It has been suggested that primordial planets could have formed in the early Universe and the missing baryons in the Universe could be explained by primordial free-floating planets of solid hydrogen. Many such planets were recently discovered around the old and metal poor stars and such planets could have formed at early epochs. Another possibility for missing baryons in the Universe could be that these baryons are admixed with DM particles inside the primordial planets. Here we discuss the possibility of admixture of baryons to the DM primordial planets discussed earlier. We consider gravitationally bound DM objects with the DM particles constituting them varying in mass from 20 to100GeV. Different fractions of DM particles mixed with baryonic matter in forming the primordial planets are discussed. For the different mass range of DM particles forming DM planets, we have estimated the radius and density of these planets with different fractions of DM and baryonic particles. It is found that for heavier mass DM particles with the admixture of certain fractions of baryonic particles, the mass of the planet increases and can reach or even substantially exceed Jupiter-mass. The energy released during the process of merger of such primordial planets is discussed. Also the energy required for the tidal breakup of such an object in the vicinity of a black hole is also discussed.

The star matter composed of nucleons deep inside the compact star like a neutron star is believed to be very dense and various new types of concepts and physical phenomena due to the nontrivial strong correlations are naturally expected. Peudo-conformality in dense star matter has been discussed recently assuming the hidden underlying scale symmetry, which is partly supported by the recent discussions of infrared conformal window of QCD. It is found that the appearance of dilaton and the dilatonic mean field calculation of nucleonic matter lead to the density independent nucleon mass at higher density regime than normal nuclear matter density. Non-vanishing constant nucleon mass can be considered as a chiral invariant mass of the parity doublet model, in which the chiral symmetry is manifested even in the massive nucleon sector provided with a parity doubling. In this paper we will discuss how the chiral and scale symmetry are correlated to lead the parity doublet symmetry inside the core of the compact star. A simple schematic model is adopted. The star matter at T=0 is basically composed of the nucleons. As a first approximation, they can be treated as free fermions with the effective mass filled up to fermi surface. There is a nontrivial feature due to the interplay between vector meson and nucleon(or equivalently dilaton, χ). The trace of energy momentum tensor approaches density independent, the pseudo-conformal phase. Local fluctuations inside the star matter will be travelling with the speed of sound which depends on the equation of state. In the pseudo-conformal phase, the speed of sound approaches to the conformal velocity for the scale symmetric matter, vc=13c. The excitations of the parity doublets in the compact star matter as an emerging phenomena in pseudo-conformal phase will be discussed in connection to the chiral symmetry. The possible implication on the corespondence of hadrons to quark degrees of freedom will be briefly discussed.

The fundamental theory of nuclear interactions, Quantum Chromodynamics (QCD), operates in terms of quarks and gluons at higher resolution. At low resolution the relevant degrees of freedom are nucleons. Two-nucleon Short-Range Correlations (SRC) help to interconnect these two descriptions. SRCs are temporary fluctuations of strongly interacting close pairs of nucleons. The distance between the two nucleons is comparable to their radii and their relative momenta are larger than the fermi sea level. According to the electron scattering experiments held in the last decade, SRCs have far-reaching impacts on many-body systems, the nucleon-nucleon interactions, and nuclear substructure. The modern experiments with ion beams and cryogenic liquid hydrogen target make it possible to study properties of the nuclear fragments after quasi-elastic knockout of a single nucleon or an SRC pair. The first SRC experiment at BM@N (2018) with a carbon beam has shown that detection of an intact 11B nucleus after interaction selects out the quasi-elastic knockout reaction with minimal contribution of initial- and final-state interactions. Also, 25 events of SRC-breakups showed agreement in SRC properties as knows from electron beam experiments. The analysis of the second measurement of SRC at BM@N held in 2022 with an improved setup is currently ongoing. The SRC project at JINR moved to a new experimental area in 2023, where the next measurement is being planned in terms of experimental setup and physics goals.

The production of particles outside the region of nucleon-nucleon kinematics due to interactions involving dense cold clusters of quark-gluon matter in nuclei is calculated. The possibility of observing this process in the region of central rapidities and large transverse momenta in heavy ion collisions at low energies with MPD detector at the NICA collider has been demonstrated.

This article utilizes the Canny edge extraction algorithm based on contour curvature and the cross-correlation template matching algorithm to extensively study the impact of high-repetition-rate CO2 pulsed Laser on the target extraction and tracking performance of the infrared imaging detector. It establishes a quantified dazzling pattern for lasers on infrared imaging systems. By conducting laser dazzling and damage experiments, a detailed analysis of the normalized correlation between target and dazzling images is performed to quantitatively describe laser dazzling effects. Simultaneously, an evaluation system, including target distance and laser power evaluation factors, is established to determine the dazzling level and whether the target is recognizable. The research results reveal that laser power and target position are crucial factors affecting the detection performance of infrared imaging-guided weapon systems under laser dazzling. Different laser powers are required to successfully interfere with the recognition algorithm of infrared imaging-guided weapons at different distances. And laser dazzling will produce a lot of false edge information, which seriously affects the performance of pattern recognition algorithm. In laser damage experiments, the detector experienced functional damage, with a quarter of the image displaying as completely black. The energy density threshold required for functional damage to the detector is approximately 3 J/cm2. The dazzling assessment conclusions also apply to evaluating damage results. Finally, the proposed evaluation formula aligns with experimental results, objectively reflecting the actual impact of laser dazzling on the target extraction and tracking performance of infrared imaging systems. This study provides an in-depth and accurate analysis for understanding the influence of lasers on the performance of infrared imaging-guided weapons.

ω-Transaminases have been immobilized on macrocellular silica monoliths and used as heterogeneous biocatalysts in a continuous flow mode enantioselective transamination reaction. The support was prepared by a sol-gel method based on emulsion templating. The enzyme was immobilized on the structured silica monoliths both by adsorption, and by covalent grafting using amino-functionalized silica monoliths and glutaraldehyde as a coupling agent. A simple reactor set-up based on the use of a heat-shrinkable Teflon tube is presented and successfully used for the continuous flow kinetic resolution of a chiral amine, 4-bromo-α-methylbenzylamine. The porous structure of the supports ensures effective mass transfer and the reactor works in the plug flow regime without preferential flow paths. When immobilized in the monolith and used in the flow reactor, transaminases retain their activity and their enantioselectivity. The solid biocatalyst is also shown to be stable both on stream and during storage. These essential features pave the way to the successful development of an environmentally friendly process for chiral amines production.

Using multi-color flow cytometry analysis, we studied the immunophenotypical differences between leukemic blasts/LSCs from patients with AML/MDS and hematopoietic stem and progenitor cells (HSPCs) from patients in complete remission (CR) following their successful treatment. The panel of markers included CD34, CD38, CD45RA, CD123 as representatives for a hierarchical hematopoietic stem and progenitor cell (HSPC) classification as well as programmed death ligand 1 (PD-L1). Rather than restricting the evaluation on a 2- or 3-dimensional analysis, we applied a t-distributed stochastic neighbor embedding (t-SNE) approach to get a deeper insight and segregation between leukemic and normal HPSCs. For that purpose, we created a t-SNE map, which resulted in the visualization of 27 cell clusters based on their similarity concerning the composition and intensity of antigen expression. Two of these clusters were “leukemia-related” containing a great proportion of CD34⁺/CD38^- hematopoietic stem cells (HSCs) or CD34⁺ cells with a strong coexpression of CD45RA/CD123, respectively. CD34⁺ cells within the latter cluster were also highly positive for PD-L1 reflecting their immunosuppressive capacity. Beyond this proof of principle study, the inclusion of additional markers will be helpful to refine the differentiation between normal HSPCs and leukemic cells, particularly in the context of minimal disease detection and antigen-targeted therapeutic interventions. Furthermore, we suggest a protocol for the assignment of new cell ensembles in quantitative terms, via a numerical value, the Pearson coefficient, based on a similarity comparison of the t-SNE pattern with a reference.

The implementation of sentinel lymph node (SLN) biopsy is changing the scenario in the surgical treatment of early-stage cervical cancer and the oncologic safety of replacing bilateral pelvic lymphadenectomy with SLN biopsy is currently under investigation. One of the undisputed values of SLN biopsy is its diagnostic accuracy in detecting low-volume metastases (LVM) via pathologic ultrastaging. In early-stage cervical cancer, the reported incidence of LVM ranges from 4 to 20%. The prognostic impact and the role of adjuvant treatment in patients with LVM is still unclear. Some non-prespecified analyses in prospective studies showed no impact on the oncologic outcomes compared to node-negative disease. However, the heterogeneity of the studies, the differences in the disease stage and the use of adjuvant treatment, and the concomitant pelvic lymphadenectomy (PLND) make any conclusion on this topic hard. Current guidelines suggest considering micrometastasis (MIC) as a node-positive disease, while isolated tumor cells (ITC) as a node-negative disease, with a low level of evidence. This review aims to highlight the unanswered questions about the definition, identification, prognostic and therapeutic role of LVM and underline the present and future challenges we are facing. We hope this review will guide further research, giving robust evidence on LVM and their impact on clinical practice.

Particulate matter (PM) is one of the problems faced in environmental science. It has health effects on man and animals in both developed and developing countries. Research and efforts have been on it several years back. Policy statements and efforts have been published. This review paper is an added information on air pollution. In it, efforts were made in discussing these: classification, effects, methodology, case studies and source apportionment. It is hoped that this paper would contribute to existing knowledge on PM.

Nowadays the relationship between planning land use and actual land use is not so clear in general. A lot of efforts have been put in the failures of regulation for the expansion of construction land. However, it still lacks an integrated approach to study the effectiveness of land use regulation in terms of different land use types. Furthermore, the existing evaluation of land use plan mainly focuses on a general level, a detailed research on the regulation effectiveness of each construction land use type is absent. Therefore, this research tries to evaluate regulation effectiveness of land use plan, which takes Cangwu country, Guangxi Province as an example. The finding by analysis is that the total area of construction land expansion was about 3494.73 ha, nearly 1.1 times of the plan quota. Moreover, the effectiveness differs greatly in various construction land use types. Town, industrial/mining sites can be well regulated through the quota of land use plan. While, the quota regulation system is not as effective for other type of construction land. Thus, we suggest to improve the regulation effectiveness of construction land through different plan instruments.

A portable laser photoacoustic sensor based on a Field-Programmable Gate Array (FPGA) is reported for methane detection. A tunable DFB diode laser in the 1654 nm wavelength range is used as an excitation source. The photoacoustic signal processing was implemented by a FPGA device. A small resonant photoacoustic cell is designed. The minimum detection limit (1σ) of 10 ppm for methane (CH₄) is demonstrated.

NiV2O6 thin films were grown on glass slides with varying thicknesses using the nebulizer spray pyrolysis. The impact of thickness on the thin films' optical, structural, morphological, and electrical characteristics was systematically investigated. The X-ray diffraction and micro-Raman analysis confirmed the formation of the triclinic NiV2O6 system. Surface morphology and roughness variations in the as-deposited NiV2O6 films were studied using scanning electron microscopy (SEM) and a profilometer. Optical properties, including optical band gap (Eg), extinction coefficient (k), absorption coefficient (α), and refractive index (n), were determined through optical reflectance and transmittance measurements. The optical energy gap of the as-deposited NiV2O6 films decreased from 2.3 eV to 1.9 eV with increased layer thickness. Furthermore, the photo-detectivity of the films demonstrated an enhancement corresponding to the prolonged spray time. The sensitivity values obtained for visible irradiation are 328, 511, and 433 for samples S1, S2, and S3, respectively. The obtained results are imputed to the specific porous microstructure.

A persistent idea in cosmology is that the universe originated and then continued to evolve as a black hole. While the notion of a black hole universe has generally been framed within the standard cosmological model, the latter has had numerous problems related to dark matter, dark energy and other issues. To avoid such problems an alternative is proposed which omits cosmic expansion, dark matter and dark energy. The observable universe is cast instead as primarily a thin spherical shell of cold (~29 K) baryonic matter situated near the Hubble radius. This shell of plasma holds 95% of the observable universe’s mass, the remaining 5% existing in the interior galaxies and gas clouds. A key premise of the model is that spacetime is fundamentally photonic in nature. This allows photon energy to be transferred to spacetime in the Hubble redshift and to be transferred back to photons in a novel blueshift. These exchanges together drive a cosmic energy cycle for gravity and the cosmological constant, Λ. Photons of the cosmic microwave background originating in the plasma shell lose energy to ‘cooler’ regions of spacetime in interior zones via the Hubble redshift. This gives rise to gravity through the optical gravity approach. The depleted photons moving back towards the shell are then reenergized in ‘hotter’ spacetime regions via the Hubble blueshift. These photons eventually exert outward pressures on the shell which perfectly balance the inward forces of gravity, in this manner functioning as Einstein’s cosmological constant. The observable universe behaves as a closed system in thermodynamic equilibrium with constant energy and entropy and indeterminate age. Black holes are suggested to have analogous plasma shell structures and gravity/Λ cycles.

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

Methods to handle uncertainty in economic evaluation have gained much attention in the literature and the cost-effectiveness acceptability curve (CEAC) is the most widely used method to summarize and present uncertainty associated with program costs and effects in cost-effectiveness analysis. Some researchers have emphasized the limitations of the CEAC for informing decision and policy makers as the CEAC is insensitive to radial shifts of the joint distribution of incremental costs and effects in the North-East and South-West quadrants of the cost-effective plane (CEP). Furthermore, it has been pointed out that the CEAC does not incorporate risk-aversion in valuing uncertain costs and effects. In the present article we show that the cost-effectiveness affordability curve (CEAFC) captures both dimensions of the joint distribution of incremental costs and effects on the CEP and is therefore sensitive to radial shifts of the joint distribution on the CEP. Furthermore, the CEAFC also informs about the budget impact of a new intervention as it estimates the joint probability an intervention is both affordable and cost-effective. Moreover, we show that the cost-effectiveness risk-aversion curve (CERAC) allows to incorporate risk-aversion into the analysis and can therefore be used to inform decision-makers who are risk-averse. We use data from a published cost-effectiveness model of palbociclib in addition to letrozole versus letrozole alone for the treatment of oestrogen-receptor positive, HER-2 negative, advanced breast cancer to demonstrate the differences between CEAC, CEAFC and CERAC and show how these can jointly be used to inform decision and policy makers.

The aim of this study was to evaluate the effect of two different insertion speeds at 8 different insertion torque values ranging from 25-60 during implantation in a dense polyurethane D1 bone model on the placement status and removal torque of dental implants. In this study, 50 pcf single layer polyurethane plates were used. In the study, a total of 320 implant sockets were divided into 2 groups as Group 1 (30 rpm) and Group 2 (50 rpm) in terms of insertion speed. Group 1 and Group 2 were divided into 8 subgroups as 25, 30, 35, 40, 45, 50, 55 and 60 torques. There were 20 implant sockets in each subgroup. During the implantations, implant placement status and removal torque values were assessed. There was a statistically significant difference between the 30 and 50 RPM groups in terms of overall implant placement status (p<0.01). It was found that the removal torque values at 50 RPM were statistically significantly higher than those at 30 RPM (p<0.01). This study showed that in dense D1 bone, the minimum parameters at which all implants could be placed at bone level were 50 torque at 30 rpm and 40 torque at 50 rpm.

A sparse language is a formal language such that the number of strings of length $n$ is bounded by a polynomial function of $n$. We create a class with the opposite definition, that is a class of languages that are dense instead of sparse. We define a dense language on $m$ as a formal language (a set of binary strings) where there exists a positive integer $n_{0}$ such that the counting of the number of strings of length $n \geq n_{0}$ in the language is greater than or equal to $2^{n - m}$ where $m$ is a real number and $0 < m \leq 1$. We call the complexity class of all dense languages on $m$ as $DENSE(m)$. We prove that there exists an $\textit{NP--complete}$ problem that belongs to $DENSE(m)$ for every possible value of $0 < m \leq 1$.

The ever-rising demands for energy dense electrochemical storage systems have been driving interests in beyond Li-ion batteries such as those based on lithium and magnesium metals. These high energy density batteries suffer from several challenges, several of which stem from the flammability/volatility of the electrolytes and/or instability of the electrolyte with either the negative, positive electrode or both. Recently, hydride-based electrolytes have been paving a path towards overcoming these issues. Namely, highly performing solid state electrolytes have been reported and several key challenges in multivalent batteries were overcome. In this review, the classes of hydride-based electrolytes reported for energy dense batteries are discussed. Future perspectives are presented to guide research directions in this field.

Abstract: Author attribution refers to identifying the author of a document by distinguishing between texts written by various authors. Since the author’s writing style is a straightforward concept of his writing habits, an author’s attribution can be used in various sections of society, including legal work, court cases, and plagiarism. This paper studies and compares a deep architecture that automatically identifies Persian writers through their writing styles. For this purpose, since there were no existing datasets suitable for author identification in Persian, the first step was to collect three different datasets: Novels, News, and Twitter. Afterward, the Word2Vec algorithm is trained on many Persian datasets and used as word embedding. To have syntactic features besides semantic ones, Part Of Speech (POS) embedding has also been used. In the next step, an attention mechanism and Long Short-Term Memory (LSTM) are coupled with residual connections. Thus, the current layer input becomes the output of all previous layers rather than the top one. The model implemented is superior in performance for all three types of data compared to earlier models in text classification and author attribution. Absolute accuracies of 90.22%, 85.10%, and 71.39% were achieved among the three Novels, News, and Tweets datasets.

The main objective of this work is to investigate the temporal variation of PM10 concentrations within the urban area of Athens during the years 2001-2015. For this purpose, the time series of the particulate matter with aerodynamic diameter less than 10μm (PM10) is recorded for a 15-year period (2001-2015) in two different monitoring stations located in the urban area of Athens. The results show a totally different behavior of PM10 concentrations between the Athens city center and the suburban areas. It seems that in the city center the main sources of PM10 are traffic and heating systems especially during the cold period of the year. Furthermore, in the city center a significant seasonal variation was found with high concentrations during the cold period of the year and lower concentrations during the warm period of the year. Moreover, it was found that during the weekends, there is a decrease in PM10 concentrations probably due to the fact that majority of people do not use their vehicles. Finally, for both locations a significant temporal decreasing trend of the mean annual PM10 concentrations was found which indicates that during the last years, there have been improvements towards a better air quality.

The main objective of this work is the assessment of the annual number of hospital admissions for respiratory disease (HARD) due to the exposure to in-healable particulate matter (PM10), within the greater Athens area (GAA), Greece. Towards this aim, the time series of the particulate matter with aerodynamic diameter less than 10μm (PM10) recorded in six monitoring stations located in the GAA, for a 13-year period 2001-2013, is used. Initially, a descriptive statistical treatment of PM10 concentrations took place. Furthermore, the AirQ2.2.3 software developed by the WHO was used to evaluate adverse health effects by PM10 in the GAA during the examined period. The results show that, during the examined period PM10 concentrations present a significant decreasing trend. Also, the mean annual HARD cases per 100,000 inhabitants ranged between 20 (suburban location) and 40 (city centre location). Approximately 70% of the annual HARD cases are due to city centre residents. In all examined locations, a declining trend in the annual number of HARD cases is appeared. Moreover, a strong relation between the annual number of HARD cases and the annual number of days exceeding the European Union daily PM10 threshold value was found.

Tellurium exhibits exceptional intrinsic electronic properties. However, investigations into the modulation of tellurium's electronic properties through physical modification are notably scarce. Here, we present a comprehensive study focused on the evolution of the electronic properties of tellurium crystal flakes under plasma irradiation treatment by employing conductive atomic force microscopy and Raman spectroscopy. The plasma-treated tellurium experienced a process of defect generation through lattice broken. Prior to the degradation of electronic transport performance due to plasma irradiation treatment, a remarkable observation emerged: in the low-energy region of hydrogen plasma-treated tellurium, a notable enhancement in conductivity was unexpectedly detected. The mechanism underlying this enhancement in electronic transport performance was thoroughly elucidated by comparing it with the electronic structure induced by argon plasma irradiation. This study not only fundamentally uncovers the effects of plasma irradiation on tellurium crystal flakes, but also unearths an unprecedented trend of enhanced electronic transport performance at low irradiation energies when utilizing hydrogen plasma. This abnormal trend bears significant implications for guiding the prospective application of tellurium-based 2D materials in the realm of electronic devices.

: The radar multi target tracking (MTT) technique requires prior knowledge of a number of parameters about the sensor, the target and backgrounds. The Integrated Track Splitting (ITS) is a fully automatic track-while-scan (TWS) target tracking algorithm capable of extracting and tracking a target in a dense clutter environment using quality false track discrimination (FTD) methodology. The computational complexity in ITS algorithm is limited, compared to other algorithms they use statistical methods to discriminate between false and true tracks, such as multiple hypothesis tracking (MHT), mainly due to the FTD performed. The paper provides an analysis of tracking parameters that allows determining the limit of the possibility of successful target tracking. Extensive experiments have confirmed that the recursive determination of the probability of the existence of a track during tracking can confirm a true track and reject a false track. The clutter density, number of random occurred targets, targets load during the maneuver and the target detection probability were varied. The results of experiments, carried out via Monte Carlo simulations, shown over representative confirmed true tracks (CTT) diagrams, root mean square error position and normalized tracking efficiency parametric diagrams allow the user to select optimal multi-target tracking parameters for different scenarios and clutter densities.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the Kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the Kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously-emitted thermal fluctuations and the background turbulence leads to the formation of non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the Kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment.

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven a promising method for fast SOM content estimation. However, soil physical properties significantly affect the sensitivity of satellite hyperspectral imaging to SOM, leading to poor generalization ability of the estimation model. This study aims to improve the spatiotemporal transferability of the SOM prediction model by alleviating the coupling effect of soil physical properties on the spectra. Based on satellite hyperspectral images and soil physical variables, including soil moisture (SM), soil surface roughness (root mean squared height, RMSH), and soil bulk weight (SBW), a soil spectral correction strategy was established based on the information unmixing method. Two important grain-producing areas in Northeast China were selected as study areas to verify the performance and transferability of the spectral correction model and SOM content prediction model. The results showed that soil spectral corrections based on fourth-order polynomials and the XG-Boost algorithm had excellent accuracy and generalization ability, with residual predictive deviations (RPD) exceeding 1.4 in almost all bands. In addition, when the soil spectral correction strategy was adopted, the accuracy of the SOM prediction model and the generalization ability after model migration were significantly improved. The SOM prediction accuracy based on the XG-Boost corrected spectrum was the highest, with a coefficient of determination (R2) of 0.76, root mean square error (RMSE) of 5.74 g/kg, and RPD of 1.68. The prediction accuracy, R2, RMSE, and RPD of the model after migration were 0.72, 6.71 g/kg, and 1.53, respectively. Compared with the direct migration prediction of the model, adopting the soil spectral correction strategy based on fourth-order polynomials and XG-Boost reduced the RMSE of the SOM prediction results by 57.90% and 60.27%, respectively. The performance comparison highlighted the advantages of considering soil physical properties in regional-scale SOM prediction.

Bulk composition, mineralogy and microchemistry of various fractions of the filling of the Crater No. 4 at Emmerting were investigated. Here we present mainly the fine fractions, which, in contrast to pebbles larger than ca. 4 cm, are relatively poor in material affected by melting. A 0.1 mm long meteorite fragment without ablation features was found, and remelted fragments of the same body have been identified. The projectile was dominated by enstatite, also containing forsterite, basic plagioclase, Ni-rich pyrrhotite and troilite, kamacite, silica, and probably merrillite. The molten fragments contain porous Mg-rich glass (indicating temperature &gt; 1500 °C), minor Fe oxides, and occasionally uncommon Ni-rich minerals. The bulk composition and electron microprobe show that the amount of meteoritic material is low (&lt;&lt; 1 %), and it is not unequivocally manifested even in platinum-group elements abundances and osmium isotope ratios (the latter, however, were only measured in two samples). This can be explained by dilution of the filling by particles brought after the crater formation, and by probably achondritic composition of the projectile. Relatively large hollow spheroid Fe oxide particles were observed in thin sections from the magnetic fraction. A Mn oxide hollow spherule has also been found. In magnetically separated filling from the nearby Crater No. 5, bulk chemical composition points to contamination with several metals and metalloids probably due to influence of recent alluvial sediments. Therefore, the extent of meteoritic contamination in this crater may be even smaller.

Spectral characteristics of CDOM in water column are a key parameter for bio-optical modeling. Knowledge of CDOM optical properties and spatial discrepancy based on the relationship between water quality and spectral parameters in Yinma River watershed with in situ data collected highly-polluted waters are exhibited in this study. Seasonal field data sets collected over a period of 2 months in 2015 in Yinma River Watershed. Based on the comprehensive index method, the riverine waters showed serious contamination, especially the COD, Fe, Mn, Hg and DO were out of range contamination warning. Dissolved organic carbon (DOC) and total suspended matter (TSM) with prominent non-homogenizing were significantly high in the riverine waters, but chlorophyll-a (Chl-a) was opposite. Ternary phase diagram showed that non-algal paritcles absorption played an important role in total non-water light absorption (>50%) in most sampling locations, and mean contribution of CDOM were 13% and 22% in summer and autumn respectively. Analysis of ratio of absorption at 250-365 nm (E_250:365) and spectral slope (S_275-295) indicated that CDOM had higher aromaticity and molecular weight in autumn than in summer, is consistent with the results of water quality and relative contribution. Redundancy analysis (RDA) indicated that the environmental variables OSM had a strong correlation with CDOM absorption, followed by heavy metal, e.g., Mn, Hg and Cr⁶⁺. However, for the specific UV absorbance (SUVA₂₅₄), the seasonal values showed opposite results compared with the reported literature. The potential reasons were the more UDOM (uncolored Dissolved Organic Matter) from human source (wastewater effluent) existed in waters. Terrigenous inputs simultaneously are in relation to the a_CDOM(440)-DOC relationship with the correlation coefficient was 0.90 in summer (2-tailed, p<0.01), and 0.58 in autumn (2-tailed, p<0.05). Spatial distribution of CDOM parameters exhibited that the downstream regions focused on dry land have high CDOM molecular weight and aromatic hydrocarbon. Partial sampling locations around the cities or countries generally showed abnormal values due to terrigenous inputs. As a bio-optical model parameter, spectral characteristic of CDOM is helpful in adjusting the derived algorithms in highly-polluted environments. The study on organic carbon and pollutants in highly-polluted waters had an important contribution to global carbon balance estimation and water environment protection.

The performance of lattice-Boltzmann solver implementations usually depends mainly on memory access patterns. Achieving high performance requires then complex code which handles careful data placement and ordering of memory transactions. In this work, we analyse the performance of an implementation based on a new approach called the data-oriented language, which allows the combining of complex memory access patterns with simple source code. As a use case, we present and provide the source code of a solver for D2Q9 lattice and show its performance on GTX Titan Xp GPU for dense and sparse geometries up to 4096 2 nodes. The obtained results are promising, around 1000 lines of code allowed us to achieve performance in the range of 0.6 to 0.7 of maximum theoretical memory bandwidth (over 2.5 and 5.0 GLUPS for double and single precision, respectively) for meshes of size above 1024 2 nodes, which is close to the current state-of-the-art. However, we also observed relatively high and sometimes difficult to predict overheads, especially for sparse data structures. The additional issue was also a rather long compilation, which extended the time of short simulations, and a lack of access to low-level optimisation mechanisms.

With the development of deep learning, the Super-Resolution (SR) reconstruction of microscopic images has improved significantly. However, the scarcity of microscopic images for training, the underutilization of hierarchical features in original Low Resolution (LR) images, and the high-frequency noise unrelated with the image structure generated during reconstruction process are still challenges in the Single Image Super-Resolution (SISR) field. Faced with these issues, we first collected sufficient microscopic images through Motic, a company engaged in the design and production of optical and digital microscopes, to establish a dataset. Secondly, we proposed a Residual Dense Attention Generative Adversarial Network (RDAGAN). The network comprises a generator, an image discriminator, and a feature discriminator. The generator includes a Residual Dense Block (RDB) and a Convolutional Block Attention Module (CBAM), focusing on extracting the hierarchical features of the original LR image. Simultaneously, the added feature discriminator enables the network to generate high-frequency features pertinent to the image’s structure. Finally, we conducted experimental analysis and compared our model with six classic models. Compared with the best model, our model improved PSNR and SSIM by about 1.5dB and 0.2, respectively.

Stemming from the object overlap and undertraining from the few samples, the road dense object detection is confronted with the poor object identification performance and the inability to recognize edge objects. Based on this, one transfer learning-based YOLOv3 approach for identifying dense objects in the road has been proposed. Firstly, Darknet-53 network structure is adopted to obtain pre-trained YOLOv3 model, then the transfer training is introduced as the output layer for the special dataset of 2000 images containing vehicles; in the proposed model, one random function is adapted to intialize and optimize the weights of the transfer training model, which is seperately designed from the pre-trained YOLOv3; and the object detection classifier replaces the fully connected layer, which further improves the detection effect, the reduced size of the network model can further reduce the training and detection time, and can be better applied to actual scenarios. The experimental results demonstrate that the object detection accuracy of the presented approach is 87.75% for the Pascal VOC 2007 dataset, which is superior to the traditional YOLOv3 and the traditional YOLOv2 by 3.05% and 11.15%, respectively. Besides, the test was carried out using UA-DETRAC, a public road vehicle detection dataset, the object detection accuracy of the presented approach reaches 79.23% in detecting images, which is 4.13% better than the traditional YOLOv3, and compared with the existing relatively new object detection algorithm YOLOv5, the detection accuracy is 1.36% better. Moreover, the detection speed of the proposed YOLOv3 method reaches 31.2 Fps/s in detecting images, which is 7.6 Fps/s faster than the traditional YOLOv3, and compared with the existing relatively new object detection algorithm YOLOv5, the speed is 4.3 Fps/s faster; the proposed YOLOv3 performs 79.38Bn of floating point operations per second in detecting video, which obviously surpasses the traditional YOLOv3 and the newer object detection algorithm YOLOv5.

At present there is a renewed interest in theories of ”modified” gravity. Here, under a more drastic modification enforced by Galilei group, we obtain a completely new gravitational structure, and which exists in addition to the already available general relativity of today. Correlated with this, we show that in addition, there is a new ”modified” quantum mechanics, in as much as it exists as an independent and new ”pure” non-relativistic quantum me- chanics, and which has no relativistic counterpart. This is in addition to the present quantum mechanics, where the relativistic and non-relativistic structures are counterparts of each other. The above holds, firstly due to the correlation between Galilei group and quantum mechanics. These math- ematical conclusions are consolidated by the fact that there exists a physical Majorana interaction between each neutron- proton pairs in nuclei. Galilei invariance of Majorana exchange in Majorana interaction, shows that the mass here is of pure gravitational nature, and which is immune to the other three forces. This makes an amazing connection between the gravitational force and the quantum mechanics. This pure gravitational mass would man- ifest itself as dark matter of the universe. It is our new modified gravity that generates the dark matter.

A close inspection of Zwicky's seminal papers on the dynamics of galaxy clusters reveals that the discrepancy discovered between the dynamical mass and the luminous mass of clusters has been widely overestimated in 1933 as a consequence of several factors, among which the excessive value of the Hubble constant $H_0$, then believed to be about seven times higher than today's average estimate. Taking account, in addition, of our present knowledge of classical dark matter inside galaxies, the contradiction can be reduced by a large factor. To explain the rather small remaining discrepancy of the order of 5, instead of appealing to a hypothetic exotic dark matter, the possibility of a inhomogeneous gravity is suggested. This is consistent with the ``cosmic tapestry" found in the eighties by De Lapparent and her co-authors, showing that the cosmos is highly inhomogeneous at large scale. A possible foundation for inhomogeneous gravitation is the universally discredited ancient theory of Fatio de Duillier and Lesage on pushing gravity, possibly revised to avoid the main criticisms which led to its oblivion. This model incidentally opens the window towards a completely non-standard representation of cosmos, and more basically calls to develop fundamental investigation to find the origin of the large scale inhomogeneity in the distribution of luminous matter

The local and global order in dense packings of linear, semi-flexible polymers of tangent hard spheres are studied by employing extensive Monte Carlo simulations at increasing volume fractions. Chain stiffness is controlled by a tunable harmonic potential for the bending angle whose intensity dictates the rigidity of the polymer backbone as a function of the bending constant and equilibrium angle. The studied angles range from acute to obtuse ones, reaching the limit of rod-like polymers. We analyze how packing density and chain stiffness affect the ability of chains to self-organize at the local and global levels. The former corresponds to crystallinity as quantified by the Characteristic Crystallographic Element (CCE) norm descriptor, while the latter is computed through the scalar orientational order parameter. In all cases, we identify the critical volume fraction for the phase transition and gauge the established crystal morphologies, developing a complete phase diagram as a function of packing density and equilibrium bending angle. A plethora of structures is obtained, ranging from random hexagonal closed packed morphologies of mixed character and almost perfect face centered cubic (FCC) and hexagonal close-packed (HCP) crystals at the level of monomers, to nematic mesophases, with prolate and oblate mesogens at the level of chains. For rod-like chains, hysteresis is observed between the establishment of long-range nematic order and crystallization, while for right-angle chains both transitions are synchronized. A comparison is also provided against the analogous packings of monomeric and fully flexible chains of hard spheres.

The article is focused on detailed framework process for hierarchized construction of periodic freight train paths (PFTPs) – allocation of pre-arranged railway capacity to freight rail operators. The framework process considers fluctuations in demand for capacity from freight rail opera-tors, so the quality of a freight train path is related with its construction priority. Introduced framework process aims to offer freight rail operators attractive train paths, with low number of scheduled stops, and this way enhance competitiveness and decrease energy consumption of freight railway as a factor for sustainable development. The proposed generic process is in-tended for all time horizons of capacity allocation. Correctness of the framework process is tested on the example of mainline Prague – Dresden, in the context of prospective (denser) mod-el passenger timetable.

The beneficial effects of Lanthanide incorporation into 0.94Na0.5Bi0.5TiO3-0.06BaTiO3 (BNT-BT) matrix on its functional properties were investigated. The conventional solid-state method was used for synthesizing samples. The structural refinement revealed that all samples crystallized in R3c rhombohedral symmetry. Raman spectroscopy study was carried out using green laser excitation and revealed that no clear perceptible variation in frequency is observed. Dielectric measurements unveiled that the introduction of rare earth obstructed the depolarization temperature promoted in BNT-BT with decreasing the diffusive phase transition with increasing the lanthanide size. Only Dysprosium addition showed comparable diffusion constant and dielectric behavior as the unmodified composition. Further, the comparison of the obtained ferroelectric hysteresis and strain-electric field loops revealed that only Dy-phase exhibited interesting properties comparing parent composition. In addition, the incorporation of lanthanides Ln3+ into the BNT-BT matrix led to the development of luminescence characteristics in the visible and near infrared regions, depending on the excitation wavelengths. The simultaneous occurrence of photoluminescence and ferroelectric/piezoelectric properties opens up possibilities for BNT-BT-Ln to exhibit multifunctionality in a wide range of applications.Keywords: Sodium Bismuth Titanate; structural refinement; dielectric properties; ferroelectric properties; piezoelectric properties; Photoluminescence.

The study aimed to estimate the prevalence of respiratory symptoms and to assess respiratory health risks associated with Particulate Matter (PM) exposure among the residents of Windhoek, Namibia. Objectives: To measure particulate pollution concentration in Windhoek through monitoring of particulate matter concentration and to identify any associations between particulate pollution, individual location and respiratory health among the Windhoek resident’s. Methods: an adapted standardized self-administered questionnaire was used to collect respiratory health related data as well as previous exposure, while PM monitoring was done using ASTM D1739 reference method. Results: A high prevalence was observed for cough (43%), breathlessness (25%), and Asthma (11.2%). PM was found to be a significant risk factor for episode of cough and phlegm, while high PM exposure category had increased odds ratio for episode of phlegm and cough (OR: 2.5, 95% CI: 0.8-8.0). No association was observed between location and respiratory health outcomes. Conclusion: The study found high levels of PM concentration across all Windhoek suburbs which were above the German, American and EPA. Enactment of legislation relating to the control and monitoring of PM related emissions at point of generation is required at country and city level.

Machine Learning has completely transformed health care system, which transmits medical data through IOT sensors. So it is very important to encrypt them to protect patient data. encrypting medical images from a performance perspective consumes time; hence the use of an auto encoder is essential. An auto encoder is used in this work to compress the image as a vector prior to the encryption process. The digital image passes across description function and a decoder to get back the image in the proposed work; various experiments are carried out on hyper parameters to achieve the highest outcome of the classification. The findings demonstrate that the combination of Mean Square Logarithmic Error as the loss function, ADA grad as an optimizer, two layers for the encoder, and another reverse for the decoder, RELU as the activation function generates the best auto encoder results. The combination of Mean square error (lose function), RMS prop (optimizer), three layers for the encoder and another reverse for the decoder, and RELU (activation function) has the best classification result. All the experiments with different hyper parameter has run almost very close to each other even when changing the number of layers. The running time is between 9 and 16 second for each epoch.

Physics theory has yet to settle on specific descriptions for new elementary particles, for dark matter, and for dark energy forces. Our work extrapolates from the known elementary particles. The work suggests well-specified candidate descriptions for new elementary particles, dark matter, and dark energy forces. This part of the work does not depend on theories of motion. This work embraces symmetries that correlate with motion-centric conservation laws. The candidate descriptions seem to explain data that prior physics theory seems not to explain. Some of that data pertains to elementary particles. Our theory suggests relationships between masses of elementary particles. Our theory suggests a relationship between the strengths of electromagnetism and gravity. Some of that data pertains to astrophysics. Our theory seems to explain ratios of dark matter effects to ordinary matter effects. Our theory seems to explain aspects of galaxy formation. Some of that data pertains to cosmology. Our theory suggests bases for inflation and for changes in the rate of expansion of the universe. Generally, our work proposes extensions to theory in three fields. The fields are elementary particles, astrophysics, and cosmology. Our work suggests new elementary particles and seems to explain otherwise unexplained data.

The extremely high rotation of some SMBHs is the origin of their relativistic rotational energy that results in their relativistic mass. Relativistic mass creates their relativistic gravity which is a partial answer to the missing dark matter.

The aim of this manuscript is to synthesize and characterize novel silylated Sm3+ and Eu3+ complexes and incorporate them into mesoporous silica nanoparticles (MSNs) and dense silica nanoparticles (DSNs). Sm3+ and Eu3+ ion complexes were chosen for their strong UV-visible emission, deep-red luminescence, and effective interaction with bidentate organic ligands, such as 2-thenoyltrifluoroacetone (tta) and 1,10-phenanthroline (phen). Silylated ligands were employed as coupling agents to form covalent bonds between the complexes and an oxide matrix via a conventional sol-gel process. This approach aims to enhance the thermal stability and photophysical properties of the resulting hybrid material compared to free complexes. The new silylated-bidentate ligand complexes, using tta and phen as organic ligands and 3-chloropropyltriethoxysilane as the silylating agent, were characterized by FTIR, luminescence spectroscopy, and luminescence decay. After incorporation into silica nanoparticles, the hybrid materials were characterized by SEM, TEM, DLS, zeta potential, SAXS, porosity, surface area measurements, luminescence spectroscopy, and MTT assay. The results confirm the successful synthesis of new luminescent silylated complexes with high luminescence intensity and their incorporation into silica nanoparticles.

A formulation of nonequilibrium thermo field dynamics has been performed using the nonequilibrium statistical operator method by D.N. Zubarev. Generalized transfer equations for a consistent description of kinetics and hydrodynamics of the dense quantum-field system with strongly coupled states are derived.

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network GY based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction. While improving [email protected] by 0.514%, the model simultaneously reduces the number of parameters by 43.976%, computational cost by 46.488%, and model size by 41.752%. Additionally, the system constructs pure static octree maps and grid maps. Tests conducted on the TUM dataset and a proprietary dataset demonstrate that GY-SLAM significantly outperforms ORB-SLAM3 in dynamic scenarios in terms of system local-ization accuracy and robustness. It shows a remarkable 92.58% improvement in RMSE for Absolute Trajectory Error (ATE). Compared to YOLOv5s, the GY model brings a 41.5944% improvement in detection speed and a 17.7975% increase in SLAM operation speed to the system, indicating strong competitiveness and real-time capabilities. These results validate the effectiveness of GY-SLAM in dynamic environments and provide substantial support for the automation of logistics tasks by robots in specific contexts.

With the ever-increasing popularity of unmanned aerial vehicles and other platforms providing dense point clouds, filters for identification of ground points in such dense clouds are needed. Many filters have been proposed and are widely used, usually based on the determination of an original surface approximation and subsequent identification of points within a predefined dis-tance from such surface. We present a new filter, Multi-view and shift rasterization algorithm (MVSR) is based on a different principle, i.e., on the identification of just the lowest points in in-dividual grid cells, shifting the grid along both planar axis and subsequent tilting of the entire grid. The principle is presented in detail and compared both visually and numerically to other commonly used ground filters (PMF, SMRF, CSF, ATIN) on three sites with different ruggedness and vegetation density. Visually, the MVSR filter showed the smoothest and thinnest ground profiles, with ATIN the only filter performing comparably. The same was confirmed when comparing ground filtered by other filters with the MVSR-based surface. The goodness of fit with the original cloud is demonstrated by the root mean square deviations (RMSD) of the points from the original cloud found below the MVSR-generated surface (ranging, depending on site, between 0.6-2.5 cm). The MVSR filter performed outstandingly at all sites, identifying the ground points with great accuracy while filtering out the maximum of vegetation/above-ground points. The filter dilutes the cloud somewhat; in such dense point clouds, however, this can be perceived rather as a benefit than as a disadvantage.

With the ever-increasing popularity of unmanned aerial vehicles and other platforms providing dense point clouds, universal filters for accurate identification of ground points in such dense clouds are needed. Many filters have been proposed and are widely used, usually based on the determination of an original surface approximation and subsequent identification of points within a predefined distance from such surface. In this paper, we present a new filter. This Multi-view and shift rasterization algorithm (MVSR) is based on an entirely different principle, i.e., on the identification of just the lowest points in individual grid cells, shifting the grid along both planar axis and subsequent tilting of the entire grid – after each of these steps, one lowest point per cell is detected. The principle is presented in detail and compared both visually and numerically to other commonly used ground filters (PMF, SMRF, CSF, ATIN) on three sites with different ruggedness and vegetation density. Visually, the MVSR filter showed the smoothest and thinnest ground profiles, with ATIN the only filter performing comparably (although the profiles were somewhat thicker and not as complete as MVSR-acquired ground). The same was confirmed when comparing ground filtered by other filters with the MVSR-based surface. The goodness of fit with the original cloud is demonstrated by the root mean square deviations (RMSD) of the points from the original cloud found below the MVSR-generated surface (ranging, depending on site, between 0.6-2.5 cm). ATIN again performed closest to MVSR, with RMSDs of ground filtered points found above MVSR-based surface at individual sites ranging between 4.5-7.4 cm. The remaining filters performed comparable in the simplest flat area but poorly in rugged and much-vegetated sites, with RMSDs above the MVSR surface ranging at such sites from 21 to 95 cm. In conclusion, the novel filter presented in this paper performed outstandingly at all sites, identifying the ground points with great accuracy while filtering out the maximum of vegetation/above-ground points. The filter dilutes the cloud somewhat; in such dense point clouds, however, this can be perceived rather as a benefit than as a disadvantage.

This paper presents a novel approach for semantic segmentation of building roof in dense urban environment with Deep Convolution Neural Network (DCNN) using imagery acquired by a Chinese Very High Resolution (VHR) satellite mission, i.e. GaoFen-2 (GF-2). To provide an operational end-to-end work flow for accurate build roof mapping with feature extraction as well as image segmentation, a fully convolutional DCNN with both convolutional and deconvolutional layers is designed to perform the VHR image analysis for labeling pixels. Since the diverse urban patterns and building styles in large areas, sample image data sets of building roof and non-building roof are collected over different metropolitan regions in China. We selected typical cities with dense urban environment in each metropolitan region as study areas for collecting training and test samples. High performance cluster with GPU-mounted workstations is employed to perform the model training and optimization. With the building roof samples collected over different cities, the predictive model with multiple NN layers is developed for building roof labeling. The validation of the building roof map shows that the overall accuracy(OA) and the mean Intersection Over Union( mIOU) of DCNN based segmentation are 94.67%, 0.85 respectively, while CRF-refined segmentation achieved OA of 94.69% and mIOU of 0.83. The results suggest that the proposed approach is a promising solution for building roof mapping with VHR images over large areas across different urban and building patterns. With the operational acquisition of GF2 VHR imagery, it is expected to develop an automated pipeline for operational built-up area monitoring and timely update of building roof map over large areas.

In this paper we will find that, according to holographic principle {\cite{Holografico}} and thus considering Universe as the ensemble of $\aleph$ information bits or minimum particles of mass $m_{g}$, the contribution to galactic rotation curves can be due the rest of the visible Universe through a non-local collective gravitational interaction of all particles within the Universe's horizon, as a consequence of which all particles are gravitationally entangled and form a unified statistical ensemble. Therefore, we can to describe this global effect in terms of standard local Newtonian gravity within galaxies for the explanation of flatness galactic rotation curves as a possible alternative to the dark matter or MOND hypothesis. We will find a solution for the baryonic Tully-Fischer relation: $M_{b} = A v_{f}^4 \iff A = \left[a_{0}G \right]^{-1}$ with $a_{0} = \frac{cH_{0}}{2\pi}$, where $H_{0}$ is the Hubble constant at present Time $t_{0}$ and $M_{b}$, $G$ and $c$ are the galaxy baryonic mass, gravitational constant and constant speed of light in vacuum respectively. Also we will find the mass discrepancy-acceleration relation, thus obtaining a possible solution for each of the three laws of rotationally supported galaxies proposed in ({\cite{McGaugh}},{\cite{McGaugh1}}).

An evanescent wave is a non-propagating wave with an imaginary wave vector. In this study, we prove that these are solutions of the tachyon-like Klein–Gordon equation, and that in the tunneling of ultrarelativistic spin-1/2 particles they describe superluminal states arising from interactions between a particle and barrier. These states decay as a particle emerges from the opposite side of a potential barrier, conserving the same initial energy but not necessarily the same mass. The obtained theory is applied to the neutrino, to explain flavor oscillations during free flight and determine the conditions that maximize the probability of their occurrence.

Crack inspection in railway sleepers is crucial for ensuring rail safety and avoiding deadly accidents. Traditional methods for detecting cracks on railway sleepers are very time-consuming and lack efficiency. Therefore nowadays, researchers are paying attention to the vision-based algorithm, especially Deep Learning algorithms. In this work, we adopted the U-net for the first time for detecting cracks on a railway sleeper and proposed a modified U-net architecture named Dense U-net for segmenting the cracks. In the Dense U-net structure, we established several short connections between the encoder and decoder blocks, which enabled the architecture to obtain better pixel information flow. Thus, the model extracted the necessary information in more detail to predict the cracks. We collected images from railway sleepers, processed them in a dataset, and finally trained the model with the images. The model achieved an overall F1-score, precision, Recall, and IoU of 86.5% 88.53%, 84.63%, and 76.31% respectively. We compared our suggested model with the original U-net, and the results demonstrate that our model outperformed the U-net in both quantitative and qualitative results. Moreover, we considered the necessity of crack severity analysis and measured a few parameters of the cracks (e.g., length, maximum width, area, density). The engineers must know the severity of the cracks to have an idea about the most severe locations and take the necessary steps to repair the badly affected sleepers.

In recent years, with the development of social media, people are more and more inclined to upload text, pictures and videos on the platform to express their personal emotions, thus the number of short videos is increasing and becoming the first choice for people to socialize. Unlike the traditional way, people can convey their personal emotions and opinions through media other than words, such as video images, etc. for external information. Therefore, the expression and analysis of emotions is not only through text, but also through the analysis of emotional needs in images and videos, and the research scholars have customized products for individual users. Compared with pure text content, video information can more intuitively express users' happiness, anger and sorrow, thus short video-related applications have gained more and more popularity among Internet users in recent years. However, not all short videos on social networking sites can accurately express users' emotions, and related text information can more accurately assist sentiment analysis and thus improve accuracy. However, short video sentiment analysis based on video frame images is inaccurate in some scenarios, such as when expressing tears of joy, the sentiment expressed by the user's facial expression and voice are different, which will cause errors in the analysis of sentiment. As a result, researchers began to consider multimodal sentiment analysis to reduce the impact of the above scenarios on short video sentiment analysis. This paper focuses on proposing a sentiment analysis method for short videos. We first propose a residual attention model to make full use of the information in audio to classify the emotions contained in them. Then the text information in the dataset is classified by feature extraction. The key to extract features from text information is not only to retain the semantic information of the text, but also to explore the potential emotional information in the text, so as to ensure the integrity of the text information features. The experiments show that the sentiment analysis model proposed in this paper is more superior than the baselines.

Dark energy is the primordial energy of the universe. It was not created and will not be destroyed. Dark energy is the “stuff” out of which universal space is made off. Stellar objects exist in dark energy which is a kind of superfluid energy, that we do not know much about it. In interstellar areas, dark energy has a Planck energy density that diminishes in the center of stellar objects accordingly to the amount of their mass. Motion and rotation of stellar objects put in motion and rotation also surrounding dark energy around them. The rotation of supermassive black holes in the center of spiral galaxies rotates the surrounding dark matter and causes the so-called “dark matter effect”. The orbital velocity of stars that are rotating around the central black hole is not diminishing with the distance, as is the case in our solar system. There is no hidden dark matter that causes this effect. The cause is the rotating dark energy of the entire area of the galaxy around the central black hole.

About a century ago, in the spirit of ancient atomism, the quantum of light was renamed the photon to suggest its primacy as the fundamental element of everything. Since the photon carries energy in its period of time, a flux of photons inexorably embodies a flow of time. Time comprises periods as a trek comprises legs. The flows of quanta naturally select optimal paths, i.e., geodesics, to level out energy differences in the least time. While the flow equation can be written, it cannot be solved because the flows affect their driving forces, affecting the flows, and so on. As the forces, i.e., causes, and changes in motions, i.e., consequences, cannot be separated, the future remains unpredictable, however not all arbitrary but bounded by free energy. Eventually, when the system has attained a stationary state, where forces tally, there are no causes and no consequences. Then time does not advance as the quanta only orbit on and on.

Elucidating the nature of dark matter in galactic systems remains one of the important unsolved mysteries of modern cosmology. As a thought experiment, we consider a galaxy model where the light radiating outward from stellar objects produces a gravitational effect larger than Einstein's theory of gravity predicts. Using computer simulations, we observe that this assumption allows the basic rotation curve profiles observed in both dwarf and late-type spiral galaxies to be recreated. It is important to highlight that a separate mass model describing the dark matter halo is not needed or used. This toy model may also lead to insights about the nature of dark energy. If the gravitational effects in the universe are currently dominated by radiated light as this toy model may suggest, the cosmic scale factor would be closely linked to the time-history and spatial distribution of star formation and death rates. An accelerating universe may simply be a manifestation of star death rates exceeding star formation rates in the current epoch.

Vibro-fluidized dry coal beneficiation involves the unavoidable mixing of -1 mm coal dust into the fluidized bed, which compromises the stability and homogeneity of the bed density and reduces the effectiveness of fine-grained coal separation. In order to understand the features of coal powder separation and mixing (-1 mm) in a vibrating fluidized bed, as well as to achieve a uniform and stable bed density, a wide-grained dense medium consisting of -1 mm coal dust and 0.3-0.15 mm magnetite powder was homogeneously mixed in this work. The degree of density separation in the entire bed was examined, as well as the local mixing properties of the Wide-grained Dense Medium. It was discovered that when low vibrational energy was introduced at the same gas velocity, particle separation was enhanced in comparison to the usual fluidized bed. Little bubbles were found to ensnare fine coal dust and migrate upward, increasing density separation. The introduction of high vibrational energy leads to particle disorder within the bed and an increase in the level of particle mixing. The beneficial effects of vibration on the bed are diminished when the gas velocity is gradually increased under specified vibration circumstances. This causes big bubbles to develop more frequently, which increases particle mixing. Among them, the 1-0.5 mm fine-grained coal exhibits the best mixing state; it is less impacted by variations in air velocity and vibration levels, whereas the -0.5 mm coal dust is more affected by each of these variables. Furthermore, a wide range of air velocity regulation without a significant segregation state change was discovered to be achievable by the particle system under vibration circumstances of f=25Hz A=1mm and f=25Hz A=2mm.

.Various synthetic nematicides are currently used effectively in the control of plant parasitic nematodes. However, these nematicides have adverse effects on humans and the environment. Neem oil is eco-friendly alternatives to synthetic nematicides. The effectiveness of repeated neem oil application in suppressing the root-knot nematodes infestation in figs seedlings was therefore examined in this study, both in its natural form (10 ml/L) and in its nano-emulsion form (5 and 7 ml/L). The recorded reduction parameters of M. incognita were J2/250g soil, galls and egg masses / 5g roots of infected fig seedlings were measured at that time, and the effects of these natural additives were compared with the Fosthiazate (Krenkel 75%EC). The impact of such soil amendments on some typical plant parameters, the total microbial count of soil, and the overall enzymatic activity of the fig rhizosphere were also included. Obtained results revealed that the soil population density of root knot nematode suppressed by 80.3% , reduction of nematode egg masses (60.4%) due to the application of nano-emulsion of neem oil (at 7ml/L). Present work recommend the use of nano-emulsion of neem oil as one of the effective and eco-friendly means to reduce the root- knot nematode on fig .

As urban development increases in density, the space to grow urban trees becomes more constrained. In heavily developed areas, small stature trees can be planted to reduce both above- and below-ground conflicts with infrastructure elements. However, even these species have their limits when placed in extremely confining conditions. In this study, we build on past work to determine the minimum planting widths of small stature urban trees. We found that species, stem diameter, and the height at which stem diameter measurements occurred were all strong predictors of trunk flare diameter (adjusted R² of 0.843). Additionally, we modelled the relationship between planting space and the presence or absence of hardscape conflicts – using the predictions derived from this effort to project the potential cost savings in two United States cities. Study results provide a guideline to create sufficient space for urban trees and minimize infrastructure damage and associated cost savings.

The increased deployment of IoT devices in specific areas results in an interference among them and the quality of communications can be severely degraded. To deal with this interference issue, the IEEE 802.11ax standard has been established in hyper-densely wireless networking systems. The 802.11ax adopts a new candidate technology that is called multiple network allocation vector in order to mitigate the interference problem. In this paper, we point out potential problem in multiple network allocation vector which can cause delays to the communication among IoT devices in hyper-dense wireless networks. Furthermore, this paper introduces an adaptive beam alignment algorithm for interference issue resolution. In addition, we analyze potential delays of communications among IoT devices under interference conditions. Lastly, we simulate our proposed algorithm in densely deployed environment and show that the interference issue can be mitigated and the IEEE 802.11ax-based IoT devices can utilize the air interface more fairly compared to conventional IEEE 802.11 distributed coordination function.

Climate adaptation is a major challenge. Chasing the sufficient amount of hay is getting in higher priority. Distant mass hay producers give favourable offers despite long distances. Quality is also gaining position and indicators like RFQ (Relative Forage Quality) is highlighting the marketing language. Hay market as we knew no longer exists in Hungary. Most farmers produce their own hay and do not spend extra cents to buy bales. Climate change however, force them to adapt and store more bales for the future. Horse owners and dairy farmers are the main driver to convince hay producers to provide high quality forage. We gathered Hungarian regional hay-price information and evaluated the trends in this sector. The demand-driven hay-price is in contradiction with premium quality timothy grass hay.

Research shows that stress, a common problem in dense cities, can be relieved in the natural environment. As great significance has been attached to the urban environment and public health in the society, this paper aims to study the relation and interaction between the perceived sensory dimension of urban park green space, attention restoration and state empathy. Therefore, we conducted an on-site questionnaire survey in four typical parks in Chengdu in terms of age, sex, daily stress, frequency of access in parks and other basic information of the respondents. The main part consists of perceived dimension, state empathy and attention restoration. The software SPSS24.0 is applied to the test of the validity and reliability of the PSD Scale, and then the important correlation between the perceived sensory dimensions in the parks and visitors' attention restoration is analyzed through multiple linear regression. Finally, the moderation effect of state empathy is tested by PROCESS. The findings show that (1) only seven dimensions in the PSD Scale are effective; (2) Serene and Refuge in the perceived sensory dimensions have significant effect on the restorative components of attention. (3) Except the dimensions of Rich in Species and Refuge, empathy enhanced the moderation effect in the interaction between the other five dimensions the Perceived Restorative Scale(PRS), especially in the interaction between the dimension Social and PRS. However, this study needs to be further explored to provide scientific basis and design strategy guidance for the research on the restoration potential of urban park green space in high-density urban areas.

The holographic principle states that the information about the volume of space is stored on its boundary. Assuming this holds, we can explain the aspects of gravity. The spacetime needs to be extended to 5D to explain gravity in this context. This naturally explains the four classical tests of gravity namely the gravitational redshift, the perihelion precession, the bending of light, and the gravitational time delay. We also show a novel way in which the universe expands in an accelerated manner at late times without the need for any form of dark energy.

It is shown that quantum entanglement is the only force able to maintain the fourth state of matter, possessing fixed shape at an arbitrary volume. Accordingly, a new relativistic Schrödinger equation is derived and transformed further to the relativistic Bohmian mechanics via the Madelung transformation. Three dissipative models are proposed as extensions of the quantum relativistic Hamilton-Jacobi equation. The corresponding dispersion relations are obtained.

Rising organic charge in northern freshwaters is attributed to increasing levels of Dissolved Natural Organic Matter (DNOM) and shifts in water chemistry. Organic charge concentration may be determined by charge balance calculations (Org.-) or modelled (OAN-) using the conceptual Oliver and Hruška models based on the density of weak acid functional sites (SD) present in DNOM. The charge density (CD) is governed by the SD and protonation and complexation reactions on the functional groups. The models use this SD as a key parameter in empirically fitting the model to Org.-. Utilizing extensive datasets of water chemistry, this study shows that spatial and temporal differences in SD and CD are influenced by variations in the humic-to-fulvic ratio of DNOM and the organic aluminum (Al) complexation, as well as the mole fraction of CD to SD governed by the acidity. Site median SD obtained for 44 long-term monitored acid-sensitive lakes was 11.1 and 13.9 µEq/mg C for the Oliver and the Hruška model, respectively. During the 34 years of monitoring the CD increased by 70%, likely due to rising pH and declining Al complexation with DNOM. Present-day median SD values for the Oliver and Hruška models in 16 low-order streams are 13.8 and 15.8 µEq/mg C, respectively, and 10.8 and 12.5 µEq/mg C, respectively, in 10 high order rivers.

In a recent Foundations of Physics paper [5] by the current author it was shown that, when the self-force problem of classical electrodynamics is properly solved, it becomes a plausible ontology underlying the statistical description of quantum mechanics. In the current paper we extend this result, showing that ordinary matter, thus represented, possibly suffices in explaining the outstanding observations currently requiring for this task the contrived notions of dark-matter, dark-energy and inflation. The single mandatory 'fix' to classical electrodynamics, demystifying both very small and very large scale physics, should be contrasted with other adhoc solutions to either problems. Instrumental to our cosmological model is scale covariance (and 'spontaneous breaking' thereof), a formal symmetry of classical electrodynamics treated on equal footing with its Poincare covariance, which is incompatible with the (absolute) metrical attributes of the GR metric tensor.

With reference to our recently proposed Planck Scale White Hole Cosmology (PS-WHC) or Flat Space Cosmology (PS-FSC), we make an attempt to quantify galactic dark matter and flat rotation speeds in terms of galactic visible matter and cosmic mass. Considering recently observed dwarf galaxies having very little dark matter and assuming a time dependent reference mass unit of $M_X\cong \left(\mbox{3.0 to 4.0}\right)\times 10^{38}$ kg, we suggest an empirical relation for galactic dark matter $M_d$ via galactic visible mass $M_v$ as,$M_d \cong \frac{M_v^{3/2}}{M_X^{1/2}}$. This relation helps in fitting flat rotation speeds starting from 8 km/sec (for Segue 2) to 500 km/sec (for UGC12591). Modifying MOND's galactic flat rotation speed relation with Hubble mass $M_0\cong \left(\frac{c^3}{2GH_0}\right)$ of the universe, ratio of galactic flat rotation speed $V_G$ to speed of light $c$ can be shown to be approximately $\frac{V_G}{c} \cong 0.5 \left(\frac{M_v}{M_0}\right)^{1/4}$. Considering the sum of galactic dark matter and visible matter, ratio of galactic flat rotation speed to speed of light can be shown to be approximately $\frac{V_G}{c}\cong 0.25 \left(\frac{M_v+M_d}{M_0}\right)^{1/4}$. With further study, dark matter's nature, effect and distribution can be understood in terms of visible matter's extended gravity and extended theories of gravity can be understood with 'distance cosmic mass' rather than the empirical 'minimum acceleration'.

In the field of low power wireless networks, one of the techniques on which many researchers are putting their efforts is related to positioning methodologies such as fingerprinting in dense urban areas. This paper presents an experimental study aimed at quantifying the mean location estimation error in densely urbanized areas.Using a dataset made available by the University of Antwerp, a neural network was implemented with the aim of providing the position of the end-devices. In this way it was possible to measure the mean location estimation error in an area with high urban density. The results obtained show an accuracy in the localization of the end-device of less than 150 meters.This result would make it possible to use the fingerprint instead of alternative, energy consuming, methodologies such as GPS in IoT (Internet of Things) applications where battery life is the primary requirement to be met.

In this paper, after reviewing some of the most important concepts about Dark Matter and methods of its registration, in particular by using SQUIDs, a toy uniform model for Dark Matter and Dark Energy is proposed. In the frame of the model Dark Matter particles is interpreted as an excitation of Dark Energy field. The devices based on SQUID, in particular the SQUID-paramagnetic absorber and the SQUID-magnetostrictor systems, both suitable for investigations of above problems, are considered. Estimates, is carried out within this model, indicate the possibility of experimental detection of the "ether wind" pressure, created by the non-corpuscular incoming flow, corresponding to the galactic orbital motion of the Earth.

Dietary pattern (DP) and its relationship with disease biomarkers has received recognition in nutritional epidemiology investigations. However, DP relationships with adipokines (i.e., adiponectin and leptin) among breast cancer survivors remain unclear. Therefore, we assessed relationships between DP with high molecular weight (HMW) adiponectin and leptin concentration among breast cancer survivors. This cross-sectional study involved 128 breast cancer survivors who attended the oncology outpatient clinic at two main government hospitals in East Coast of Peninsular Malaysia. The serum concentration of HMW adiponectin and leptin were measured using enzyme-linked immunosorbent assay (ELISA) kits. Reduced rank regression method was used to analyze DP. Relationships between DP with HMW adiponectin and leptin were examined using regression models. Findings showed that a one-unit increase in the ‘energy-dense, high-saturated fat and low-fiber’ DP z-score was associated with a 0.41 µg/mL lower HMW adiponectin (95% CI: -0.806, -0.014) which was independent of age, BMI, cancer stage, duration since diagnosis, education level and occupation status. A similar relationship with leptin concentration was not observed. In conclusion, ‘energy-dense, high-saturated fat and low-fiber’ DP, which is characterized by high sugar-sweetened drink and fat-based spread but low intake of fruits and vegetables, is an unhealthy dietary pattern and unfavorable for HMW adiponectin concentration but not for leptin. These findings could serve as a basis in developing specific preventive strategies that are tailored to the growing population of breast cancer survivors.

The soil organic matter (SOM) content and stability in natural gypsum soils and soils from mining/industrial areas were compared, in terms of their physical, chemical and micromorphological properties, to determine whether the old brownfield soils were acting as carbon (C) sinks, counteracting increasing carbon dioxide concentrations in the atmosphere. The mining/industrial soils were 50–400 years old, so had been left sufficiently long for full self-restoration. Despite having very different origins, both natural and brownfield soils stored similar amounts of SOM, and had similar pH values, calcium carbonate contents and textures. They were also fully covered with similar grass plant communities. The mining/industrial soils exhibited similar microstructures to the gypsum soils and were often quite porous. The most striking difference between them and the natural gypsum soils was that the mining/industrial soils were strongly polluted with zinc, lead and cadmium. The 50-year-old brownfield soils differed from the others in terms of having a lower state of SOM transformation, with a much higher C/N ratio, lower aggregate water resistance index, lower dehydrogenase activity and greater areas of undecomposed or slightly decomposed plant residues. These parameters in the older (150–400 years) brownfield soils were similar to those of the natural soils.

The combination of organic matter, iron oxide, and clay minerals is of great significance for the adsorption of copper ions (Cu). The purpose of this study is to explore the characteristics of Cu adsorption and laws governing Cu complexation to organic–inorganic, organic–clay mineral, and iron-oxide–clay mineral complexes in the sediments in the estuary of plateau fault and sinking lake——Dianchi Lake. In this study, Cu adsorption tests were performed on the three complexes, in order to study the kinetic behavior of adsorption, Langmuir and Freundlich isotherm models were used. The samples before and after adsorption were characterized via scanning electron microscope (SEM), Fourier infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Our results show that, the Freundlich isotherm models model was able to describe adsorbent behavior in comparison to the Langmuir models. During the Cu adsorption process, the iron-oxide–clay mineral complex is able to adsorb Cu, via coordination exchange, through the –OH contained therein. Organic-matter–clay mineral complexes bonded to the surfaces of clay minerals by replacing the hydroxyl groups with functional groups (carboxyl groups or phenolic hydroxyl groups) contained in the organic matter. Organic–inorganic composites then adsorbed Cu through the coordination exchange of –OH in the polar functional groups of alcohols, phenols, and carboxylic acids. The adsorption capacity of Cu in these three sediment complexes was observed to have the following order: organic–inorganic complex &gt; organic-matter–clay mineral complex &gt; iron-oxide–clay mineral complex. The semi-quantitative analysis results of Fourier Infrared Spectroscopy show that the organic matter (changes in the peak area of functional groups such as carboxyl groups) in the organic-inorganic composite material has an important effect on the amount of copper ions adsorbed by clay minerals.

Dirac’s equation depicts electron mass as either positive or negative. Taken as correct description of nature, the equation identifies electron mass as ‘electrically active’ and therefore fundamentally different from the ordinary, ‘electrically passive’ mass. Following this cue, I demonstrate that electron mass (m_e) is the natural elementary mass: positive (m_e⁺) and negative (m_e^–) elementary masses neutralise to an elementary unit of the electrically passive mass (2m_e⁰). Further, I show that electron mass (m_e^± ) and the electrostatic field (e_f^±) surrounding it compose an elementary charge (e^±), thereby relating charge to mass. Two plain principles underlie these findings. 1) Electric charge and gravitational mass have a common root: positive (e⁺) and negative (e^–) charges coexist as neutral charge (2e⁰), which is the quantum of gravitational mass. 2) Charge is a static (nonrelativistic) ‘atom of electricity’ and obeys the laws of electrostatics; electron is the same ‘atom of electricity’ at ultrahigh (relativistic) speed and obeys the laws of electrodynamics. That is, charges are electricity at rest; electrons are electricity in motion – ‘same physical entities two behavioural identities.’ A decisive proof that this paradigm shift correctly portrays is that it verifiably unifies Newton’s law of gravity and Coulomb’s law of electrostatics to: 8G/m_pm_e = K/e²; where G and K are the respective constants, m_p the proton mass, m_e the electron mass, and e the elementary charge. Ultimately, the insights simplify matter to pure ‘atoms’ of positive and negative electricity.

I review the solution of QCD in two spacetime dimensions. Following the analysis of Baluni, for a single flavor the model can be analyzed using Abelian bosonization. The theory can be analyzed in strong coupling, when the quarks are much lighter than the gauge coupling. In this limit, the theory is given by a Luttinger liquid.

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

Since general relativity (GR) has already established that matter can simultaneously have two different values of mass depending on its context, we argue that the missing mass attributed to non-baryonic dark matter (DM) actually obtains because there are two different values of mass for the baryonic matter involved. The globally obtained "dynamical mass'' of baryonic matter can be understood as a small perturbation to a background spacetime metric even though it's much larger than the locally obtained "proper mass". Having successfully fit the SCP Union2.1 SN Ia data without accelerating expansion or a cosmological constant, we employ the same ansatz to compute dynamical mass from proper mass and explain galactic rotation curves (THINGS data), the mass profiles of X-ray clusters (ROSAT and ASCA data) and the angular power spectrum of the cosmic microwave background (Planck 2015 data) without DM. We compare our fits to modified Newtonian dynamics (MOND), metric skew-tensor gravity (MSTG) and scalar-tensor-vector gravity (STVG) for each data set, respectively, since these modified gravity programs are known to generate good fits to these data. Overall, we find our fits to be comparable to those of MOND, MSTG and STVG. While this favorable comparison does not establish the validity of our proposition, it does provide confidence in using the fits to pursue an underlying action. Indeed, the functional form of our ansatz reveals an interesting structure in these fits.

The treatment of the bulky Rind-based dibromosilanes, (Rind)2SiBr2 (2) [Rind = 1,1,7,7-tetra-R1-3,3,5,5-tetra-R2-s-hydrindacen-4-yl: EMind (a: R1 = Et, R2 = Me) and Eind (b: R1 = R2 = Et)], with two equivalents of tBuLi in Et2O at low temperatures resulted in the formation of blue solutions derived from the diarylsilylenes, (Rind)2Si: (3). Upon warming the solutions above −20 °C, the blue color gradually faded, accompanying the decomposition of 3 and yielding the cyclic hydrosilanes (4) via intramolecular C−H bond insertion at the Si(II) center. The molecular structures of the bulky Eind-based 3b and 4b were confirmed by X-ray crystallography. Thus, at −20 °C, blue crystals were formed (Crystal-A), which were identified as mixed crystals of 3b and 4b. Additionally, colorless crystals of 4b as a singular component were isolated (Crystal-B), whose structure was also determined by an X-ray diffraction analysis. Although the isolation of 3 was difficult due to their thermally-labile nature, their structural characteristics and electronic properties were discussed based on the experimental findings complemented by computational results. We also examined the hydrolysis of 3b to afford the silanol, (Eind)2SiH(OH) (5b).

Volumetric models are a crucial tool for forest management. The study aimed to adjust the mixed model by Schumacher and Hall for estimating commercial volume in a dense ombrophilous forest situated in Ferreira Gomes, Amapá, Brazil. Cubage data from 100 sample trees of 5 species were used to adjust the Schumacher and Hall model in fixed and mixed non-linear forms with the diameter class as a random effect. In addition, the same model was also adjusted for each class to verify whether good equations will be generated by stratifying by diameter class. After analysis, it was found that most of the equations by diameter class do not present all significant parameters. On the other hand, the mixed models using class as a random effect showed good results. Finally, it can be seen that mixed models are a much better alternative than stratification by diameter class for volume estimation.

Purpose: The purpose of this study is to further explore how e-loyalty and E-marketing influences E-trust and satisfy the demand by offering fresh perspectives based on research as well as emphasis on the factors influencing the E-trust such as culture as a mediator. This study not only contributed theoretically but also presented practical implementations. Design/methodology/approach: Online survey was used to obtain data by focusing the Hospitality sector (Hotel Industry) and verifying the conceptual framework. Data was collected in multiple time lags. Findings: Findings showed that the E-trust influenced by E-loyalty and E-Marketing. E-trust comes from the previous experiences, e-loyalty and e-marketing. Further, some trends such as culture influenced the e-trust. Research limitation/implications: The present study is quite suitable for those Researchers interested in learning more about the effects of E-loyalty and E-marketing on user E-trust and how to mitigate cultural influences can benefit from the current study. This research also has implications for those who wish to improve market allure and survival in digital world. This study focused on the hospitality sector (Hotel Industry) in China; however, the sector and geography could be altered to suit the needs of the study's participants. Practical implications: The present study delivers the practical guidelines which are quiet suitable for understanding the formation of E-loyalty, E-marketing, and E-trust through which specific E-marketing strategy can be designed to deal with the consumer’s E-loyalty and their expectations as per their Cultural perspective. At some particular regions/countries, cultural trends are more important than practical market. This research study practically showed that how culture changed the consumer set of mind. Originality/value: The relationship between E-loyalty, E-marketing, E-trust, specifically with the cultural influence in digital market has been the subject of few research.

We introduce two symmetric concepts to physics: “distance” (space and time in one) and “wavematter” (electromagnetic wave packet and matter in one). We claim that physics has chosen the wrong concept of time: It is not aware that the time of a moving object flows in a direction other than my time. We provide 15 proofs for our claim by solving 15 mysteries of physics graphically! For example, we prove that length contraction and time dilation are actually geometrical effects in a 4D manifold that we call “Euclidean spacetime” (ES). We prove that the discrepancy in calculating the Hubble constant stems from a systematic error in the redshift measurement. We prove that what I deem wave, deems itself matter, which solves wave–particle duality. We even untangle quantum entanglement without the issue of non-locality. We finally understand why alternative theories of Euclidean relativity have failed: They are all based on four dimensions of space rather than distance. A huge amount of energy was injected into ES at a point that we take as origin. Ever since has this energy been moving radially away at the speed of light. We live in the 3D hypersurface of an expanding 4D hypersphere. Hyperspherical coordinates have the great advantage that they reduce all that is ever happening to just one formula. So, it is the Theory of Everything in these coordinates: “Energy is covering radial distance which, divided by Euclidean time, is equal to the speed of light.” Acceleration and force like gravitation emerge from a rotation of objects in ES and a subsequent projection to 3D space. Matching the symmetry simplifies physics.

We consider partition functions, in the form of state sums, and associated probabilistic measures for aperiodic substrates described by model sets and their associated tiling spaces. We propose model set tiling spaces as microscopic models for small scales in the context of quantum gravity. Model sets possess special self-similarity properties that allow us to consider implications on large and observable scales from the underlying (non-ergodic) dynamics. In particular we consider the implication of the underlying aperiodic substrate for the well known problem of time in quantum gravity, and propose a correspondence between small and large scales, the so-called ergodic correspondence, that addresses the emergence of matter properties and spacetime structure. In the process we find a possible bound in the mass spectrum of fundamental particles.

We emphasize the point that, standard model of cosmology is basically a model of classical general relativity and it seems inevitable to have a revision with reference to quantum model of cosmology. Utmost important point to be noted is that, ‘Spin’ is a basic property of quantum mechanics and ‘rotation’ is a very common experience. In this context, we propose five assumptions in line with Planck mass as the baby universe. We appeal that, 1) Universe can be modeled as a time-reversed black hole (a white hole) with rotation and light speed expansion, and 2) ‘Light speed expanding cosmic space’ can be called as ‘Flat space’. With reference to light speed expansion, if one is willing to re-define cosmic red shift as [z/(1+z)], without considering Lambda cosmology model of matter density fractions, light travel distances can be reproduced with a marginal error of +8.6% at z =1.2, (i.e. traditional light travel distance is 8.6% higher than our estimate), 0% at z = 11.5 and -5.5% at z = 1200.( i.e. traditional light travel distance is 5.5% lower than our estimate). Advantages of our model are, 1) A quantum model of cosmology can be developed with unification of general theory of relativity and quantum mechanics. 2) Tension in estimating the current Hubble parameter can be eliminated via scaled Hawking’s black hole temperature formula with great confidence. 3) Galactic dark matter and visible matter can be studied in a unified manner. 4) Galactic light travel distances can be estimated very easily without matter density fractions. 5) Big Bang and Inflation like non-general relativistic concepts can be relinquished with further study.

Multispectral and 3D LiDAR remote sensing data sources are valuable tools for characterizing the 3D vegetation structure and thus understanding the relationship between forest structure, biodiversity and microclimate. This study focuses on mapping riparian forest species in the canopy strata using a fusion of Airborne LiDAR data and multispectral multi-sources and multi-resolution satellite imagery; Sentinel-2 and Pleiades at tree level. The idea is to assess the contribution of each data source in the tree species classification at the considered level. The data fusion was processed at feature-level and decision level. At feature level, LiDAR 2D attributes were derived and combined with vegetation indices. At decision level, LiDAR data was used for 3D tree crown delimitation providing unique trees or groups of trees that are used as a support for the species classification. Data augmentation techniques were used to improve the training process. Best results were obtained by the fusion of Sentinel-2 time series and LiDAR data with a Kappa of 0.66 thanks to red-edge based indices that better discriminate vegetation species and the temporal resolution of Sentinel-2 images that allows monitoring the phenological stages helping to discriminate the species.

In this paper, we introduce a new formulation based on Floquet (Fourier) spectral analysis combined with a spectral modulation technique (and its spatial form) to study strongly coupled sublattices predefined in the infinite and large finite extent of almost periodic antenna arrays (e.g metasurfaces). This analysis is very relevant for dense massive MIMO, intelligent surfaces, 5G, and 6G applications (used for very small areas with a large number of elements such as millimeter and terahertz waves applications). The numerical method that is adopted to model the structure is the method of moments simplified by equivalent circuits MoM GEC. Other numerical methods (as the ASM array scanning method and windowing Fourier method) used this analysis in their kernel that to treat periodic and pseudo-periodic (or quasi-periodic) arrays.

This study aimed to evaluate the relationship between various asbestos exposure routes and asbestos-related disorders (ARDs). The study population comprised 11,186 residents of a metropolitan city who lived near asbestos factories, shipyards, or in slate roof-dense areas. ARDs were defined from chest X-rays indicating lower lung fibrosis (LFF), pleural disease (PD), and lung masses (LMs). Of the subjects, 11.2%, 10.4%, 67.2% and 8.3% were exposed to asbestos via occupational, household, neighborhood, and slate roof routes, respectively. Regarding adjusted confounders and other exposure routes, the odds ratio (OR) of PD from household exposure (i.e., living with asbestos-producing workers) was 1.9 (95% confidence interval: 0.9–4.2), and that of LLF and PD from neighborhood exposure, or residing near asbestos factories) for <19 or >20 years, or near a mine, were 4.1 (2.8–5.8) and 4.8 (3.4–6.7), 8.3 (5.5–12.3) and 8.0 (5.5–11.6), and 4.8 (2.7–8.5) and 9.0 (5.6–14.4), respectively. The ORs of LLF, PD, and LM among those residing in slate-dense areas were 5.5 (3.3–9.0), 8.8 (5.6–13.8), and 20.5 (10.4–40.4), respectively. Substantial proportions of citizens residing in industrialized city have potentially been exposed to asbestos, and various exposure routes are associated with the development of ARDs. Notably, this may be the first finding of the health effects of slate roof exposure. However, given the limitations of this study, including potential confounders such as socioeconomic status, further research is needed.

The continuous flowing spacetime forms a spacetime group G, one of its fundamental groups is the Poincare group PO(1,3), and the matter and interaction fields are representations of its intrinsic spacetime group. As a kind of quantized space-time unit, space-time group elements generate both space-time manifolds and matter. Matter and fields are aggregates of the quantum space-time within them and determine their type: the Lorentz group SO(1,3) represents a rotating spacetime corresponding to visible matter and the translation group P^1,3 represents a translational spacetime corresponding to dark matter and dark energy. The aggregation mode of space-time degrees of freedom in matter reveals that charge conjugation symmetry is the inverse symmetry of internal time of charged particles, and the external parity breaking of neutrinos is also due to their internal spatial aggregation mode.

Sustainability has become increasingly important. Existing project management methodologies are underdeveloped in sustainability. PM² is a methodology developed by the European Commission that aims to provide solutions and benefits to organizations. However, it doesn't include sustainability in its guide, because it aims to be generic. PRiSMTM aims to make the project management process more sustainable, it is based on the P5™ standard that aims to align portfolios, programmes and projects with sustainability. The major difference between the two methodologies is their main objectives. PRiSMTM has P5 Impact Analysis and Sustainability Management Plan as the main differentiating deliverable compared to other approaches, including PM². The most cited characteristic of PM² was to include best practices from other bodies of knowledge, and in PRiSMTM and P5™, it was to be an extension of the Triple Bottom Line, as it also includes product and process. The CEO of the PM² Alliance believes that PM² aims to be generic and usable for any project, so a focus on sustainability would remove the "elasticity" of the methodology. However, users wishing to use PM² and consider sustainability can include it in the additional objectives and use the P5 Impact Analysis and Sustainability Management Plan.

The late universe contains a wealth of information about fundamental physics and gravity, wrapped up in non-Gaussian fields. To make use of as much information as possible it is necessary to go beyond two-point statistics. Rather than going to higher order N-point correlation functions, we demonstrate that the probability distribution function (PDF) of spheres in the matter field (a one-point function) already contains a significant amount of this non-Gaussian information. The matter PDF dissects different density environments which are lumped together in two-point statistics, making it particularly useful for probing modifications of gravity or expansion history. Our approach in Cataneo et. al. 2021 extends the success of Large Deviation Theory for predicting the matter PDF in ΛCDM in these “extended” cosmologies. A Fisher forecast demonstrates the information content in the matter PDF via constraints for a Euclid-like survey volume combining the 3D matter PDF with the 3D matter power spectrum. Adding the matter PDF halves the uncertainties on parameters in an evolving dark energy model, relative to the power spectrum alone. Additionally, the matter PDF contains enough non-linear information to substantially increase the detection significance of departures from General Relativity, with improvements up to six times the power spectrum alone. This analysis demonstrates that the matter PDF is a promising non-Gaussian statistic for extracting cosmological information, particularly for beyond ΛCDM models.

Dark energy and dark matter are described as different manifestations of vacuum energy in a new cyclic universe framework of Extra Dimensional Symmetry (EDS) that doubles large spatial dimensions with microscopic partners. In this testable framework, vacuum energy, constrained by a Planck density constraint, exists in a gravitationally dark state where actual gravitational constant G_o = 0G. While a small repulsive component is constrained by an asymptotically evolving asymmetry to the active state where G_o = 2G, some components in the inert state are enabled to gravitationally attract by neutrino induced gravitational constant with light and shear activated heavy components. Observational and experimental tests are briefly discussed.

The energy E takes the place of the gravitational mass m_G to produce gravity [1]. We wonder whether the inertial mass m_i in the inertial force is also replaced by E. The experiments to measure the inertial force and weight of a carrier are presented. Now we can test the principle of equivalence and study foundations of physics in condensed matter.

In the author's opinion, many global problems that face humanity - in the fields of education, medicine, management etc can be tackled more effectively if the cyclic nature of self-reproducing systems – including living beings – is taken into account. Summarizing the main physiological findings of the last decades on "adaptation reactions", one can very roughly say that the way of action which is effective in the sense of productive activity of people happens at the same time to be healthy, and it gives the participants of the process the feeling of happiness. The present paper represents a very short overview of the contemporary concepts of the adaptation reactions based on the fundamental understanding of their cyclic nature due to general properties of self-reproducing systems. One interesting feature of self-reproduction cycles is its first "phase of orientation" which was not discussed in detail in the past but plays a key role in the whole cycle.

The extraction of roof feature lines is an important foundation for realizing large-scale and batch 3D modeling. However, the current traditional point cloud segmentation algorithms do not have satisfactory results in extracting roof feature lines of Chinese traditional residential buildings. In this paper, taking Jingping Village in Western Hunan as an example, we propose a method that combines multiple algorithms based on slope segmentation of roof patches to extract feature lines. Firstly, VDVI and CSF algorithms are used to extract the building and roof point cloud based on the MVS point cloud. Secondly, according to roof features, village buildings are classified, and 3D roof point cloud is projected into 2D regular grid data. Finally, the roof slope is segmented via slope direction, and internal and external feature lines are obtained after refinement through Canny edge detection and Hough straight line detection. Results reveal that this method effectively extracts feature lines of low-building roofs in traditional villages, with slope-based roof surface segmentation accuracy surpassing 99.6%. This method significantly outperforms the RANSAC algorithm and region segmentation algorithm.

Urbanization induced land use land cover (LULC) changes intensify the urban heat island effects. It magnifies the risk of urban dwellers and sometimes causes the loss of human life, defined as heat-related health risk (HRHR). Hence, urban LULC planning plays a crucial role. Present study analyses the impact of composition and configuration of urban LULC defined as urban landscape metric (ULM) on HRHR in Delhi at the ward level. Firstly, the HRHR is measured by using satellite thermal and other digital data. Then, measured HRHR is validated by conducting a rapid field survey. Thirdly, ULM measured at ward level using Fragstat 4 software. Finally, both, HRHR and ULM linked with bi-variate Moran's I and impacts of ULM are assessed using ordinary least square (OLS) and spatial error (SE) regression. The result indicates the high risk is found as clustered in north-east, central and middle of south-west Delhi. Built-up density intensifies HRHR and abundance of vegetation reduce it; however, it is not similar for all vegetation patches. Larger vegetation patches surrounded by dense built-up might not able to reduce the risk as much as a large vegetation patch could in other regions. Findings can be helpful for heat resilient city planning.

Technology is in the way to reach in its climax but the basic understanding of science in many phenomena is still awaited even though the nature witnesses it. Scientific research reveals strong analogy between photon and electron. When an atom deals neutral state, it levitates electron of outer ring from the back surface while placing the bit-energy at front surface. Gravitation behavior of that electron starts at the centre of relaxation point by including the force of side pole where the pulling force of nearby unfilled state of that atom from the front surface results into depict forcing energy shape like Gaussian distribution symbol with both ends turned called unit photon. The inertia is being involved at each stage of changing direction of that electron by introducing the disappearances of forces of two poles against the appearances of forces of two opposite poles during rest to motion and motion to rest in the first half-cycle. The same is the case in the second half-cycle of that electron during rest to motion and motion to rest but it is under different introduction of the disappearances of forces against appearances of forces. However, at stage of levitating or gravitating period of electron, only one force is being involved at one time where the opposite force is disappeared. The uninterrupted confined inter-state electron-dynamics of atom under the availability of several bits of bit-energy results into generate forcing energy shape like a wave. Two bits of bit-energy where shape of bit for first half-cycle is like integral symbol and second half-cycle is like opposite integral symbol which are being placed along the configuring trajectory of inter-state electron-dynamics during forward-direction cycle and two bits of bit-energy shape in opposite order are being placed along the trajectory of inter-state electron-dynamics during back-direction cycle. Generating forcing energy of unit photon in each cycle is pushing to the rear side by remaining connected till the electron is not restoring the state of rest. Silicon atom is considered as a model system under neutral state. Uninterrupted confined inter-state electron-dynamics result into generate forcing energy that can travel immeasurable length and unavailability of necessitating bit-energy at any interrupted stage result into generate an overt photon. Inter-state electron-dynamics for at least two cycles generate an overt photon –a photon length twice to unit photon. Under certain interaction of unit photon, it divides equally into two bits of bit-energy instead of dividing into tits and bits of heat. The mechanism of generating photon characteristic current by the electron of neutral state atom validates that atoms are four-dimensional discs at centre of dealing no force. An isolated electron is being grounded under directed forcing energy to impinge a neutral state atom where the gained instantaneous velocity under merged energy resulting into distort atom at that point. Matter changes the role of energy and force under various sorts of interactions. Here, heat energy and photon energy explore matter at atomic and electron levels, thus, devise basis of science to describe.

In a search for a solution of the galaxy rotation problem, a novel view on cosmological gravity is developed. In this view, the origin of gravity is traced back to the basic nuclear field of energy, spread by quarks as elementary pointlike sources. This gives a common basis for gravity, electromagnetism, the strong nuclear force and the weak nuclear force. After a review on gravimagnetism and the causality problem of gravity, a hypothetical concept for the gravity field is proposed, which solves the rotation problem without the need to accept dark matter as the deus ex machina.

I argue that the main feature of elliptical space – the topological identification of its antipodal points – might be behind some observational facts on both cosmological and microscopic scales. I use calculated distance moduli of type-Ia supernovae, which are commonly regarded as “standard candles” for distance measure in cosmology. These are compared with the observational data collected in a catalogue called “Pantheon+”. On the microscopic scale I show that a physical elliptical space, in which the mathematical connectedness between antipodal points is replaced with physical connections via the Einstein-Rosen bridges (also called “wormholes”), gives rise to sub-particle structures similar to J.A. Wheeler’s geons. The interactions between these structures leading to their equilibrium configurations can explain the experimentally observed pattern of properties of elementary particles forming the standard model of particle physics. The answer to the question why we have this particular set of fundamental particles might lie in the fundamental properties of elliptical space.

Recent inference results of the sound velocity in the cores of neutron stars are summarized. Implications for the equation of state and the phase structure of highly compressed baryonic matter are discussed. In view of the strong constraints imposed by the heaviest known pulsars, the equation of state must be very stiff in order to ensure the stability of these extreme objects. This required stiffness limits the possible appearance of phase transitions in neutron star cores. In view of these empirical findings, much discussed issues such as the quest for a phase transition towards restored chiral symmetry and the active degrees of freedom in cold and dense baryonic matter, are explored.

Solar energy is a rapidly growing sector, and solar farms are playing an increasingly important role in meeting the world's energy needs. However, as the size and complexity of these farms increase, so do the challenges associated with managing them efficiently. This article presents a comprehensive analysis of the fundamental parameters that underpin solar energy systems. Focusing on the latest research, we examine the challenges and opportunities intrinsic to the implementation of solar energy systems, paying particular attention to the various parameters that contribute to their performance. These parameters encompass a range of factors such as thermal performance, atmospheric boundary layer, solar energy meteorology, heat islands, cloud influences, agrivoltaic systems, shading factors, and surface energy budget. The review underscores the importance of considering a diverse array of parameters when developing solar energy systems to optimize their efficiency and effectiveness. Ultimately, by unraveling these challenges and opportunities, we can work towards creating more sustainable and reliable renewable energy sources and reducing our dependence on non-renewable alternatives.

Electron can tunnel between cofactor molecules positioned along biological electron transport chains up to the distance of ≃20 Å on the millisecond time scale of enzymatic turnover. This tunneling range mostly determines the design of biological energy chains facilitating cross-membrane transport of electrons. Tunneling distance and cofactors’ redox potentials become main physical parameters of this design. The protein identity, flexibility, or dynamics are missing from this picture assigning universal charge-transport properties to all proteins. This paradigm is challenged by dynamical models of electron transfer showing that the hopping rate is constant within the crossover distance R*≃12 Å, followed with an exponential tunneling falloff at longer distances. In this view, energy chains for electron transport are best designed by placing redox cofactors near the crossover distance R*. Protein flexibility and dynamics affect the magnitude of the maximum hopping rate within the crossover radius. Protein charge transport is not driven by universal parameters anymore and protein identity matters.

We considered a vacuum polarization around a massive object in the eikonal approximation and found two types of vacuum polarization. The first type has the equation of state similar to radiation and can produce a halo that increases the rotation velocity of a test particle with a radial distance. The second type of vacuum polarization has a more complicated equation of state. As a static physical effect, it produces renormalization of the gravitational constant. Besides, we demonstrate that a nonstationary polarization of the second type caused by a swift increase of the galactic nuclei mass results in a gravitational potential looking like a dark matter halo.

Since several years there is the discussion about dark matter in the halos of galaxies. This is aconsequence of observation of halo-velocity curves in dependence of distance which don‘t fulfillthe third Kepler-law. Maybe the ansätze are wrong. Shown is a simple physical model in classicalNewton-dynamics which fits qualitative the form of observation curves. Additional Parameters canbe used to fit the curves quantitative exactly without the hypothesis of dark matter.

The detection of Dark Matter is the greatest outstanding problem in modern cosmology. Several attempts have been taken for this without any remarkable success. To find out a suitable way of detection we need to understand its nature comprehensively. In the present article, a hypothesis is described considering Dark Matter as a normal matter. Its peculiar behavior is explained considering its existence in BEC state in the coolest part of the universe that makes it an electromagnetic insulator. Depending upon this hypothesis an experimental verification method is proposed.

Particulate matter (PM) represents an air quality management challenge for confined swine production systems. Because of the limited space and ventilation rate, PM can reach relatively high concentrations in swine barns. PM in swine barns possesses different physical, chemical, and biological characteristics than that in the atmosphere and other indoor environments. As a result, it exerts different environmental and health effects and creates some unique challenges regarding PM measurement and mitigation. Numerous research efforts have been made, generating massive data and information. However, relevant review reports are sporadic. This study aims to provide an updated comprehensive review of swine barn PM, focusing on publications since 1990. It covers various topics, including PM characteristics, sources, measurement methods, and in-barn mitigation technologies. Since PM in swine barns is of primarily biological origins, bioaerosols are reviewed in great detail. Relevant topics include bacterial/fungal counts, viruses, microbial community composition, antibiotic-resistant bacteria, antibiotic resistance genes, endotoxins, and (1→3)-β-D-glucans. For each topic, existing knowledge is summarized and discussed and knowledge gaps are identified. Overall, PM in swine barns is complicated in chemical and biological composition and highly variable in mass concentrations, size, and microbial abundance. Feed, feces, and skins constitute the major PM sources. Regarding in-barn PM mitigation, four technologies (oil/water sprinkling, ionization, alternation of feed and feeders, and recirculating air filtration) are dominant. However, none of them have been widely used in commercial barns. A collective discussion of major knowledge gaps and future research needs is offered at the end of the report.