As for their large surface area and pore volume, three-dimensional covalent organic frameworks (3D COFs) have emerged as competitive porous materials. However, due to the structural dynamic behavior particularly for imine-linked 3D COFs, potentially unlock their potential for gas storage application. Herein, we showed a pre-locked linker strategy introduces breaking dynamic behavior in 3D COFs. A predesigned planar linker based 3,8-diamino-6-phenylphenanthridine (DPP) was prepared to produce non-dynamic 3D JUC-595, as benzylideneamine moiety in DPP locked the linker flexibility and restrict the molecular-bond rotation of the imine linkages. Upon solvent inclusion and release, the PXRD profile of JUC-595 remained intake, while JUC-594 with flexible benzidine linker experienced crystal transformation due to framework contraction-expansion. As a result, the activated JUC-595 achieved higher surface areas (754 m² g-1) than that of JUC-594 (548 m² g-1). Furthermore, improved CO2 and CH4 storages were also seen in JUC-595 compared with JUC-594. Impressively, JUC-595 recorded high normalized H2 storage capacity that surpass other reported high surface area 3D COFs. This works shows important insight on manipulating structural properties of 3D COF to tune the gas storage performance.

The study aims to explain the different effects between the multiplication, addition, division and subtraction equations. In this sense, multiplication and addition equations develop a new element or fact, meanwhile, division equations express information within the element or fact, subtraction is the selection of element or fact. Furthermore, for a multiplication and addition equation results in the new element or fact, it is necessary to depend on specific physical concepts, without extreme alteration, as it would result in the alteration of the element or fact. It is worth highlighting the importance of fixed values ​​in the equation to describe the specific nature of the element or fact. The study makes it possible to understand open equations (without solutions) in mathematics and physics, in addition to understanding existing equations. The study makes reference to the theory of obligatory necessity and the theory of differences between elements.

Countless disasters have resulted from climate change, causing severe damage to infrastructure and the economy. These disasters have significant societal impacts, necessitating mental health services for the millions affected. To prepare for and respond effectively to such events, it is crucial to understand people's emotions and the life incidents they experience both before and after a disaster strikes. In this case study, we mined the emotions and life incidents expressed on Twitter during the 2017 Hurricane Harvey. Between August 20 and August 30, we collected a dataset of approximately 400,000 public tweets related to the storm. Using a BERT-based model, we predicted the emotions associated with each tweet. Following emotion prediction, we applied various natural language processing techniques to analyze the content of the tweets, aiming to uncover the 'topics' discussed alongside specific 'emotions.' To efficiently identify these topics, we utilized the Latent Dirichlet Allocation (LDA) technique for topic modeling, which allowed us to bypass manual content analysis and extract meaningful patterns from the data. However, rather than stopping at topic identification, we further refined our analysis by integrating Graph Neural Networks (GNN) and Large Language Models (LLM). The GNN was employed to generate embeddings and construct a similarity graph of the tweets, which was then used to optimize clustering. This step ensured that related tweets were accurately grouped together based on their content and context. Subsequently, we used an LLM to automatically generate descriptive names for each event cluster. This advanced approach allowed us to identify and label life incidents automatically, providing a nuanced understanding of the key issues faced by the community during the hurricane. The results revealed significant emotional shifts as the hurricane reached its most devastating phase. These shifts coincided with pressing concerns and demands from the population, such as evacuation plans, animal safety, safety updates, public policy, help requests, flood impacts, and the spread of fake news. By combining GNN and LLM for automatic event name prediction, our study not only mapped out the emotions but also accurately categorized the specific life incidents that were most relevant during the disaster, offering critical insights for disaster preparedness and response strategies.

Abstract Using the Pauli algebra version of the Dirac equation six symmetric but non-equivalent copies of the QED Lagrangian are constructed. The group of symmetries is the group of outer automorphisms of the finite quaternion group, isomorphic to the group of permutations on three letters. Solutions to corresponding Dirac equations form six sectors of fermion fields. The intersections between different sectors can only contain massless fields, implying that the sectors are distinct. If the symmetry could be extended to the full Standard Model Lagrangian it would predict the ratio of dark matter to ordinary matter of 5 : 1 which is close to the ratio of 5.2 : 1 according to current observations.

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.

The nucleon-pair shell model (NPSM) with broken symmetry basis is studied. The results demonstrate the validity of NPSM with symmetry broken basis, which leads to a significant reduction in the dimensionality of the multi-pair configuration space. We have observed that the axial-deformed basis provides a satisfactory description of the low-lying spectrum, even without the need for the projection procedure. In the case of the triaxial-deformed basis, we have investigated the variation after angular momentum projection, indicating the potential for NPSM to find exact solutions in the half-closed system.

Quantum effects arising from manifestly broken time-reversal symmetry are investigated using time-dependent perturbation theory in a simple model. The forward time and the backward time Hamiltonians are taken to be different and hence the forward and backward amplitudes become unsymmetrical and are not complex conjugates of each other. The effects vanish when the symmetry breaking term is absent and ordinary quantum mechanical results such as Fermi Golden rule are recovered.

In this paper we consider Changhee polynomials of type two, which are motivated from the recent work of Kim and Kim. We investigate some symmetry identities for the Changhee polynomials of type two which are derived from the properties of symmtery for the fermionic p-adic integral on Zp.

This study presents a comparative analysis of length deformation in Classical and Relativistic Mechanics, specifically investigating 10-gram objects accelerating to 1% of the speed of light. By employing Hooke's Law in Classical Mechanics and the Relativistic Lorentz Factor, the research explores the implications of acceleration dynamics and the limitations inherent in Relativistic Mechanics. The results reveal significant differences in predicted length changes between the two frameworks, emphasizing the necessity of considering relativistic effects beyond velocity alone. This study underscores the critical importance of addressing the incomplete treatment of acceleration dynamics in Relativistic Mechanics to achieve a more accurate depiction of length deformation in high-speed scenarios.

The classification and summarization of online reviews using machine learning and deep learningbased approaches are the subject of this systematic literature review. Consumers, companies, and researchers can now find vital information from online reviews. Automatically categorizing and summarizing these reviews can offer useful information and facilitate decision-making. The purpose of this study is to offer a thorough overview of the current methodology, approaches, and developments in this area. The review concentrates on machine learning-based methods for categorization and summarizing tasks, highlighting their advantages, drawbacks, and new developments. This systematic review provides insights into the most recent methodologies and indicates prospective directions for further investigation by synthesizing the data from a wide range of pertinent research publications

We elucidate the versatility of intriguing symmetry and asymmetry phenomena outside and inside black holes. For description of the test particle (planet and photon) motion it is used the Kerr-Newman metric of the rotating and electrically charged black hole. In particular, it is demonstrated the symmetry and asymmetry of the one-way Einstein-Rosen bridge inside black hole toward and through the plethora of endless and infinite universes.

We establish a new Gagliardo-Nirenberg inequality characterized by radial symmetry and involving potentials exhibiting pure power polynomial behaviour. As an application of our result, we investigate the existence of extremals for this inequality, which also correspond to stationary solutions for the nonlinear Schrödinger equation with inhomogeneous nonlinearity, competing with Hs-subcritical nonlinearities, either of local or non-local nature.

In physics, symmetry is mostly about the symmetry between elementary particles, between matter and antimatter. In the universe, we have two fundamental types of energy: energy of matter and energy of space. These two energies have a symmetry that is not geometry type, not electric charge type, it is energy type. Every physical object with mass m symmetrically diminishes the energy density of space in its center exactly for the amount of its mass. This symmetry of matter and space energies is the physical source of gravity that is also valid in the centre of black holes.

Intermittent claudication (IC) is the most common symptom of peripheral artery disease (PAD). IC affects the quality of life and results in marked exercise intolerance and limitation to daily activities with increased risk of cardiovascular complications. Exercise training is the first line of conservative management in PAD. However, patients with IC Patient cannot tolerate exercise because of leg discomfort induced by physical effort. This review will address alternative rehabilitation strategies to reduce exercise limitations and improve exercise tolerance in patients with IC.

Abstract: Social media has become a vital tool in ensuring productivity among Undergraduates, as studies have shown an increased number of users globally. This study assessed the impact of social media usage on undergraduates’ academic performance and working memory. Participants from three different universities such as the University of Georgia (UG), Eastern European University (EEU), and Batumi State University (BSU) completed this study using online google forms. UG and EEU are in the capital city, and BSU is in Batumi City. The study questionnaires were approved by the institutional review board before the data collection. Descriptive analyses were assessed for all study populations, characteristics, frequencies, percentages, means, and standard deviations using Statistical Package for Social Science (SPSS Inc., Chicago, IL, version 25.0 for Windows) software. 41.3% were male students, as most of the participants were foreign students living and studying in Georgia. Male students had the risk of ‘conflict’ with families and friends because of social media. Female students are at increased risk of using social media as an ‘escape’ from negative feelings. 89.7% of students that perform physical activities, considering their academic workload had the risk of preoccupation complaints. 87.9% felt dissatisfied regularly because they wanted to spend more time on social media. Utilization of social media differed based on the characteristics of the participants such as age, gender, and geography. We observed the increase in prevalence of social media addiction, its effect on academic performance and working memory among undergraduate students.

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.

Recent observations of the dark energy density demonstrates the fine-tuning problem and challenges in theoretical modelling. In this study, we apply the self-similar symmetry (SSS) model, describing the hierarchical structure of the universe based on the Dirac large numbers hypothesis, to Einstein's cosmological term. We introduce a new similarity dimension, D_B, in the SSS model. Using the D_B SSS model, the cosmological constant, vacuum energy density, and Hubble parameter can be simply expressed as a function of the cosmic microwave background (CMB) temperature. We show that the initial value of the vacuum energy density at the creation of the universe is ρ₀ = 1/8πα_f⁶, where α_f is the fine structure constant. The results indicate that the CMB is the primary factor for the evolution of the universe, providing a unified understanding of the problems of naturalness.

In the past decade, targeted therapies for solid tumors, including non-small cell lung cancer (NSCLC), have advanced significantly, offering tailored treatment options for patients. However, individuals without targetable mutations pose a clinical challenge, as they may not respond to standard treatments like immune-checkpoint inhibitors (ICIs) and novel targeted therapies. While the mechanism of action of ICIs seems promising, the lack of a robust response limits their widespread use. Although the expression levels of programmed death ligand 1 (PD-L1) on tumor cells are used to predict ICI response, identifying new biomarkers, particularly those associated with the tumor microenvironment (TME), is crucial to address this unmet need. Recently, inflammatory cytokines such as interleukin-1 beta (IL-1β) have emerged as a key area of focus and hold significant potential implications for future clinical practice. Combinatorial approaches of IL-1β inhibitors and ICIs may provide a potential therapeutic modality for NSCLC patients without targetable mutations. In this review, we discuss the role of IL-1β in NSCLC, its involvement in inflammatory pathways, and explore its potential role in the treatment of NSCLC.

In this work, we study the dynamical behaviors of the electromagnetic fields and material responses in the hyperbolic metamaterial consisting of periodically arranged metallic and dielectric layers. The thickness of each unit cell is assumed to be much smaller than the wavelength of the electromagnetic waves, so the effective medium concept can be applied. When electromagnetic (EM) fields are present, the responses of the medium in the directions parallel to and perpendicular to the layers are like that of Drude and Lorentz media, respectively. We derive the energy density of the EM fields and the power loss in the effective medium based on Poynting theorem and the dynamical equations of the polarization field. We also show that the Lagrangian density of the system can be constructed. The Euler-Lagrangian equations yield the correct dynamical equations of the electromagnetic fields and the polarization field in the medium. The canonical momentum conjugates to every dynamical field can be derived from the Lagrangian density via differentiation or variation with respect to that field. We apply Legendre transformation to this system, and find that the resultant Hamitonian density is identical to the energy density, up to an irrelevant divergence term.

Recently, a new theory based on superluminal tunnelling has been proposed to explain the transition of highly energetic neutrinos propagating in matter to tachyonic states. In this work, we determine the possible mechanisms that lead neutrinos into a superluminal realm based on the assumption that ultrarelativistic particles travelling in matter lose part of their energy with the emission of Bremsstrahlung radiation. The obtained photons, in turn, can create neutrino-antineutrino pairs, one or both of which can be superluminal. We also prove that pair creation may occur with neutrino flavour oscillation provided that only one of them is a space-like particle. This suggests that mass oscillation and superluminal behaviour could be related phenomena. Finally, using the generalised Lorentz transformations, we formulate the Lagrangian of the kinematically allowed scattering processes. The structure of this Lagrangian is consistent with the formalism of the Standard Model. Based on this Lagrangian, at least one of the particles forming the pair must always be subluminal. The possibility that the pair creation process is mediated by a dark photon is also discussed.

We review some properties of a relativistic classical massless charged particle with spin interacting with an external electromagnetic field. We give in particular a proper definition of kinetic energy and total energy, the latter being conserved when the external field is stationary. We find that the particle’s velocity may differ from c as a result of the spin - electromagnetic field interaction, without jeopardizing Lorentz invariance.

In a particle swarm with a fixed kinetic energy, the constituent particles move randomly and their velocity magnitudes follow a Maxwell distribution characterized by specific parameters. Within a certain time frame, particles in a sub-swarm may exhibit a bias in their movement direction. Thus, the particles may exhibit a special characteristic (biased random motion), where the group velocity in a particular direction remains constant u. For this biased particle swarm, composed of randomly moving particles with a fixed average speed c, particles have a higher probability of moving in a specific direction. Conversely, their likelihood of moving in all other directions is equally reduced. This study starts from the perspective of biased random walks and using Mathematica software proves that the diffusion rate of particles (in the reference frame R_u observed from R₀) in all directions is slower than that of an unbiased particle swarm with the same average speed c. Specifically, the degree of reduction is determined by the Lorentz-like factor. Lastly, we present the Ito equation for this biased random motion and provide associated verification examples. This study aims to serve as a reference for comprehending the underlying principles of the special relativity effect.

The realization of a BRST cohomology of the 4D topological gauge-affine gravity is established in terms of a superconnection formalism. Identification of fields in the quantized theory is occurred directly as usual in terms of superconnection and its supercurvature components with the double covering of the general affine group GA¯(4,R). Then, by means of an appropriate decomposition of the metalinear double-covering group SL¯(5,R) with respect to the general linear double-covering group GL¯(4,R) one can easily obtain the enlargements of the fields while remaining consistent with the BRST algebra. This leads to the descent equations allowing us to build the observables of the theory by means of the BRST algebra constructed using a sa¯(5,R) algebra-valued superconnection. In particular, we discuss the construction of topological invariants with torsion.

A black hole in a Schwarzschild spacetime is considered. A transformation is proposed that describes the relationship between the coordinate systems exterior and interior to an event horizon. Application of this transformation permits considerations of the (a)symmetry of a range of phenomena taking place on both sides of the event horizon. The paper investigates two distinct problems of a uniformly accelerated particle. In one of these, although the equations of motion are the same in the regions on both sides, the solutions turn out to be very different. This manifests the differences of the properties of these two ranges.

Antimicrobial resistance (AMR) poses a critical global health threat, leading to approximately 1.27 million deaths annually from infectious diseases resistant to existing antibiotics. Factors such as antibiotic misuse and environmental contamination have accelerated AMR, with the COVID-19 pandemic exacerbating the issue due to increased antibiotic usage. However, the development of new antibiotics has stagnated, with only a few approved in recent years, and many facing resistance. Among the priority pathogens identified by the WHO, Pseudomonas aeruginosa stands out as a significant concern due to its multidrug resistance and virulence. P. aeruginosa infections are challenging to treat due to intrinsic and acquired resistance mechanisms, as well as its ability to form biofilms. Additionally, P. aeruginosa produces a plethora of virulence factors, including proteases, siderophores, and toxins, further complicating treatment. Quorum sensing (QS) systems play a crucial role in regulating bacterial physiology and virulence factor expression. P. aeruginosa employs three QS systems, making it an attractive target for quorum quenching (QQ) strategies. Enzymes such as AHL lactonases, acylases, and oxidoreductases have shown promise in inhibiting QS, thus reducing virulence without impacting bacterial growth. Furthermore, natural QS inhibitors produced by various organisms offer potential therapeutic alternatives. Despite promising results in vitro, translating QQ strategies to clinical settings remains challenging. Nevertheless, QQ represents a novel approach in combating multidrug-resistant infections and warrants further investigation as a complementary therapeutic strategy alongside traditional antibiotics. This review summarizes enzymes with Qurorum Quenching activity evaluated against the pathogen P. aeruginosa and their potential applications in combination therapies.

Efficient heat management and control in optical devices, facilitated by advanced thermo-optic materials, is critical for many applications such as photovoltaics, thermal emitters, mode-locked lasers, and optical switches. Here, we investigate the thermo-optic properties of 2D graphene oxide (GO) films by precisely integrating them onto microring resonators (MRRs) with control over the film thicknesses and lengths. We characterize the refractive index, extinction coefficient, thermo-optic coefficient, and thermal conductivity of for the GO films with different layer numbers and degrees of reduction, including reversible reduction and enhanced optical bistability induced by photo-thermal effects. Experimental results show that the thermo-optic properties of 2D GO films vary widely with the degree of reduction, with significant polarization anisotropy, enabling efficient polarization sensitive devices. The versatile thermo-optic response of 2D GO substantially expands the scope of functionalities and devices that can be engineered, making it promising for a diverse range of thermo-optic applications.

A record-breaking dust episode took place in Crete on 22 March 2018. The event was characterized by surface concentrations exceeding 1 mg m-3 for a period of 4-7 hours, reaching record values higher than 6 mg m-3 at the background station of Finokalia. We present here a detailed analysis of the atmospheric dynamical processes during this period, to identify the main reasons that resulted in such extreme dust advection over Crete. At synoptic scale, the weakening of the polar vortex and the meridional transport of polar air masses at upper tropospheric layers resulted in a strong jet streak over N. Africa and Central Mediterranean and corresponding tropospheric folding that brought cold stratospheric air in mid and upper troposphere. Cyclogenesis occurred at the Gulf of Sirte in Libya, resulting on strong winds over the NE parts of Libya, enhancing particle emissions. The dust plume traveled at low heights (0.5-3 km) along the warm conveyor belt preceding the depression cold front. This type of dusty southerly wind is commonly known as “Khamsin”. As the flow approached Crete, Foehn winds at the lee side of the island favored the downward mixing of dust towards the surface, resulting in local maxima of PM10 in Heraklion and Finokalia. The analysis is based on the synergy of high resolution WRF-Chem simulations reaching up to 1×1 km grid space over Crete, ground-based and satellite remote sensing of the dust plumes (PollyXT lidar, MSG-SEVIRI, MODIS) and detailed surface aerosol in-situ measurements at urban (Heraklion, Chania) and background (Finokalia) stations in Crete.

In this paper, we study the constrained minimization problem for an energy functional which is related to the following Kirchhoff type equation \begin{equation*} -\Big(\eta+b\big(\int_{\R^{3}}|\nabla u|^{2}dx\big)^{s}\Big)\Delta u+V(x)u=\mu u +\lambda|u|^{p}u,\end{equation*} where $b$ is a positive constant, parameters $\eta\geq0, \lambda>0$, exponents $s>0$, $0

The search for fundamental determinants of bio-molecular chirality is a hot topic in biology, clarifying the meaning of evolution and the enigma of life's origin. Non-biological and biological entities obey the universal laws of nature grounded on space-time symmetry (STS) transformations. The fabric of STS is the immense subject of our review. The symmetry, encompassing behavior of elementary particles and galaxy structure, imposes its fundamental laws on all hierarchical levels of the biological world. Objects across spatial scales may be classified as chiral or achiral concerning a specific space-related symmetry transformation - mirror reflection. Chirality as a symmetry element reflecting the property of asymmetry (or dissymmetry) is the critical structural feature of natural systems, including sub-atomic particles and living matter. The inheritance of molecular symmetry from the symmetry of elementary particles points to the bi-directional causal pathway of prevalent bio-chirality. We assume that both extremities of spatial dimension naturally influence this transitional state of biological matter. The current review promotes an integrative holistic approach to the new experimental results in fast-developing and divergent branches of STS and biological chirality. The generalized view on biological chirality is a necessary and promising avenue for adequately understanding the link between protein folding, cell morphology, neuronal signaling, and laterality of cognitive functions.

Within the spectrum of a natural image, the amplitude of modulation decreases with spatial frequency. The speed of such an amplitude decrease, or the amplitude spectrum slope, of an image affects the perceived aesthetic value. Additionally, a human observer would consider a symmetric image more appealing than they do an asymmetric one. We investigated how these two factors jointly affect aesthetic preferences by manipulating both the amplitude spectrum slope and the symmetric level of images to assess their effects on aesthetic preference on a 6-point Likert scale. Our results showed that the preference ratings increased with the symmetry level but had an inverted U-shape relation to amplitude spectrum slope. In addition, a strong interaction existed between symmetry level and amplitude spectrum slope on preference rating, in that symmetry can amplify the amplitude spectrum slope’s effects. Such effects can be described by a quadratic function of the spectrum slope. That is, preference is an inverted U-shape function of spectrum slope whose intercept is determined by the number of symmetry axis. In addition, the interaction between the two factors is manifested as the modulation depth of the quadratic function.

Quantum coherence is an important physical resource in quantum information science, and also as one of the most fundamental and striking features in quantum physics. In this paper, we obtain a symmetry-like relation of relative entropy measure $C_r(\rho)$ of coherence for $n$-partite quantum states $\rho$, which gives lower and upper bounds for $C_r(\rho)$. Meanwhile, we discuss the conjecture about the validity of the inequality $C_r(\rho)\leq C_{\ell_1}(\rho)$ for any state $\rho$. We observe that every mixture $\eta$ of a state $\rho$ satisfying $C_r(\rho)\leq C_{\ell_1}(\rho)$ and any incoherent state $\sigma$ also satisfies the conjecture. We also note that if the von Neumann entropy is defined by the natural logarithm $\ln$ instead of $\log_2$, then the reduced relative entropy measure of coherence $\bar{C}_r(\rho)=-\rho_{\rm{diag}}\ln \rho_{\rm{diag}}+\rho\ln \rho$ satisfies the inequality ${\bar{C}}_r(\rho)\leq C_{\ell_1}(\rho)$ for any mixed state $\rho$.

Using a nonclassical symmetry of nonlinear reaction-diffusion equations, some exact multi-dimensional time-dependent solutions are constructed for a fourth-order Allen-Cahn-Hilliard equation. This models a phase field that gives a phenomenological description of a two-phase system near the critical temperature. Solutions are given for the changing phase of a cylindrical or spherical inclusion, allowing for a 'mushy zone' with mixed state that is controlled by imposing a pure state at the boundary. The diffusion coefficients for transport of one phase through the mixture, depend on the phase field value, since the physical structure of the mixture depends on the relative proportions of the two phases. A source term promotes stability of both of the pure phases but this tendency may be controlled or even reversed through the boundary conditions.

Introduction: The purpose of this study was to determine the normative values of muscles’ contractile properties, lateral symmetry, and the impact of aging on muscle contractility in gymnastics. Materials and Methods: A survey of 81 athletes from different disciplines was undertaken: MAG (n = 26), WAG (n = 28), and RG (n = 27). The athletes’ average age was 15.41 ± 5.03 years. We try to establish the normative values for contraction time (muscle pairs) in gymnastics for Slovenian athletes for ten skeletal muscles. Results: Athletes’ age affects contractility in a negative way. Differences between the duration of contractility and age were found in all disciplines: m. BF (r = 0.48, p < 0.001), m. TB (r = 0.37, p < 0.013), m. ES (r = 0.17, p < 0.025), m. VL (r = 0.36, p < 0.00) and m. VM (r = 0.40, p < 0.000) at a statistical significance of p < 0.05. Conclusions: A comparison between the left and right sides shows little asymmetry in WAG and that the occurrence of injuries is in the middle range. In RG we see a bigger deviation, which could trigger the emergence of pain or injury in m. BF (13%) and m. GL (14.5%), but in MAG the deviation is greater in m. BB (12%), m. BF (11%) and m. GM (13%).

Particles and photons appear to be total opposites; the former has rest mass which requires space to exist; the latter has kinetic energy which requires time to occur (oscillate). But they do share certain properties (e.g., quantization) that remain invariant when one is transformed (swapped) for the other. This gauge invariance is developed in some detail.The symmetry between particle and photon turns out to be one of inversion. It is the equalities of special relativity that support this inversion and the accompanying invariances: mass transformed to energy; space transformed to time. The great advantage of these symmetries (inversions) is that they provide guidance for an object little understood (the photon) based upon an object well understood (the particle). On this basis, progress can be made in the understanding of some long-standing issues: wave-particle duality, time’s arrow, the constant speed of light and nonlocality.

Analytical modeling has symmetries and aesthetic-mathematical characteristics that distinguish it from numerical computation. Nanoscience plays an extremely important role in unification efforts that also include holistic aspects of reality. In this paper I present new discovered results about the complete analytical quantum relativistic form of the mean square deviation of position false related to a lately appeared Drude-Lorentz-like model (DS model), already performed at classical, quantum and relativistic level. The function false gives precise information about the distance crossed by carriers (electrons, ions, etc.) inside a nanostructure, considering both quantum effects and relativistic velocities. The model has a wide scale range of applicability; the nanoscale is considered in this paper, but it holds from sub-pico-level to macro-level because of the existence of a gauge factor, making it applicable to every oscillating processes in Nature. Examples of application and suggestions supplement the paper, as well as interesting developments to be studied related to the model and to one of the basic elements of a current unified holistic approach based on the vacuum energy.

Optinalysis, as a method of symmetry detection, is a new algorithm that intrametrically (within elements or variables) or intermetrically (between elements or variables) computes and compares two or more univariate or multi-clustered or multivariate sequences as a mirror-like reflection of each other (optics-like manner), hence the name is driven. Optinalysis is based by the principles of reflection and moment about a symmetrical line which detects symmetry that reflects a similarity measurement. This proposed methodology was validated in comparison with Pearson method of skewness detection, and also with some algorithms for pairewise alignment and comparison of genomic sequences (Needle, Stretcher, Water, Matcher) on EMBL-EBI website. A results comparison shows that optinalysis is more advance, more sensitive, more inferential and simple alternative approach of skewness detection and pairewise sequence comparison.

High-efficiency rock breaking by hydraulic jetting is the key to radial horizontal drilling technology. In order to improve the drilling efficiency of hydraulic jet rock breaking in radial horizontal wells, based on LS-Dyna display dynamics, a numerical simulation model of single nozzle jet rock breaking is established to analyze the influence of different nozzle parameters on rock breaking effect. Then, the numerical simulation model of the spin multi-nozzle jet bit is established, and the influence of different rotation speeds on the rock breaking effect of the jet bit is analyzed. Finally, the rock breaking drilling characteristics of the spin multi-nozzle jet bit and the conventional multi-nozzle jet bit are compared and analyzed. The results show that when the jet impacts the rock surface, the larger the inclination angle is, the larger the rock breaking width formed by the jet is. The smaller the dip angle, the greater the rock breaking depth. When the inclination angle is greater than 60 °, it is difficult to meet the needs of reaming. The width and depth of the nozzle gradually increase with the increase of the diameter. When the nozzle diameter is greater than 1.3mm, the growth rate of rock breaking depth begins to decrease. The optimum nozzle diameter is 1.3 mm. When v = 50m / s, the damage caused by the jet to the rock surface is very small, because the condition of rock fracture is not reached at this time. This shows that there is a critical value of the water jet impact velocity, and only when the velocity is reached, the rock will break. When the velocity is v = 150m / s, v = 200m / s, v = 250m / s, v = 300m / s, the rock breaks. At the same time, the higher the speed, the higher the degree of rock fracture, the greater the fracture depth, the greater the fracture area, the better the fracture effect. The tangential and radial velocity of the jet increases the shear and tensile failure rate of the sample, and improves the rock breaking efficiency of the jet, which has certain guiding significance for improving the rock breaking drilling efficiency of radial horizontal well drilling.

Deep neural networks with powerful auto-optimization tools have been widely applied in various research fields, e.g., NLP and computer vision. However, existing neural network architectures typically are constructed using different inductive biases, e.g., preconceptions, expecting to decrease parameter search space during training, reduce computational cost or introduce expert knowledge in the neural network design. As an alternative, Multilayer Perceptron (MLP) provides much better freedom for exploration, has a lower inductive bias than convolutional neural networks (CNNs), and offers good flexibility in learning complex patterns. Even though, such neural architectures are commonly built in a flat Euclidean space, which is not necessarily the optimal space for any data, and is especially not good for modeling hierarchical correlations. Hyperbolic neural networks (HNNs) have gained attention for their ability to capture hierarchical structures present in complex data types like graphs. Recently, there has been an increasing interest to extend HNNs to computer vision tasks, motivated by the observations that images possess rich hierarchical relations. However, this is generally applied by employing a Euclidean backbone for learning higher-level semantic representations and only incorporating a hyperbolic classifier for classification, which, we argue, does not make full use of the advantage of hyperbolic space. Considering the recovery of the attention-free Multilayer Perceptron(MLP), in this paper, we extend it to non-Euclidean space and propose a novel architecture, named Hyperbolic Res-MLP (HR-MLP), that leverages fully hyperbolic layers to learn feature embeddings and perform image classification in an end-to-end fashion. With the help of the proposed Lorentz cross-patch and cross-channel layers, we can directly perform operations in the hyperbolic domain with fewer parameters, making it faster to train and providing comparatively better performance than its Euclidean counterpart. Experiments on CIFAR10, CIFAR100, and MiniImageNet demonstrate a comparable and superior performance when compared to Euclidean baselines. Our code is available at (https://github.com/Ahmad-Omar-Ahsan/HR-MLP)

Scator set, introduced by Fernández-Guasti and Zaldívar, is endowed with a very peculiar non-distributive product. In this paper we consider the scator space of dimension $1+2$ and the so called fundamental embedding which maps the subset of scators with non-zero scalar component into 4-dimensional space endowed with a natural distributive product. The original definition of the scator product is induced in a straightforward way. Moreove, we propose an extension of the scator product on the whole scator space, including scators with vanishing scalar component.

In this paper, the quantum theory of the infinite-component Majorana field for the fermionic tower is formulated. This study proves that the energy states with increasing spin are simply composite systems made by a bradyon and antitachyons with half-integer spin. The quantum field describing these exotic states is obtained by the infinite sum of four-spinor operators, which each operator depends on the spin and the rest mass of the bradyon in its fundamental state. The interaction between bradyon-tachyon, tachyon-tachyon and tachyon-luxon has also been considered and included in the total Lagrangian. The obtained theory is consistent with the CPT invariance and the spin-statistics theorem and could explain the existence of new forms of matter not predictable within the standard model.

The notion of the informational measure of symmetry is introduced according to: HsymG=-i=1kPGilnPGi, where PGi is the probability of appearance of the symmetry operation Gi within the given 2D pattern. HsymG is interpreted as an averaged uncertainty in the presence of symmetry elements from the group G in the given pattern. The informational measure of symmetry of the “ideal” pattern built of identical equilateral triangles is established as HsymD3=1.792. The informational measure of symmetry of the random, completely disordered pattern is zero, Hsym=0. Informational measure of symmetry is calculated for the patterns generated by the P3 Penrose tessellation. Informational measure of symmetry does not correlate neither with the Voronoi entropy of the studied patterns nor with the continuous measure of symmetry of the patterns.

In this work, we analytically describe a superconducting transition in a non-equilibrium state taking into account many-body interactions; the obtained transition temperatures indicate the presence of superconductivity at room temperatures.First, we consider many-body interactions and discuss the case of locally thermal equilibrium with many-body interactions; in this section, we derive statistical equations that describe many-body interactions at locally thermal equilibrium state. Then, the same theory is used to derive a many-body statistical equation that is expanded to include the case of non-equilibrium states; in this case a transition temperature is derived. Moreover, a wave function of an Einstein–Podolsky–Rosen pair (EPR pair) is calculated according to the Lorentz conservation, and a specific condensation is observed and the Meissner effect is found to be present.Furthermore, considering the Lorentz conservations, relativistic energy, and Boltzmann statistics, algorithms are presented to calculate charge density, current density, and internal local energy. We note that these calculations do not require a specific code but instead utilize the software Microsoft Excel.We present plots showing the charge density and current density vs. the applied electric potential, which demonstrate the practical applicability of the theory. Moreover, internal local energy was found to be close to zero for sufficiently large electric potentials at room temperature.In the discussion section, the universally induced superconducting current is derived, which can be employed as the renewable energy.This paper describes non-equilibrium and EPR-pair type superconductivity, with the complete consideration of many-body interactions.

Physical roots, exemplifications and consequences of periodic and aperiodic ordering (represented by Fibonacci series) in biological systems are discussed. The role and physical and biological roots of symmetry and asymmetry appearing in biological patterns is addressed. Generalization of the Curie-Neumann Principle as applied to biological objects is presented, briefly summarized as: “asymmetry is what creates a biological phenomenon”. The “up-bottom approach” and “bottom up” approaches to the explanation of symmetry in organisms are presented in detail. The “up-bottom approach”, implies that the symmetry of the biological structure follows the symmetry of media in which this structure is functioning; the “bottom-up” approach, in turn, adopt that the symmetry of biological structures emerges from the symmetry of molecules constituting the structure. A diversity of mathematical measures applicable for quantification of ordering in biological patterns is introduced. The continuous, Shannon and Voronoi measures of symmetry/ordering and their application to biology objects are addressed. The fine structure of the notion of “ordering” is discussed. Informational/algorithmic roots of ordering inherent for the biological systems are considered. Ordered/symmetrical patterns provide economy of biological information, necessary for algorithmic description of a biological entity. Application of the Landauer principle bridging physics and theory of information to the biological systems is discussed.

The Na+/K+ ATPase is a protein involved in the active transport of ions across the cellular membrane. Ouabain is a cardiotonic glycoside that, by inhibiting the Na+/K+ pump, interferes with cell processes mediated directly by the pump, but also indirectly influences other cellular processes, such as cellular cycle and proliferation, growth, cell differentiation, angiogenesis, migration, adhesion and invasion. We used the SK-BR-3 breast cancer cell line, mesenchymal stem cells (MSCs), and tumor-associated fibroblasts (TAFs) in vitro for determining the changes induced by Ouabain in concentration of 10-5 M, 10-6 M, 10-8 M, 10-9 M on these cellular types, employing specific methods: SEM for morphological evaluation; immunocytochemistry, flowcytometry to assess immunophenotypical markers expression, cell cycle and Annexin V/PI assay for cellular proliferation and viability testing; flowchamber assay to evaluate functional adhesion behavior; RT-PCR for Na+/K+ ATPase subunits molecular expression. Being indicative of the pro-apoptotic and inhibitory effect of Ouabain on tumor invasion and metastasis, the results support the addition of Ouabain to the oncological therapeutic arsenal, trailing the “repurposing drugs” approach.

Every subset S of a Cartesian spaces Rd, endowed with differen- tial structure C∞(S) generated by restrictions to S of functions in C∞(Rd), has a canonical partition M(S) by manifolds, which are or- bits of the family X(S) of all derivations of C∞(S) that generate local one-parameter groups of local diffeomorphisms of S. This partition satisfies the frontier condition, Whitney’s conditions A and B. If M(S) is locally finite, then it satisfies all definitions of stratification of S. This result extends to Hausdorff locally Euclidean differential spaces.

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

Keywords: Innovation ecosystems, Economic sustainability, Hydrocarbon-based economies, Economic diversification, Qualitative approach

Standards are not only crucial for obtaining a certification for practical use, but also an essential guidance for inferring how and what to simulate as well test experimentally. This paper examines the potential applicability of existing standards from various domains, including aerospace and automotive, to Wing-Structure- Integrated high-pressure Hydrogen Tanks (SWITHs). It highlights the associated challenges and uncertainties, acknowledging the absence of a single, all-encompassing standard for SWITHs. We embark on an exploration aimed at identifying alternative standards that are best suited for SWITHs. The analysis scrutinizes existing standards that could potentially facilitate SWITH certification, with a particular focus on the inclusivity of externally loaded hydrogen tanks. Assessment criteria are established to filter standards that best meet the needs of SWITHs. Through this process, we identify two key standards that present themselves as the most promising alternatives. Moreover, we delineate the technical constraints involved in selecting the maximum nominal working pressure for high-pressure tanks intended for burst tests. Our findings reveal a current upper limit of 525 bar, imposed by the limitations of existing test facilities. The study underscores that these standards should serve as flexible guiding frameworks rather than rigid protocols, encouraging progressive development in the SWITH field.

Bamboo biomass is a potential source for the production of monomeric sugars containing high cellulose content with low amount of lignin. However, for efficient hydrolysis, the biomass treatment by effective pretreatment technique is required to minimize lignin content and other barrier components. During present study, the bamboo biomass was treated with different physical, chemical, biological and combined treatments to reduce the lignin content. Among all the pretreatments, the maximum lignin removal (14.5%) was obtained with the combined chemical and biological treatment under 2% NaOH+1% H2O2 +WDP2 fungal culture (5 plugs) conditions. In addition, lignolytic fungus and NaOH pretreatment was mainly effective in removing lignin, whereas the H2O2 pretreatment efficiently minimize cellulose crystallinity. To analyze structural changes of raw and treated biomass, we used scanning electron microscopy and fourier transform infrared spectroscopy. The structural analysis indicated that all treatments causes disruption in the biomass structure and loses the compactness of the biomass which facilitates the biomass conversion during hydrolysis process. The findings of the present study indicate effective pretreatment methods in breaching the recalcitrancy of the potential lignocellulosic biomass for maximum hydrolysis.

This study investigates via Lie symmetry analysis the Hunter-Saxton equation, an equation relevant to the theoretical analysis of nematic liquid crystals. We employ the multiplier method to obtain conservation laws of the equation derived from first-order multipliers. Conservation laws of the Hunter-Saxton equation, in combination with the Lie point symmetries of the equation, enable us to perform symmetry reductions through employment of the double reduction method. The method exploits the relationship between Lie point symmetries and conservation laws to effectively reduce both the number of variables and the order of the equation. Five nontrivial conservation laws of the Hunter-Saxton equation are derived, four of which are found to have associated Lie point symmetries. Applying the double reduction method to the Hunter-Saxton equation results in a set of first-order ordinary differential equations, the solutions of which represent invariant solutions for the equation.

We study the Gaudin models with gl(1|1) symmetry that are twisted by a diagonal matrix and defined on tensor products of polynomial evaluation gl(1|1)[t]-modules, extending all the results of to the twisted case. Namely, we give an explicit description of the algebra of Hamiltonians (Gaudin Hamiltonians) acting on tensor products of polynomial evaluation gl(1|1)[t]-modules and show that there exists a bijection between common eigenvectors (up to proportionality) of the algebra of Hamiltonians and monic divisors of an explicit polynomial written in terms of the highest weights and evaluation parameters. In particular, our result implies that each common eigenspace of the algebra of Hamiltonians has dimension one. We also give dimensions of the generalized eigenspaces.

A new method of line shape calculations of hydrogen-like atoms in magnetized plasmas is presented. This algorithm makes it possible to solve two fundamental problems in the broadening theory: the analytical description of the radiation transition array between excited atomic states and account of a thermal ion motion effect on the line shapes formation. The solution to the first problem is based on the semiclassical approach to dipole matrix elements calculations and the usage of the specific symmetry properises of the Coulomb field. The second one is considered in terms of the kinetic treatment of the frequency fluctuation model (FFM). As the result one has a universal description of line shapes under the action of the dynamic of ion’s microfield. The final line shape is obtained by the convolution of the ionic line shape with the Voigt electron-Doppler profile. The method is applicable formally for large values of principle quantum numbers. However, it is demonstrated the efficiency of the results even for well known first members of the hydrogen Balmer series Dalpha and Dbeta. The comparison of obtained results with accurate quantum calculations is presented. The new method may be of interest for investigations of spectral line shapes of hydrogen-like ions presented in different kinds of hot ionized environments with the presence of a magnetic field, including SoL and divertor tokamak plasmas.

Abstract: The second part of the paper develops the approach, suggested in the Entropy 2020, 22(1), 11; https://doi.org/10.3390/e22010011 , which relates ordering in physical systems to their symmetrizing. Entropy is frequently interpreted as a quantitative measure of “chaos” or “disorder”. However, the notions of “chaos” and “disorder” are vague and subjective to a much extent. This leads to numerous misinterpretations of entropy. We propose to see the disorder as an absence of symmetry and to identify “ordering” with symmetrizing of a physical system; in other words, introducing the elements of symmetry into an initially disordered physical system. We explore the initially disordered system of elementary magnets exerted to the external magnetic field H ⃗. Imposing symmetry restrictions diminishes the entropy of the system and decreases its temperature. The general case of the system of elementary magnets demonstrating the j-fold symmetry is treated. The interrelation T_j=T/j takes place, where T and T_j are the temperatures of non-symmetrized and j-fold-symmetrized systems of the magnets correspondingly.

We define a spinor-Minkowski metric for SL(4,C). It is not a trivial generalization of the SL(2,C) metric and it involves the Minkowskian one. We define 4x4 version of the Pauli matrices and eight 4-component associated generalized eigenvectors that can be regarded as undotted covariant spinors. The 4-component spinors can be grouped into four categories. Each category transforms in its own way. The outer products of pairwise combinations of 4-component spinors can be associated with 4-vectors. Including the dotted covariant, undotted and dotted contravariant forms totally we have sixteen pairs of spinors. Eight of them live in the conjugate space which has no countepart in SL(2,C).

Weak interaction processes continue to be hot topics in fundamental physics research. In this paper, we briefly review some recent advances in the theoretical study of beta and double-beta decays that include both the nuclear and atomic part of these processes. On the nuclear side, we present a statistical approach for the computation of the nuclear matrix elements (NME) for neutrinoless double-beta (0νββ). A range of NME values, the most probable value for NME, and the associated theoretical uncertainty are given. Correlations with other related observables are shown as well. On the atomic side, we first briefly review the methods used to get the electrons’ wave functions. Further, we use them for the computation of some relevant kinematic quantities such as Fermi functions, electron spectra and angular correlation between the emitted electrons. Then, we present applications of these calculations to the experimental data analysis related to the search of the Lorentz invariance violation in two-neutrino double-beta (2νββ) decay and description of the decay rates and decay rate ratios for allowed and unique forbidden electron capture (EC) processes.

Newton's kinetic energy equation delineates the laws of motion for objects travelling at speeds much less than the speed of light, an equation extensively validated at these lower velocities. Any new, more complete formulation of kinetic energy must approximate Newton's kinetic energy equation under these conditions. Einstein's special relativity, utilizing the Lorentz factor, introduces a new perspective on spacetime, adhering to the requirement that the Newtonian kinetic energy equation serves as an approximation at low velocities. In this paper, we identify all factor expressions satisfying the condition that their approximate solutions at low velocities align with Newton's kinetic energy equation. We introduce the Yuyunrui factor, incorporating two real number hyperparameters, $\alpha$ and $\beta$, encompassing all potentially correct factors, with the Lorentz factor as a specific instance where $(\alpha=0$, $\beta=1)$. We classify all potentially correct $(\alpha, \beta)$ combinations into six categories based on their distinct scaling effects and present the corresponding scaling effects. The combinations of $(\alpha, \beta)$ values applicable in the real world are necessarily included within these candidates, with the precise values requiring rigorous experimental validation. This work aims to refine our understanding of special relativity beyond the Lorentz factor.

It is universally accepted that Maxwell equations do not remain invariant under the Galilean transformation. This conflicts the principle of relativity which states that the physical law must remain invariant in the mathematical form in all inertial frames of reference. For this reason, the Lorentz transformation is invented, and the Galilean transformation is nowadays superseded by the Lorentz transformation. However, this paper challenges this widely held belief that the Maxwell equations are not invariant under the Galilean transformation. By applying the Galilean transformation to Lienard-Wiechert electromagnetic fields it is mathematically proven that the Maxwell equations indeed remain invariant under the Galilean transformation. In addition, the critical error in Lorentz's proof of Galilean non-invariance of Maxwell equations is pointed out, and it turns out that Lorentz's conclusion that Maxwell equations are not invariant under the Galilean transformation is the result of a mathematical error.

The system of non-interacting electrically charged core-massless spring-shell mechanical units, demonstrating negative effective mass, is considered, seen as a Drude-Lorentz gas. When such an ideal gas is exposed to the external harmonic field, it demonstrates as the certain conditions the negative frequency-dependent electrical conductivity. The negative value of the electrical conductivity implies that the electrical current will flow against the direction of the electric field and correspondingly the direction of the electrical force. Low- and high-frequency asymptotic behavior of the electrical conductivity is addressed. The same system demonstrates at low frequencies the negative asymptotic refraction. Experimental realization of the introduced model system, based on the exploitation of plasma oscillations of the free electron gas is suggested.

We study spherically symmetric spacetimes in Einstein-aether theory in three different coordinate systems, the isotropic, Painlev\`e-Gullstrand, and Schwarzschild coordinates, and present both time-dependent and time-independent exact vacuum solutions. In particular, in the isotropic coordinates we find a class of exact static solutions characterized bya single parameter $c_{14}$ in closed forms, which satisfies all the current observational constraints of the theory, and reduces to the Schwarzschild vacuum black hole solution in the decoupling limit ($c_{14} = 0$). However, as long as $c_{14} \not= 0$, a marginally trapped throat with a finite non-zero radius always exists, and in one side of it the spacetime is asymptotically flat, while in the other side the spacetime becomes singular within a finite proper distance from the throat, although the geometric area is infinitely large at the singularity. Moreover, the singularity is a strong and spacetime curvature singularity, at which both of the Ricci and Kretschmann scalars become infinitely large.

In this paper, we revisit the two theoretical approaches for the formulation of the tachyonic Dirac equation. The first approach works within the theory of restricted relativity, starting from a Lorentz invariant Lagrangian consistent with a spacelike four-momentum. The second approach uses the theory of relativity extended to superluminal motions and works directly on the ordinary Dirac equation through superluminal Lorentz transformations. The equations resulting from the two approaches show mostly different, if not opposite, properties. In particular, the first equation violates the invariance under the action of the parity and charge conjugation operations. Although it is a good mathematical tool to describe the dynamics of a space-like particle, it also shows that the mean particle velocity is subluminal. In contrast, the second equation is invariant under the action of parity and charge conjugation symmetries, but the particle it describes is consistent with the classical dynamics of a tachyon. This study shows that it is not possible with the currently available theories to formulate a covariant equation that coherently describes the neutrino in the framework of the physics of tachyons, and depending on the experiment, one equation rather than the other should be used.

To embrace the special theory of relativity with classical thermodynamics correct Lorentz transformations of thermodynamic state functions are formulated. All of these Lorentz transformations of state functions equally support the time dilation phenomenon which is experimentally verified fact. Relativistic Boltzmann constant proves entropy to be the Lorentz variant. Twin paradox thought experiments for heat engines prove heat flux to be Lorentz variant. Lorentz transformation of entropy and heat flux proves temperature Lorentz invariant. All thermodynamic state functions are proved to be Lorentz variant which is shown in accord with Lorentz transformation of thermodynamic work.

Alginate-silver nanocomposites in the form of spherical beads and films were prepared using a green approach by using the aqueous extract of Ajwa dates seeds. The nanocomposites were fabricated by in situ reduction and gelation method by ionotropic crosslinking using calcium ions in solution. The rich phytochemicals of the dates seeds extract played a dual role as reducing and stabilizing agent in the synthesis of silver nanoparticles. The formation of silver nanoparticles was studied using UV-Vis absorption spectroscopy and a distinct surface plasmon resonance (SPR) peak at 421 nm characteristic of silver nanoparticles confirmed the green synthesis of silver nanoparticles. The morphology of the nanocomposite beads and film was compact with even distribution of silver nanoclusters. The catalytic property of the nanocomposite beads was evaluated for the degradation of 2-nitrophenol in the presence of sodium borohydride. The degradation followed pseudo-first order kinetics with a rate constant of 1.40 ´ 10^-3 s^-1 at 23 °C with an activation energy of 18.45 kJ mol^-1. The thermodynamic parameters such as changes in enthalpy and entropy were evaluated to be 15.22 kJ mol^-1 and -197.50 J mol^-1 K^-1, respectively. The nanocomposite exhibited properties against three clinically important pathogens (Gram-positive and Gram-negative bacteria)

Abstract: Wildfires in forest ecosystems exert substantial ecological, economic, and social impacts. The effectiveness of fire management hinges on precise pre‐fire risk assessments to inform mitigation efforts. This study aims to investigate the relationship between predictions from pre‐fire risk assessments and outcomes observed through post‐fire burn severity analyses. In this study, forest fire risk was assessed with the Fuzzy Analytical Hierarchy Process, in which fire behavior factors were used as input. The degree of burn was determined using the Random Forest method using 11519 training points and 400 test points on Sentinel‐2 satellite images in three different classes. According to the results obtained from 266 selected test points located within the forest boundaries, all primary factors showed an increased effect in areas with high burn severity. Climate, in particular, emerged as the most influential factor, accounting for 52% of the overall impact. However, in cases of high fire severity, climate proved to be the most effective risk factor, ac‐counting for 67%. It followed by topography with 50% accuracy at high fire intensity. In the risk assessment is based on the FAHP method, climate was assigned the highest weight value among other factors with 32.2%. Topography emerged as the second most effective risk factor with 27 %. To evaluate the results more comprehensively both visually and statistically, two regions with different stand canopy characteristics were selected within the study area. While high burn severity had the highest accuracy in Case 1 area, moderate burn severity had the highest in Case 2 area. During the days when the fire continued, the direction of spread was obtained from MODIS images. In this way, the fire severity depending on the direction of fire progression was also interpreted. Through an analysis of various case studies and existing literature, the research underscores both the strengths and limitations inherent in predicting forest fire behavior‐based pre‐fire risk assessments. Furthermore, it emphasizes the necessity of continuous improvement to increase the success of forest fire management.

We show that the compound samarium hexaboride is a strong topological insulator using the eigenvalues of the space inversion operator in the low-energy limit of the periodic Anderson model. Additionally, we assume the presence of the ferromagnetic exchange interaction (M). A Dirac cone like feature in the surface state energy spectra is observed for M equals zero in a certain parameter range. For M not equal to zero, there is no Kramers degeneracy. We have been able to show that this phase corresponds to the quantum anomalous Hall state by calculating Berry curvature and the Chern number. Using Floquet theory, we further show that the access to a novel state with broken time reversal symmetry is possible due to the normal incidence of circularly polarized optical field on the surface of the compound despite M being absent.

In light of Liu \emph{at el.}'s original works, this paper revisits the solution of Burgers's nonlinear equation $u_t=a(u_x)^2+bu_{xx} $. The study found two exact and explicit solutions for groups $G_4$ and $G_6$, as well as a general solution. A numerical simulation is carried out. In the appendix a Maple code is provided

The construction of molecular robotic-like objects that imitate living things is an important challenge for current chemists. Such molecular devices are expected to perform their duties robustly to carry out mechanical motion, process information, and make independent decisions. Dissipative self-organization plays an essential role in meeting these purposes. To produce a micro-robot that can perform the above tasks autonomously as a single entity, a function generator is required. Although many elegant review articles featuring chemical devices that mimic biological mechanical functions have been published recently, the dissipative structure, which is the minimum requirement, has not been sufficiently discussed. This article aims to show clearly that dissipative self-organization is a phenomenon involving autonomy, robustness, mechanical functions, and energy transformation. Moreover, the author details the recent experimental results of an autonomous light-driven molecular device that achieves all of these features. In addition, a chemical model of cell-amplification is also discussed to focus on the generation of hierarchical movement by dissipative self-organization. By reviewing this research, it may be perceived that mainstream approaches to synthetic chemistry have not always been appropriate. In summary, the author proposes that the integration of catalytic functions is a key issue for the creation of autonomous microarchitecture.

4-component relativistic atomic and molecular calculations are typically performed within the no-pair approximation where negative-energy solutions are discarded, hence the symmetry between electronic and positronic solutions is not considered. These states are however needed in QED calculations, where furthermore charge conjugation symmetry becomes an issue. In this work we shall discuss the realization of charge conjugation symmetry of the Dirac equation in a central field within the finite basis approximation. Three schemes for basis set construction are considered: restricted, inverse and dual kinetic balance. We find that charge conjugation symmetry can be realized within the restricted and inverse kinetic balance prescriptions, but only with a special form of basis functions that does not obey the right boundary conditions of the radial wavefunctions. The dual kinetic balance prescription is on the other hand compatible with charge conjugation symmetry without restricting the form of the radial basis functions. However, since charge conjugation relates solutions of opposite value of the quantum number κ, this requires the use of basis sets chosen according to total angular momentum j rather than orbital angular momentum ` . As a special case, we consider the free-particle Dirac equation, where the solutions of opposite sign of energy are related by charge conjugation symmetry. We note that there is additional symmetry in those solutions of the same value of κ come in pairs of opposite energy.

The structural, electronic and magnetochemical properties of the star-shaped polyoxopalladate [Pd₁₅O₁₀(SeO₃)₁₀]¹⁰⁻ (POPd) and its lanthanide functionalized derivatives have been investigated on the basis of density functional theory followed by a ligand field analysis using the Radial Effective Charge (REC) model. Our study predicts that heteroPOPd is a robust cryptand that enforces D_5h symmetry around the encapsulated Ln³⁺ centers. This rigid coordination environment favors interesting potential magnetic behavior in the Er and Ho derivatives, which may be of interest for molecular spintronics and quantum computing applications.

Agriculture has been experiencing a difficult situation because of limiting factors in its production, Natural biostimulants (NBs) have emerged as a novel alternative. This study reviews NBs produced through Solid-State Fermentation (SSF) from organic waste, focusing on the processes and production methods. The aim is to highlight their potential for improving agricultural productivity and promoting sustainable agriculture. Through a literature review, the effects of NBS on crops were examined, as well as the challenges associated with their production and application. The importance of standardizing production processes, optimizing fermentation conditions, and assessing their effects on different crops is emphasized. Furthermore, future research areas are identified, such as enhancing production efficiency and evaluating the effectiveness of SSF-produced NBS in different agricultural systems. In conclusion, SSF-produced NBS offers a promising alternative for sustainable agriculture, but further research and development are needed to maximize its efficacy and enable large-scale implementation.

Wave breaking is one of the most important yet poorly understood water wave phenomena. It is via wave breaking that waves dissipate most of their energy and the occurrence of wave breaking directly influences several environmental processes, from ocean-atmosphere gas exchanges to beach morphodynamics. Large breaking waves also represent a major threat for navigation and for the survivability of offshore structures. This paper provides a systematic search for intermediate to deep water breaking waves with particular focus on the elusive occurrence of plunging breakers. Using modern remote sensing and deep learning techniques, we identify and track the evolution of over four thousand unique wave breaking events using video data collected from La Jument lighthouse during ten North Atlantic winter storms. Out of all identified breaking waves (Nb=4683), ≈22% were dominant breaking waves, that is, waves that have speeds within [0.77cp, 1.43cp], where cp is the peak wave speed. Correlations between the occurrence rate of dominant breaking waves (that is, waves per area and time per peak wave period) and wave steepness and wave age were observed. As expected, the number of identified plunging waves was small and six waves of all detected breaking waves, or 0.13%, could undoubtedly be considered as plunging waves. Two waves were also identified as unusually large, or rogue waves. Although afflicted by several technical issues, the data presented here provides a good indication that the probability of occurrence of plunging waves should be better incorporated into the design of offshore structures, particularly the ones that aim to harvest energy in offshore environments.

In the rapidly evolving landscape of cybersecurity, Intrusion Detection Systems (IDS) play a critical role in safeguarding networks and systems from unauthorized access and malicious activities. Traditional IDS approaches, relying heavily on predefined rules and signature-based detection, often struggle to keep pace with the dynamic nature of modern cyber threats. Deep learning, with its ability to automatically learn complex patterns and representations from large datasets, offers a promising solution to this challenge. This paper explores the application of deep learning techniques in enhancing the effectiveness and accuracy of IDS. By leveraging advanced neural network architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders, deep learning-based IDS can detect both known and unknown (zero-day) attacks with higher precision. We discuss the advantages of deep learning in IDS, including its capability to handle large-scale data, adaptability to evolving threats, and reduced dependency on human intervention. Furthermore, this paper reviews recent advancements in deep learning for IDS, highlights the challenges associated with their implementation, and suggests future directions for research to overcome these hurdles. The integration of deep learning into IDS frameworks represents a significant step forward in the development of intelligent and autonomous cybersecurity systems.

In horses, quantitative assessment of gait parameters, as the use of inertial measurement units system (IMUs), might help in the decision-making process. However, it requires financial investment, is time-consuming, and lacks accuracy if displaced. An innovative Artificial Intelligence marker-less Motion Tracking System (AI-MTS) may overcome these limitations in the field. Our aim was to compare the level of agreement and accuracy between both systems and visual clinical assessment. Twenty horses underwent locomotion analysis by visual assessment, IMUs and AI- MTS systems, in the following conditions: straight hard (SH), straight soft (SS), left and right circle hard (LCH, RCH) and soft (LCS, RCS). A greater number of horses were considered sound by clinical examination, compared to those identified as symmetric by the two gait analysis systems. More limbs were considered asymmetric by the AI-MTS compared to IMUs, suggesting its greater sensitivity. The greatest agreement between the two systems was found for the difference between two minima in vertical head position in SH, while the lowest for the difference between two minima in vertical pelvis position in SS, reflecting the difficulties in assessing asymmetry of hindlimbs. Some degree of asymmetry may be clinically relevant, suggesting its regular use in training horses.

Hox Gene Collinearity (HGC) is a fundamental property that determines the development of many animal clades including Vertebrates. In the Hox gene clusters the genes are located in a sequence Hox1, Hox2, Hox3,… along the 3’ to 5’ direction of the cluster in the chromosome. During Hox cluster activation the Hox genes are expressed sequentially in the ontogenetic units D1, D2, D3,… along the anterior (A)- Posterior (P) axis of the early embryo. This collinearity, first observed by E.B. Lewis, is surprising because the spatial extent of these structures (Hox clusters and embryos) differ by about 4 orders of magnitude. Biomolecular mechanisms alone cannot explain this correlation. Long range physical interactions like diffusion or electric attractions should be involved. A biophysical model (BM) has been formulated which cooperates with the biomolecular processes and describes the data successfully. Hundred years ago E. Noether made a fundamental discovery in Mathematics and Physics. She proved rigorously that a physical system obeying a symmetry law (e.g.rotations or self similarity) is linked to a conserved physical quantity. It is argued here that HGC obeys a ‘primitive’ self similarity symmetry of the genes of a Hox cluster along a finite straight line. In the case of Vertebrates, the associated partially conserved quantity is the ever increasing ‘ratchet’- like gene ordering where some Hox genes are missing. Another application of Noether’s Theory is performed to rotationally symmetric embryos like the sea urchin.

This paper explores the views of a group of young men aged 16–18, studying towards a Level 1 diploma in music in the North East area of England. It uses the conceptualization of “social haunting” to focus our discussions about how Level 1 learners articulated their experiences in the context of their learning journeys and perceived marginalization. The research took place at a large Further Education (FE) college and included a series of five “research encounters” with the group of Level 1 learners. These encounters included a range of activities, resulting in a variety of data being collected, including several activity worksheets, structured and unstructured focus group interviews, and questionnaires. This paper focusses on the outcomes of a single research activity that focused on exploring the topic of marginalization. We present a discussion on social haunting as one of the emerging findings from this research encounter, outlining how the reality of the social and cultural legacy of the UK’s industrial past can shape today’s youth and their futures. We will talk about the young men’s views of marginalization, their school-to-work transitions, the formation of masculinity in post-industrial communities and the role of Further Education in it. The paper concludes by discussing some insights for practice and future research.

The purpose of this study was to identify potential causes of violence and crime in informal settlements and residents’ strategies for response and prevention to these issues, as perceived by women living in Mathare informal settlement in Nairobi, Kenya. A total of 55 in-depth interviews were conducted with women living in the informal settlement in 2015-2016. A modified grounded theory approach was used to guide data collection and analysis. The most common contributor to violence and crime identified by women in Mathare informal settlement was idle youth, but leadership and government challenges, corruption and/or inadequacy of police, community barriers, tribalism, and lack of protective infrastructure also emerged as contributing factors. Despite facing many economic, environmental, and day-to-day challenges, women in Mathare identified violence and crime as predominant issues; thus, developing effective response and prevention strategies to these issues in informal settlements is paramount. Women suggest there are many strategies and initiatives to reduce and prevent violence and crime in informal settlements, but also identified barriers to implementing them. Findings suggest there is a need for trust-building between formal and informal organizations and institutions, systems of accountability, and long-term investment to foster sustainable and effective violence and crime response and interventions in these settlements.

We will apply Pascal’s hydrostatic pressure law to black holes and also to the Hubble sphere. Haug has recently demonstrated how hydrostatic pressure in water can be utilized to determine the Planck length. One can conceptualize the energy in the Hubble sphere as a type of superfluid, and if this is correct, then Blaise Pascal’s hydrostatic pressure formula may also be applicable to such a superfluid, even within the Hubble sphere. By employing the same method on the Hubble sphere and considering it as a Schwarzschild black hole with the critical Friedmann mass, we can estimate the Planck length based on its hypothetical hydrostatic pressure.

Gc protein-derived Macrophage Activating Factor (GcMAF), a powerful immunostimulant endowed with anti-cancer and anti-angiogenetic activities, offers significant advantages when combined with radiation therapy. A stronger immune response improves the effectiveness of radiation therapy by allowing the body to better eliminate residual cancer cells after treatment. In addition, by boosting the immune system, GcMAF mitigates some of the immunosuppressive side effects of radiation therapy, leading to faster recovery. In order to fully exploit the potential of GcMAF in cancer therapy, knowledge of the molecular interactions with its receptor is essential. This study proposes the first extracellular domain (residues 1-34) of the CCR1 protein as the GcMAF receptor. The CCR1 gene, expressed in monocytes and 168 other cell types or tissues, encodes this transmembrane protein. Electrostatic and hydrophobic interactions, along with hydrogen bonds mediate the molecular interactions between the TPT^420-GalNAcELAK (or TPK⁴²⁰ELAK) sequences of GcMAF (or Gc2 protein variant) and the TTEDYDTTT sequence of its receptor.

In the field of delta-sigma modulators, reducing system power consumption without sacrificing accuracy has become a challenge. The summing circuit, as the main part of the cascade-of-integrator-in-feedforward delta-sigma modulator, consumes a significant amount of power in active summing. On the other hand, passive summing circuits have low power consumption but can cause attenuation in the summing results. This article proposes a low-power multi-bit delta-sigma modulator based on passive and attenuationless summation scheme. The summation circuit achieves multiplication of the voltage signal carried on the summation capacitor through bidirectional sampling technique, compensating for the inherent attenuation caused by passive summation, thus eliminating the need for active OTA to achieve perfect summation. A 2-order delta-sigma modulator based on 4-bit 1-order passive noise-shaping (NS) SAR quantizer is designed to verify the scheme. By combining a passive NS SAR as the 4-bit quantizer and the third-stage integrator of the system, and incorporating an energy-efficient cascode floating inverter amplifier (FIA) structure as the core active OTA, these elements have significantly enhanced the energy-efficiency of the modulator. Simulation results show that at a supply voltage of 1.2 V and a bandwidth of 20 kHz, the SNDR reaches 102.62 dB, power consumption is only 148.32 μW, and Schreier figure-of-merit (FoM) of SNDR is 183.92 dB.

Dirac's Large Number Hypothesis (LNH), proposed in 1937, has captivated the scientific community with its exploration of profound correlations between cosmic and atomic scales. This hypothesis delves into the intricate interplay between the infinitesimally small and the vastly large, offering potential insights into the fundamental nature of the universe. As we continue to uncover the mysteries of the cosmos, the LNH oscillates on the precipice of scientific acceptance—neither fully validated nor entirely dismissed. In this review paper, we embark on a comprehensive journey through Dirac's LNH, shedding light on its theoretical underpinnings, its implications for universe models, and its resonance with the Anthropic Principle. We delve into the possibilities of variable gravitational constants and continuous mass creation, inviting further exploration into the intricacies of our cosmic symphony. By embracing the ongoing quest for understanding, we endeavor to unravel the profound harmonies that connect the infinitesimal with the infinite, contributing to the symphony of knowledge in theoretical physics and cosmology.

This paper is a part of the broader research on “Adaptation of Laws in Science” and explores the limitations and challenges involved in adapting mathematical concepts to describe natural reality in physics. Specifically, the analysis focuses on two major examples: Euler's exponential laws and spacetime dilation derived from Lorentz transformations. By examining these concepts, the paper emphasizes that some complex laws are not universally applicable for deeper studies of nature, as they originate from mathematics and are correct only for specific parts of nature to which they have been adapted. These complex laws are particularly unsuitable where there is limited information available for adaptation. Therefore, without appropriate adaptations and a deep understanding of the physical context under investigation, the direct use of complex laws can lead to incorrect results. It is essential to avoid excessive generalization of these laws, once they become part of physics, unless a corresponding adaptation to the research context can be made. Furthermore, this paper supports the correctness of relativity theories by invoking that, like Euler's exponential growth theory, they were initially mathematical concepts. However, the nature of mathematics coincided with that of the phenomena in our universe, although through certain adaptations.

Theories of quantum gravity suggest that Lorentz invariance, the fundamental symmetry of the Theory of Relativity, may be broken at the Planck energy scale. While any deviation from conventional Physics must be minuscule in particular at attainable energies, this hypothesis motivates ever more sensitive tests of Lorentz symmetry. In the photon sector, astrophysical observations, in particular polarization measurements, are a very powerful tool because tiny deviations from Lorentz invariance will accumulate as photons propagate over cosmological distances. The Standard-Model Extension (SME) provides a theoretical framework in the form of an effective field theory that describes low-energy effects due to a more fundamental quantum gravity theory by adding additional terms to the Standard Model Lagrangian. These terms can be ordered by the mass dimension d of the corresponding operator and lead to a wavelength, polarization, and direction dependent phase velocity of light. In this paper, we analyze optical polarization measurements from 63 Active Galactic Nuclei (AGN) and Gamma-ray Bursts (GRBs) in order to search for Lorentz violating signals. We derive the first set limits on each of the 10 individual birefringent coefficients of the minimal SME with d = 4, with 95% confidence limits on the order of 10⁻³⁴ on the dimensionless coefficients.

This article explores the efficiency of various clustering methods for image segmentation under different luminosity conditions. Image segmentation plays a crucial role in computer vision appli-cations, and clustering algorithms are commonly used for this purpose. The search for an adaptive clustering mechanism aims to ensure maximum symmetry of real objects with objects/segments in their digital representations. However, clustering methods performance can fluctuate with varying lighting conditions during image capture. Therefore, we assess the performance of several clustering algorithms — including k-means, K-Medoids, fuzzy c-means, Possibilistic C-Means, Gus-tafson-Kessel, Entropy-based Fuzzy, Riddler-Calvard, Kohonen Self-Organizing Maps, and Meanshift — across images captured under different illumination conditions. Additionally, we develop an adaptive image segmentation system utilizing empirical data. Conducted experiments highlight varied performance among clustering methods under different luminosity conditions. This research enhance better understanding of luminosity's impact on image segmentation and aiding in method selection for diverse lighting scenarios.

Dynamical manipulation of plasmon-induced transparency (PIT) in graphene metasurfaces is promising for optoelectronic devices such as optical switching and modulating, however, previous design approaches are limited within one or two bright/dark modes, and the realization of dual PIT windows through triple bright modes in graphene metasurfaces is rare and urgently needed. Here we demonstrate that dual PIT can be realized through a symmetry-engineered graphene metasurface, which consists the graphene central cross (GCC) and graphene rectangular ring (GRR) arrays. The GCC supports a bright mode from electric dipole (ED), the GRR supports two nondegenerate bright modes from ED and electric quadrupole (EQ) due to the C2v symmetry breaking, and the resonant coupling of these three bright modes induces the dual PIT windows. A triple coupled-oscillator model (TCM) is proposed to evaluate the transmission performances of the dual PIT phenomenon, and the results are in good agreement with the finite-difference time-domain (FDTD) method. In addition, the dual PIT windows are robust to the variation of the structural parameters of the graphene metasurface except the y-directioned length of the GRR. By changing the carrier mobility of graphene, the amplitudes of the two PIT windows can be effectively tuned. The alteration of the Fermi level of graphene enables the dynamic modulation of the dual PIT with good performances for both modulation degree (MD) and insertion loss (IL).

The paper's main goal is to introduce a novel type of interpolative convex contraction and build up some fresh findings for it using the interpolative convex contractions' progressive approach. We have established certain conclusions using orbitally S-complete and Suzuki type contractions in F-metric spaces. My research aims to examine the fixed point method's efficacy in solving fractional differential equation with boundary conditions.

We investigate the dynamics and stationary states of a semiconductor exciton-polariton condensate in a double well potential. We find that upon the population build up of the polaritons by above-threshold laser pumping, coherence relaxation due to the phase fluctuations of the polaritons drives the system into a stable fixed point corresponding to a self-organized PT-symmetric phase.

In this paper, we study the symmetry between the supersingular prime number according to smallest sphenic number. With this symmetry, we show that the elements of sporadic group generates all prime numbers with the order by a simple application.

We propose a description of the electromagnetic field in the form of a four-component complex spinor, from which a vector of electromagnetic potential with two degrees of freedom, calibrated by two conditions - zero length and zero component along the y-axis - is obtained by using Pauli matrices. A similar approach is applied to the field of a fermion, in particular, the electron. It is known that the quantum field of the electron and the electron itself is a four-component complex spinor, so, existing in the Minkowski vector space, we cannot observe it directly. But with the help of Pauli matrices a vector is formed from the electron spinor, which is known to us as an electric current vector, and this current vector describes exactly a single particle. As a vector, it is available to us for observation in our vector space. Similarly, the electromagnetic field and its photon particle is also a four-component spinor, from which the universal formula using Pauli matrices produces a vector, it is known to us as the electromagnetic potential vector, and it too describes even a single photon. All the differences in the properties of the current vector and the electromagnetic potential vector, and hence the electron and the electromagnetic field, are due only to a slight difference in the structures of their four-component spinors and inextricable linked to them momentum spinors and coordinate spinors. Expressions for the electric and magnetic fields of a photon during its interaction with an electron.Thus, a unified way to describe bosons and fermions in spinor space is proposed. Each spinor using the same formula corresponds to a vector, in the case of a fermion it is a current vector, in the case of a boson it is a vector, for example, of the electromagnetic potential. Each spinor of a field is matched with a spinor of coordinates and a spinor of momentum, which are transformed by the same Lorentz transformations and which have the same structure as their corresponding field spinor, that is, the momentum and coordinates of boson have a bosonic spinor structure, while momentum and coordinates of fermion are a spinor with a fermionic structure. Field, coordinates and momentum vectors of boson automatically have a zero length, while in the case of fermion they all have a nonzero length, so the fermion, in contrast to the boson, has a nonzero mass, nonzero charge and moves with a sub light speed.While quantum mechanics treats probability as a real number, quantum field theory deals with probability as a four-dimensional real vector. The place of the probability amplitude, which in quantum mechanics is a complex number, in quantum field theory is taken by a complex spinor.In the same way as in quantum mechanics the processes of propagation and interaction are described at the level of complex probability amplitudes, and the final result is translated into a real probability value, so in quantum field theory all processes should be described in terms of complex spinor space, and the result is translated into the form of a real vector in Minkowski space.The presented approach, at its proper development, makes it possible to carry out calculations of the interaction of particles in two-dimensional spinor space, and to interpret in terms of the Minkowski vector space only the final results.

The response of plasmonic metal particles to an electromagnetic wave undergoes significant features at the nanoscale level. Different properties of the internal composition of a metal, such as its ionic background and the free electron gas, begin to manifest more prominently. As the dimensions of the nanostructures decrease, the classical local theory gradually becomes inadequate. Therefore, Maxwellʹs equations need to be supplemented with a relationship determining the dynamics of current density which is the essence of nonlocal plasmonic models. In this field of physics, the standard (linearized) hydrodynamic model (HDM) has been widely adopted with great success, serving as the basis for a variety of simulation methods. However, ongoing efforts are also being made to expand and refine it. Recently, the GNOR (general nonlocal optical response) modification of the HDM has been used, with the intention of incorporating the influence of electron gas diffusion. Clearly, from the classical description of fluid dynamics, a close relationship between viscosive damping and diffusion arises. This offers a relevant motivation for introducing the GNOR modification in an alternative manner. The standard HDM and its existing GNOR modification also do not include the influence of interband electron transitions in the conduction band and other phenomena that are part of many refining modifications of the Drude‐Lorentz and other models of metal permittivity. In this article, we present a modified version of GNOR‐HDM that incorporates the viscosive damping of the electron gas and a generalized Drude‐Lorentz term. In the selected simulations, we also introduce Landau damping which corrects the magnitude of the standard damping constant of the electron gas based on the size of the nanoparticle. We have chosen a spherical particle as a suitable object for testing and comparing HD models and their modifications because it allows finding precise analytical solutions for the interaction and, simultaneously, it is a relatively easily fabricable nanostructure in practice. Our contribution also includes our own analytical method for solving the HDM interaction of a plane wave with a spherical particle. This method forms the core of calculations of the characteristic quantities, such as the extinction cross‐sections and the corresponding components of electric fields and current densities.

The behaviour and bifurcations of solutions to three-dimensional (three-phase) quadratic polynomial dynamical systems (DSs) are considered. The integrability in elementary functions is proved for a class of autonomous polynomial DSs. The occurrence of bifurcations of the type twisted fold is discovered on the basis and within the frames of the elements of the developed DS qualitative theory. The discriminant criterion applied originally to two-phase quadratic polynomial DSs is extended to three-phase DSs investigated in terms of their coefficient matrices. Specific classes of D- and S-vectors are introduced and complete description of the symmetry relations inherent to the DS coefficient matrices is performed using the discriminant criterion.

Over the last few decades, advancements in astrophysics have been closely linked to the development of powerful machine-learning models that can accurately classify celestial bodies. At the same time, however, many astronomical datasets are filled with new features collected by increasingly powerful telescopes. These features can cause overfitting, clouding predictive abilities, and dampening the ability of many models to classify images. Therefore, motivation to design more efficient models has skyrocketed—aiming to optimize for lower run times and high accuracies, even with fewer provided features. In our project, we seek to optimize a convolutional neural network model using a technique known as wavelet analysis. This technique allows us to pick the key features of an astronomical image and accentuate niche details, saving time and boosting accuracy. We applied it to the MiraBest Dataset, a dataset compiled from the FIRST sky survey using a virtual telescope. In the end, after training our neural network on the original images and the five filters (approximation, horizontal, vertical, diagonal, and combined), we found that with fewer features and less overfitting, the vertical Daubechies-family wavelet filter outperformed the original runs with the unaltered images by over 10%. Our findings suggest that wavelet analysis can help harvest the most valuable features in images of celestial bodies–leading to enhanced predictions in astronomical applications and perhaps bolstering modern astrophysical theory.

Prostate cancer is the second most frequent malignancy (after lung cancer) in men worldwide. Prostate tissue biopsies are usually graded using scores according to the Gleason grading system. This Gleason score is the most popular prognostic marker that reveals the potential aggressiveness of the disease. However, inter-observer variability in rating by human assessors is a major limiting factor. Such variability could lead to missing a severe case or suggesting unnecessary treatments. This study explores the discriminative ability of artificial intelligence (deep learning models) for Gleason score assessment. The study was designed to use whole-slide images of digitized H&E-stained biopsies of prostate tissues to automate the grading process and provide a remotely accessible clinical decision support system. Custom convolutional neural network architectures were trained on 10,616 images of prostate tissues. Gaussian filters were applied to pre-process the images and improve model performance. Transfer learning was applied to train eight machine learning architectures namely: Xception, VGG16 & 19, ResNet101, MobileNet, DenseNet121, EfficientNetB5 & B7. Efficient NetB7 had the best performance 85.2% compared with ground-truth classification by experts. Performance improves as more data is available. The model was deployed and hosted as a web application API on Google cloud service to ensure remote access. Tissue biopsy images can be uploaded and the corresponding Gleason score recovered immediately. This system reduces diagnostics turnaround time, increase throughput, and compensate for limited skills, especially in low resource settings.

To accurately identify high-quality functional wood with superior mechanical properties and enhance its durability, it is imperative to understand the relationships between the physical and mechanical attributes of diverse wood types. Presently, there exist issues related to accuracy, efficiency, and differentiation in studying these performance correlations. The Liang Kleeman (L-K) information flow theory, a causative analytical approach rooted in fundamental physics principles, offers swift computational capabilities. Furthermore, the coefficient of variation in L-K information flow quantitatively gauges the intensity of causal effects. Therefore, this article adopts a causal artificial intelligence perspective and introduces a wood performance analysis method based on L-K information flow.This study focuses on four Chinese fir varieties, including fast-growing Chinese fir (YKS), red heart Chinese fir (CSH, XXH), and iron heart Chinese fir (XXT). By computing and comparing variation coefficients of L-K information flow for various physical properties and their impact on mechanical properties, causal relationships between these properties are elucidated. These findings are then applied to predict wood mechanical properties, achieving a remarkable maximum accuracy of 90%.In the future, these findings will prove invaluable for the selection of high-quality wood and for improving the manufacturing process to prolong the service life of functionalized wood.

In this work, the properties of a composition based on synthetic rubber ethylene-propylene ter-polymer and polymers with functional groups of the mixture are studied. Low efficiency of some compositions based on ethylene and propylene copolymer limits their use in the production of tires and rubber products. Therefore, we conducted a study to improve the disadvantages of SREPT-60 using butyl rubber + choro polyisoprene + butadiene-nitrile + butadiene styrene rubber and adding a plasticizer to the composition = α, methacrylate-(bis-diethylene glycol phthalate) -(btegf-9) The data obtained showed that a number of its indicators of rubber based on them were improved. Tear resistance, resistance to repeated stretching increased, adhesion of the composition to metal, chemical resistance increased, the degree of swelling in benzene and gasoline-benzene mixture decreased. Compositions based on the mixture SREPT-60 using butyl rubber + choro polyisoprene + butadiene-nitrile + butadiene styrene rubber and adding a plasticizer to the composition = α, methacrylate-(bis-diethylene glycol phthalate) -(btegf-9) +Dioctyl phthalate: (70:20:10) have high resistance to swelling in an aggressive environment (Benzene, gasoline, alcohol, acid, oil, etc.) mixture.

Aim: the main aim of this study is to compare the onset of effectiveness of mental nerve block with lingual infiltration and inferior alveolar nerve block on patients visiting dental hospital for extraction of mandibular anterior teeth. Materials and methods: The study was set in a clinical setting. This was a randomized controlled double-blind cross study, where 25 subjects received two treatments at an interval of at least 1 week in a within a dental hospital.Inferior alveolar nerve block and lingual nerve block injection is given with 2mL lignocaine 2% with 1:2,00,000 epinephrine was administered for the right side. Mental nerve block along with lingual infiltration of the corresponding tooth was given with 2mL lignocaine 2% with 1:2,00,000 epinephrine was administered on the left side.Visual analogue scale (VAS) was used in this study, which consists of a scale with range of 0-10 pain severity on which 0 indicated absence of pain and 10 the worst pain possible. The patients were asked to give scores corresponding to his/her pain, after IANB, mental nerve block and lingual infiltration and these scores were recorde.Results: From the results we can see that patients gave scores between 3-4, stating that they had moderate pain during extraction after administration of IANB (54%) (graph 2) and VAS scores of 0-1 were given by patients, which is suggestive of no pain during extraction after administration of Mental nerve block and lingual nerve infiltration (62%)Conclusion: Within the limits of the study we can conclude that mental nerve block along with lingual infiltration is an effective way to completely and quickly anaesthetise the central incisor to the 1st premolar region.

The possibility of a shock wave recovery at a discrete closed interface with a heated gas has been investigated. A two-dimensional model applied to conditions of optical discharges featuring spherical, elliptical, and drop-like configurations demonstrated that non-symmetry in the shock refraction contributes to the specific mechanism of recovery other than simply its compensation. Even though the full restoration of the hypersonic flow state doesn’t occur in a strict sense of it, clear reverse changes toward the initial shape of the shock front eventually take place, thus creating an appearance of a full recovery seen in experiments. From analysis for different interfaces symmetries, the factors determining the recovery dynamics are identified. The results are directly applicable to the problem of energy deposition into a hypersonic flow, however it can be useful anywhere else where the flow modifications following the interaction are important. The dimensionless form of the equations allows applications on any scale other than that demonstrated for the optical discharges.

Introduction: In Traditional Chinese Medicine (TCM), tongue diagnosis plays an important role. Besides shape, colour and textural attributes of tongue regions have significance due to their association with different organs (viz. heart, lung, kidney-bladder, liver-gallbladder and stomach-spleen) in health and disease. Although numerous quantitative methods have been proposed to reduce inter and intra observer variability in tongue diagnosis, almost all of them considered only global colour/ textural features i.e. from entire body of tongue. In this work, regional colour and texture information of tongue have been analysed for healthy subjects (NOM) and patients suffering from chronic acidity-indigestion (ACD). Methods: Tongue boundaries are marked manually in each image and then tongue bodies are automatically partitioned into five regions linked with said internal organs. Rough assessments of regions’ boundaries are obtained from literature and then they are fine-tuned according to experts’ advice. As boundaries are not well defined, regions near the common boundary of two or more organs, are not assigned to any organ. Several first and second order statistical features based on grey scale intensities and a* values of LAB colour space (indicative of redness) have been extracted from five different regions of tongue images. Intragroup analysis using Wilcoxon signed rank test compared different regions within individual study group. Additionally, intergroup analysis using Wilcoxon rank sum test compared tongues of NOM with ACD for each region separately. Results: Intragroup analysis reveals a* values are statistically different (p&lt;0.01) between stomach-spleen and liver-gallbladder regions for ACD while no significant change of a* are noted between these regions of normal tongue. It was found from intergroup analysis that correlation (one of the second order texture features extracted from grey scale images) of heart region has significantly decreased while correlation of kidney, liver-gallbladder and stomach-spleen regions significantly increased from NOM to ACD. Conclusion: This study sheds light on importance of inclusion of regional textural analysis of tongue in quantitative studies and can be applied to automated tongue diagnosis for other diseases.

Quantum chemical topology addresses the study of the chemical structure by applying the tools of differential topology to scalar and vector fields obtained by quantum mechanics. Here the magnetically induced isotropically averaged Lorentz force density has been computed and topologically analysed for 11 small molecules. Critical points (attractors, repellers and saddles) have been determined and trajectories connecting the attractors have been computed. It is shown that kinds and numbers of the critical points are rather transferable in similar molecules. CC bonds of different order are endowed with critical points of different kind close to their centre. The long range behaviour of the force allows understanding the value of the sum of topological indices of the isolated critical points.

We solve the problem of Apollonius by applying the Lorentz transformation within the frame- work of special relativity to go to a frame of simultaneity, where the solutions are the circum- center. We transform back to get the solutions in a general frame. We show that the solutions in a general frame are the foci of the ellipse going through the centers of the given 3 circles.

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

A cloud of relativistic material particles is considered, for which the distortions of length and time caused by the presence of the Lorentz factor an order of magnitude greater than curvature of space-time by gravity. The gravitational mass of the cloud is found in the region where its size is insignificant. It is established that the coefficient of dependence of the cloud mass on the total rest mass of its particles includes a complete elliptic integral of the 2nd kind.