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Where Is Phase Velocity in Minkowski Space?

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j.urnal of Modern Physics 2024年第10期15卷 1555-1566页

作者： Antony j. Bourdillon Ultra-High Resolution Lithography San Jose CA USA

In the special theory of relativity, massive particles can travel at neither the speed of light c nor faster. Meanwhile, since the photon was quantized, many have thought of it as a point particle. How pointed? The idea could be a mathematical device or physical simplification. By contrast, the preceding notion of wave-group duality has two velocities: a group velocity vg and a phase velocity vp. In light vp = vg = c;but it follows from special relativity that, in massive particles, vp > c. The phase velocity is the product of the two best measured variables, and so their product constitutes internal motion that travels, verifiably, faster than light. How does vp then appear in Minkowski space? For light, the spatio-temporal Lorentz invariant metric is s2=c2t2−x2−y2−z2, the same in whatever frame it is viewed. The space is divided into 3 parts: firstly a cone, symmetric about the vertical axis ct > 0 that represents the world line of a stationary particle while the conical surface at s = 0 represents the locus for light rays that travel at the speed of light c. Since no real thing travels faster than the speed of light c, the surface is also a horizon for what can be seen by an observer starting from the origin at time t = 0. Secondly, an inverted cone represents, equivalently, time past. Thirdly, outside the cones, inaccessible space. The phase velocity vp, group velocity vg and speed of light are all equal in free space, vp = vg = c, constant. By contrast, for particles, where causality is due to particle interactions having rest mass mo > 0, we have to employ the Klein-Gordon equation with s2=c2t2−x2−y2−z2+mo2c2. Now special relativity requires a complication: *** = c2 where vg c and therefore vp > c. In the volume outside the cones, causality due to light interactions cannot extend beyond the cones. However, since vp > c and even vp >> c when wavelength λ is long, extreme phase velocities are then limited in their causal effects by the particle uncertainty σ,

关键词： Event Horizon Scattering Range Wave Packet Phase Velocity Group Velocity Dispersion Dynamics Quantum Physics

Mass-Based Environmental Factor and Energy Assessment of Microwave-Assisted Synthesized Transition Metal Nanostructures

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American j.urnal of Analytical Chemistry 2024年第6期15卷 201-218页

作者： Victor j. Law School of Mechanical and Materials Engineering University College Dublin Dublin Ireland

This paper describes mass-based energy phase-space proj.ction of microwave-assisted synthesis of transition metals (zinc oxide, palladium, silver, platinum, and gold) nanostructures. The proj.ction uses process energy budget (measured in kj. on the horizontal axes and process density (measured in kj.−1) on the vertical axes. These two axes allow both mass usage efficiency (Environmental-Factor) and energy efficiency to be evaluated for a range of microwave applicator and metal synthesis. The metrics are allied to the: second, sixth and eleventh principle of the twelve principle of Green Chemistry. This analytical approach to microwave synthesis (widely considered as a useful Green Chemistry energy source) allows a quantified dynamic environmental quotient to be given to renewable plant-based biomass associated with the reduction of the metal precursors. Thus allowing a degree of quantification of claimed “eco-friendly” and “sustainable” synthesis with regard to waste production and energy usage.

关键词： Microwave-Assisted Synthesis Transition Metals Nanostructures Allometry Scaling Power-Law Signature Green Chemistry

j.vian Planet Influence on the Forcing of Sunspot Cycles

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World j.urnal of Condensed Matter Physics 2024年第1期14卷 1-9页

作者： Fred j. Cadieu Physics Department Queens College of CUNY New York USA

The history of our solar system has been greatly influenced by the fact that there is a large gas giant planet, j.piter that has a nearly circular orbit. This has allowed relics of the early solar system formation to still be observable today. Since j.piter orbits the Sun with a period of approximately 12 years, it has always been thought that this could be connected to the nearly 11-year periodic peak in the number of sunspots observed. In this paper, the Sun and planets are considered to be moving about a center of mass point as the different planets orbit the Sun. This is the action of gravity that holds the solar system together. The center of mass for the j.piter-Sun system actually lies outside the Sun. The four gas giant planets dominate such effects and the four gas giant j.vian planets can be proj.cted together to determine an effective distance from the Sun’s center. Taken together these effects do seem to function as a sunspot forcing factor with a periodicity very close to 11 years. These predictions are made without consideration of any details of what is happening in the interior of the Sun. From these estimates, sunspot cycle 25 will be expected to peak in about September-October of 2025. Sunspot cycle 26 should peak in the year March of 2037.

关键词： Sun Cycles Solar System Formation j.piter

Adaptive Random Effects/Coefficients Modeling

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Open j.urnal of Statistics 2024年第2期14卷 179-206页

作者： George j. Knafl School of Nursing University of North Carolina at Chapel Hill Chapel Hill USA

Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.

关键词： Adaptive Regression Correlated Outcomes Extended Linear Mixed Modeling Fractional Polynomials Likelihood Cross-Validation Random Effects/Coefficients

A systematic review of risk prediction models for diabetic foot infections

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Chinese j.urnal of Nursing 2024年第19期59卷 2346-2352页

作者： Zhu j. Chen X. Zhu Y. Zhou j. Bai j. 复旦大学附属华东医院护理部上海市200040 中国医学科学院皮肤病医院麻醉手术科复旦大学护理学院

Obj.ctive To systematically evaluate the risk prediction models of diabetic foot infections, and to explore its implications for clinical nursing care. Methods Relevant studies in the databases of CNKI, VIP, Wanfang, CBM, CINAHL, PubMed, Web of Science, Cochrane Library, Embase, ProQuest, and Ovid were searched for the timeframe of database construction to December 2023. Literature was screened independently by 2 investigators and the area under the model curve(AUC) and its 95% confidence interval(CI), calibration method and predictors were extracted, and the quality of the model was evaluated using the Predictive Modeling Study Risk of Bias Assessment Tool. Meta-analysis of the predictive value of model predictors was performed using RevMan 5.4 software. Results 7 studies were included, containing 8 risk prediction models, all of which reported the AUC(0.748-0.922), and 6 models underwent model calibration. The overall fit of the included studies was good, among which 1 model was low fit, and all 7 studies were at high risk of bias, mainly focusing on predictors and analysis. Meta-analysis showed that the area under the curve of the combined models was 0.831(95%CI:0.780~0.883);the disease duration(OR=2.460, 95%CI:1.850~3.270), vascular disease(OR=3.110, 95%CI:1.070~9.000), and neuropathy(OR=3.550, 95%CI:1.920~6.560) were effective predictors of diabetic foot infection. Conclusion The current diabetic foot infection risk prediction model is still in the developmental stage, and further optimization and external validation of the existing model is recommended for the future. © 2024 Chinese Nursing j.urnals Publishing House Co.,Ltd. All rights reserved.

关键词： Diabetic Foot Evidence-Based Nursing Infections Prediction Model Systematic Review

The Reality of Baryonic Acoustic Oscillations

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j.urnal of Modern Physics 2024年第3期15卷 377-402页

作者： j. C. Botke Ronin Institute Montclair New Jersey USA

The initial idea for baryonic acoustic oscillations (BAO) came about during early efforts to understand the origin of galaxies by studying perturbed versions of the Friedmann-Robertson-Walker (FRW) model. In more recent times, the emphasis has shifted to the idea that 2-point galaxy correlations embedded in the distribution of matter by the BAO could be used as a standard ruler to fix the parameters of cosmological models. In this paper, we first consider the actual business of extracting the correlation length from large data sets of measured galaxy locations. To facilitate this process, we introduce a much-improved method for extracting the correlation peak from the data set. Fundamental to this process in any model is the use of a fiducial cosmological model to transition from redshift space to comoving coordinate space where the correlations actually exist. The belief is that the correlation length so determined can then be reverted to redshift space to fix the parameters of cosmological models. We show, however, that this process is circular and hence of no value whatsoever for fixing model parameters. All one obtains are the parameters of the model used to transition to comoving space in the first place. Finally, we present simple arguments that show that the idea of BAO being responsible for the structure of the universe, i.e. the cosmic web, is unworkable.

关键词： Baryonic Acoustic Oscillations Two-Point Correlations CMB Anisotropy Early Universe Time-Varying Curvature

The Origin of Cosmic Structures Part 6: CMB Anisotropy

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j.urnal of High Energy Physics, Gravitation and Cosmology 2024年第1期10卷 257-276页

作者： j. C. Botke Ronin Institute Montclair New Jersey USA

In a recent series of papers, we introduced a new model of nucleosynthesis in which the matter content of the universe came into existence at a time of about 4 × 10-5 s. At that time, a small percentage of the vacuum energy was converted into neutron/antineutron pairs with a very small excess of neutrons. This process was regulated by an imprint that was established in the vacuum during an initial Plank-era inflation. Immediately after their inception, annihilation and charge exchange reactions proceeded at a very high rate and ran to completion after an interval of about 10-11 s. By then, all the antibaryons had disappeared thereby establishing the matter/antimatter asymmetry of the universe. What remained were very high densities of mesons and leptons, somewhat lower densities of protons and neutrons, and finally, the very high density of photons that eventually became the CMB. The density of matter so created varied from one location to another in such a manner as to account for all cosmic structures and because the energy density of the photons varied in proportion to that of the matter, the CMB-to-be came into existence with an anisotropic spectrum already in place. For structures, the size of galaxy clusters, the initial anisotropy magnitudes were on the order of 25%. In this paper, we will follow the subsequent evolution of the photons and show that this model predicts with accuracy the temperature of the warmest anisotropies in the observed CMB spectrum. .

关键词： CMB Anisotropy Dispersion Nucleosynthesis Early Universe Time-Varying Curvature

Graph Attention Residual Network Based Routing and Fault-Tolerant SchedulingMechanism for Data Flow in Power Communication Network

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Computers, Materials and Continua 2024年第1期81卷 1641-1665页

作者： Lin Z. Zeng Z. Yu Y. Ren Y. Qiu X. Chen j. State Key Laboratory ofNetworking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China State Grid j.angsu Electric Power Co. Ltd Nanjing 210008 China

For permanent faults (PF) in the power communication network (PCN), such as link interruptions, the timesensitive networking (TSN) relied on by PCN, typically employs spatial redundancy fault-tolerance methods to keep service stability and reliability, which often limits TSN scheduling performance in fault-free ideal states. So this paper proposes a graph attention residual network-based routing and fault-tolerant scheduling mechanism (GRFS) for data flow in PCN, which specifically includes a communication system architecture for integrated terminals based on a cyclic queuing and forwarding (CQF) model and fault recovery method, which reduces the impact of faults by simplified scheduling configurations of CQF and fault-tolerance of prioritizing the rerouting of faulty time-sensitive (TS) flows; considering that PF leading to changes in network topology is more appropriately solved by doing routing and time slot inj.ction decisions hop-by-hop, and that reasonable network load can reduce the damage caused by PF and reserve resources for the rerouting of faulty TS flows, an optimization model for j.int routing and scheduling is constructed with scheduling success rate as the obj.ctive, and with traffic latency and network load as constraints; to catch changes in TSN topology and traffic load, a D3QN algorithm based on a multi-head graph attention residual network (MGAR) is designed to solve the problem model, where the MGAR based encoder reconstructs theTSNstatus into feature embedding vectors, and a dueling network decoder performs decoding tasks on the reconstructed feature embedding vectors. Simulation results show that GRFS outperforms heuristic fault-tolerance algorithms and other benchmark schemes by approximately 10%in routing and scheduling success rate in ideal states and 5% in rerouting and rescheduling success rate in fault states. © 2024 The Authors. Published by Tech Science Press.

关键词： deep reinforcement learning fault tolerance graph attention network Time-sensitive network

Modeling of Total Dissolved Solids (TDS) and Sodium Absorption Ratio (SAR) in the Edwards-Trinity Plateau and Ogallala Aquifers in the Midland-Odessa Region Using Random Forest Regression and eXtreme Gradient Boosting

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j.urnal of Geoscience and Environment Protection 2024年第5期12卷 218-241页

作者： Azuka I. Udeh Osayamen j. Imarhiagbe Erepamo j. Omietimi Department of Geoscience University of Texas Permian Basin Odessa Texas USA Department of Geology University of Pretoria Pretoria South Africa

Efficient water quality monitoring and ensuring the safety of drinking water by government agencies in areas where the resource is constantly depleted due to anthropogenic or natural factors cannot be overemphasized. The above statement holds for West Texas, Midland, and Odessa Precisely. Two machine learning regression algorithms (Random Forest and XGBoost) were employed to develop models for the prediction of total dissolved solids (TDS) and sodium absorption ratio (SAR) for efficient water quality monitoring of two vital aquifers: Edward-Trinity (plateau), and Ogallala aquifers. These two aquifers have contributed immensely to providing water for different uses ranging from domestic, agricultural, industrial, etc. The data was obtained from the Texas Water Development Board (TWDB). The XGBoost and Random Forest models used in this study gave an accurate prediction of observed data (TDS and SAR) for both the Edward-Trinity (plateau) and Ogallala aquifers with the R2 values consistently greater than 0.83. The Random Forest model gave a better prediction of TDS and SAR concentration with an average R, MAE, RMSE and MSE of 0.977, 0.015, 0.029 and 0.00, respectively. For the XGBoost, an average R, MAE, RMSE, and MSE of 0.953, 0.016, 0.037 and 0.00, respectively, were achieved. The overall performance of the models produced was impressive. From this study, we can clearly understand that Random Forest and XGBoost are appropriate for water quality prediction and monitoring in an area of high hydrocarbon activities like Midland and Odessa and West Texas at large.

关键词： Water Quality Prediction Predictive Modeling Aquifers Machine Learning Regression eXtreme Gradient Boosting