant of π is absent for 0 ≤ n < 2. For n < -1 self-dual n-simplices are undefined in the negative, integer dimensions, and their volumes and surfaces are imaginary in the negative, fractional ones, and divergent with decreasing n. In negative, integer dimensions n-orthoplices reduce to the empty set, and their real volumes and imaginary surfaces are divergent in negative, fractional ones with decreasing n. Out of three regular, convex polytopes present in all natural dimensions, only n-orthoplices, n-cubes (and n-balls) are defined in the negative, integer dimensions.

For the first time, this study identified seven potential ligands with high binding energies through the docking approach against the Crystal Structure of human Melanoma-associated antigen B1 (MAGEB1). The ligands—Imatinib, Bafatinib, Diosmin, Ginkgetin, Bilobetin, Amentoflavone, and Hypericin—showing strong binding energies around -10 kcal/mol, indicate a potentially robust interaction with the target protein. Moreover, the additional step of predicting toxicity properties using the pKCSM server provides valuable insights into the safety profiles of these ligands. From these results, the parameters for Diosmin: —Max. tolerated dose (human),- Oral Rat Acute Toxicity (LD50), and - Oral Rat Chronic Toxicity (LOAEL)—suggest a favorable safety profile, making it a potential candidate for further consideration against Melanoma. Moving forward, it's advisable to conduct further experimental validations, including in vitro and in vivo studies, to confirm the efficacy and safety of Diosmin and other potential ligands. Consideration of pharmacokinetics, metabolism, and specific mechanisms of action will contribute to a comprehensive understanding of these compounds' potential as therapeutic agents.

The effects of the coolant pulsation and the film cooling with the plasma aerodynamic actuation (PAA) could be herein explored via large eddy simulations. The electrohydrodynamic force derived from the PAA was solved through the phenomenological plasma model. The Strouhal number of the sinusoidal coolant pulsation and the averaged pulsation blowing ratio were 0.25 and 1.0, respectively. Comprehensive analyses were carried out on the time-averaged flow fields, and the results revealed that the pulsed cooling jet might cause a deeper penetration into the crossflow, and this phenomenon could be remarkably mitigated by the downward force of the PAA. Furthermore, because of the coolant pulsation, the counter rotating vortex pair (CRVP) expanded to lifted off the wall less well, and the PAA lessened the negative lift-off impact and entrapment from the CRVP. Then, the spatial-temporal development of the coherent structures was figured out by the alterations of the centerline temperature, reflecting formation of the intermittent coherent structures rather than hairpin vortices due to the coolant pulsation, and their size and upcast behaviors were reduced by the PAA. Consequently, there was a basic suppression of the turbulent mixing of the cooling fluid with the crossflow. Finally, the three-dimensional streamlines confirmed that the coherent structure dynamic behaviors were significantly regulated by the PAA for alleviating the adverse influences of the coolant pulsation. In summary, through controlling how the dominating coherent structures evolve throughout time and space, the PAA can effectively increase the pulsed film cooling efficiency.

In this paper, some characterizations of fuzzifying strong compactness are given, including characterizations in terms of nets and pre -subbases. Several characterizations of locally strong compactness in the framework of fuzzifying topology are introduced and the mapping theorems are obtained.

The strong coupling between individual quantum emitters and resonant optical micro/nanocavities is beneficial to understand light and matter interactions. Here we propose a plasmonic nanoantenna placed on a metal film to achieve an ultra-high electric field enhancement in the nanogap and ultra-small optical mode volume. The strong coupling between a single quantum dot and the designed structure is investigated in detail by both numerical simulations and theoretical calculations. When a single QD is inserted into the nanogap of the silver nanoantenna, scattering spectra show remarkably large spectral splitting and typical anti-crossing behavior of the vacuum Rabi splitting, which can be realized in the scattering spectra by varying the nanoantenna thickness. Our work shows a possible way to enhance light-matter interaction at a single quantum emitter limit, which can be useful for future quantum and nanophotonic applications.

New setting is introduced to study chromatic number. Neutrosophic chromatic number and chromatic number are proposed in this way, some results are obtained. Classes of neutrosophic graphs are used to obtains these numbers and the representatives of the colors. Using colors to assigns to the vertices of neutrosophic graphs is applied. Some questions and problems are posed concerning ways to do further studies on this topic. Using strong edge to define the relation amid vertices which implies having different colors amid them and as consequences, choosing one vertex as a representative of each color to use them in a set of representatives and finally, using neutrosophic cardinality of this set to compute neutrosophic chromatic number. This specific relation amid edges is necessary to compute both chromatic number concerning the number of representative in the set of representatives and neutrosophic chromatic number concerning neutrosophic cardinality of set of representatives. If two vertices have no strong edge, then they can be assigned to same color even they’ve common edge. Basic familiarities with neutrosophic graph theory and graph theory are proposed for this article.

The purpose of this paper is to bring to light a method through which the global in time existence for arbitrary large in H¹ initial data of a strong solution to 3D periodic Navier-Stokes equations follows. The method consists of subdividing the time interval of existence into smaller sub-intervals carefully chosen. These sub-intervals are chosen based on the hypothesis that for any wavenumber m, one can find an interval of time on which the energy quantized in low-frequency components (up to m) of the solution u is lesser than the energy quantized in high-frequency components (down to m) or otherwise the opposite. We associate then a suitable number m to each one of the intervals and we prove that the norm ||u(t)||_H1 is bounded in both mentioned cases. The process can be continued until reaching the maximal time of existence T_max which yields the global in time existence of strong solution.

Background: Increase of collagen I (COL I)/COL III ratio enhances vessel wall stiffness and renders vessels less resistant to blood flow and pressure changes. We hypothesized that COL I/COL III ratio is increased in the brain arteriovenous malformations (bAVMs), which is associated with bAVM hemorrhage. Method: Surgically resected human bAVM samples and mouse bAVMs induced in three transgenic mouse lines with activin receptor-like kinase 1 or endoglin deletion in the endothelial cells or in the brain focally. Colony-stimulating factor receptor inhibitor was used to transiently deplete microglia. COL I and COL III levels, hemorrhage, and gene expression in bAVMs were analyzed. Results: The COL I and COL III levels and the COL I/COL III ratio were higher on human and mouse bAVMs than controls, which was associated with bAVM hemorrhage. Col I and Col III mRNAs were also increased in mouse bAVMs. The degree of microhemorrhage in mouse bAVMs was positively correlated with Col I/Col III ratios. Transient depletion of microglia reduced Col I/Col III ratio and microhemorrhage in mouse bAVMs. Conclusion: COL I/COL III ratio are increased in bAVM vessels, which is associated with bAVM hemorrhage. Depletion of microglia reduces Col I/Col III ratio and hemorrhage in mice bAVMs.

In this paper, we explore a new norm on L^p-space called r-norm, and hence producing a new normed space called r-normed space. Measure theoretic and functional analytic properties are covered such as the relation between r-norm and the classical p-norm. An application of r-normed space in probability theory and statsitics is also presented, notably, its role as a rigorous framework in describing the coefficient of determination.

A closed chain of oscillators can be considered as a model of ring-shaped ecosystems, such as atolls or coastal zones of inland reservoirs. As an oscillator model, we use the logistic map that often referred to as an archetypical example of how complex dynamics can arise from very simple nonlinear equations. We investigate the influence of the model parameters both on the nature of oscillations in the oscillator ring and on the spatial structures that arise in this case. Namely, we demonstrate a variety of emerging spatial structures depending on the initial conditions.

In mathematics, the Riemann hypothesis is a conjecture that the Riemann zeta function has its zeros only at the negative even integers and complex numbers with real part 1/2. Many consider it to be the most important unsolved problem in pure mathematics. It is one of the seven Millennium Prize Problems selected by the Clay Mathematics Institute to carry a US 1,000,000 prize for the first correct solution. We prove the Riemann hypothesis using the Complexity Theory. Number theory is a branch of pure mathematics devoted primarily to the study of the integers and integer-valued functions. The Goldbach's conjecture is one of the most important and unsolved problems in number theory. Nowadays, it is one of the open problems of Hilbert and Landau. We show the Goldbach's conjecture is true using the Complexity Theory as well. An important complexity class is 1NSPACE(S(n)) for some S(n). These mathematical proofs are based on if some unary language belongs to 1NSPACE(S(log n)), then the binary version of that language belongs to 1NSPACE(S(n)) and vice versa.

A fast algorithm is established to transform points of the unit sphere into fundamental region symmetrically. With the resulting algorithm, a flexible form of invariant mappings is achieved to generate aesthetic patterns with symmetries of the regular polyhedra. This method avoids the order restriction of symmetry groups, which can be similarly extended to treat regular polytopes in n-dimensional space for n>=4.

To understand the mystery of final unification, in our earlier publications, we proposed that, 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions; and 2) There exists a strong interaction elementary charge (e_s) in such a way that, it's squared ratio with normal elementary charge is close to inverse of the strong coupling constant. In this context, starting from lepton rest masses to stellar masses, we have developed many interesting and workable relations. We noticed that, electroweak field seems to be operated by a primordial massive fermion of rest energy 585 GeV. It can be considered as the zygote of all elementary particles and galactic dark matter. Proceeding further, with a characteristic fermion-boson mass ratio of 2.27, quarks can be classified into quark fermions and quark bosons. Considering strong charge conservation and electromagnetic charge conservation, fractional charge quark fermions and quark bosons can be understood. Quark fermions that generate observable massive baryons can be called as Fluons. Quark bosons that generate observable mesons can be called as Bluons. By considering a new hadronic fermion of rest energy 103.4 GeV, rest masses of fluons and bluons can be estimated and there by baryon masses and meson masses can be estimated.

With reference to our earlier published views on large nuclear gravitational constant , nuclear elementary charge and strong coupling constant , in this paper, we present simple relations for nuclear stability range, binding energy of isotopes and magic proton numbers.

This article presents a proposed system that enables energy transfer from the dc grid to a single-phase onboard grid, operating at an hi frequency. In addition to the energy transfer function, it additionally enables compensation of reactive power in the ac grid when the converter operates at less than rated power. To operate in compensator mode, it is necessary to decouple the current from the grid into active and reactive components and control them independently. To achieve good dynamics, synchronizers that operate in the dq system are used. In the case of a single-phase grid, it requires such a synchronizer to generate virtual quadrature signals. The used systems based on second-order generalized integrator are good, but to improve dynamics in the work a quadrature generator based on trigonometric calculations was proposed. The developed system was implemented in a proportional resonant current control system. Tests performed in steady state and in dynamic states related to typical grid disturbances showed better dynamic properties than the standard integrator-based system.Keywords: power transfer; compensator; P+R controller

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

Herein, a chemophenetic significance, based on phenolic metabolite profiling of three Senecio (S. hercynicus, S. ovatus and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima) coupled to morphometric data, is presented. A set of twelve morphometric characters were recorded from each plant species and used as predictor variables in a Linear Discriminant Analysis (LDA) model. From a total 75 observations (15 from each of the five species), the model correctly assumed their species' membership, except 2 observations. Among the studied species, S. hercynicus and S. ovatus presented the greatest morphological similarity. A phytochemical profiling of phenolic specialized metabolites by UHPLC-Orbitrap-HRMS revealed 46 hydroxybenzoic, hydroxycinnamic, acylquinic acids and their derivatives, 1 coumarin, and 21 flavonoids. Hierarchical and PCA clustering applied to the phytochemical data corroborated the similarity of S. hercynicus and S. ovatus, observed in the morphometric analysis. This study contributes to the phylogenetic relationships between the tribe Senecioneae taxa and highlights the chemophenetic similarity/dissmilarity of the studied species belonging to Senecio and Jacobaea genera.

Neuroinflammation, defined as inflammatory reactions mediated by cytokines, chemokines, reactive oxygen species, and secondary messengers in the central nervous system (CNS) including the brain and spinal cord is the basis of many neurological disorders. Recently, erythropoietin (EPO) has been considered and studied as a modulator of neuroinflammation. On this article minireview of pathophysiology of neuroinflammation and the neuroprotective effects of EPO is discussed and a case of subacute huge subdural hematoma with double mydriasis operated urgently, treated with low daily dose (vs high dose once or twice a month in the literature) of EPO and recovered fully and discharged home with good consciousness is reported. In addition, the probable unfavorable outcome of erythropoietin administration in patients with neuroinflammation in COVID-19 is considered.

High-quality optical Fano resonances, which exist in a spherical dielectric microparticle in the spatial configurations of the "whispering-gallery modes" (WGMs) and recently are referred to as the “super-resonances”, possess extremal sensitivity not only to the micro-cavity size and shape but also to the optical properties of the particulate material. The increase in the power of light radiation coupling into a super-resonance can lead to the manifestation of strong optical nonlinearity of the resonator material due to the cubic nonlinearity (optical Kerr effect) and generation of free electron plasma in certain regions of the spherical microcavity. In fact, an optically linear medium of the resonance cavity transforms into a Drude-Kerr-type medium with a strong dependence on input laser intensity. With the help of the finite-elements numerical simulations, we theoretically analyze the transformations of the resonant contour for a number of high-quality WGMs excited in a lanthanum-glass microsphere exposed to an optical radiation of different intensity. We show that in a certain input intensity range, the competition of Kerr and plasma optical nonlinearities can stop and even reverse the Stokes shift of the super-resonance observed in a pure Kerr medium. Additionally, optical ionization and plasma generation within the mode volume significantly reduce the strength of the magnetic super-resonance and lead to its spoiling and frequency splitting.

Current artificial intelligence (AI) technology is still considered weak AI. However, the progression towards strong AI unavoidably involves grappling with concerns surrounding consciousness, the mind, and creativity. This paper focuses on analyzing consciousness, creativity, and the generation of emotions to explore the possibility of machine-based consciousness, creativity, and emotion. We believe that the emergence of consciousness relies on the complex interplay at different layers within a complex system, rather than wholly relying on the underlying substrates of the system. Thus, it is plausible to consider the existence of machine-based consciousness, creativity, and emotion. Furthermore, swarm intelligence should be recognized as a distinct form of intelligence. Human individuals serve as the foundational substrate enabling the realization of swarm intelligence, with individual intelligence reflecting the projection of swarm intelligence at the individual level. The advanced state of human civilization is primarily attributable to the effect of swarm intelligence. Building upon basic emotions to adapt to environmental conditions, advanced human emotions are a product of the evolutionary process by swarm intelligence. Emotions serve as a pivotal impetus for the formation and development of societies grounded in swarm intelligence. In pursuit of super-AI that surpasses human civilization in the future, nurturing swarm intelligence represents an inevitable trajectory.

The overcrowding of high-rise buildings in the city adversely affects the wind environment by changing the air currents in the surrounding areas. In particular, extreme climate phenomena caused by climate change are stronger and more frequent, causing social damages in cities. To comprehensively better understand the wind properties around high-rise buildings, actual filed measurement is necessary to determine the environment assessment of wind effect. We performed the on-site measurement on LCT residential complex regions (411.6m tall) with highly concentrated high-rise buildings in coastal city Busan, South Korea under extreme weather conditions such as typhoon invasions to determine wind fluid characteristics. In the field monitoring, five anemometers were installed to analyze the wind environment around high-rise buildings when typhoon 'Hinnamnor' invaded. Compared to the nearby weather station operated by KMA(Korea Meteorological Administration), the gust was 3.7 times stronger and the max 1 min-mean wind speed was 3.1 times stronger, and the characteristics of the downward wind and the canyon wind were shown depending on the location characteristics of the point. Turbulence intensity decreased as the wind speed increased and converged to a certain value. Likewise, the gust factor also decreased as the wind speed increased and converged to 2.0, which is considered to be the parameter that best represents the intensity of the instantaneous gust caused by the skyscraper wind effect.

In this article some important observations have been reported on recent works related to weakly tripotent rings and locally invo-regular rings. Our findings give additional results as well as correct some recent results on weakly tripotent rings and locally invo-regular rings appeared in Rendiconti Sem. Mat. Univ. Pol. Torino (2021) and Azerbaijan Journal of Mathematics (2021) respectively. In addition we exhibit that if the Jacobson radical J(A) of a ring is strongly involution t-clean then the characteristic of J(A) need not be four. This finding improves an important result appeared in Eur. J. Pure Appl. Math (2022).

In this paper, we give the Galois adjunction form of the regular relation, and by using residuated mapping, we find the connection between it and order-generating set. Furthermore, we obtain the equivalent conclusion of "regular". In addition, by using the specialization order of topological space and the lower approximate operator in the rough set, we find a continuous homeomorphic mapping from a regular space to a Alexandrov topological space

In this note we generalize the regularity concept for semigroups in two ways simultaneously: to higher regularity and to higher arity. We show that the one-relational and multi-relational formulations of higher regularity do not coincide, and each element has several inverses. The higher idempotents are introduced, and their commutation leads to unique inverses in the multi-relational formulation, and then further to the higher inverse semigroups. For polyadic semigroups we introduce several types of higher regularity which satisfy the arity invariance principle as introduced: the expressions should not depend of the numerical arity values, which allows us to provide natural and correct binary limits. In the first definition no idempotents can be defined, analogously to the binary semigroups, and therefore the uniqueness of inverses can be governed by shifts. In the second definition called sandwich higher regularity, we are able to introduce the higher polyadic idempotents, but their commutation does not provide uniqueness of inverses, because of the middle terms in the higher polyadic regularity conditions.

In this lecture notes, we will introduce Asymptotics, then we will give a short glimpse on Perturbation theory (regular versus singular), which plays a crucial role especially in theoretical physics. Our goal is to find Asymptotic series that approximates the values of integrals depending on some parameter or the solutions of differential equations. These methods that lead to obtain more effective algorithms of numerical evaluation are called: Asymptotic Methods.

The inherited ‘EIA’ process at Brexit is based on a ‘Project’ period from Inception tothe start of construction works. The ‘Incompleteness’ of the process covers andidentifies stages that will impact on the environmental cycle: construction period,operational life, de-commissioning and a return to acceptable environmental footprint.A master environment structure-plan framework is required to commence with theupgrading of the complete ‘EIA’ process, embracing separate limbs for the UK’spriority environmental targets for climate change, and other major adverse effectswhich result in serious ‘harm’ to the UK environment. The identification of the processfor ‘incompleteness’ requires effective sustainability, and inclusion of effectivemanagement tools, for the essential ‘monitoring/control/recording’ proceduresthroughout the project life and the natural environmental cycle. This will allow theopportunity for a new approach to a structured ‘Suite of EIAR Directives’, to enable a‘EIAR’ regime that ‘will remain fit and proper for UK purpose’.

Introduction: EEGLAB is one of the most famous software for processing, analyzing, and researching experiments that have Electroencephalography (EEG) datasets. Due to the numerous and famous add-ins along with global, widespread communications and online free training, its popularity increased every year. Method: To address this phenomenon from a bibliographic perspective, we found 20,464 citations in Google Scholar for the main EEGLAB reference since 8/27/2023. Then, only the Web of Science (WOS) articles were 12,700 that they were extracted. The results were analyzed with Bibliometrix package from CRAN R software. Results: The time span of these articles is from 2004 to 2023 with 12,700 documents in 1,125 sources (journals, books, etc.), 29,125 authors, 19,062 author’s keywords, 13,707 keywords PLUS, 279,617 references. The annual growth rate is 28.12 %, international Co-authorship is 37.27 % and Co-authors per document is s 4.89 and the average citations per document is 22.51. The most relevant sources are Neuroimage, Frontiers in Human Neurosciences, Scientific Reports, Psychophysiology, and PLOS One with 780, 526, 446,425, and 371 articles, respectively. The most cited countries are the USA, Germany, and the United Kingdom with 93,093, 32,621, and 20,748 total citations, respectively. The ERPLAB, ADJUST, and ICLabel add-ins have the local to global citation ratios equal to 85.4%, 65.1%, and 78.2% respectively. Other bibliometric analyses such as co-occurrence networks and thematic maps of abstracts, titles, and keywords are estimated and presented. Conclusions: EEGLAB is among the most cited MATLAB toolboxes in computational neuroscience. Many developed and developing countries use it in their research publications.

This research aims to obtain empirical evidence of the influence of the masculinity of male CEOs on the of research & development, this research seeks to identify the influence of the face of mas-culinity of male CEO’s on the of research & development. The study used a quantitative approach with population and research samples using companies listed on the Indonesia Stock Exchange from 2016 to 2021. The study collected images of faces identified as male CEOs from data from the Indonesia Stock Exchange website and company as utilizing Google searches. The data analysis method in this study used Regression Ordinary Least Square (OLS) with Stata Software. Stata software is one of the regression completion procedures that has a high degree of flexibility in re-search that connects theories, concepts and data that can be done on variables in research. The findings empirically explain that the higher the face value of male CEO masculinity has an impact on reducing research & development costs, and vice versa the lower the face value of male CEO masculinity has an impact on increasing research & development. The practical implications of the research results can help the Indonesian Association of Accountants in developing Financial Accounting Standard No. 19 in Indonesia. The theoretical implications of the research results can explain the Theory of Agency and the Theory of Consistency of Behavior. The policy implications of the results of the study can provide empirical evidence that the higher the facial value of male CEO masculinity has an impact on reducing research & development, while also the lower the face value of male CEO masculinity has an impact on increasing research & development.

Potholes on roads pose a major threat to motorists and autonomous vehicles. Driving over a pothole has the potential to cause serious damage to a vehicle, which in turn may result in fatal accidents. Currently, many pothole detection methods exist. However, these methods do not utilize deep learning techniques to detect a pothole in real-time, determine the location thereof and display its location on a map. The success of determining an effective pothole detection method, which includes the aforementioned deep learning techniques, is dependent on acquiring a large amount of data, including images of potholes. Once adequate data had been gathered, the images were processed and annotated. The next step was to determine which deep learning algorithms could be utilized. Three different models, including Faster R-CNN, SSD and YOLOv3 were trained on the custom dataset containing images of potholes to determine which network produces the best results for real-time detection. It was revealed that YOLOv3 produced the most accurate results and performed the best in real-time, with an average detection time of only 0.836s per image. The final results revealed that a real-time pothole detection system, integrated with a cloud and maps service, can be created to allow drivers to avoid potholes.

In this work, we explore a the different forms of a new type of modified gravity, namely f(φ) gravity. We construct the Big Rip type for the energy density and the curvature of the universe. We show that dark energy is a result of the transformation of the field φ mass (dark matter) to energy. In addition, we provide that Ω_{m}≈0,050, Ω_{DM}≈0,2, Ω_{DE}≈0,746, is in excellent agreement with observation data. We explore a generalized formalism of braneworld modified gravity. We also construct a new field equations, which generalize the Einstein field equations. We provide a relation between the extra dimension in 3-brane with the vacuum energy density. We show that the energy density of matter depends directly on the number of dimensions. We manage to find the value of the Gauss-Bonnet coupling α=1/4 which is a good agreement with the results in the literature, this correspondence creates a passage between f(R) gravity and Gauss-Bonnet gravity, this comparison leads to a number of bulk dimensions equal to D=10¹²¹+4.

The study focuses on the application of R programming language towards marine geological research with a case study of Mariana Trench. Due to its logical and straightforward syntax, multi-functional standard libraries, R is especially attractive to the geologists for the scientific computing. Using R libraries, the unevenness of various factors affecting Mariana Trench geomorphic structure has been studied. These include sediment thickness, slope steepness, angle aspect, depth at the basement and magmatism of the nearby areas. Methods includes using following R libraries: {ggplot2} for regression analysis, Kernel density curves, compositional charts; {ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for compositional similarities among the bathymetric profiles, association plots; {car} for ANOVA. Bathymetric GIS data processing was dome in QGIS and LaTeX. The innovativeness of the work consists in the multi-disciplinary approach combining GIS analysis and statistical methods of R which contributes towards studies of ocean trenches, aimed at geospatial analysis of big data.

The three-dimensional morphology of frictional sub-surfaces holds significant importance for studying tribological issues. However, the uniformity of horizontal datum in 3D scanning is limited for curved surfaces, resulting in the inability to obtain accurate contour characterization parameters from the scanning results. This study aims to address this issue by constructing regular surface equations and normalizing the 3D profiler scanning results. By fitting the data, a "plane" surface representative of the surface features is obtained, and the paper demonstrates this approach on the surface morphology of different worn parts in the frictional area of spherical bearings located in the specific environment of the Three Gorges gate. The results indicate that the obtained "plane" effectively reconstructs the three-dimensional morphology map of the regular surface. Moreover, this reconstructed plane not only clearly illustrates the surface characteristics but also provides the foundation for analyzing the wear mechanism.

Here we analyze three well-known conjectures: (i) the existence of infinitely-many twin primes, (ii) Goldbach’s strong conjecture, and (iii) Polignac’s conjecture. We show that the three conjectures are related to each other. In particular, we see that in analysing the validity of the Goldbach’s strong conjecture, one must consider also the existence of an infinite number of twin primes. As a consequence of how we approach this analysis, we also observe that if this conjecture is true, then so is Polignac’s conjecture. Our first step is an analysis of the existence of infinitely-many twin primes numbers. For this, using the formula 4((n−1)!+1) ≡ −n (mod n(n + 2)) – satisfied if and only if (n, n + 2) are twin primes –, together with Wilson’s theorem, we obtain conditions that must be met for two numbers to be twin primes. Our results, obtained from an analytic and functional study, lead us to conclude that there may exist infinitely-many twin primes. Next, we consider the validity of the Goldbach’s strong conjecture. After showing that the conjecture is true for the first even numbers, we notice a pattern that we analyze for any even number, reducing it to three cases: (i) when the even number 2n is two times a prime number n; (ii) when the even number 2n is such that n = 2m, with 2m − 1 and 2m + 1 twin primes; (iii) all other cases, i.e., for any 2n even number ∀n ∈ N with n > 1, n prime or not, with independence of n = 2m being 2m−1 and 2m+1 twin primes or not. In this last case we show that one can always find a certain r ∈ N such that 1 < r < n satisfying that n−r and n+r are primes, so that their sum is 2n. In this case we use the reduction to absurd method, and our results lead us to conclude that Goldbach’s strong conjecture is true to the best of our calculations, as well as the Polignac’s conjecture.

We construct a repeated quantum game with public goods by the quantum entanglement and strong reciprocity. By using the paradigm of quantum game analysis, we obtain that both the quantum entanglement and strong reciprocity are helpful to intensify cooperation and achieving Pareto optimality. In addition, under an example which is greenhouse green viable planting industry, we verify that the quantum entanglement and strong reciprocity have a positive role in cooperation.

A physical scrutiny of experimental results published in Physical Review Letters (December 2015, M. Giustina, et al., Phys. Rev. Lett. 115, 250401, and L. K. Shalm et al., Phys. Rev. Lett. 115, 250402) is undertaken. These articles reported that measured outcomes were fitted with quantum states possessing a dominant component of non-entangled photons, thereby contradicting their own claim of quantum nonlocality. With probabilities of photon detections lower than 0.1 %, the alleged quantum nonlocality cannot be classified as a resource for developing quantum computing devices, despite recent publicity. Experimental evidence of a feasible process for quantum-strong correlations has been identified (M. Iannuzzi, et al., Phys. Lett. A, 384 (9), 126200, 2020) in terms of correlations between independent and multi-photon states evaluated as Stokes vectors on the Poincaré sphere. As single-photon sources are not needed, the design and implementation of quantum computing operations will be significantly streamlined.

Physics of high-Tc superconducting cuprates is obscured by the effect of strong electronic correlations. One way to overcome the problem is to seek for an exact solution at least within the small cluster and expand it to the whole crystal. Such an approach is in the heart of the cluster perturbation theory (CPT). Here we develop CPT for the dynamic charge and spin susceptibilities (spin-CPT), within which the correlation effects are explicitly taken into account by the exact diagonalization. We apply spin-CPT to the effective two-band Hubbard model for the cuprates obtained from the three-band Emery model and calculate one- and two-particle correlation functions, namely, spectral function and spin and charge susceptibilities. Doping dependence of the spin susceptibility was studied within spin-CPT and CPT-RPA that is the CPT generalization of the random phase approximation (RPA). Both methods produce the low energy response at four incommensurate wave vectors in qualitative agreement to the results of the inelastic neutron scattering on overdoped cuprates.

When applying deep learning methods to detect micro defects on low-contrast LCD surfaces, there are challenges related to the imbalance in samples dataset, as well as the complexity and laboriousness of annotating and acquiring target image masks. In order to solve these problems, a method based on sample and mask auto-generation for deep generative network models is proposed. We first generate an augmented dataset of negative samples using a generative adversarial network(GAN), and then highlight the defect regions in these samples using the training method constructed by the GAN to generate masks for the defect images automatically. Experimental results shows the effectiveness of our proposed method, as it allows for the simultaneous generation of LCD image samples and their corresponding image masks. Through a comparative experiment on the deep learning method Mask R-CNN, we demonstrate that the automatically obtained image masks have high detection accuracy.

The purpose of this study was to determine the income, costs and revenue of the Gontor Putri 3 bakery. Want to know the efficiency of the bakery business in Karangbanyu Regency. The method used in this research is analytical descriptive by conducting a survey. The data used in this research is primary data. Data collection techniques use observation, interviews and documentation, while the process of analysis is quantitative descriptive. Using the R/C ratio, a value of 1.72 per month is obtained. This value indicates that the bakery factory in Karangbanyu is efficient because the value is more than one.

Revenue-sharing (RS) contracts are a common approach to incentivize innovation of upstream suppliers by addressing the uneven profit distribution between upstream and downstream firms. Considering the possible overconfidence characterizing decision makers in the supply chain, we investigate the effect of the RS contract and the tendency of overconfidence of supply chain members on the investment in R&D of key components of products in the context of an upstream supplier that is the leader in the R&D and production of key components. We find that regardless of the bargaining power of either party, a RS contract can increase the R&D investment in key components. Regarding the effects of overconfidence of either downstream manufacturer or up-stream supplier, it can increase the R&D investment in key components. Supplier (manufacturer) overconfidence can harm their own profits but increase the profits of the manufacturer (supplier), and when the level of overconfidence is below a certain threshold, the damage to their own profits is less than the increase in each other's profits, thus benefiting the whole supply chain. In addition, we also find a joint effect of RS contracts and overconfidence: when the bargaining power of the supplier is low, the RS contract has a certain compensatory effect on the loss of their own profits caused by overconfidence.

The circular economy (CE) has emerged as a viable alternative for tackling the problems caused by rising consumption, including solid waste (SW). The present study conducted a meta-analysis of research published between 2012 and 2022 on CE and solid waste management (SWM). A bibliometric analysis was used from the Web of Science (WoS) and Scopus databases. By studying the articles, we briefly discussed the connections between them and how one contributes to the evolution of the other. Some findings point to greater collaboration between Italy and Bolivia, followed by China and Malaysia. However, they move away from the traditional axes as the United States and Canada. In addition, it was found that the adoption of reuse and selective collection, in fact, allow the reduction of the volume of discarded materials. In this way, it was possible to conclude that a greater connection between CE and GRS makes it possible to optimize the useful life of landfills through the treatment of organic waste and recycling, to encourage waste picker cooperatives and selective collection programs, and to reduce the financial costs of the system as a whole, making it more durable and sustainable.

Low-resource languages often face the problem of insufficient data, which leads to poor quality in machine translation. One approach to address this issue is data augmentation. Data augmentation involves creating new data by transforming existing data through methods such as flipping, cropping, rotating, and adding noise. Traditionally, pseudo-parallel corpora are generated by randomly replacing words in low-resource language machine translation. However, this method can introduce ambiguity as the same word may have different meanings in different contexts. This study proposes a new approach for low-resource language machine translation, which involves generating pseudo-parallel corpora by replacing phrases. The performance of this approach is compared with other data augmentation methods, and it is observed that combining it with other data augmentation methods further improves performance. To enhance the robustness of the model, R-Drop regularization is also used. R-Drop is an effective method for improving the quality of machine translation. The proposed method was tested on Chinese-Kazakh (Latin script) translation tasks, resulting in performance improvements of 4.99 and 7.7 for Chinese-to-Kazakh and Kazakh-to-Chinese translations, respectively.

The aim of this study, for determination of verteporfin in real samples (simulated body fluid, and simulated tears, 0.9% isotonic sodium chloride solution, Lactated Ringer IV solution for infusion, 5% dextrose IV solution for infusion, lemon juice and drinking water) was the method validation and to examined by HPLC-DAD-UV. Metod validation parameters such as specificity, linearity, precision, accuracy, robustness, limit of detection (LOD) and limit of quantitation (LOQ) for verteporfin were validated and developed according to the International Conference on Harmonization (ICH) Q2 R1 guidelines. The LOD and LOQ for verteporfin were found 0.06 µg/L and 0.2 µg/L, respectively. The recovery values of the optimization and validation for verteporfin were found in the range of 97.5-100.7%. The relative standard deviations (RSD) for vertepofin were <1%. The developed method was successfully applied to real samples with high accuracy and the recoveries (%) from real samples were 99.9, 100, 98.2, 99.2, 99.4, 98.8 and 99.4, respectively.

Crocodilepox virus (CRV) belongs to the Poxviridae family and mainly infects hatchling and juvenile Nile crocodiles. Most poxviruses encode inhibitors of the host antiviral protein kinase R (PKR), which is activated by viral double-stranded (ds) RNA formed during virus replication, resulting in the phosphorylation of eIF2 and subsequent shutdown of general mRNA translation. Because CRV lacks orthologs of known poxviral PKR inhibitors, we experimentally characterized one candidate (CRV157), which contains a predicted dsRNA-binding domain. Bioinformatic analyses indicated that CRV157 evolved independently from other poxvirus PKR inhibitors. CRV157 bound to dsRNA, co-localized with PKR in the cytosol, and inhibited PKR from various species. To analyze whether CRV157 could inhibit PKR in the context of a poxvirus infection, we constructed recombinant vaccinia virus strains that contain either CRV157 or a mutant CRV157 deficient in dsRNA binding in a strain that lacks PKR inhibitors. The presence of wild type CRV157 rescued vaccinia virus replication, while the CRV157 mutant did not. The ability of CRV157 to inhibit PKR correlated with virus replication and eIF2alpha phosphorylation. The independent evolution of CRV157 demonstrates that poxvirus PKR inhibitors evolved from a diverse set of ancestral genes in an example of convergent evolution.

In this article we have presented a new perception of herd immunity threshold (HIT) which considers that only a “band of population” are susceptible to any pathogenic infection. This is termed as the “effective herd immunity threshold” (EHIT) and the progression of the disease (caused by this pathogenic infection) is mainly determined by this EHIT value. We have argued here that this EHIT value (considering the immunity band picture in the population) will be substantially lower than the estimated canonical HIT values obtained from various existing models. We propose that the actual prediction of the disease progression should now be calculated using the EHIT values.

Inspired by the work of S. D. Odintsov and V. K. Oikonomou, Phys. Rev. D 92, 024016 (2015) [1], the present study reports a reconstruction scheme for f (R) gravity with the scale factor a(t) µ (t _* - t) _c²²describing the pre-bounce ekpyrotic contraction, where t is the big crunch time. The reconstructed f (R) is used to derive expressions for density and pressure contributions and the equation of state parameter resulting from this reconstruction is found to behave like "quintom". It has also been observed that the reconstructed f (R) has satisfied a sufficient condition for a realistic model. In the subsequent phase the reconstructed f (R) is applied to the model of chameleon scalar field and the scalar field f and the potential V(f) are tested for quasi-exponential ex pansion. It has been observed that although the reconstructed f (R) satisfies one of the sufficient conditions for realistic model, the quasi-exponential expansion is not available due to this reconstruction. Finally, the consequences pre-bounce ekpyrotic inflation i n f (R) gravity are compared to the background solution for f (R) matter bounce.

The crux of the paper is to present a detailed analysis of COVID-19 data which is available on global basis. This analysis is performed using some specific package of R software. It provides various insights from the data and help to understand the current status of this pandemic in India so that effective measures can be formulated by policymakers. These insights include global summary of this disease, growth rate of this pandemic and performance of SIR model for the given global data. The analysis has been presented in different tables and graphs to understand the outputs of the problem in a more detailed point of view.

Collisions of low energy electrons with molecules are important for understanding many aspects of the environment and technologies. Understanding the processes that occur in these types of collisions can give insights into plasma etching processes, edge effects in fusion plasmas, radiation damage to biological tissues and more. A radical update of the previous expert system for computing observables relevant to these processes, Quantemol-N, is presented. The new Quantemol Electron Collision (QEC) expert system simplifyies the user experience, improving reliability and implements new features. The QEC GUI interfaces the Molpro quantum chemistry package for molecular target setups and to the sophisticated UKRmol+ codes to generate accurate and reliable cross-sections. These include elastic cross-sections, super elastic cross-sections between excited states, electron impact dissociation, scattering reaction rates, dissociative electron attachment, differential cross-sections, momentum transfer cross-sections, ionization cross sections and high energy electron scattering cross-sections. With this new interface we will be implementing dissociative recombination estimations, vibrational excitations for neutrals and ions, and effective core potentials in the near future.

This paper introduces an application of R programming language for geostatistical data processing with a case study of the Mariana Trench, Pacific Ocean. The formation of the Mariana Trench, the deepest among all hadal oceanic depth trenches, is caused by complex and diverse geomorphic factors affecting its development. Mariana Trench crosses four tectonic plates: Mariana, Caroline, Pacific and Philippine. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. The methodology includes following steps. Firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology. Secondly, 25 cross-section profiles were drawn across the trench. The length of each profile is 1000-km. The attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. Finally, this table was processed by methods of the statistical analysis on R. The programming codes and graphical results are presented. The results include geospatial comparative analysis and estimated effects of the data distribution by tectonic plates: slope angle, igneous volcanic areas and depths. The innovativeness of this paper consists in a cross-disciplinary approach combining GIS, statistical analysis and R programming.

We present a methodology to enable users to interact with statistical information owned by an institution and stored in a cloud infrastructure. Mainly based on R, this approach was developed following the open-data philosophy. Also, since we use R, the implementation is mainly based on open-source software. R gives several advantages from the point of view of data management and acquisition, as it becomes a common framework that can be used to structure the processes involved in any statistical operation. This simplifies the access to the data and enable to use all the power of R in the cloud information. This methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to other institutions to enable open access to its data. The infrastructure also was deployed to a cloud infrastructure, to assure the scalability and a 24/7 access.

The exceptional increase in molecular DNA sequence data in open repositories is mirrored by an ever-growing interest among evolutionary biologists to harvest and use those data for phylogenetic inference. Many quality issues, however, are known and the sheer amount and complexity of data available can pose considerable barriers to their usefulness. A key issue in this domain is the high frequency of sequence mislabelling encountered when searching for suitable sequences for phylogenetic analysis. These issues include the incorrect identification of sequenced species, non-standardised and ambiguous sequence annotation, and the inadvertent addition of paralogous sequences by users, among others. Taken together, these issues likely add considerable noise, error or bias to phylogenetic inference, a risk that is likely to increase with the size of phylogenies or the molecular datasets used to generate them. Here we present a software package, phylotaR, that bypasses the above issues by using instead an alignment search tool to identify orthologous sequences. Our package builds on the framework of its predecessor, PhyLoTa, by providing a modular pipeline for identifying overlapping sequence clusters using up-to-date GenBank data and providing new features, improvements and tools. We demonstrate our pipeline’s effectiveness by presenting trees generated from phylotaR clusters for two large taxonomic clades: palms and primates. Given the versatility of this package, we hope that it will become a standard tool for any research aiming to use GenBank data for phylogenetic analysis.

Radar altimetry provides valuable measurements to characterize the state and the evolution of the Antartica and Greenland ice sheet cover. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential capacity of complementing the dedicated radar altimeters incrementing the temporal and spatial resolution of the surface height measurements. In this work we perform an study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission, designed primarily to provide sea state information, like sea surface roughness or wind, but not altimetric products. The data has been analyzed with altimetric methodologies, already proved in aircraft based experiments, to extract signal delay observables to be used to infer the topography of the Greenland cover. The penetration depth of the GNSS signals into ice has also considered. The topographic signal obtained is consistent with those obtained with other passive or active microwave sensors. The main conclusion derived from this work is that GNSS-R also provides valuable measurements of the ice sheet cover and, as taken at a variety of geometries and at least two frequency bands, they prospect different depths into the ice. They have thus potential to complement our understanding of the ice firn and its evolution.

Let N = N₀+ N₁+ N₂ be a Z₃-graded Novikov algebra. The main goal of the paper is to prove that over a field of characteristic not equal to 3 the algebra N is solvable if N₀ is solvable. We also show that a $Z_2$-graded Novikov algebra N=N₀+ N₂ over a field of characteristic not equal to 2 is solvable if N₀ is solvable. This implies that for every n of the form n=2^k3^l, any Z_n-graded Novikov algebra N over a field of characteristic not equal to 2,3 is solvable if N₀ is solvable.

A lot of research studies have been surveyed the completed genomes of prokaryotic and eukaryotic and focused on the correlation between the percentage of microsatellite sequences in completed genomes and the whole size of the organism genomes. There are fewer studies made in repetitive sequences otherwise simple sequence repeats or long tandem repeats of virus genomes. simple sequence repeats (SSRs) are the most important regions for recombination and moving repeats blocks from site to another site in the genomes. A tool was programmed and designed by visual basic 6.0 to find the long tandem repeats in DNA sequences of the small genomes. The tool named “Repeater Finder Regular Expression”, (RFRE) Version 1.0, 2016. The tool was utilized to discover different pattern of long tandem repeats (LTR) motifs on the completed genomes of human corona virus strains by using a joined regular expression language. In this study, a twenty-nine accession numbers of human coronavirus completed genomes, (hku1) strains were retrieved from the Genbank. The researcher can write a different regular expression patterns and joined regular expression patterns through the designed tool to search and find a specific motif of nucleotide sequences inside the complete genomes. The RFRE tool searched and found three different total lengths of a perfect long tandem repeats (240bp, 300bp and 480bp). A Dot plot gave a picture view for the long tandem repeat sequences in the completed genome sequence (KF430201.1) of human coronavirus. The genomic dot plot tool YASS was used as a genomic similarity searching tool to check for the uninterrupted repeats and confirm the sensitivity of the (RFRE) tool. To identify the recombination site in the genomes of human coronavirus the RAT tool was applied to find the recombination sites between the completed genomes of human corona viruses .The RAT tool recognized the recombination site in the nucleotide position (3012) and at the same time this recombination site position (3012) was also recognized as a beginning position of a long tandem repeat. A precise motif was predicted from the translated repeats of Human Corona Virus which found by PRATT tool. There was a relationship between the total length of long tandem repeats and genome size of Human Corona Virus and the correlation value R² was equal to (0,451). In conclusion, this study presented the importance of finding the long tandem repeats of human coronavirus and gives a relationship between the completed genome size of human coronavirus types and long tandem repeats. The nucleotide position (3012) was a hot spot site for a recombination among the complete genomes of human coronavirus and also identified as a repetitive site in the genomes of human corona virus (hku1). The repeats in human coronavirus (hku1) were predicated to be a main major role of virus evolution.

We consider Pisot family substitution tilings in $\R^d$ whose dynamical spectrum is pure point. There are two cut-and-project schemes(CPS) which arise naturally: one from the Pisot family property and the other from the pure point spectrum respectively. The first CPS has an internal space $\R^m$ for some integer $m \in \N$ defined from the Pisot family property, and the second CPS has an internal space $H$ which is an abstract space defined from the property of the pure point spectrum. However it is not known how these two CPS's are related. Here we provide a sufficient condition to make a connection between the two CPS's. In the case of Pisot unimodular substitution tiling in $\R$, the two CPS's turn out to be same due to [5, Remark 18.5].

We developed two human induced pluripotent stem cell (hiPSC)/human embryonic stem cell-specific glycan-recognizing mouse antibodies, R-10G and R-17F, using the Tic (JCRB1331) hiPSC line as an antigen. R-10G recognizes a low-sulfate keratan sulfate, and R-17F recognizes lacto-N-fucopentaose-1. To evaluate the general characteristics of stem cell glycans, we used the hiPSC line 201B7 (HPS0063), a prototype iPSC line. Using an R-10G affinity column, an R-10G-binding protein was isolated. The protein yielded a single but very broad band from 480 to 1,236 kDa by blue native gel electrophoresis. After trypsin digestion, the protein was identified as podocalyxin by liquid chromatography/mass spectrometry. According to Western blotting, the protein reacted with R-10G and R-17F. The R-10G positive band was resistant to digestion with glycan-degrading enzymes, including peptide N-glycanase, but the intensity of the band was decreased significantly by digestion with keratanase, keratanase II, and endo-β-galactosidase, suggesting the R-10G epitope to be a keratan sulfate. These results suggest that keratan sulfate-type epitopes are shared by hiPSCs. However, the keratan sulfate from 201B7 cells contained a polylactosamine disaccharide unit (Galβ1-4GlcNAc) at a significant frequency, whereas that from Tic cells consisted mostly of keratan sulfate disaccharide units (Galβ1-4GlcNAc(6S)). In addition, the abundance of the R-10G epitope was significantly lower in 201B7 cells than in Tic cells.

Nondipole terms in the atom-laser interaction arising due to the presence of a magnetic component in an electromagnetic wave and its inhomogeneity lead to nonseparability of the center-of-mass (CM) and electron variables in the neutral atom and, as a consequence, to its acceleration. We investigate this effect as well as the accompanying excitation and ionization processes for the hydrogen atom in strong (1012 - 2×1014 W/cm2) linearly polarized short-wavelength (5eV ≲ℏω≲ 27 eV) electromagnetic pulses of about 8 fs duration. The study has been carried out within the framework of a hybrid quantum-quasiclassical approach in which the coupled time-dependent Schrödinger equation for an electron and the classical Hamilton equations for the CM of an atom are simultaneously integrated. Optimal conditions with respect to the frequency and intensity of the electromagnetic wave for the acceleration of atoms without their noticeable ionization are found in the analyzed region.

We introduce a new variation on the domination theme which we call vertex domination as reducing waste of time in transportation planning and optimization of transport routes. We determine the vertex domination number $\gamma_v$ for several classes of fuzzy graphs. The bounds is obtained for it. In fuzzy graphs, monotone decreasing property and monotone increasing property are introduced. We prove both of the vizing's conjecture and the Grarier-Khelladi's conjecture are monotone decreasing fuzzy graph property for vertex domination. We obtain Nordhaus-Gaddum (NG) type results for these parameters. The relationship between several classes of operations on fuzzy graphs with the vertex domination number of them is studied. Finally, we discuss about vertex dominating set of a fuzzy tree by using the bridges and $\alpha$-strong edges equivalence.

The aim of this expository article is to present recent developments in the centuries-old discussion on the interrelations between several types of domination in graphs. However, the novelty even more prominent in the newly discovered simplified presentations of several older results. Domination can be seen as arising from real-world application and extracting classical results as first described by this article.The main part of this article, concerning a new domination and older one, is presented in a narrative that answers two classical questions: (i) To what extend must closing set be dominating? (ii) How strong is the assumption of domination of a closing set? In a addition, we give an overview of the results concerning domination. The problem asks how small can a subset of vertices be and contain no edges or, more generally how can small a subset of vertices be and contain other ones. Our work was as elegant as it was unexpected being a departure from the tried and true methods of this theory that had dominated the field for one fifth a century. This expository article covers all previous definitions. The inability of previous definitions in solving even one case of real-world problems due to the lack of simultaneous attentions to the worthy both of vertices and edges causing us to make the new one. The concept of domination in a variety of graphs models such as crisp, weighted and fuzzy, has been in a spotlight. We turn our attention to sets of vertices in a fuzzy graph that are so close to all vertices, in a variety of ways, and study minimum such sets and their cardinality. A natural way to introduce and motivate our subject is to view it as a real-world problem. In its most elementary form, we consider the problem of reducing waste of time in transport planning. Our goal here is to first describe the previous definitions and the results, and then to provide an overview of the flows ideas in their articles. The final outcome of this article is twofold: (i) Solving the problem of reducing waste of time in transport planning at static state; (ii) Solving and having a gentle discussions on problem of reducing waste of time in transport planning at dynamic state. Finally, we discuss the results concerning holding domination that are independent of fuzzy graphs. We close with a list of currently open problems related to this subject. Most of our exposition assumes only familiarity with basic linear algebra, polynomials, fuzzy graph theory and graph theory.

Acute intense exercise causes significant oxidative stress and consequently an increase in total antioxidant capacity; however, the mechanisms and combined effects of intense exercise and smoking on oxidative stress among active and non-active smokers are not clear. The aim of this study was to investigate the effect of acute intense exercise on antioxidant enzyme activity responses in active and non-active individuals exposed to cigarette smoke. The study included 40 subjects who were equally classified as: smokers that did exercise (SE), smokers that did not do exercise (SnE), non-smokers that did exercise (NSE), and non-smokers that did not do exercise (NSnE). The adjusted Astrand test was used to exhaust the subjects. Salivary enzymes of peroxidase (POX), catalase (CAT), and superoxide dismutase (SOD) were measured, by spectrophotometry methods, at 3 different time points: pre-test (TP1), post-test (TP2), and one hour after finishing the test (TP3). Significant (p<0.05) group x time interactions were found for the three enzymes. Salivary POX, CAT and SOD increased in all groups from TP1 to TP2 and decreased from TP2 to TP3. Only the NSE showed a significant difference between TP1 to TP3 in POX and SOD by +0.011 ± 0.007 and +0.075 ± 0.02 (U/ml), respectively. The NSE showed significantly higher levels of POX, CAT and SOD in TP2 compared to the other groups. Furthermore, NSE and NSnE had higher levels of POX, CAT and SOD in TP1 and TP3 (p<0.05) compared with SE and SnE. Only in the NSnE, were no differences observed in CAT compared with SE and SnE in TP3. These results showed that the antioxidant level at rest and in the recovery time after the acute intense exercise was lower in SE and SnE compared with NSE and NSnE, suggesting that smoking habit may reduce the ameliorating effect of regular physical activity on acute exercise-induced oxidative stress.

General characteristics of K changes together with their fine structure associated with ground flashes in Sri Lanka in the tropics are presented. It is found that on average there are about 2 K changes associated with each return stroke. Analysis of the fine structure of the K changes shows that the K change is a chaotic pulse burst. Some of these chaotic pulse bursts start and the others end as a regular pulse bursts. Sometimes the chaotic part occurs in between two regular pulse bursts. This is in agreement with the recent published results that claim that chaotic pulse bursts are a random superposition of regular pulse bursts. The results show that the small step fields identified in the literature as K changes are the static fields associated with these pulse bursts.

We investigate the impact of incoming nuclear data on the predictions of the neutron star (NS) stripping model for short gamma-ray bursts. The main area to which we pay attention is the NS crust. We show that the uncertain properties of the NS equation of state can significantly influence the stripping time tstr, the main dynamical parameter of the model. Based on the known time delay (tstr≈1.7s) between the peak of the gravitational wave signal GW170817 and the detection of gamma photons from GRB170817A, we obtain new restrictions on the nuclear matter parameters, in particular, the symmetry energy slope parameter: L&lt;114.5MeV. In addition, we study the process of nucleosynthesis in the outer and inner crusts of a low-mass NS. We show that the nucleosynthesis is strongly influenced by both the incoming nuclear data and the equation of state of the NS matter.

We analyze the behavior of relativistic spherical objects within the context of modified $f(R,T)$ gravity considering Tolman VI spacetime, where gravitational lagrangian is a function of Ricci scalar(R) and trace of energy momentum tensor(T) i.e,$ f(R,T)= R+ 2\beta T$, for some arbitrary constant $\beta$. For developing our model, we have chosen $\pounds_{m} = -p$, where $ \pounds_{m}$ represents matter lagrangian. For this investigation, we have chosen three compact stars namely PSR J1614-2230 [Mass=(1.97$\pm$ 0.4)M$_\odot$; Radius= 9.69$_{-0.02} ^{+0.02}$ Km] ,Vela X-1 [Mass=(1.77$\pm$ 0.08)M$_\odot$; Radius= 9.560$_{-0.08} ^{+0.08}$ Km] and 4U 1538-52 [Mass=(9.69)M$_\odot$; Radius= 1.97 Km]. In this theory the equation of pressure isotropy is identical to standard Einstein's theory. So all known metric potential solving Einstein's equations are also valid here. In this paper, we have investigated the effort of coupling parameter ($\beta$) on the local matter distribution. Sound of speed and adiabatic index are higher with grater values of $\beta$ while on contrary mass function and gravitational redshift are lower with higher values of $\beta$ . For supporting the theoretical results, graphical representation are also employed to analyze the physical viability of the compact stars.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

It is a common practice to detect outliers in a financial time series in order to avoid the adverse effect of additive outliers. This paper investigated the performance of GARCH family models (sGARCH; gjrGARCH; iGARCH; TGARCH and NGARCH) in the presence of different sizes of outliers (small, medium and large) for different time series lengths (250, 500, 750, 1000, 1250 and 1500) using root mean square error (RMSE) and mean absolute error (MAE) to adjudge the models. In a simulation iteration of 1000 times in R environment using rugarch package, results revealed that for small size of outliers, irrespective of the length of time series, iGARCH dominated, for medium size of outliers, it was sGARCH and gjrGARCH that dominated irrespective of time series length, while for large size of outliers, irrespective of time series length, gjrGARCH dominated. The study further leveled that in the presence of additive outliers on time series analysis, both RMSE and MAE increased as the time series length increased.

GNSS have been widely used in navigation, positioning and timing. Nowadays, the multipath errors previously considered detrimental may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), e.g. GPS- Multipath Reflectometry (GPS-MR). In this paper, a new element describing bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model linking the GPS observables (SNR, phase and pseudorange) with detailed vegetation parameters, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that wheat will decrease the amplitudes of GPS multipath observables, if we increase the vegetation moisture contents or the scatters sizes (stem or leaf), the amplitudes of GPS multipath observables (SNR, phase and code) decrease. Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with published results for environmental parameter detections with GPS-MR.

The idea of strong and weak adjacencies between vertices has been generalized into fuzzy graphs and intuitionistic fuzzy graphs (IFGs) and it is an important part of making decisions. However, one or two membership degrees are not always sufficient for making decisions on real-world problems that need an answer of types “yes, neutral, and no". Consequently, in previous work, we generalized the concept into picture fuzzy graphs (PFGs) where each element in the PFG has membership, neutral, and non-membership degrees. Moreover, we constructed the notion of the coloring of PFGs based on strong and weak adjacencies between vertices. In this paper, we investigate some properties of the chromatic number of PFGs based on the concept of strong and weak adjacencies between vertices. According to the properties, we construct an algorithm to find the chromatic number of PFGs. The algorithm is usefull when we work with large PFGs. Further, we improve the method to implement the PFG’s coloring for determining traffic signal phasing at an intersection. A case study has also been done to evaluate the method.

In this work we report recent theoretical calculations of a superconducting island in a strong vortex confinement regime. The obtained results reveal the evolution of superconducting condensate as a function of electron mean-free path (l) with the evolution of an applied magnetic field H0. The results of this study provide an insight about the emergent superconducting properties under such conditions, using the Ginzburg-Landau numerical simulations where spatial variation of thickness d on island, omnipresent in these kind of structures grown on Si (111), is taken into account. These results offer a new route to tailor superconducting circuits by using the controlled bombardment, in order to explore the impact on vortex distribution, phase of order parameter, number of vortices, free energy and the first H1 and second critical field H2.

We present simple relations for nuclear stability and nuclear binding energy with respect to three gravitational constants associated with electroweak, strong and electromagnetic interactions.

In this note we consolidate and give a brief description of several recently published results in ring theory having disproof. These results have been published during 2016 to 2021 in the so called non-predatory reputed mathematical journals indexed in the well known database like Scopus. We have considered results on rings in which each element is a sum of two idempotents appeared in Canad. Math. Bull. (2016), weakly tripotent rings appeared in Bull. Korean Math. Soc. (2018) and Rendiconti Sem. Mat. Univ. Pol. Torino (2021), involution t-clean rings appeared in Eur. J. Pure Appl. Math (2022) and strongly 2-nil clean rings with units of order two appeared in Eur. J. Pure Appl. Math (2023).

Since its initial development in the 1970’s by Phil Burke and his collaborators, the R-matrix theory and associated computer codes have become the de facto approach for the calculation of accurate data for general electron-atom/ion/molecule collision and photoionization processes. The use of a non-orthonormal set of orbitals based on B-splines, now called the B-spline R-matrix (BSR) approach, was pioneered by Zatsarinny. It has considerably extended the flexibility of the approach and improved particularly the treatment of complex many-electron atomic and ionic targets, for which accurate data are needed in many modelling applications for processes involving low-temperature plasmas. Both the original R-matrix approach and the BSR method have been extended to the interaction of short, intense electromagnetic (EM) radiation with atoms and molecules. Here we provide an overview of the theoretical tools that were required to facilitate the extension of the theory to the time domain. As an example of a practical application, we show results for two-photon ionization of argon by intense short-pulse extreme ultraviolet radiation

. Background: regular exercise elicits adaptive changes from several organs and physiological processes, including erythrocyte properties. Methods: in a group of 79 subjects (62 men and 17 women; mean age 31.37 +/- 10.19 years) who trained several times a week as they practiced amateur sports, we evaluated the elongation index, marker of erythrocyte deformability, the red blood cell distribution width (RDW), indicator of erythrocyte anisocytosis, hematocrit, hemoglobin and the main erythrocyte indices (MCV, MCH, MCHC) in basal conditions. Results: in comparison with a group of healthy not trained volunteers, the values of the elongation index, and not the RDW, are increased and this datum is accompanied by an increase of MCV and MCHC, likely related to an increased presence of circulating young erythrocytes in trained subjects. We also divided the same group according to the median of the VO2max, observing that the subgroup above the median shows both an increase in the elongation index values and a decrease in MCH and MCHC. Conclusions: in trained subjects there is no correlation between the values of elongation index and the RDW, while of particular interest and of a certain complexity seem the interrelations among elongation index, RDW and the main erythrocyte indices.

Background: Sickle cell disease (SCD) is a public health problem in the Democratic Republic of Congo. While reference sickle cell centers have been implemented in capital cities of African countries and have proven to be beneficial for SCD patients, they have never been set up in rural areas for families with very low sources of income. Method: A cohort of 143 children with SCD aged 10 years old (IQR (interquartile range): 6–15 years) (sex ratio male/female = 1.3) were clinically followed for 12 months without any specific intervention aside from the management of acute events, and then for 12 months with a monthly medical visit, biological follow-up, and regular prophylaxis. Results: The median age of patients at the diagnosis of SCD was 2 years (IQR: 1–5). The implementation of standardized and regular follow-ups in a new sickle cell referral center in a remote city showed an increase in the annual mean hemoglobin level from 50 to 70 g/L (p = 0.001), and a decrease in the lymphocyte count and spleen size (p < 0.001). A significant decrease (p < 0.001) in the average annual number of hospitalizations and episodes of vaso-occlusive crises, blood transfusions, infections, and acute chest syndromes were also observed. Conclusions: Creation of a sickle cell referral center and the regular follow-up of children with SCD are possible and applicable in the context of a remote city of an African country and represent simple and accessible measures that can reduce the morbimortality of children with sickle cell disease.

This article explores the relationship between convex functions defined on integers ($\mathbb{Z}$) and their extension to real numbers ($\mathbb{R}$). We introduce key definitions and investigate the hypothesis that there exists a unique convex curve within this family of functions, leading to a proof by contradiction. Our findings highlight the preservation of convexity as functions transition from integers to real numbers.

Disgust evolved as a way to protect one’s self from illness. DS-R measures disgust propensity of three kinds of disgust (Core, Animal Reminder and Contamination). Although the DS-R scale was refined mainly with young and largely female student population its impact on educational orientation has not been assessed. In the present study we examined the DS-R scoring and the choice of postgraduate studies in medical (n= 94) and psychology (n= 97) students. They responded to an anonymous web-based survey and completed the DS-R and a questionnaire on their demographics and plans for postgraduate studies. Female students outnumbered males (3:1) and scored higher in Total DS-R score (median: 59 vs. 50, p<0.05). Psychology students scored higher in all three kinds of disgust (p<0.05), indicating a higher level of disease avoidance. Medical students willing to follow Internal Medicine scored higher in Core Disgust (p<0.05) while psychology students willing to study Experimental Psychology scored lower in Animal Reminder subscale (p<0.001). Also, the higher the psychology students scored in Core Disgust scale the higher was the probability to choose Experimental Psychology. In conclusion, disgust propensity as rated by DS-R differentiates medical from psychology students and is also related to orientation preferences in postgraduate studies.

We propose an electrocardiogram (ECG) signal-based algorithm to estimate the respiratory rate is a significant informative indicator of physiological state of a patient. The consecutive ECG signals reflect the information about the respiration because inhalation and exhalation make transthoracic impedance vary. The proposed algorithm extracts the respiration-related signal by finding out the commonality between the frequency and amplitude features in the ECG pulse train. The respiration rate can be calculated from the principle components after the procedure of the singular spectrum analysis. We achieved 1.7569 breaths per min of root-mean-squared error and 1.7517 of standard deviation with a 32-seconds signal window of the Capnobase dataset, which gives notable improvement compared with the conventional Autoregressive model based estimation methods.

The development of integrated, compact, and multifunctional photonic circuits is crucial to increase the capacity of all-optical signal processing for communications, data management or microsystems. Plasmonics brings compactness to numerous photonic functions, but its integration into circuits in not straightforward due to insertion losses and poor modes matching. The purpose of this article is to detail the integration strategies of plasmonic structures on dielectric waveguides, and to show through some examples the variety and the application prospect of integrated plasmonic functions.

Ship pilots and maritime safety administration have an urgent need for more accurate and earlier warnings on strong wind gusts. This study firstly investigates the “Oriental Star” cruise ship cap-sizing event in 2015, one of the deadliest shipwreck events in recent years, and explores all related hydro-meteorological components in a global mesoscale model. It is found that, rather than the missing signal in raw surface wind prediction, the cumulus precipitation variable (CP) increases dramatically during the accident occurrence, which significantly corresponds to the sub-grid strong wind gust. The effective lead-time can be extended from 24hr (deterministic model) to 48hr (en-semble model). This finding is then verified in another two recent deadly cruise boat accidents. The introduction of the new variable is bearing the hope of improvement to the current maritime safeguard system, on predicting sub-grid strong wind gusts for small-size cruise boats in offshore and inland rivers. Finally, an automatic-response system is developed to provide economical con-vection prediction via Inmarsat email communication, aiming to explore operational severe con-vective gust early-warning and appropriate numerical mesoscale model application.

In an historic perspective on the development of the Standard Model of particle physics it is shown how mathematically driven axioms have masked the merits of a physically comprehensible structural view. It is concluded that the difference between the two approaches can be traced back to two major issues. Whereas in the Standard Model the quark is a Dirac particle with a single real dipole moment, the quark in the structural model, in confinement with other quarks, is a Dirac particle with two real dipole moments. The second issue is the view that empty space does not exist, but that space is filled with a polarisable energetic fluid. It is shown how recognition of these two issues pave a road to reconcile particle physics with gravity, in which the quark can be seen as a magnetic electron and in which the gluon, as the strong force carrier, can be seen as a massive photon.

We report the strong coupling between plasmonic surface lattice resonances (SLRs) and photonic Fabry-Pérot (F-P) resonances in a microcavity embedded with two-dimensional periodic array of metal-insulator-metal nanopillars. For such a plasmonic-photonic system, we show that the SLR can be strongly coupled to the F-P resonances of both the odd- and even orders, and that the splitting energy reaches as high as 138 meV in the visible regime. We expect that this work will provide a new scheme for strong coupling between plasmonic and photonic modes.

The study shows that the volumes and surfaces of $n$-balls, $n$-simplices, and $n$-orthoplices are holomorphic functions of $n$, which makes those objects omnidimensional, that is well defined in any complex dimension. Applications of these formulas to the omnidimensional polytopes inscribed in and circumscribed about $n$-balls reveal previously unknown properties of these geometric objects. In particular, for $0 < n < 1$, the volumes of the omnidimensional polytopes are larger than those of circumscribing $n$-balls, and both their volumes and surfaces are smaller than those of inscribed $n$-balls. The surface of an $n$-simplex circumscribing unit diameter $n$-ball is spirally convergent to zero with real $n$ approaching negative infinity but first has a local maximum at $n=-3.5$. The surface of an $n$-orthoplex circumscribing unit diameter $n$-ball is spirally divergent with real $n$ approaching negative infinity but first has a local minimum at $n=-1.5$, where its real and imaginary parts are equal to each other; similarly, as its volume, where the similar local minimum occurs at $n=-3.5$. Reflection functions for volumes and surfaces of these polytopes inscribed in and circumscribed about $n$-balls are proposed. symmetries of products and quotients of volumes in complex dimensions $n$ and $-n$ and of surfaces in complex dimensions $n$ and $2-n$ are shown to be independent of the metric factor and the gamma function. Specific symmetries also hold between volumes and surfaces in dimensions $n = -1/2$ and $n = 1/2$.

With our long experience in the field of unification of gravity and quantum mechanics, we understood that, when mass of any elementary is extremely small/negligible compared to macroscopic bodies, highly curved microscopic space-time can be addressed with large gravitational constants and magnitude of elementary gravitational constant seems to increase with decreasing mass and increasing interaction range. In our earlier publications, we proposed that, 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions; 2) There exists a strong interaction elementary charge in such a way that, it's squared ratio with normal elementary charge is close to inverse of the strong coupling constant; and 3) Considering a fermion-boson mass ratio of 2.27, quarks can be split into quark fermions and quark bosons. Further, we noticed that, electroweak field seems to be operated by a primordial massive fermion of rest energy 584.725 GeV and hadron masses seem to be generated by a new hadronic fermion of rest energy 103.4 GeV. In this context, starting from lepton rest masses to stellar masses, we have developed many interesting and workable relations. With further study, a workable model of final unification can be developed.

Here we evaluate the chemistry of mineral soil solutions collected by suction lysimeters in a small mountain catchment that was affected by acidification-related spruce die-back. The aim was to obtain new insights into spatial patterns of nutrient partitioning during acidification recovery. This was achieved by comparing nutrient concentrations in soil solutions, collected along a V-shaped valley, with those in runoff. Five nests of suction lysimeters were installed in the 33-ha UDL catchment at different topographic positions (hilltops, slopes and valley). Following a 1-year equilibration, monthly samples of soil solutions were collected over a 2-year period. In the vicinity of each lysimeter nest, soil pits were excavated for a study of soil chemistry. Soil solutions were analyzed for SO42-, NO3-, DOC, NH4+, Na+, K+, Ca2+, Mg2+, and total dissolved Al concentrations, DOC and pH. For a P release estimation, ammonium oxalate extraction of soil samples was performed. Comparison of soil water data from this study with other European studies indicated that major environmentally relevant chemical species at UDL had concentrations similar to median concentrations across numerous previously acidified sites. CEC (≤ 58 meq kg-1) and BS (≤ 13 %), however, were significantly lower at UDL than at other European sites, documenting incomplete recovery from acidification. Spatial trends and seasonality in soil water chemistry support belowground inputs from mineral-stabilized legacy pollutants and soil nutrients. Seasonal variability of soil water sulfate and nitrate was significant. High nitrate in soil solutions during summer originated during the preceding dormant season, and high sulfate concentrations observed during the winter originating from recycled organic S during the summer. Higher concentrations of SO42-, NO3-, and base cations in runoff than in soil solutions may be explained by lateral surficial runoff leaching pollutants and nutrients from very shallow soil horizons. Nearly 30 years after peak acidification, solutions in mineral subsoil at UDL exhibited similar concentrations of SO42-, Ca2+ and Mg2+ as median values at the Pan-European International Co-operative Program (ICP) Forest sites, yet NO3- concentrations were an order of magnitude higher than the ICP sites. Calcium applied on soil surface by liming 32 to 11 years ago affected runoff more than soil solutions, suggesting contribution of both shallow soil water and groundwater to runoff.

In this paper, a kind of single-walled carbon nanotube nonlinear model is developed, and the strongly nonlinear dynamic characteristics of such carbon nanotubes subjected to random magnetic field are studied. The nonlocal effect of microstructure is considered based on the theory of nonlocal elasticity. The natural frequency of the strongly nonlinear dynamic system is obtained by the energy function method, the drift coefficient and the diffusion coefficient are verified. The stationary probability density function of the system dynamic response is given and the fractal boundary of the safe basin is provided. Theoretical analysis and numerical simulation show that stochastic resonance occurs when varying the random magnetic field intensity. The boundary of safe basin has fractal characteristics and the area of safe basin decreases when the intensity of the magnetic field permeability increases.

We introduce a special vector field ω on a Riemannian manifold (N^m, g), such that the Lie derivative of the metric g with respect to ω is equal to ρRic, where Ric is the Ricci curvature of (N^m, g) and ρ is a smooth function on N^{m} and call this vector field a ρ-Ricci vector field. We use ρ-Ricci vector field on a Riemannian manifold (N^m, g) and find two characterizations of m-sphere S^m(α). In first result, we show that an m-dimensional compact and connected Riemannian manifold (N^m, g) with nonzero scalar curvature admits a ρ-Ricci vector field ω such that ρ is nonconstant function and the integral of Ric(ω,ω) has a suitable lower bound is necessary and sufficient for (N^m, g) to be isometric to m-sphere S^m(α). In second result, we show that an m-dimensional complete and simply connected Riemannian manifold (N^m, g) of positive scalar curvature admits a ρ-Ricci vector field ω such that ρ is a nontrivial solution of Fischer-Marsden equation and the squared length of the covariant derivative of ω has an appropriate upper bound, if and only if, (N^m, g) to be isometric to m-sphere S^m(α).

Bone Scan Index (BSI) is an image biomarker for quantification on bone metastasis of cancers. To compute BSI, not only the hotspots (metastasis) but also the bones have to be segmented. Most related researches focus on binary classification on bone scintigraphy: having metastasis or none. Rare studies focus on pixelwise segmentation. In this study we compare three advanced convolutional neural network (CNN) based models to explore the bone segmentation on dataset in house. The best model is Mask R-CNN, which reaches the precision, sensitivity and F1-score: 0.93, 0.87, 0.90 for prostate cancer patients and 0.92, 0.86, 0.88 for breast cancer patients, respectively. The results are the average of 10-fold cross-validation, which reveals the reliability for clinical use on bone segmentation.

In the first part of this article, we discuss and generalize the complete convergence introduced by Hsu and Robbins (1947) to the r-complete convergence introduced by Tartakovsky (1998). We also establish its relation to the r-quick convergence first introduced by Strassen (1967) and extensively studied by Lai (1976). Our work is motivated by various statistical problems, mostly in sequential analysis. As we show in the second part, generalizing and studying these convergence modes is important not only in probability theory but also to solve challenging statistical problems in hypothesis testing and changepoint detection for general stochastic non-i.i.d. models.

In this paper, we investigated the trajectory of the massive particle in the vicinity of a general spherical symmetric black hole. Also, in the framework of general sphericalily symmetric black hole, Pseudo-Newtonian potential (PNP) and effective potentials has been investigated. As an example, static spherically symmetric black hole in f(R) gravity is considered and presented the brief discussion on the structure of spacetime and horizons. We calculated energy and angular momentum in the framework of general relativity as well as in Pseudo-Newtonian theory. A graphical comparison of angular momentum in this both framework has been studied.

Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires’ fast spread in the early stage. NOAA’s geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection. However, advanced processing algorithms are needed to provide timely and reliable detection of wildfires. In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series data. GRU model maintains good performance on temporal modelling while keep a simple architecture, makes it suitable to efficiently process time-series data. 36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The detection times based on GOES-R are compared with VIIRS active fire products at 375m resolution in NASA’s Fire Information for Resource Management System (FIRMS). The results show that GRU-based GOES-R detections of the wildfires are earlier than that of the VIIRS active fire products in most of the study areas. Also, results from proposed method offer more precise location on the active fire at early stage than GOES-R Active Fire Product in mid-latitude and low-latitude regions.