Recently, cloud technology has become popular for smart societies. The Cloud technology has made dynamical network changes by enabling the construction of a logical network without building a physical network. Despite recent research on the cloud, it is necessary to study security functions for the identification of fake VNFs and the encryption of communication between entities. In this paper, we proposed an LW_PKI mechanism that detects a fake VNF and guarantees data security through mutual authentication between VNFs. To evaluate the LW_PKI, we built a MANO environment to test the performance of authentication and key generation for data security. In addition, we applied the artificial intelligence algorithm to detect abnormal behavior by using real attack data in the MANO environment. The LW_PKI guaranteed the reliability of a smart service by enhancing the security of the cloud environment.

Aiming at the difficult problem of broadband oscillation localization in power systems, the intel-ligent localization method of oscillation source based on the digital twin is proposed and the os-cillation source localization system based on the digital twin is constructed. Firstly, a digital twin-based oscillation source localization method and system architecture are proposed. Fur-thermore, an intelligent positioning method of oscillation source based on data-driven and mechanism fusion is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the su-per-resolution technique is used to realize the super-resolution measurement of broadband os-cillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, the branch potential energy is used as input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

The use of visual signals in horticulture has attracted significant attention and encompassed a wide range of data types such as 2D images, videos, hyperspectral images, and 3D point clouds. These visual signals have proven to be valuable in developing cutting-edge computer vision systems for various applications in horticulture, enabling plant growth monitoring, pest and disease detection, quality and yield estimation, and automated harvesting. However, unlike other sectors, developing deep learning computer vision systems for horticulture encounters unique challenges due to the limited availability of high-quality training and evaluation datasets necessary for deep learning models. This paper investigates the current status of vision systems and available data in order to identify the high-quality data requirements specific to horticultural applications. We analyse the impact of the quality of visual signals on the information content and features that can be extracted from these signals. To address the identified data quality requirements, we explore the usage of a deep learning-based super-resolution model for generative quality enhancement of visual signals. Furthermore, we discuss how these can be applied to meet the growing requirements around data quality for learning-based vision systems. We also present a detailed analysis of the competitive quality generated by the proposed solution compared to cost-intensive hardware-based alternatives. This work aims to guide the development of efficient computer vision models in horticulture by overcoming existing data challenges and paving a pathway forward for contemporary data acquisition.

Spatial biology is a rapidly growing research field which focuses on the transcriptomic or proteomic profiling of single cells within tissues with preserved spatial information. Imaging-based spatial transcriptomics uses epifluorescence microscopy, which has shown remarkable results for identification of multiple targets in situ. Nonetheless, the number of genes that can be reliably visualized is limited by the diffraction of light. Here, we investigate the effect of structured illumination (SIM), a super-resolution microscopy approach, over the performance of single gene transcript detection in spatial transcriptomics experiments. We performed direct mRNA-targeted hybridization in situ sequencing for multiple genes in mouse coronal brain tissue sections. We evaluated spot detection performance in widefield and confocal images versus those with SIM in combination with 20X, 25X and 60X objectives. In general, SIM increases the detection efficiency of gene transcripts spots compared to widefield and confocal modes. For each case, the specific fold increase in localizations is dependent on gene transcripts density and the numerical aperture of the objective used, which showed to play an important role especially for densely clustered spots. Taken together, our results suggest that SIM has the capacity to improve spot detection and overall data quality in spatial transcriptomics.

Laser shock peening as an innovative surface treatment technology can effectively improve the fatigue life, sur-face hardness, corrosion resistance, and residual compressive stress. Compared with the laser shock peening, the warm laser shock peening (WLSP) is a new surface treatment technology to improve materials’ surface performances, which takes advantage of thermal mechanical effects on stress strengthening and micro-structure strengthening, results in more stable distribution of the residual compressive stress under heating and cyclic loading process. In this paper, the microstructure of GH4169 nickel super-alloy processed by WLSP technology with differ-ent laser parameters were investigated. The proliferation and tangling of dislocations in GH4169 were observed and the dislocation density increased after WLSP treatment. The influences of different treatment by LSP and WLSP on the microhardness distribution of the surface and along cross-sectional depth were investi-gated. The microstructure evolution of the GH4169 alloy being shocked with WLSP were studied by TEM. The effect of temperature on the stability of high temperature microstructure and properties of GH4169 alloy WLP was investigated.

To develop green super rice varieties with high and stable yields under the rainfed conditions and improved nutrient use efficiency (NuUE), a modified backcross (BC) breeding approach was adopted using a high yielding and widely adaptable Xian variety, WTR1, as the recipient and a Geng variety, HAN, as the donor. Starting from the BC1F2 generation, the BC population had gone through one generation of selection under the IG, LI and RF conditions, followed by consecutive four generations of screening and selection for high GY under six different nutrient conditions, leading to the development of 230 BC1F6 introgression lines (ILs). The final evaluation of the 230 ILs under the six nutrient conditions identified many ILs with improved yields under various combinations of nutrient deficient conditions, including 12 promising lines that had significantly improved NuUE under two or more nutrient deficiency conditions. Our results demonstrated an efficient inter-subspecific BC breeding procedure with first round selection under the rainfed-drought condition followed by four generations of progeny testing for yield performances under six different nutrient conditions. The promising ILs were studied under replicated yield trials under 75N and -NPK conditions for developing high yield rice varieties with improved NuUE. Our results indicated that NuUE in rice was controlled by complex genetic and physiological mechanisms and the developed ILs provided useful materials for genetic and molecular dissection of NuUE in rice.

Dealing with and maintaining high-quality standards in the design and construction phases is challenging, especially for on-site construction. Issues like improper implementation of building components and poor communication can widen the gap between design specifications and actual conditions. To prevent this, particularly for energy-efficient buildings, it's vital to develop resilient, sustainable strategies. These should optimize resource use, minimize environmental impact, and enhance livability, contributing to carbon neutrality by 2050 and climate change mitigation. Traditional post-occupancy evaluations, which identify defects after construction, are impractical for addressing energy performance gaps. A new, real-time inspection approach is necessary throughout the construction process. This paper suggests an innovative guideline for prefabricated buildings, emphasizing digital 'self-instruction' and 'self-inspection'. These procedures ensure activities impacting quality adhere to specific instructions, drawings, and 3D models, incorporating relevant acceptance criteria to verify completion. This methodology, promoting alignment with planned energy-efficient features, is supported by BIM-based software and Augmented Reality (AR) tools, embodying Industry 4.0 principles. BIM and AR bridge the gap between virtual design and actual construction, improving stakeholder communication and enabling real-time monitoring and adjustments. This integration fosters accuracy and efficiency, key for energy-efficient and Nearly Zero-Energy Buildings, marking a shift towards a more precise, collaborative, and environmentally sensible construction industry.

The Mine Internet of Things (MIoT), as a key technology for reconstructing post-disaster communication networks, enables to realize the safety monitoring and controlling of the affected roadway. However, due to the challenging underground mine environment, the MIoT suffers from severe signal attenuation, vulnerable nodes, and limited energy, which result in low network reliability of the post-disaster MIoT. To improve the transmission reliability as well as to reduce energy consumption, a directional-area-forwarding-based energy-efficient opportunistic routing (DEOR) for the post-disaster MIoT is proposed. DEOR defines a forwarding zone (FZ) for each node to route packets toward the sink. The candidate forwarding set (CFS) is constructed by the nodes within the FZ that satisfy the energy constraint and the neighboring node degree constraint. The nodes in CFS are prioritized based on the routing quality evaluation by taking the local attributes of nodes into consideration, such as the directional angle, transmission distance, and residual energy. DEOR adopts a recovery mechanism to address the issue of void nodes. The simulation results validate that the proposed DEOR outperforms ORR, OBRN and ECSOR in terms of energy consumption, average hop count, packet delivery rate, and network lifetime.

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.

Ninety percent of the existing building stock in Europe was built before 1990. These buildings are in urgent need for a significant improvement of energy-efficiency through renovation. Regrettably, so far only five percent of renovation projects have been able to yield energy-saving at deep renovation level. State-of-the-art renovation solutions are available, but costly and lengthy renovation processes and incomprehensible technical complexities hinder the achievement of a wide impact at a European scale. This paper presents research on Plug-and-Play (PnP) technologies supported by Building Information Modelling (BIM) to provide affordable, interchangeable and quick-installation solutions to overcome the main barriers of building deep renovation.

With reference to Planck scale Hubble parameter, super luminal expansion speeds, super luminal rotation speeds, Mach’s principle and Holographic principle, we review the current cosmological observations with eight simple assumptions. By understanding Yuri N. Obukhov and V.A. Korotky proposed cosmic rotational effects of polarization of radiation due to massive bodies, to some extent cosmic rotation can be deep-rooted in an observational approach and the ratio of current angular velocity and Hubble parameter can be estimated. It is possible to show that, at H₀ =70 km/sec/Mpc, current cosmic temperature, age, radius, mass, mass density are 2.721 K, 4.41x10¹⁷ sec, 90 billion light years, 1.14654x10⁵⁴ kg, 0.0482 times the current critical density respectively. Clearly speaking, current universe seems to constitute 267 Hubble spheres. Important point to be noted is that, current rotational kinetic energy is 0.6667 times the current critical energy. Based on the estimated current mass density and current rotational kinetic energy, current cosmic dark matter density can be shown to be 0.2851 times the current critical density. These numerical coincidences cast serious doubt on the on the real existence of currently believed ‘dark energy’. Initial and current expansion speeds are 3x10⁸ m/sec and 3.56x10⁹ m/sec respectively. With increasing cosmic age and increasing cosmic expansion speed, current universe is expanding with a speed of 11.885c. By knowing the time to time future cosmic temperatures, future Hubble parameters and corresponding future cosmic expansion speeds can be estimated and thus future expansion speed can be understood. Starting from ‘speed of light’, our model assumes a continuous increase in expansion speed and attains a current radius of 90 billion light years (without inflationary concepts) and casts a serious doubt on the actuality of currently believed ‘inflation’.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Imaging of the ocular vasculature can provide new insights into the pathophysiology of ocular diseases. This study proposes a novel high-frequency super-resolution ultrasound localization microscopy (SRULM) technique and evaluates its ability to measure in vivo perfusion changes in the rat eye at elevated intraocular pressure (IOP). A 38.4 MHz center frequency linear array transducer on a VisualSonics Vevo F2 imaging platform was used to collect high frame rate (1 kHz) radiofrequency data of the posterior rat eye following systemic microbubble contrast injection. Following clutter and spatiotemporal non-local means filtering, individual microbubbles were localized and tracked. The microbubble tracks were accumulated over 10,000 frames to generate vascular images quantifying perfusion velocity and direction. Experiments were performed using physiologic relevant controlled flow states for algorithm validation and subsequently performed in vivo on the rat eye at 10 mm Hg IOP increments from 10 to 60 mm Hg. The posterior vasculature of the rat eye, including the ophthalmic artery, long posterior ciliary arteries and their branches, central retinal artery and retinal arterioles and venules were successfully visualized, and velocities quantified at each IOP level. Significant reductions in arterial flow were measured as IOP was elevated. High-frequency SRULM can be used to visualize and quantify perfusion velocity of the rat eye in both the retrobulbar and intraocular vasculature simultaneously. The ability to detect ocular perfusion changes throughout the depth of the eye may help elucidate the role ischemia has in the pathophysiology of ocular diseases such as glaucoma.

This paper demonstrates an on-off keying (OOK) super-regenerative quenching transmitter operating in 402- 405MHz MICs band applications. To reduce power consumption, the transmitter is controlled by a novel digital quenching signal controller that generates a digital control signal to start transmitter operation when a baseband signal is input to the transmitter. The digital signal controller consists of an envelope detector, a comparator, and a quench timer designed using a state machine to synchronize the operation between the digital controller and the input baseband signal. The transmitter consists of a Colpitts oscillator operating in double operating frequency followed by a frequency divider by 2, this configuration reduces system area and improves phase noise and signal spectrum. The proposed transmitter is implemented using UMC 130nm CMOS technology, and a 1.2V supply. Simulation shows that the proposed transmitter can meet MICS band mask specifications with data rates up to 1Mbps and total power dissipation of 537uW.

The dynamic effects observed in collisions represent a specific area of high-energy interaction located at the boundary of mechanics, hydrodynamics, shock wave physics, and alternating high-pressure regions. The paper shows that in the volume of a solid metal body, as a result of dynamic alloying by a high-speed stream of powder particles in the super-deep penetration mode (SDP), fibre structures of altering material arise, forming the framework of the composite material. The stream of powder particles in the metal obstacle following the path of least resistance and the impact of shock waves on particles results in a volumetric framework from the products of interaction between the injected and matrix materials. When using SDP, defective structural elements (channelled) - germs of reinforcing fibres arise. At the subsequent heat treatment, there is an intensive diffusion. The growth process of reinforcing fibres shifts to higher temperatures (as compared to the standard mode), leading to an increase in the bending strength of the fibre material up to 13 times for high-speed tool W6Mo5Cr4V2 steel. As a result of the completion of the growth of reinforcing fibres in the volume of the W6Mo5Cr4V2 steel, the material's bending strength in 1.2 times is realised. Simultaneously, it provides an increase of wear resistance 1.7-1.8 times.

We derive time evolution equations, namely the Schrodinger-like equations and the Klein-Gordon equations for coherent fields and the Kadanoff-Baym (KB) equations for quantum fluctuations, in Quantum Electrodynamics (QED) with electric dipoles in 2 + 1 dimensions. Next we introduce a kinetic entropy current based on the KB equations in the 1st order of the gradient expansion. We show the H-theorem for the Leading-Order self-energy in the coupling expansion (the Hartree-Fock approximation). We show a conserved energy in the spatially homogeneous systems in the time evolution. We derive aspects of the super-radiance and the equilibration in our single Lagrangian. Our analysis can be applied to Quantum Brain Dynamics, that is QED with water electric dipoles. The total energy consumption to maintain super-radiant states in microtubules seems to be within the energy consumption to maintain the ordered systems in a brain.

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.

Multiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real- time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

A super-porous hybrid platform can offer significantly increased number of reaction sites for the analytes and thus can offer advantages in the biosensor applications. In this work, a significantly improved sensitivity and selectivity of hydrogen peroxide (H2O2) cancer sensor is demonstrated by a super-porous hybrid CuO/Pt NP platform. The super-porous hybrid platform is fabricated by a physiochemical approach combining the physical vapor deposition of Pt NPs and electrochemical deposition of super-porous CuO structures by adopting a dynamic hydrogen bubble technique. Under an optimized condition, the hybrid CuO/Pt biosensor demonstrates a very high sensitivity of 2,205 µA/mM∙cm2 and a low limit of detection (LOD) of 140 nM with a wide range of H2O2 detection. This is meaningfully improved performance as compared to the CuO-based H2O2 sensors as well as to the previously reported metal oxide based H2O2 sensors. The hybrid CuO/Pt platform exhibits excellent selectivity against other interfering molecules such as glucose, fructose, dopamine, and ascorbic acid. Due to the synergetic effect of highly porous CuO structures and underlying Pt NPs, the CuO/Pt architecture offers extremely abundant active sites for the H2O2 reduction and electron transfer pathways.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

The arrival of new developments in the field of power electronics circuit’s applications in power systems builds new control strategy to improve voltage quality for power grid by overcome interruptions. Wind energy resources are unconventional resources and get advanced problems to power grid when it is connected. Uncertainty of load sharing, peak energy management, climatic conditions, wind velocity and wind energy injected into power grid leads many of power quality problems on power grid based on the existing guidelines specified in IEC-61400 standard. This system plans efficient operation of DFIG to eliminate the voltage collapse and mismatch frequency to power grid. The DFIG connected diode rectifier and rotor side converter wind generator works as an Efficient Static Synchronous Compensator (E-SATCOM) for supplying the demand of reactive power for power grid to mitigate PQ problems. The benefit of using a combined controller was verified by simulink/Matlab and its simulated results used Doubly Fed Induction Generator (DFIG), wind Turbine. This simulation results gives good quality transient and stable state response to manage and support reactive power for both symmetrical and unsymmetrical faults in connection of grid codes to provide continuous quality of power supply, multiple wind generators are required for 140 bus power grid.

Accurate climate data at fine spatial resolution are essential for scientific research and the development and planning of crucial social systems, such as energy and agriculture. Among them, sea surface temperature plays a critical role as the associated El Niño-Southern Oscillation (ENSO) is considered a significant signal of global interannual climate system. In this paper, we propose an implicit neural representation-based interpolation method with temporal information (T_INRI) to reconstruct climate data of high spatial resolution, with sea surface temperature as the research object. Traditional deep learning models for generating high-resolution climate data are only applicable to fixed resolution enhancement scales. In contrast, the proposed T_INRI method is not limited to the enhancement scale provided during the training process and its results indicate that it can enhance low-resolution input by arbitrary scale. Additionally, we discuss the impact of temporal information on the generation of high-resolution climate data, specifically, which month the low-resolution sea surface temperature data is from. Our experimental results indicate that T_INRI is advantageous over traditional interpolation methods under different enhancement scales, and the temporal information can improve T_INRI performance for a different calendar month. We also examined the potential capability of T_INRI in recovering missing grid value. These results demonstrate that the proposed T_INRI is a promising method for generating high-resolution climate data and has significant implications for climate research and related applications.

Super duplex stainless steel (SDSS) is used for manufacturing large valves and pipes in offshore plants because of its excellent strength and corrosion resistance. Large valves and pipes are manufactured by forging after casting, and the outside and inside microstructures are different owing to the difference in the cooling rate caused by the thermal conductivity. This microstructural variation causes cracks during solution annealing, which breaks the materials. To study toe corrosion resistance of the SDSS forged material, the microstructure was conducted based on the difference in the cooling rate between the inside and outside of the cast SDSS. To analyze the effects of the secondary phase fraction before solution annealing on the solution and corrosion resistance, the corrosion resistance with and without solution annealing was measured using the potentiodynamic polarization test and critical temperature test after the precipitation of the secondary phase. In the potentiodynamic polarization test, the secondary phase decreased the activation polarization and increased the corrosion rate. The critical pitting temperature exhibited the effect of the secondary phase.

In our recently published papers, considering Planck mass based light speed growing black hole universe and scaled Hawking’s black hole temperature formula, we have developed a simple procedure for estimating the current Hubble parameter and current cosmic mass. In addition to that, without considering galactic dark matter, starting from 10 km/sec to 500 km/sec, we have tried to fit the observed galactic flat rotation speeds with a concept of super gravity of galactic baryonic mass. To estimate the equivalent mass of currently hypothecated galactic dark matter, we have introduced a timely increasing cosmological reference mass unit. Its current magnitude seems to be around 200 million solar masses. In this paper, considering 200 million solar masses as a characteristic representation of cosmic weak interaction mass unit, we have developed a simple formula for its estimation. We would like to appeal that, weak interaction boosts the gravity of galaxies in proportion with their virtual dark mass as (galactic baryonic mass)^3/2 / (200 million solar masses)^1/2. With further study- dark matter existence and physical properties can be understood in a theoretical approach.

The holy grail of Artificial Intelligence (AI) has been to mimic human intelligence using computing machines. Autopoiesis which refers to a system with well-defined identity and is capable of re-producing and maintaining itself and cognition which is the ability to process information, apply knowledge, and change the circumstance are associated with resilience and intelligence. While classical computer science (CCS) with symbolic and sub-symbolic computing has given us tools to decipher the mysteries of physical, chemical and biological systems in nature and allowed us to model, analyze various observations and use information to optimize our interactions with each other and with our environment, it falls short in reproducing even the basic behaviors of living organisms. We present the foundational shortcomings of CCS and discuss the science of infor-mation processing structures (SIPS) that allows us to fill the gaps. SIPS allows us to model su-per-symbolic computations and infuse autopoietic and cognitive behaviors into digital machines. They use common knowledge representation from the information gained using both symbolic and sub-symbolic computations in the form of system-wide knowledge networks consisting of knowledge nodes and information sharing channels with other knowledge nodes. The knowledge nodes wired together fire together to exhibit autopoietic and cognitive behaviors.

This paper combines the Good Regulator Theorem with the Law of Requisite Variety and seven other requisites that are necessary and sufficient for a cybernetic regulator to be effective and ethical. The resulting Ethical Regulator Theorem provides a basis for systematically evaluating and improving the adequacy of existing or proposed designs for systems that make decisions that can have ethical consequences; regardless of whether the regulators are human, machines, cyberanthropic hybrids, organizations, corporations, or government institutions. The theorem is then used to define an ethical design process that has potentially far-reaching implications for society. A six-level framework is proposed for classifying cybernetic and superintelligent systems, which highlights the existence of a possibility-space bifurcation in our future time-line. The implementation of “super-ethical” systems is identified as an urgent imperative for humanity to avoid the danger that superintelligent machines might lead to a technological dystopia. Third-order cybernetics is defined as the cybernetics of ethical systems. Concrete actions, a grand challenge, and a vision of a super-ethical society are proposed to help steer the future of the human race and our wonderful planet towards a realistically achievable minimum viable cyberanthropic utopia.

Single Image Super Resolution (SSIR) is a problem in computer vision where the goal is 1 to create high-resolution images from low-resolution ones. It has important applications in fields 2 such as medical imaging and security surveillance. While traditional methods such as interpolation 3 and reconstruction-based models have been used in the past, deep learning techniques have recently 4 gained attention due to their superior performance and computational efficiency. This article proposes 5 an Autoencoder based Deep Learning Model for SSIR, in particular, a light model that uses fewer 6 parameters without compromising performance. The down-sampling part of the Autoencoder 7 mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose 8 convolution and residual connections from the down sampling part. The model is trained using a 9 subset of the VILRC ImageNet database. The model is evaluated using quantitative metrics PSNR, 10 SSIM as well as qualitative measures such as perceptual quality. PSNR and SSIM figures as high as 11 76.06 and 0.93 are reported.

With 500+ papers and 20+ books spanning many scientific disciplines, Mark Burgin has left an indelible mark and legacy for future explorers of human thought and information technology professionals. In this paper, I discuss his contribution to the evolution of machine intelligence using his general theory of information (GTI) based on my discussions with him and various papers I co-authored during the past eight years. His construction of a new class of digital automata to overcome the barrier posed by the Church-Turing Thesis, and his contribution to Super-Symbolic Computing with Knowledge Structures, Cognizing Oracles, and Structural Machines are leading to practical applications changing the future landscape of information systems. GTI provides a model for the operational knowledge of biological systems to build, operate, and manage life processes using 30+ trillion cells capable of replication and metabolism. The schema, and associated operations derived from GTI are also used to model a digital genome specifying the operational knowledge of algorithms executing the software life processes with specific purposes using replication and metabolism. The result is a digital software system with a super-symbolic computing structure exhibiting autopoietic and cognitive behaviors that biological systems also exhibit. We discuss here one of these applications.

This paper presents results of the magnetic dynamics study (the microwave power absorptions at the fixed frequencies, during magnetic field sweeping) in samples of Y3Fe5O12 single crystals in the form of plates and spheres of various sizes, at frequencies exceeding 30 GHz, in magnetic fields up to 18 kOe, at room temperature and T=77 K. It was found, that in this case, the inhomogeneity’s of the magnetic state manifested itself in the Y3Fe5O12 samples in as 2D local phase separation regions. These 2D phase separation regions formed inside domain walls representing superlattices with size’s 700 – 900 Å. Landau diamagnetism or de Haas van Alphen oscillations observed in the 2D phase separation regions at room temperature and T=77 K, depending on the shape and size of the studied plates and spheres.

We introduce a new class of Vertex Operator Algebras Y+ and their duals, which generalize the standard W-algebras WN of type sl(N). These algebras can be defined in terms of junctions of boundary conditions and interfaces in the GL-twisted N = 4 Super Yang Mills gauge theory. The aim of these technical calculations is to find the relation of these ortho-symplectic Y-algebras to truncations of even W\infinity.

Deep Learning is a recent and important addition to the computational toolbox available for image reconstruction in fluorescence microscopy. We review state-of-the-art applications such as image restoration, super-resolution, and light-field imaging, and discuss how the latest Deep Learning research can be applied to other image reconstruction tasks such as structured illumination, spectral deconvolution, and sample stabilisation. Despite its successes, Deep Learning also poses significant challenges, has often misunderstood capabilities, and overlooked limits. We will address key questions, such as: What are the challenges in obtaining training data? Can we discover structures not present in the training data? And, what is the danger of inferring unsubstantiated image details?

This paper describes a novel concept of producing energy efficient ”Maroon enriched natural gas “ and then Pink hydrogen” from any hydrocarbon base. The key idea is the extraction of hydrogen from water in addition to that from the hydrocarbon in an optimal fashion. This has the benefit of higher water vapor to CO2 exhaust ratio than conventional carbonaceous fuels when generating energy via combustion, a prudent step in achieving Netzero goals in a shorter time, and creating energy independence in most places.. The process of production makes concentrated CO₂ available for use and or sequestration. The process also maximizes use of renewable electricity in hydrogen generation, and maximizes use of existing infrastructure, with a minimum capital cost by energy recycle in the process. The process design applies sound thermodynamic principles which evolved during the nineteenth century, and mimics the geochemical processes going on in some of the natural 'colorless hydrogen'.

A system of simultaneous multi-variable nonlinear equations can be solved by the Newton’s method with local q-quadratic convergence if the Jacobian is analytically available. If this is not the case, then quasi-Newton methods with local q-superlinear convergence give solutions by approximating the Jacobian in some way. Unfortunately, the quasi-Newton condition (secant equation) doesn’t completely specify the Jacobian approximate in multi-dimensional case, so its full-rank update is not possible with classic variants of methods. The suggested new iteration strategy (“T-Secant”) allows full-rank update of the Jacobian approximate in each iteration by determining two independent approximates for the solution. They are used to generate a set of new independent trial approximates, then the Jacobian approximate can fully be updated. It is shown, that the T-Secant approximate is in the vicinity of the classic quasi-Newton approximate, providing that the solution is evenly surrounded by the new trial approximates. The suggested procedure increases the super-linear convergence of the secant method (φS = 1.618...) to super-quadratic (φT = φS + 1 = 2.618...) and the quadratic convergence of the Newton-method (φN = 2) to cubic (φT = φN + 1 = 3) in one dimensional case. The Broyden-type efficiency (mean convergence rate) of the suggested method in multi-dimensional case is an order higher than the efficiency of other classic low-rank update quasi-Newton methods as shown by numerical examples on a Rosenbrock-type test-function with up to 1000 variables. The geometrical representation (hyperbolic approximation) in single variable case helps explaining the basic operations and a vector-space description is also given in multi-variable case.

This study focuses on mimicking constitutive phosphorylation in the N-terminus of the myosin regulatory light chain (S15D-RLC) as a rescue strategy for the mutation-induced cardiac dysfunction in transgenic (Tg) models of restrictive (RCM) and dilated (DCM) cardiomyopathy caused by mutations in myosin essential (ELC) or regulatory (RLC) light chains. S15D-RLC phosphomimetic was reconstituted in left ventricular papillary muscle (LVPM) fibers from two mouse models of cardiomyopathy, RCM-E143K ELC and DCM-D94A RLC, along with their corresponding Tg-ELC and Tg-RLC wild type (WT) mice. The beneficial effects of S15D-RLC in rescuing cardiac function were manifested by S15D-RLC-induced destabilization of the super-relaxed (SRX) state that was observed in both models of cardiomyopathy. S15D-RLC promoted a shift from the SRX state to the disordered relaxed (DRX) state, increasing the number of heads readily available to interact with actin and produce force. Additionally, S15D-RLC reconstituted fibers demonstrated significantly higher maximal isometric force per cross-section of muscle compared with reconstitution with WT-RLC protein. The effects of the phosphomimetic S15D-RLC were compared to those observed for Omecamtiv Mecarbil (OM), a myosin activator shown to bind to the catalytic site of cardiac myosin and increase myocardial contractility. A similar SRX↔DRX equilibrium shift was observed in OM=treated fibers as in S15D-RLC-reconstituted preparations. Additionally, treatment with OM resulted in significantly higher maximal pCa 4 force per cross-section of muscle fibers in both cardiomyopathy models. Our results suggest that both treatments with S15D-RLC and OM may improve the function of myosin motors and cardiac muscle contraction in RCM-ELC and DCM-RLC mice.

The cellular cytoskeleton provides the cell with a mechanical rigidity which allows mechanical interaction between cells and the extracellular environment. The actin structure plays a key role in mechanical events like motility, or establishment of cell polarity. From the earliest stages of development, as represented by ex vivo expansion of naïve embryonic stem cells (ESCs), the critical mechanical role of the actin structure is becoming recognized as a vital cue for correct segregation and lineage control of cells and as a regulatory structure that controls several transcription factors. Naïve ESCs have a characteristic morphology and the ultrastructure that underlies this condition remains to be further investigated. Here, we investigate the 3D actin cytoskeleton of naïve mouse ESCs using super resolution optical reconstruction microscopy (STORM). We investigate the morphological, cytoskeletal and mechanical changes in cells cultured in 2i or Serum/LIF media reflecting a homogenous preimplantation cell state and a state that is closer to embarking on differentiation. STORM imaging showed that the peripheral actin structure undergoes a dramatic change between the two media conditions. We also detected micro-rheological differences in the cell periphery between the cells cultured in these two media correlating well with the observed nano-architecture of the ESCs in the two different culture conditions. These results pave the way for linking physical properties and cytoskeletal architecture to cell morphology during early development.

Sulfur dioxide (SO2) reduction remains an area of global necessity further enhanced by the current international focus on pandemic diseases mitigation, elimination of air pollution, and promotion of renewable green energy. The dynamics of chemical bond-strength breaking and reformation in the transition state (TS) is a fundamental process in the reduction of SO2 by CO. Density Functional Theory (DFT) has been used to determine optimal TS reaction pathway via a novel triple-hybrid catalyst utilizing doubly-charged negative atomic V, Mn, and Au. The triple-hybrid catalyst is furthermore tailored to the subsequent minimization of each individual step of the 3-Step SO2 reduction by CO chemical reaction. Each optimized step 1, 2, and 3 is minimized with doubly-charged V, Mn, and Au, respectively, with TS barrier reductions ranging from 1.18 eV to 0.002 eV. Super-benzene, armchair (6, 6) single wall carbon nanotube, and fullerene TS reaction pathways have also been calculated to compare the nanoscale catalytic effectiveness with that of the atomic scale transition metals.

Identifying macroeconomic events that are responsible for dramatic changes of economy is of particular relevance to understand the overall economic dynamics. We introduce an open-source available efficient Python implementation of a Bayesian multi-trend change point analysis which solves significant memory and computing time limitations to extract crisis information from a correlation metric. Therefore, we focus on the recently investigated S&P500 mean market correlation in a period of roughly 20 years that includes the dot-com bubble, the global financial crisis and the Euro crisis. The analysis is performed two-fold: first, in retrospect on the whole dataset and second, in an on-line adaptive manner in pre-crisis segments. The on-line sensitivity horizon is roughly determined to be 80 up to 100 trading days after a crisis onset. A detailed comparison to global economic events supports the interpretation of the mean market correlation as an informative macroeconomic measure by a rather good agreement of change point distributions and major crisis events. Furthermore, the results hint to the importance of the U.S. housing bubble as trigger of the global financial crisis, provide new evidence for the general reasoning of locally (meta)stable economic states and could work as a comparative impact rating of specific economic events.

KLHL genes and the related KBTBD genes encode components of the Cullin-E3 ubiquitin ligase complex and typically target tissue-specific proteins for degradation, thereby affecting differentiation, homeostasis, metabolism, cell signaling, and the oxidative stress response. Despite their importance in normal cell function and in disease (KLHL40, KLHL41, KBTBD13, KEAP1, and ENC1), previous studies that examined epigenetic factors affecting transcription were predominantly limited to promoter DNA methylation. Using diverse tissue and cell culture whole-genome profiles, we examined 17 KLHL or KBTBD genes preferentially expressed in skeletal muscle or brain to identify tissue-specific enhancer and promoter chromatin, open chromatin (DNaseI hypersensitivity), and DNA hypomethylation. Sixteen of the 17 genes displayed muscle- or brain-specific enhancer chromatin in their gene bodies, and most exhibited specific intergenic enhancer chromatin as well. Seven genes were embedded in a super-enhancer. The enhancer chromatin regions typically displayed foci of DNA hypomethylation at peaks of open chromatin. In addition, we found evidence that gene neighbors (HHATL and FBXO32) of KLHL40 and KLHL38 harbor enhancer chromatin that likely upregulates the adjacent KLHL gene. Many KLHL/KBTBD genes had tissue-specific promoter chromatin at their 5’ ends, but surprisingly, two (KBTBD11 and KLHL31) had constitutively unmethylated promoter chromatin in their 3’ exons that overlaps a retrotransposed KLHL gene. Our findings demonstrate the importance of expanding epigenetic analyses beyond the 5’ ends of genes in studies of normal and abnormal gene regulation.

The efficiency of data sorting algorithms is the key aspect which determines the speed of data processing and searching. The best known efficiency of sorting algorithm has been Log (N) if there are N terms. All of the well-known sorting algorithms use various techniques to sort data. The basis for most of these are comparing the data terms with each other. In this manuscript, we are introducing a new approach for sorting data. This method is postulated to have the highest efficiency ever achieved by any of the sorting algorithms. We achieve this by sorting data without comparing the data terms. Or achieving results of data comparison without comparing the terms explicitly.

Ultrasonic imaging & NDE applications can greatly improve their signal-to-noise ratios (SNR) by driving each transducer (composing piezoelectric arrays) with a spike giving pulsed power of k-Watts, repetitively at a PRF = 5000 spikes/s, by using a HV capacitive-discharge generator. However very-high levels, of pulsed intensities (3-10 A) and voltages (300-700 V) must be considered for a rigorous spike modeling. Even though the consumed "average" power will be small, the intensity through each transducer achieves several amperes, so the pulsed powers delivered by each HV generator can attain levels higher than in CW high-power ultrasonic applications: e.g., up to 5 kW / spike. This is concluded here from a transient modeling of the loaded generator. Then, unforeseen phenomena rise: intense brief pulses of driving power & emitted force in transducers, and non-linearities in driver semiconductors, because their characteristic curves only include linear ranges. But fortunately, piezoelectric devices working in this intense regime do not show serious heating problems, because the average power remains being moderate. Intensity, power and voltage, driving a broadband transducer from a HV capacitive pulser, are calculated to drastically improve (in ≅ 40 dB) the ultrasonic net dynamic range available, with emitted forces ≅ 250 Newtons pp and E/R received pulses of 70 V pp.

Ever since pharmacy has become a profession, pharmacist's role has been continuously subjected to changes due to specific influences from historical, socio-economic, political, and scientific context. Nowadays the classic perception of pharmaceutical profession in Community Pharmacy is facing worldwide extinction due to many factors. Modern services, such as online, mail-order, and telephone-order pharmacies are increasingly gaining ground thanks to their ability to facilitate customer demand. However, at the same time, they are endangering “face-to-face” contact, affecting the building of customer loyalty based on direct “human” interaction, and consequently reducing pharmacists to mere commercial figures. Communication is in fact emphasized as the essential element to build a solid and appropriate interpersonal relationship with the client, to make the consultancy process effective, and to strengthen pharmacist's professionalism in community pharmacy. The aim of this work is to analyze pharmacist’s role in modern society by pinpointing the factors affecting pharmacy profession practice. Specific purpose will be improving both the academic training of future professionals and their capacity to approach public relations through a deepened study and practice of behavioral, communication, educational, and sociological methodologies and techniques that would allow the development of more effective communication skills useful for providing an efficient consultancy service.

Based on four major cosmological and astrophysical coincidences, it seems possible to develop a new model of Hubble-Hawking Universe having light speed expansion. Considering the analysis of 740 super novae data, it is possible to consider a constant rate of cosmic expansion. As there is no physical reasoning for the observed speed of light and all the cosmological observations are completely based on speed of light-by considering ‘light speed expansion’ as a characteristic nature of the universe, big bang, inflation, dark energy, quintessence and lambda term like ideal and unidentified concepts can be reviewed and relinquished at fundamental level and a practical model of expanding universe can be developed with ease and clarity. In this context, we would like to emphasize the point that, traditional definition of cosmic red shift is absolutely wrong. In terms of energy of photon, true cosmic red shift must be defined as - ratio of loss of energy in photon to the energy of photon at galaxy. We encourage the reader to see Figure 1 and Table 1 pertaining to light travel distances prepared with $\left(\frac{z}{1+z}\right)\left(\frac{c}{H_0}\right)\cong z_{new}\left(\frac{c}{H_0}\right)$. For data comparison, readers are encouraged to visit https://cosmocalc.icrar.org/ and http://www.atlasoftheuniverse.com/cosmodis.c. It may be noted that, considering 200 million solar masses as a cut off for ordinary gravity, dark matter can be considered as an effect of power law based super gravity of galactic baryonic mass. It is well believed that, Hawking’s findings about black holes are the most important contributions to physics in recent decades. Hence, we appeal the science community to recommend our Hubble-Hawking model for further research and study.

Classical models of gene expression were built using genetics and biochemistry. Although these approaches are powerful, they have very limited consideration of the spatial and temporal organization of gene expression. Although the spatial organization and dynamics of RNA polymerase II (RNAPII) transcription machinery has fundamental functional consequences for gene expression, its detailed studies have been for long time abrogated by the limits of classical light microscopy. The advent of super-resolution microscopy (SRM) techniques allowed for the visualization of the RNAPII transcription machinery with nanometer resolution and millisecond precision. In this review, we summarize the recent methodological advances in SRM, focus on its application for studies of the nanoscale organization in space and time of RNAPII transcription, and discuss its consequences for the mechanistic understanding of gene expression.

In the dynamic landscape of 6G and smart cities, Visible Light Communication (VLC) assumes critical significance for IoT (Internet of Things) applications spanning diverse sectors. The escalating demand for bandwidth and data underscores the need for innovative solutions, positioning VLC as a complementary technology within the electromagnetic spectrum. This paper focuses on the relevance of VLC in the 6G paradigm, shedding light on its applicability across smart cities and industries. The paper highlights the growing efficiency of lighting LEDs in infrastructure, facilitating the seamless integration of VLC. The study then emphasizes VLC’s robustness in outdoor settings, demonstrating effective communication up to 10 meters. This resilience positions VLC as a key player in addressing the very last meter of wireless communication, offering a seamless solution for IoT connectivity. By introducing an a freely available open-source simulator combined to an alternative waveform, UFMC, the study empowers researchers to dimension applications effectively, showcasing VLC’s potential to improve wireless communication in the evolving landscape of 6G and smart cities.

An event occurring within a stationary environment, in the direction toward which an observer self-rotates, is perceived to precede a simultaneous event, in the direction away from which she moves. When self-rotation results from angular acceleration in the dark, perception of space is also distorted, such that the subjective straight-ahead shifts in the opposite direction to motion and temporal event promotion. A reference frameshift theory, based on the special theory of relativity, is proposed to explain these findings. Here, a hyperbolic tangent transformation of objective angular velocity constrains subjective self-rotation velocity within finite bounds, consistent with it being a limited perceptual resource. Identifying this subjective variable with vestibular nystagmus slow-phase angular velocity, the asymptotic perceived self-rotation velocity is estimated at ~200 °⁄s. When included in the Lorentz transformations of the new formalism, this value predicts experimental simultaneity distortion. Hypothetically, the hyperbolic tangent objective-to-subjective transfer function would maximize the differential entropy of the percept, and thereby also the stimulus/percept mutual information, if angular velocities of body rotation encountered in naturalistic environmental interaction have a logistic probability density distribution of scale 100 °⁄s, a proposed experimental test of the scheme.

In this work, the author employs the quantum hydrodynamic formalism to achieve the geometrization of spacetime for describing the gravitational interaction within the framework of quantum theory. This approach allows for the development of an equation of gravity that is mathematically connected to the fermion and boson fields. This achievement is accomplished by incorporating two fundamental principles: covariance of the quantum field equations and the principle of least action. By considering these principles, a theory is established that enables the calculation of gravitational corrections to Quantum Electrodynamics, and potentially, to the standard model of particle physics as well. The theory also provides an explanation for two phenomena: the existence of a cosmological pressure density similar to quintessence, that is compatible with the small value of the observed cosmological constant, and the breaking of matter-antimatter symmetry at high energies offering insights into why there is an imbalance between the two in the early universe. In the cosmological modeling of the theory, there exists a proposal to account for the formation of supermassive black holes that are accompanied by their own surrounding galaxies, without relying on the process of mass accretion. The model, in accordance with recent observations conducted by the James Webb Space Telescope, supports the notion that galactic configurations were established relatively early in the history of the universe, shortly after the occurrence of the Big Bang.

It is extremely fascinating and astonishing that the gravitational field on the surface of a neutron star is with a relativistic mass density of 2.65*10¹⁶~5.87*10¹⁸kgm^-3 which can be larger than the mass density of the neutron star (~10¹⁷kgm^-3).Therefore, it is the author’s first intuitional imagining that this field could directly convert into mass. In so strong a gravitational field, electron and proton could be produced directly from graviton–photon collision. The gravitational field exists in everywhere in our universe. No vacuum that the region of a space is “empty” does exist. A particle is clearly always being acted on by the gravitational field. The quantum vacuum fluctuation and vacuum polarization need be re-understood with the interaction between photon and gravitational field. Therefore, the gravitational field is naturally one of the foundations of modern physics.

With an estimated 3 to 5 million human cases annually and the potential to infect domestic and wild animal populations, influenza viruses are one of the greatest health and economic burdens to our society [1] and pose an ongoing threat of large-scale pandemics. Despite our knowledge of many important aspects of influenza virus biology, there is still much to learn about how influenza viruses replicate in infected cells, for instance how they use entry receptors or exploit host cell trafficking pathways. These gaps in our knowledge are due, in part, to the difficulty of directly observing viruses in living cells. In recent years, advances in light microscopy, including super-resolution microscopy and single-molecule imaging, have enabled many viral replication steps to be visualised dynamically in living cells. In particular, the ability to track single virions and their components, in real time, now allows specific pathways to be interrogated providing new insights to various aspects of the virus-host cell interaction. In this review, we discuss how state-of-the-art imaging technologies, notably quantitative live-cell and super-resolution microscopy, are shedding new nanoscale and molecular insights into influenza virus replication and revealing new opportunities for developing antiviral strategies.

Space-time evolution is briefly explained by using the 3-dimensional quantized space model (TQSM) based on the 4-dimensional (4-D) Euclidean space. The energy (mass), charges and absolute time are newly defined based on the 4-D Euclidean space. The photons and gravitons are understood as the 2-D space fluctuations along the space axes and 1-D time fluctuations along the time axis, respectively. This indicates that the electromagnetic (EM) and gravitational (G) waves can be unified into the so called gravityelectromagnetic (GEM) wave which has both space and time fluctuations. The photon with zero force fields is the 2EM wave because an EM wave corresponds to a charged fermion. The dark matter bosons, weak force bosons, strong force bosons are the 1-D time fluctuations which can be expressed by the G waves. This indicates that all five forces are unified by the GEM wave. It is called as the super unification theory in the present work. And the force carrying bosons and mesons are, for the first time, proposed as the possible candidates of the magnetic monopoles like the fermions and baryons are the electric monopoles. The signs of the magnetic charges quantized as q_m=cq are newly defined. The big bang is understood by the space-time evolution of the 4-D Euclidean space but not by the sudden 4-D Minkowski space-time creation. The big bang process created the matter universe with the positive energy and the partner anti-matter universe with the negative energy from the CPT symmetry.

The rising severity and frequency of wildfires in recent years in the United States have raised numerous concerns regarding the improvement in wildfire emergency response management and decision-making systems, which require operational high temporal and spatial resolution monitoring capabilities. Satellites are one of the tools that can be used for wildfire monitoring. However, none of the currently available satellite systems provide both high temporal and spatial resolution. For example, GOES-17 geostationary satellite fire products have high temporal (1-5 min) but low spatial resolution (2 km), and VIIRS polar orbiter satellite fire products have low temporal (~12 h) but high spatial resolution (375 m). This work aims to leverage currently available satellite data sources, such as GOES and VIIRS, along with Deep Learning (DL) advances to achieve an operational high-resolution, both spatially and temporarily, wildfire monitoring tool. Specifically, this study considers the problem of increasing the spatial resolution of high temporal but low spatial resolution GOES-17 data products using low temporal but high spatial resolution VIIRS data products. The main idea is using an Autoencoder DL model to learn how to map GOES-17 geostationary low spatial resolution satellite images to VIIRS polar orbiter high spatial resolution satellite images. In this context, several loss functions and DL architectures are implemented and tested to predict both the fire area and the corresponding brightness temperature. These models are trained and tested on wildfire sites from 2019 to 2021 in the western U.S. The results indicate that DL models can improve the spatial resolution of GOES-17 images, leading to images that mimic the spatial resolution of VIIRS images. Combined with GOES-17 higher temporal resolution, the DL model can provide high-resolution near-real-time wildfire monitoring capability as well as semi-continuous wildfire progression maps.

AI is extraordinarily useful technology but it is becoming increasingly powerful with rapidly growing capabilities to disrupt and harm human society. We call on international and national organizations and individuals to join forces in banning the development of superintelligent AI and introducing regulations to prevent and mitigate AI-caused harm.

Space-time evolution is briefly explained by using the 3-dimensional quantized space model (TQSM) based on the 4-dimensional (4-D) Euclidean space. The energy (E=cDtDV), charges (|q|= cDt) and absolute time (ct) are newly defined based on the 4-D Euclidean space. The big bang is understood by the space-time evolution of the 4-D Euclidean space but not by the sudden 4-D Minkowski space-time creation. The big bang process created the matter universe with the positive energy and the partner anti-matter universe with the negative energy from the CPT symmetry. Our universe is the matter universe with the negative charges of electric charge (EC), lepton charge (LC) and color charge (CC). This first universe is made of three dark matter -, lepton -, and quark - primary black holes with the huge negative charges which cause the Coulomb repulsive forces much bigger than the gravitational forces. The huge Coulomb forces induce the inflation of the primary black holes, that decay to the super-massive black holes. The dark matter super-massive black holes surrounded by the normal matters and dark matters make the galaxies and galaxy clusters. The spiral arms of galaxies are closely related to the decay of the 3-D charged normal matter black holes to the 1-D charged normal matter black holes. The elementary leptons and quarks are created by the decay of the normal matter charged black holes, that is caused by the Coulomb forces much stronger than the gravitational forces. The Coulomb forces are very weak with the very small Coulomb constants (k₁(EC) = k_dd(EC) ) for the dark matters and very strong with the very big Coulomb constants (k₂(EC) = k_nn(EC)) for the normal matters because of the non-communication of the photons between the dark matters and normal matters. The photons are charge dependent and mass independent. But the dark matters and normal matters have the similar and very weak gravitational forces because of the communication of the gravitons between the dark matters and normal matters. The gravitons are charge independent and mass dependent. Note that the three kinds of charges (EC, LC and CC) and one kind of mass (m) exist in our matter universe. The dark matters, leptons and quarks have the charge configurations of (EC), (EC,LC) and (EC,LC,CC), respectively. Partial masses of elementary fermions are calculated, and the proton spin crisis is explained. The charged black holes are not the singularities.

With reference to electromagnetic interaction and Abdus Salam’s strong (nuclear) gravity, 1) Square root of ‘reciprocal’ of the strong coupling constant can be considered as the strength of nuclear elementary charge. 2) ‘Reciprocal’ of the strong coupling constant can be considered as the maximum strength of nuclear binding energy. 3) In deuteron, strength of nuclear binding energy is around unity and there exists no strong interaction in between neutron and proton. $G_s\cong 3.32688\times {10}^{28}{\mathrm{m}}^3{\mathrm{kg}}^{-1}{\sec }^{-2}$ being the nuclear gravitational constant, nuclear charge radius can be shown to be, $R_0\cong \frac{2G_s{m}_p}{c^2}\cong 1.24\mathrm{fm}.$ $e_s\cong \left(\frac{G_s{m}_p^2}{\hslash c}\right)e\cong 4.716785\times {10}^{-19}\mathrm{C}$ being the nuclear elementary charge, proton magnetic moment can be shown to be, ${\mu }_p\cong \frac{e_s\hslash }{2m_p}\cong \frac{e{G}_s{m}_p}{2c}\cong 1.48694\times {10}^{-26}\mathrm{J}{.\mathrm{T}}^{-1}.$ ${\alpha }_s\cong {\left(\frac{\hslash c}{G_s{m}_p^2}\right)}^2\cong 0.1153795$ being the strong coupling constant, strong interaction range can be shown to be proportional to $\exp \left(\frac{1}{{\alpha }_s^2}\right).$ Interesting points to be noted are: An increase in the value of ${\alpha }_s$ helps in decreasing the interaction range indicating a more strongly bound nuclear system. A decrease in the value of ${\alpha }_s$ helps in increasing the interaction range indicating a more weakly bound nuclear system. From $Z\cong 30$ onwards, close to stable mass numbers, nuclear binding energy can be addressed with, ${\left(B\right)}_{A_s}\cong Z\times \left\{\left(\frac{1}{{\alpha }_s}+1\right)+\sqrt{\sqrt{30\times 31}}\right\}\left(m_n-m_p\right)c^2\approx Z\times 19.66\mathrm{MeV}.$ With further study, magnitude of the Newtonian gravitational constant can be estimated with nuclear elementary physical constants. One sample relation is, $\left(\frac{G_N}{G_s}\right)\cong \frac{1}{2}{\left(\frac{m_e}{m_p}\right)}^{10}\left[\sqrt{\frac{G_F}{\hslash c}}/\left(\frac{\hslash }{m_{e}c}\right)\right]$ where $G_N$ represents the Newtonian gravitational constant and $G_F$ represents the Fermi’s weak coupling constant. Two interesting coincidences are, ${\left(m_p/m_e\right)}^{10}\cong \exp \left(1/{\alpha }_s^2\right)$ and $2G_s{m}_e/c^2\cong \sqrt{G_F/\hslash c}.$

Let  β= (((24!)!)!)!, and let {${\mathcal P}_{n^2+1}$} denote the set of all primes of the form {$n^2+1$}. Let ${\mathcal M}$ denote the set of all positive multiples of elements of the set {${\mathcal P}_{n^2+1} \cap (\beta,\infty)$}. The set {${\mathcal X}=\{0,\ldots,\beta\} \cup {\mathcal M}$} satisfies the following conditions: (1) ${\rm card}({\mathcal X})$ is greater than a huge positive integer and it is conjectured that ${\mathcal X}$ is infinite, (2)} we do not know any algorithm deciding the finiteness of ${\mathcal X}$, (3)~a~known and short algorithm for every {$n \in N$} decides whether or not {$n \in {\mathcal X}$}, (4) a known and short algorithm returns an integer~$n$ such that ${\mathcal X}$ is infinite if and only if ${\mathcal X}$ contains an element greater than $n$. The following problem is open: {\em simply define a set {${\mathcal X} \subseteq N$} such that ${\mathcal X}$ satisfies conditions (1)-(4), and \underline{we do not know any representation of~~${\mathcal X}$~~as a finite union of sets whose definitions are simpler than} \underline{the definition of ${\mathcal X}$}} {\tt (5)}. Let {$f(1)=2$}, {$f(2)=4$}, and let {$f(n+1)=f(n)!$} for every integer {$n \geqslant 2$}. For a positive integer $n$, let {$\Psi_n$} denote the following statement: {\em if a system of equations ${\mathcal S} \subseteq \Bigl\{x_i!=x_k: i,k \in \{1,\ldots,n\}\Bigr\} \cup \Bigl\{x_i \cdot x_j=x_k: i,j,k \in \{1,\ldots,n\}\Bigr\}$ has only finitely many solutions in positive integers \mbox{$x_1,\ldots,x_n$}, then each such solution \mbox{$(x_1,\ldots,x_n)$} satisfies {$x_1,\ldots,x_n \leqslant f(n)$}.} We prove that for every statement $\Psi_n$ the bound {$f(n)$} cannot be decreased. The author's guess is that the statements {$\Psi_1,\ldots,\Psi_9$} are true. We prove that the statement $\Psi_9$ implies that the set ${\mathcal X}$ of all {non-negative} integers $k$ whose number of digits belongs to {${\mathcal P}_{n^2+1}$} satisfies conditions {\tt (1)-(5)}.

Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Standard SAR raw data processing techniques assume uniform motion of the satellite (or aerial vehicle) and a fixed antenna beam pointing sideway orthogonally to the motion path, assumed rectilinear. Despite SAR data processing is a well established imaging technology that has become fundamental in several fields and applications, in this paper a novel approach has been used to exploit coherent illumination, demonstrating the possibility of extracting a large part of the ancillary data information from the raw data itself, to be used in the focusing procedure. In this work an effort has been carried out to try to focus the raw SAR complex data matrix without the knowledge of anyof the parameters needed in standard focusing procedures as Range Doppler (RD) algorithm, ω - K algorithm and Chirp Scaling (CS) algorithm. All the literature references regarding the algorithms needed to obtain a precise image from raw data use such parameters that refer both to the SAR system acquisition geometry and its radiometric specific parameters. In [12], authors introduced a preliminary work dealing with this problem and able to obtain, in the presence of a strong point scatterer in the observed scene, good quality images, if compared to the standard processing techniques. In this work the proposed technique is described and performances parameters are extracted to compare the proposed approach to RD.

Here, using the theory of electrical-quantum modelling of the neutron and proton as a three-phase alternating current electrical generator, we will analyse the proton decay and the inverse neutron decay and determine the following subatomic particles, Dproton, Protoniu, Dneutron and Neutroniumd.

Here we will electrically-quantum model the neutron and proton as a three-phase alternating current electric generator, for this, we will use the theory of three-phase electric generators and vector or phasor diagrams. We will use this model to hypothesize how the quarks that form neutrons and protons with a combined mass of 10 MeV/c², can generate, through quarks-antiquarks-gluon interactions, a mass of 939.56 MeV/c² for the neutron and a mass of 938.27 MeV/c² for the proton. Using quantum mechanics and the theory of the generalization of the Boltzmann constant in curved space-time we will calculate the number of quarks-antiquarks-gluons and gravitons inside a neutron. We will also analyse βˉ decay using vector diagrams, we will calculate the tension of the string T₀ and the length of the string ℓs between quarks-antiquark and finally, we will model a black hole using a neutron equivalent model. In version 2 of this article, we will update the vector diagrams of the βˉ decay and theoretically calculate the energy of the W⁻ boson, the Z⁰ boson, and the Θ angle, Θ = arc cos (W⁻/Z⁰). We will demonstrate, through vector diagrams, that quarks-antiquarks-gluon interactions are the cause of the origin of the W⁻ boson and the Z⁰ boson. We will also demonstrate how the fine structure constant α originates. It is important to make clear, in future updates, we will describe the relationship that exists between the theory described in this paper and the Isospin theory, flavour and colour theory

Here we mathematically model black holes and the early universe following dynamics similar to RLC electrical models, focusing on their similarities at the singularity. We use this mathematically modelling to hypothesize the evolution of an expanding universe as the result of a black hole collapse followed by its evaporation. Or model consists of several steps defined by: (1) the formation of a black hole following general relativity equations; (2) growth of the black hole modelled as a resistance-capacitance-like electrical circuit; (3) expansion of space-time following the disintegration of the black hole, modelled by RLC-like dynamics. In updating this article, version 2, we will expand by presenting three additional examples related to the theory of the generalization Boltzmann's constant in curved space-time and the theory of general and especial relativity. We will calculate the critical mass to produce a black hole in the LHC, the existence of a high temperature Bose-Einstein condensate and finally we will demonstrate the existence of a tangential force to the repulsion force in the disintegration of subatomic particles. In the update of this article, version 3, we will expand to develop two examples. First, we will present the relationship between M-theory, extra dimensions with the theory of the generalization of Boltzmann's constant in curved space-time. Secondly, we will propose the idea of ​​updating the Lambda-CDM model, considering the primordial gravitational waves to correctly describe the evolution of the universe.

Backward electromagnetic waves are extraordinary waves with contra-directed phase velocity and energy flux. Unusual properties of the coherent nonlinear optical coupling of the phase-matched ordinary and backward electromagnetic waves with contra-directed energy fluxes are described which enable greatly-enhanced frequency and propagation direction conversion, parametrical amplification, as well as control of shape of the light pulses. Extraordinary transient processes that emerge in such metamaterials in pulsed regimes are described. The results of the numerical simulation of particular plasmonic metamaterials with hyperbolic dispersion are presented, which prove the possibility to match phases of such coupled guided ordinary and backward electromagnetic waves. Particular properties of the outlined processes in the proposed metamaterial are demonstrated through numerical simulations. Potential applications include ultra-miniature amplifiers, frequency changing reflectors, modulators, pulse shapers, and remotely actuated sensors.