The design of more efficient photosensitizers is a matter of great importance in the field of cancer treatment by means of photodynamic therapy. One of the main processes involved in the activation of apoptosis in cancer cells is the oxidative stress on DNA once a photosensitizer is excited by light. As a consequence, it is a matter of great relevance to investigate in detail the binding modes of the chromophore with DNA, and the nature of the electronically excited states that participate in the induction of DNA damage, for example, charge-transfer states. In this work, we investigate the electronic structure of the anthraquinone photosensitizer intercalated into a double-stranded poly(dG-dC) decamer model of DNA. First, the different geometric configurations are analyzed by means of classical molecular dynamics simulations. Then, the excited states for the most relevant poses of anthraquinone inside the binding pocket are computed by an electrostatic-embedding quantum mechanics/molecular mechanics approach, where anthraquinone and one of the nearby guanine residues are described quantum mechanically to take into account intermolecular charge-transfer states. The excited states are characterized as monomer, exciton, excimer and charge-transfer states based on the analysis of the transition density matrix, and each of these contributions to the total density of states and absorption spectrum is discussed in terms of the stacking interactions. These results are relevant as they represent the footing for future studies on the reactivity of anthraquinone derivatives with DNA and give insights on possible geometrical configurations that potentially favor the oxidative stress of DNA.

Reactions of quinones with compounds containing an amino group can produce a wide variety of addition or substitution products that depend on reactivity of both quinone and amino derivative. 6,7-Dichloropyrido[1,2-a]benzimidazole-8,9-diones undergo selective nucleophilic substitution reaction with different benzohydrazides and α-hydroxy-p-quinone imine derivatives stabilized by strong intramolecular hydrogen bond were isolated. Synthesized compounds represent a combination of several structural motifs: benzimidazole core fused with α-hydroxy-p-quinone imine which contains a benzamido fragment. The protonation/deprotonation processes were investigated in a solution using UV-Vis spectroscopy and 1H NMR titration experiment. X-ray crystallography analysis revealed a set of weak non-covalent interactions such as intra- and intermolecular hydrogen bonds and π-π stacking. Additionally, the redox behavior of 6,7-dichloropyrido[1,2-a]benzimidazole-8,9-dione and its p-imino derivative was investigated in acidic and neutral environment using cyclic voltammetry measurements. Cathode material based on 6,7-dichloropyrido[1,2-a]benzimidazole-8,9-dione could act as potential effective active electrode in aqueous electrolyte batteries, however further optimization is required.

Bis-benzimidazole derivative (BBM) molecule, consisting of two 2-(2’-Hydroxyphenyl) benzim-idazole (HBI) halves, has been synthesized and successfully utilized as a ratiometric fluorescence sensor for the sensitive detection of Cu2+ based on enol-keto excited state intramolecular proton transfer (ESIPT). In this study, we strategically implement femtosecond stimulated Raman spec-troscopy and several time-resolved electronic spectroscopies, aided by quantum chemical calcula-tions to investigate the detailed primary photodynamics of BBM molecule. The results demonstrate that the ESIPT from BBM-enol* to BBM-keto* was observed in only one of HBI halves with a time constant of 300 fs, after that, the rotation of the dihedral angle between two HBI halves generate a planarized BBM-keto* isomer in 3 ps, leading to dynamics red shift of BBM-keto* emission.

The conformational dependence of the matrix element for spin-orbit coupling and of the electronic coupling for charge separation are determined for an electron donor-acceptor system containing a pyrene acceptor and a dimethylaniline donor. Different kinetic and energetic aspects that play a role in the spin-orbit charge transfer intersystem crossing (SOCT-ISC) mechanism are discussed. This includes parameters related to initial charge separation and the charge recombination pathways using the (Semi-Classical) Marcus Theory for electron transfer. The spin-orbit coupling, which plays a significant role in charge recombination to the triplet state can be probed by (TD-)DFT, using the latter as a tool to understand and predict the SOCT-ISC mechanism. The matrix elements for spin-orbit coupling for acetone and 4-thio-thymine are used for benchmarking. (Time Dependent-) Density Functional Theory (DFT and TD-DFT) calculations are applied using the quantum chemical program Amsterdam Density Functional (ADF).

The structure and phenomena arising from charge transfer in cold field emission modus in a single closed carbon nanotube under cold field emission conditions were studied. By studying microphotographs in various microscopes - AFM, SEM, TEM it was found inhomogeneities in the form of two types of superlattices. The conductivity of the emitter section of a nanodiode circuit with an emitter made of an individual closed carbon nanotube (CNT) and arrays of closed CNTs was studied. High values of cold field emission were observed, as well as nonlinearity and anomalies of the current-voltage characteristic (I-V characteristics), which manifested themselves in the form of peaks at low and high current values. Peaks in the CVC have distinct areas of negative differential conductivity. It is argued, that the anomalously high currents in the I–V characteristics of cold field emission of electrons from a nanoemitter made of closed CNTs can be associated with a sharp increase in the density of electron states at energies near the van Hove singularity.

By introducing a suitable renormalization process the charge carrier and phonon dynamics of a double-stranded helical DNA molecule is expressed in terms of an effective Hamitonian describing a linear chain, where the renormalized transfer integrals explicitly depend on the relative orientations of the Watson-Crick base pairs, and the renormalized on-site energies are related to the electronic parameters of consecutive base pairs along the helix axis, as well as to the low-frequency phonons dispersion relation. The existence of synchronized collective oscillations enhancing the π-π orbital overlapping among different base pairs is disclosed from the study of the obtained analytical dynamical equations. The role of these phonon-correlated, long-range oscillation effects on the charge transfer properties of double standed DNA homopolymers is discussed in terms of the resulting band structure.

The integration of bacteriophages, a particular class of viruses that specifically infect bacteria and archaea, in biosensors for the monitoring of pathogens in foods and beverages is highly desirable. To this end, an increasing focus has been set on the exploration of covalent and physical methods for the immobilization of phages on solid surfaces. This work investigates the electrostatic assembly of tailed phages, specifically anti-Listeria monocytogenes P100 phages, on an ultrathin self-assembled monolayer (SAM) of 11-amino-1-undecanethiol (AUT). The cationic properties of AUT may allow for the electrostatic capture of P100 in a capsid-down fashion, thus, exposing the specific receptor-binding proteins on their tails to the corresponding pathogens in analytical samples. The physical properties of immobilized phages have been studied using AFM, SEM, and electrochemical techniques, providing insight into the orientation of the phages and revealing that the pH plays a remarkable role in the morphology and charge transfer behavior of the adsorbed films. Overall, this research portrays SAMs of amino-akylthiols as a valid platform for the oriented immobilization of bacteriophages on surfaces for electroanalytical purposes.

Paleoclimate information is key to understanding the climate system and predicting future climate. Currently, stable isotope analysis of whole molecules in tree rings is among the most advanced paleoclimate tools. Still, it only enables reconstructions of one climate parameter at a time (univariate climate reconstruction), a fundamental limitation. Here, we investigated whether this limitation can be overcome by analysing isotope variability at the level of intramolecular carbon positions in tree-ring glucose. We found that drought governs isotope variability at glucose C-1 to C-3, whereas radiation governs isotope variability at glucose C-5 to C-6. These isotope-climate relationships are statistically and mechanistically robust. According to cross-validation analysis, they can be reconstructed with high accuracy and precision. Thus, intramolecular isotope analysis enables multivariate climate reconstructions (proof of concept).

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).

Hydroiodic acid (HI) treated - reduced graphene oxide (rGO) ink/conductive polymeric composites are considered as promising cold cathodes in terms of high geometrical aspect ratio and low field emission (FE) threshold devices. In this study, four simple, cost-effective, solution-processed approaches for rGO-based field effect emitters were developed, optimized and compared; rGO layers were coated on a) n+ doped Si substrate, b) n⁺-Si/P3HT:rGO, c) n⁺-Si/PCDTBT:rGO and d) n⁺-Si/PCDTBT:PC₇₁BM:rGO composites, respectively. The fabricated emitters were optimized by tailoring the concentration ratios of their preparation and field emission characteristics. In a critical composite ratio, FE performance was remarkably improved compared to the pristine Si, as well as n⁺-Si/rGO field emitter. In this context, the impact of various materials, such as polymers, fullerene derivatives, as well as different solvents on rGO function reinforcement and consequently on FE performance upon rGO-based composites preparation was investigated. The field emitter consisted of n⁺-Si/PCDTBT:PC₇₁BM(80%):rGO(20%)/rGO displayed a field enhancement factor of ∼2850, with remarkable stability over 20h and low turn-on field in 0.6V/μm. High-efficiency graphene-based FE devices realization paves the way towards low-cost, large-scale electron sources development. Finally, the contribution of this hierarchical, composite film morphology was evaluated and discussed.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

This review deals with the functionalization of double bonds carried out in the presence of a chiral catalyst exploiting the intramolecular attack to haliranium ions by nucleophilic nitrogen of amides or carbamates prepared from achiral aminoalkenes, and the C-N bonds formation leads to highly enantioenriched non-aromatic heterocycles. A range of protocols are reported, emphasizing the synthesis of many natural and biologically active products of pharmacological interest prepared according to this methodology.

It has been known since the 1930’s that all immunoglobulins carry a weak negative charge in physiological solvents. However, there has been no systematic exploration of this fundamental property. Accurate charge measurements have been made using membrane confined electrophoresis in two solvents (pH 5.0 and pH 7.4) on a panel of twelve mAb IgGs, as well as their F(ab’)₂ and Fc fragments. The following observations were made at pH 5.0: 1) the measured charge differs from the calculated charge by ~40 for the intact IgGs, and by ~20 for the Fcs; 2) the intact IgG charge depends on both Fv and Fc sequences, but does not equal the sum of the F(ab)’₂ and Fc charge; 3) the Fc charge is consistent within a class. In phosphate buffered saline, pH 7.4: 1) the intact IgG charges ranged from 0 to -13; 2) the F(ab’)₂ fragments are nearly neutral for IgG1s and IgG2s, and about -5 for some of the IgG4s; 3) all Fc fragments are weakly anionic, with IgG1 < IgG2 < IgG4; 4) the charge on the intact IgGs does not equal the sum of the F(ab’)₂ and Fc charge. In no case is the calculated charge, based on H⁺ binding, remotely close to the measured charge. The charge on IgGs in physiological solvent is sufficiently small to minimize its contribution to thermodynamic nonideality. Some of the mAbs carried a charge in physiological salt that was outside the range observed for serum-purified human poly IgG. To best match physiological properties, a therapeutic mAb should have a measured charge that falls within the range observed for serum-derived human IgGs.

The most important plastic resins used for wire coating are Polyvinyl Chloride (PVC), Nylon, Polysulfone and Low-high density polyethylene (LDPE / HDPE). In this article,the coating process is performed using elastic-viscous fluid as a coating material for wire coating in a pressure type coating die. The elastic-viscous fluid is electrically conducted in the presence of an applied magnetic field. The governing non-linear equations are modeled and then solved analytically by utilizing an Adomian decomposition method (ADM). The convergence of the series solution is established. The results are also verified by Optimal Homotopy Asymptotic Method (OHAM). The effect of different emerging parameters such as non-Newtonian parameters α and β, magnetic parameter M and the Brinkman number Br on solutions (velocity and temperature profiles) are discussed through several graphs. Additionally, the current result also compares with the published work already available in the literature.

Biohydrogen is a versatile energy carrier for the generation of electric energy from renewable sources. Hydrogenases can be used in enzymatic fuel cells to oxidize dihydrogen. The rate of electron transfer (ET) at the anodic side between the [NiFe]-hydrogenase enzyme distal iron-sulfur cluster and the electrode surface can be described by the Marcus equation. All parameters for the Marcus equation are accessible from DFT calculations. The distal cubane FeS-cluster has a three cysteine and one histidine coordination [Fe₄S₄](His)(Cys)₃ first ligation sphere. The reorganization energy (inner- and outer-sphere) is almost unchanged upon a histidine-to-cysteine substitution. Differences in rates of electron transfer between the wild-type enzyme and the all-cysteine mutant can be rationalized by a diminished electronic coupling between the donor and acceptor molecules in the [Fe₄S₄](Cys)₄ case. The fast and efficient electron transfer from the distal iron-sulfur cluster is realized by a fine-tuned protein environment which facilitates the flow of electrons. This study enables the design and control of electron transfer rates and pathways by protein engineering.

Huperzine A is an herbal reversible inhibitor of Acetylcholinesterase (AChE). A molecular docking analysis on Huperzine A molecule has been carried out to understand its structure, conformational flexibility, intermolecular interaction and the binding affinity in the active site of AChE enzyme. Further, the charge density distribution of huperzine A molecule (lifted from the active site of AChE) was determined from the high level quantum chemical calculations coupled with charge density analysis. The binding affinity of Huperzine A towards AChE was calculated from the molecular docking; the lowest docked energy is -8.46 kcal/mol. In the active site, huperzine A molecule interacts with acyl binding pocket-Phe330 of AChE, that is, the bicyclo ring group of huperzine A forms an intermolecular interaction with the oxygen atom of main chain of the amino acid residue Phe330 at the distances 3.02 and 3.25 Å respectively. On the other hand, a gas phase study on huperzine A molecule also performed using HF and DFT (B3LYP) methods with the basis set 6-311G**. The molecular structure, conformation, and the charge density distribution of huperzine A molecule in the gas phase have determined using quantum chemical calculations and the charge density analysis. The comparative studies between the gas phase and the active site forms of huperzine A molecule, explicitly reveals the degree of conformational modification and the charge density redistribution of huperzine A when present in the active site. The dipole moment of the molecule in the active site is 6.85 D, which is slightly higher than its gas phase value (5.91 D). The electrostatic potential (ESP) surface of active site molecule clearly shows the strong electronegative and positive ESP regions of the molecule, which are the expected strong reactive locations of the molecule.

The oscillating heat pipe (OHP) is a new member in the family of heat pipes, and it has great potential applications in energy conservation. However, the fluid flow and heat transfer in the OHP as well as the fundamental effects of inner diameter on them have not been fully understood, which are essential to the design and optimization of the OHP in real applications. Therefore, by combining the high-speed visualization method and infrared thermal imaging technique, the fluid flow and thermal performance in the OHPs with inner diameters of 1, 2 and 3 mm are presented and analyzed. The results indicate that three fluid flow motions, including small oscillation, bulk oscillation and circulation, coexist or, respectively, exist alone with the increasing heating load under different inner diameters, with three flow patterns occurring in the OHPs, viz. bubbly flow, slug flow and annular flow. These fluid flow motions are closely correlated with the heat and mass transfer performance in the OHPs, which can be reflected by the characteristics of infrared thermal images of condensers. The decrease in the inner diameter increases the frictional flow resistance and capillary instability while restricting the nucleate boiling in OHPs, which leads to a smaller proportion of bubbly flow, a larger proportion of short slug flow, a poorer thermal performance, and easier dry-out of working fluid. In addition, when compared with the 2 mm OHP, the increasing role of gravity induces the thermosyphon effect and weakens the 'bubble pumping' action, which results in a little smaller and bigger thermal resistances of 3 mm OHP under small and bulk oscillation of working fluid, respectively.

Surface initiated atom transfer radical polymerization (SI-ATRP) is one of the most versatile technique to modify the surface properties of material. Recent developed metal free SI-ATRP makes such technique more widely applicable. Herein photo-induced metal-free SI-ATRP of methacrylates, such as methyl methacrylate, N-isopropanyl acrylamide, and N,N- dimethylaminoethyl methacrylate, on the surface of SBA-15 was reported to fabricate organic-inorganic hybrid materials. SBA-15 based polymeric composite with adjustable graft ratio was obtained. The structure evolution during the SI-ATRP modification of SBA-15 was monitored and verified by FT-IR, XPS, TGA, BET, and TEM. The obtained polymeric composite showed enhanced adsorption ability for the model compound toluene in aqueous. This procedure provides a low cost, ready availability, and facile modification way to synthesize the polymeric composites without the contamination of metal.

In this paper we review dynamics and roughness of bonds in proteins on example of albumin, that is important from the physiological point of view. We have performed computer simulations of albumin chain. Statistics were collected by performing many simulations realizations for each experimental setting. We concentrate on hydrogen bonds, cation-π and π- π interactions and NP contacts. Histograms of hydrogen bonds length are positively skewed in contrary to histograms of interactions and HP contacts that are negatively skewed. Scaling exponents of power spectra of energies of bonds / interactions /contacts are in range -0.2 to -0.5 and significantly differ between various hydrogen bonds or interactions. Varying scaling of such spectra can be used to classify between distinct bonds or contacts. Concerning particular amino-acids, largest amount of HBO H20 bonds are between Glutamate (GLU) amino-acids and water particle, while large amount of HBO bonds are formed with Lysine (LYS). For HP contacts the mayor role plays Phenylalanine (PHE) and Leucine (LEU) amino-acids. From decay curves HBO H2O bonds decays in fastest rate, while HBO bonds and HP contacts at slowest rate. We present as well decay curves of bonds formed by particular amino-acids, that gives interesting results.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

Due to environmental concerns, natural refrigerants and their use in refrigeration and air conditioning systems are receiving more attention from manufacturers, end users and the scientific community. The study of heat transfer and pressure drop is essential for accurate design and more energy efficient cycles using natural refrigerants. The aim of this work is to provide an overview of the latest outcomes related to heat transfer and pressure drop correlations for ammonia, propane, isobutane and propylene and to investigate the current state of the art in terms of operating conditions. Available data on the existing correlations of heat transfer coefficient and pressure drop for natural refrigerants have been collected through a systematic search. Whenever possible, validity intervals are given for each correlation and the error is quantified. It is the intention of the authors that this could be a valuable support for researchers and an aid to design, with particular reference to heat pumps. A procedure based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was adopted, and the Scopus database was used to query the relevant literature. A total of 135 publications qualified for inclusion in the survey; 34 articles report experimental investigations for not usual geometric conditions. Of the 101 selected papers related to usual geometric conditions, N = 50 deal only with HTC, N = 16 deal only with pressure drop and the remainder (N = 35) analyse both HTC and pressure drop. Among the 85 HTC papers (N = 53) deal with the evaporating condition, N = 30 with condensation and only N = 2 with the heat transfer correlations under both conditions. Most of the 101 articles concern propane and isobutane. The high temperatures are less widely investigated.

This paper presents an innovative multi-agent, data-driven reinforcement learning (RL) approach to develop and utilize the thermal equivalent network model that represents the motor's thermal dynamics. A multi-agent reinforcement learning is designed and trained to adjust the model parameters using data from several motor driving cycles. To ensure the incoming driving cycle matches the historical data before employing the pre-trained RL agents, offline statistical analysis and clustering techniques are developed and used. Numerical simulations highlighted the RL agent's ability to develop strategies that effectively address the variability of driving cycles. The proposed RL framework showed its capability to accurately reflect the motor's thermal behavior under various driving conditions.

In this paper, we propose an assumption of which the relation between electron and phonon is discussed and investigated based on the experiment of γ photon and electric interconverting with each other. We calculated the charge of a particular standing wave topology with Maxwell’s equation rotated in accordance space with the SO3 transformation. The derived charge value is 1.6035 × 10E−19C around 0.0826% different from the experimental data, indicating the proposal is a promising theory to explain the origin of charge and spin of electron particle. Electron spin angular momentum comes from the orbital angular momentum of photon rotation (electromagnetic field rotation), and electron charge comes from photon, that is, the space-time rotation effect of electromagnetic wave.

The intramolecular ionic Diel-Alder (IIDA) reactions of two dieniminiums have been studied within the Molecular Electron Density Theory (MEDT) at the B97XD/6-311G(d,p) computational level. ELF topological analysis of dieniminiums shows that its electronic structure can been seen as the sum of those of butadiene and ethaniminium. The superelectrophilic character of dieniminiums accounts for the high intramolecular global electron density transfer taking place between the diene and iminium frameworks at the transition state structures (TSs) of these IIDA reactions. The activation enthalpy associated to the IIDA reaction of the experimental dieniminium, 8.7 kcal·mol-1, is closer to that of the ionic Diels-Alder (I-DA) reaction between butadiene and ethaniminium, 9.3 kcal·mol-1. However, the activation Gibbs free energy of the IIDA reaction is 12.7 kcal·mol-1 lower than that of the intermolecular I-DA reaction. The strong exergonic character of the IIDA reaction, higher than 17 kcal·mol-1, makes the reaction irreversible. These IIDA reactions present a total re/exo and si/endo diastereoselectivity, which is controlled by the most favourable chair conformation of the tetramethylene chain. Electron localization function (ELF) topological analysis of the single bond formation indicates that these IIDA reactions take place through a non-concerted two-stage one-step mechanism. Finally, ELF and atoms-in-molecules (AIM) topological analyses of the TS associated to inter and intramolecular processes show the great similitude among them.

A grand unification of electroweak and strong forces is presented based on a new idea called Unified Charged Vectors. Using this new concept, it is shown that: The electroweak and strong forces can be unified into a single electro-weak-strong force. The various charges and coupling constants of fermions (like the electroweak mixing angle) can be predicted, rather than presupposed. The Lagrangian symmetries can be predicted rather than presupposed. The standard model Lagrangian can be cast into a simple unified form.

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and re-analysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, to capture the nuanced dynamics of Cyprus's atmospheric conditions. With a temporal resolution of 15 minutes and a spatial of 0.05°x0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models' accuracy but also highlights their proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), of -2 to -4% per decade have been found in Autumn, especially marked on the island’s Northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of -2 to -3% per decade that were found in Spring do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the Daylight Integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

This article will continue ansatz gage matrix of Iyer Markoulakis Helmholtz Hamiltonian mechanics points’ fields gage to Pauli Dirac monopole particle fields ansatz gage general formalism at Planck level, by constructing a Pauli Dirac Planck circuit matrix field gradient of particle monopole flow loop. This circuit assembly gage (PDPcag) that maybe operating at the quantum level, demonstrates the power of point fields matrix theoretical quantum general formalism of Iyer Markoulakis Helmholtz Hamiltonian mechanics transformed to Coulomb gage metrics, to form eigenvector fields of magnetic monopoles as well as electron positron particle gage metrics fields. Eigenvector calculations performed based on Iyer Markoulakis quantum general formalism are substituted for gage values of typical eigenvectors of dipolar magnetically biased monopoles with their conjugate eigenvectors, as well as eigenvector fields that are of the electron and positron particles. Then they are compiled to form combinatorial eigenvector matrix bundle of the monopole particle circuit field constructs assembly. Evaluation of this monopole particle fields matrix provided eigenvector fields results like SUSY, having Hermitian quantum matrix with electron-positron annihilation alongside north and south monopoles collapsing to dipolar “stable” magnetism, representing electromagnetic gaging typical metrics fields. Applying experimental observations on magnetic poles with measuring magnetic forces John Hodge’s results were showing asymmetrical pole forces; author has mathematically constructed asymmetric\strings\gage\metrics to characterize electromagnetic gravity, putting together while integrating with stringmetrics gravity that author has been reporting in earlier published articles. Physical Analysis with generalization of mass-charge and charge-fields gage metrics to quantum relativity gage metrics fields are proposed based on author’s proof formalism paper providing derivational algorithmic steps, to determine gage parametric values within the equation of Coulomb gage. Vortex fields’ wavefunctions and the scalar potential characterized by a function and a coupling constant having quantum density matrix together define the gage metrics quantifiable observable measurement physics of electron-positron cross-diagonal fields; contrastingly, diagonal terms of PDPcag matrix characterizes electron-positron particle eigenvector fields, while Hilbert Higgs mass metrics characterizes eigen-matter. Author is already working with Christopher O’Neill about magic square symmetry configurations to quantitatively understand symmetry, structure, and the real space geometry that are expected to form out of vacuum quanta point fields’ quantitative quantum general formalism theory of Iyer Markoulakis. In addition, author is currently collaborating with Manuel Malaver’s astrophysical Einstein Minkowski modified space time metrics evaluations of the sense-time-space relativistic general metrics to have means to account for curving or shaping of spacetime topology of a five-dimensional sense-time-space. Manuel Malaver’s specialization with modified Einstein Maxwell equations for modeling galaxies and stars cosmological physics, utilizing Einstein-Maxwell-Tolman- Schwarzschild and Reissner-Nordström spacetime and black holes theoretical formalisms have author of this paper collaboratively model quantum astrophysics of dark energy Star’s theory with Einstein-Gauss-Bonnet gravity equations.

Our knowledge of electricity is based on two parallel lines of research: one focusing on ‘charge’, the other on ‘electron’. The distinction is blurred. The difficulty is that the fundamental nature of elementary charge is unknown. Here I present evidence that charge is a resting electron and electron is a moving charge – one physical entity two behavioural identities. That is, charge is nonrelativistic electron and electron is relativistic charge. Charges obey the laws of static electricity (electrostatics); electrons obey the laws of moving electricity (electrodynamics). Whether positive or negative, a charge is ejected from the atom at tremendous speed, losing the characteristics of ‘a charge’ and gaining those of ‘an electron’. I conclude that an atom, hence nature in general, contains an equal number of positive and negative electrons, recognised at rest as opposite charges. This solves the mystery of the electron-positron numerical asymmetry. It means that static positions and negatrons (charges) play equivalent roles as subatomic building blocks of matter, revealing a new atomic structure.

The Double U-pipe ground heat exchanger, recognized for its straightforward process, cost-effectiveness, high heat exchange efficiency, and low thermal resistance, stands as the predominant ground heat exchanger type in today's shallow geothermal energy development and utilization. Recent years have seen significant research into the heat transfer influencing factors and heat exchange performance of Double U-pipe ground heat ex-changers via experimental testing methods. Yet, studies integrating numerical simulation with in-situ testing have been less frequent. Drawing on the cylindrical heat source model theory and the outcomes of regional in-situ thermal response tests, this paper develops a Double U-pipe ground heat transfer model by establishing physical, mathematical, and heat transfer geometric models. It assesses the impact of varying inlet temperatures, flow rates, and initial ground temperatures on heat exchange efficiency under heating conditions. The results validate the precision of the double U-pipe ground heat exchanger model based on in-situ testing. They show that enhancing the temperature differential between the inlet and initial temperatures, elevating the initial ground temperature, and moderately increasing the flow rate can boost the system's heat exchange efficiency.

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.

The article presents a technology for producing nitrogen-containing nanoporous biocarbon with high degree of elemental composition homogeneity, confirmed by electron spectroscopy. The research explores the relationship among the electronic characteristics of supramolecular nanoporous carbon, its porous structure, and the capacitance at its interface with the electrolyte. The obtained biocarbon is characterized by micro and mesopores, as evidenced by the results of studies by the method of nitrogen adsorption/desorption. The specific area of the available porous surface was found to be 1247 m2/g. Comparing this result with the data of small-angle X-ray scattering, we conclude that micropores are open while mesopores remain closed. This material was found to have a saturation magnetization σs of 1.4 A∙m2∙kg-1 and a coercive force Hc of 10 kA/m. The impedance studies of electrochemical cells of supercapacitors made of the experimental biocarbon were carried out. Equivalent electrical circuits of the studied electrochemical processes were constructed and characterized.

A careful examination of the fundamentals of electromagnetic theory shows that due to the underlying mathematical assumptions required for Stokes' Theorem, global charge conservation cannot be guaranteed in topologically non-trivial spacetimes. However, in order to break the charge conservation mechanism we must also allow the electromagnetic excitation fields D, H to possess a gauge freedom, just as the electromagnetic scalar and vector potentials $\varphi$ and A do. This has implications for the treatment of electromagnetism in spacetimes where black holes both form and then evaporate, as well as extending the possibilities for treating vacuum polarisation. Using this gauge freedom of D, H we also propose an alternative to the accepted notion that a charge passing through a wormhole necessarily leads to an additional (effective) charge on the wormhole's mouth.

Prereactive complexes in noncovalent organocatalysis are sensitive to the relative chirality of the binding partners and to hydrogen bond isomerism. Both effects are present when a transiently chiral alcohol docks on a chiral α-hydroxy ester, turning such 1:1 complexes into elementary, non-reactive model systems for chirality induction in the gas phase. With the help of linear infrared and Raman spectroscopy in supersonic jet expansions, conformational preferences are investigated for benzyl alcohol in combination with methyl lactate, also exploring p-chlorination of the alcohol and the achiral homolog methyl glycolate to identify potential London dispersion and chirality effects on the energy sequence. Three of the four combinations prefer barrierless complexation via the hydroxy group of the ester (association). In contrast, the lightest complex shows predominantly insertion into the intramolecular hydrogen bond, like the analogous lactate and glycolate complexes of methanol. The experimental findings are rationalized with computations and a uniform helicality induction in the alcohol by the lactate is predicted, independent on insertion into or association with the internal lactate hydrogen bond. p-Chlorination of benzyl alcohol has a stabilizing effect on association, because the insertion motif prevents a close contact between the chlorine and the hydroxy ester. After simple anharmonicity and substitution corrections, the B3LYP-D3 approach offers a fairly systematic description of the known spectroscopic data on alcohol complexes with α-hydroxy esters.

The gravitational charge should be the energy instead of mass. This modification will lead to some different results and the experiments to test are also presented. Especially, we propose a scheme to achieve the negative energy and gravitational repulsive force in the lab.

Low temperature dielectric property of charge/orbital ordered manganite, Pr1-xCaxMnO3 for 0.40≤x≤0.50 is investigated systematically as a function of Ca-content, x. The Ca-content dependence of dielectric permittivity and dissipation factor exhibit distinct maxima around x=0.45. The overall dielectric response of charge ordered Pr1-xCaxMnO3 is dominated by polarization induced by polaron hopping and exhibits thermally activated relaxation behaviour. The dielectric relaxation behaviour over the investigated temperature range is analysed with the help of small polaron hopping model and as well as variable range hopping model. The estimated polaron parameters also display non-monotonic variation with x and exhibit broad minima between x=0.425-0.45. The observed results suggest that a modulation of checker board type charge ordering pattern in Pr1-xCaxMnO3 is possibly taking place in the Ca-content range of investigation 0.40≤x≤0.50.

Atoms in Molecules (AIM), Natural Bond Orbital (NBO), and normal coordinate analysis have been carried out at the global minimum structures of TH₅⁺ (T = C/Si/Ge). All these analyses lead to a consistent structure for these three protonated TH₄ molecules. The CH₅⁺ has a structure with three short and two long C-H covalent bonds and no H-H bond. Hence, the popular characterization of protonated methane as a weakly bound CH₃⁺ and H₂ is inconsistent with these results. However, SiH₅⁺ and GeH₅⁺ are both indeed a complex formed between TH₃⁺ and H₂ stabilized by a tetrel bond, with the H₂ being the tetrel bond acceptor. The three-center-two-electron bond (3c-2e) in CH₅⁺ has an open structure, which can be characterized as a V-type 3c-2e bond and that found in SiH₅⁺ and GeH₅⁺ is a T-type 3c-2e bond. This difference could be understood based on the typical C-H, Si-H, Ge-H and H-H bond energies. Moreover, this structural difference observed in TH₅⁺ can explain the trend in proton affinity of TH₄. Carbon is selective in forming a ‘tetrel bond’ and when it does, it might be worthwhile to highlight it as a ‘carbon bond’.

With metal oxide semiconductors being a promising candidate for accurate indoor air quality assessments, multiple drawbacks of the gas sensors prevent their widespread use. Examples include poor selectivity, instability over time, and sensor poisoning. Complex calibration methods and advanced operation modes can solve some of those drawbacks. However, this leads to long calibration times, which are unsuitable for mass production. In recent years, multiple attempts to solve calibration transfer have been made with the help of direct standardization, orthogonal signal correction, and many more methods. Besides those, a new promising approach is transfer learning from deep learning. This article will compare different calibration transfer methods, including direct standardization, piecewise direct standardization, transfer learning for deep learning models, and global model building. The machine learning methods to calibrate the initial models for calibration transfer are feature extraction, selection, and regression (established methods) and a custom convolutional neural network TCOCNN. It is shown that transfer learning can outperform the other calibration transfer methods regarding the root mean squared error, especially if the initial model is built with multiple sensors. It was possible to reduce the number of calibration samples by up to 99.3 % (from 10 days to approximately 2 hours) and still achieve an RMSE for acetone of around 18 ppb (15 ppb with extended individual calibration) if six different sensors were used for building the initial model. Furthermore, it was shown that the other calibration transfer methods (direct standardization and piecewise direct standardization) also work reasonably well for both machine learning approaches, primarily when multiple sensors are used for the initial model.

This article presents a novel approach to understanding the influence of electric Energy on space-time curvature. EFE actual calculations refer solely to gravitational charges. In this article, I expand them to include the electric charge with calculations carried specifically for electric charges, with exciting results. The article leverages the universal consistency of physical laws, applying the known effects of gravitational charges on space-time curvature to electric charges. The research focuses on calculating the specific impact of electric charges on space-time curvature, rooted in the principle that space-time curvature is omnipresent. The findings reveal that space-time curvature's alteration due to an electric charge is influenced by various factors, including the charge's location, magnitude, mass, density, associated electric field, and its motion through space-time. Notably, the conversion factor for electric charges differs from the conversion factor for gravitational charges. These insights significantly enhance our understanding of electromagnetism and general relativity, paving the way for a more profound comprehension of electric charges.

Almost all modern inorganic light-emitting diode (LED) designs are based on double heterojunctions (DHJs) whose structure and current injection principle have remained essentially unchanged for decades. Although highly efficient devices based on the DHJ design have been developed and commercialized for energy-efficient general lighting, the conventional DHJ design requires burying the active region (AR) inside a pn-junction. This has hindered the development of emitters utilizing nanostructured ARs located close to device surfaces such as nanowires or surface quantum wells. Modern DHJ III-N LEDs also exhibit resistive losses which arise from the DHJ device geometry. The recently introduced diffusion-driven charge transport (DDCT) emitter design offers a novel way to transport charge carriers to unconventionally placed ARs. In a DDCT device, the AR is located apart from the pn-junction and the charge carriers are injected into the AR by bipolar diffusion. This device design allows the integration of surface ARs to semiconductor LEDs and offers a promising method to reduce resistive losses in high power devices. In this work, we present a review of the recent progress in gallium nitride (GaN) based DDCT devices, and an outlook of potential DDCT has for opto- and microelectronics.

Noninvasive brain stimulation technique can be used for modulation of motor behaviors such as reaction time (RT). The main aim of this study was to investigate whether RT during a sequential visual isometric pinch task (SVIPT) can be affected by anodal transcranial direct current stimulation (a-tDCS) over three different stimulation sites such as dorsolateral prefrontal cortex (DLPFC), primary motor cortex (M1) or posterior parietal cortex (PPC). We also aimed to assess if stimulation of these cortical sites affect the transfer of learning during SVIPT. A total of 48 right-handed healthy participants were randomly assigned to one of the four a-tDCS groups: 1) left M1, 2) left DLPFC, 3) left PPC and 4) sham. A-tDCS was applied concurrent with SVIPT in which the participants were precisely controlled their forces to reach seven different target forces from 10 to 40% of maximum voluntary contraction (MVC) presenting on a computer screen with right dominant hand. Four test blocks were randomly performed at baseline and 15 min after the intervention including sequence and random blocks with either hand. Our results showed significant differences between a-tDCS groups on ratio RT in the sequence blocks of both the right trained (P = .041) and left untrained hands (P = .023) for target forces of 15% and 30 % of MVC, respectively. In sequence blocks, M1 showed significant elongation in ratio RT for the target force of 15% and 30 % MVC compared to PPC and Sham groups in the right hand. In sequence blocks with left hand, this negative effect were found between M1-DLPFC and M1-Sham groups. In random blocks, no significant differences were found among four groups at each target forces for the left hand while there were significant differences for 15% (P =. 04) and 40% MVC (P =. 035) in the right hand. Our findings suggest that three different stimulation sites (DLPFC, M1 or PPC) were differentially affected by a single session of a-tDCS at some target forces during SVIPT. The effects of a-tDCS on ratio RT were transferred in the left untrained hand for sequence blocks but not random blocks. Further research is needed to understand fundamental aspects of these main areas of the brain on temporal processing in a precision control task such as SVIPT.

Electric energy is one of the driving forces in every country. The supply of electrical energy continues to present various challenges, such as high costs associated with procuring raw materials for generation, sparsely populated areas that are not connected to the main grid, and the need for infrastructure to support generation and network delivery. These challenges have contributed to the growing adoption of renewable energy sources, particularly solar photovoltaics (PV).In this study, we have developed a practical method to assess the spatial PV potential in a selected urban area. The methodology combines data collected from an unmanned aerial vehicle (UAV) photogrammetry, Geographic Information System (GIS), and the energy output from three remote photovoltaic systems installed at different locations. The results obtained from this approach not only provide the energy generated per square meter, per year (kWh m-2 yr-1), but also provides a base to calculate the potential distance that electric cars could travel based on the energy generated. To illustrate the application of this method, two practical cases were selected: Senglea, Malta, and Munxar, Gozo. These examples highlight the versatility and effectiveness of our approach for evaluating and harnessing solar energy through photovoltaic panels in different contexts.

Pakistan flora is enriched with potent bioactive compounds that must be explored while Alzheimer's disease (AD) poses a global challenge driven by neurochemical imbalances. Acetylcholinesterase (AChE) inhibitors traditionally alleviate symptoms, but addressing the root cause remains elusive. This gap has led to the exploration of herbal sources for interventions. In this context, we analyzed fifty 50 medicinal plants for their phytochemical composition and antioxidant and acetylcholinesterase inhibition activities. AChE activity was measured using Ellman’s method. Santalum album exhibited significant AChE inhibition (86.2%), surpassing galantamine hydrobromide (81.8%). Promising inhibition was also seen in Bombax ceiba (77.8%), Acacia karoo (52.9%), and Phaseolus lunatus (50.1%). Detailed analysis revealed Santalum album's abundance in terpenoids, flavonoids, tannins, and phenolics, potentially correlating with its antioxidant and AChE inhibitory effects. Acacia karoo demonstrated elevated levels of total alkaloids, antioxidants, terpenoids, and tannins. Both Acacia karoo and Santalum album show promise for AD intervention due to their AChE inhibitory activities and unique phytochemical attributes, warranting further exploration, particularly for Acacia karoo's novel potential in AChE inhibition, to advance targeted AD therapeutics utilizing natural resources. This study contributes to the search for effective AD strategies from nature's pharmacological resources.

In this article, we analyze the thermodynamics, thermal fluctuations and quasi-normal modes of a torus-like charge AdS black hole. The parameters of a torus-like charged AdS black hole are its mass, electric charge, and cosmological constant. We used a torus-like charge AdS black hole to evaluate thermodynamics through thermal fluctuations and found that it significantly affected the corrected thermodynamic potentials. Black holes of larger radii are more stable and significant. The effect of thermal fluctuation has been investigated on the other thermodynamic potentials such as the Hemohltz free energy, Gibbs free energy, enthalpy, and specific heat, using the concept of corrected entropy. Finally, we use null geodesics to deal with quasi-normal modes. The null geodesics provide the photon sphere angular velocity and Lyapunov exponent, which are the real and imaginary components of the quasi-normal modes in the eikonal limit. With inceasing charge and photon radius, angular velocity reaches its maximum, similar to Lyapunov's exponent.

According to observations leptons are always produced in pairs. Both particles can be electrically charged, or just one, in which case the charged particle is accompanied by a particle specific neutrino. The period doubling process in nonlinear dynamical systems creates stable pair structures from the Planck units. The electron-positron pair is one of the stable structures, and the rest mass, electric charge and magnetic moment can be accurately calculated by the period doubling process. That the pair structure is stable means, that e.g., an electron and a positron are always born together. In the muon decay one of the pair is charged, while the other remains chargeless because there is only one charge available. It is suggested in this article that neutrino is the chargeless part of the lepton pair.

This Letter revisits the instability of jet produced by shaped charge. Scaling laws for shaped charge jet are derived by dimensional analysis. It shows that the scaling laws are universal when cross-sectional shrinkage rate is not included in the formulation.

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

The work presented in this paper represents a preliminary study on the performance of the new Silicon tracker layer, the Layer 0 (L0), that will be installed on top of the Alpha Magnetic Spectrometer (AMS-02), at the end of 2024. AMS-02 is a cosmic rays (CR) detector that has been operating on the International Space Stations (ISS) since May 2011. Thanks to its 9-layer Silicon tracker, this apparatus can perform high energy CR measurements with an unprecedented level of statistics and precision. However, high Z (Z $\ge 15$) CR nuclei statistic is strongly affected by fragmentation along the detector: with the installation of the new Silicon layer will be possible to achieve new unique high energy (TeV region) measures for those nuclei along with increased statistics for all nuclei up to Zinc. To achieve this, a Silicon ladder prototype, that will be part of the final Silicon layer, has been exposed to an ions test beam at the super-proton-synchrotron (SPS) of the CERN to characterize its charge resolution and the readout electronics. Preliminary results have shown a charge resolution of 10 $\%$ for nuclei up to Z=7.

The entropy and charge distributions have been calculated for a simple model of polyelectrolytes attached to the surface of DNA using a field-theoretic method that includes fluctuations to the lowest one-loop order beyond mean-field theory. Experiments have revealed correlation-driven behavior of DNA in charged solutions, including charge inversion and condensation. In our model, the condensed polyelectrolytes are taken to be doubly charged dimers of length comparable to the distance between sites along the phosphate chains. Within this lattice-gas model, each adsorption site is assumed to have either a vacancy or a positively-charged dimer attached with the dimer oriented either parallel or perpendicular to the double helix DNA chain. We find that the inclusion of the fluctuation terms decreases the entropy by ∼50% in the weak binding regime. There, the bound dimer concentration is low because the dimers are repelled from the DNA molecule, which competes with the chemical potential driving them from the solution to the DNA surface. Surprisingly, this decrease in entropy due to correlations is so significant that it overcompensates for the entropy increase at the mean field level, so that the total entropy is even lower than in the absence of interactions between lattice sites. As a bonus, we present a transparent exposition of the methods used that could be useful to students and others wishing to use this formulation to extend this calculation to more realistic models.

The apparent shape of the black hole shadow provides a full description of the spin, the inclination angle and the charge of a Kerr black hole, without any astrophysical process or underlying theory in the astrophysical process.

The general coupling between particle transport and ionization-recombination processes in hot plasma is considered on the key concept of equilibrium charge state (CS) transport. A theoretical interpretation of particle and CS transport is gained in terms of a two-dimensional (2D) Markovian stochastic (random) processes, a discrete 2D Fokker-Plank-Kolmogorov equation (in charge and space variables) and generalized 2D coronal equilibrium between atomic processes and particle transport. The basic tool for analysis of CS equilibrium and transport is the equilibrium cell (EC) (two states on charge and two on space), which presents (i) a unit phase volume, (ii) the characteristic scale of local equilibrium, (iii) a comprehensive solution for the simplest nonlinear relations between transport and atomic processes. The approach opens up new perspectives on transport studies: (i) the direct modelling of equilibrium and transport of impurity using the atomic data base, (ii) recovery of the complete recombination rate profile based on knowledge of density profiles and ionization rate profiles, (iii) the local transport analysis, based on the reduction of the equilibrium set to the single EC (in particular, central or edge), (iv) analysis of the reduced transport coefficients (diffusion and convection) on the density profile measurements.

A two-step, one-pot synthesis of 3-substituted 1H-dibenzo[e,g]indazoles in good to high yields via a LiOtBu-promoted intramolecular cyclization of 2’-alkynyl-biaryl-2-aldehyde N-tosylhydrazones, formed in situ by the reactions of 2’-alkynyl-biaryl-2-aldehydes with p-methylbenzenesulfonohydrazide was developed. Two kinds of hydrogen bonds forming in several products were observed in DMSO-d6 solution in 1H NMR spectroscopic data, which were assigned to the formation of solvated products and dimers of products, supported by the studies of density functional theory (DFT).

In this research, a novel method to investigation the transient heat transfer coefficient in a channel is suggested experimentally, in which the water flow, itself, is considered both just liquid phase and liquid-vapor phase. The experiments were designed to predict the temporal and spatial resolution of Nusselt number. The inverse technique method is non-intrusive, in which time history of temperature is measured, using some thermocouples within the wall to provide input data for the inverse algorithm. The conjugate gradient method is used mostly as an inverse method. The temporal and spatial changes of heat flux, Nusselt number, vapor quality, convection number, and boiling number have all been estimated, showing that the estimated local Nusselt numbers of flow for without and with phase change are close to those predicted from the correlations of Churchill and Ozoe (1973) and Kandlikar (1990), respectively. This study suggests that the extended inverse technique can be successfully utilized to calculate the local time-dependent heat transfer coefficient of boiling flow.

This work addresses the role of charge regulation (CR) and the associated fluctuations in the conformational and mechanical properties of weak polyelectrolytes. Due to CR, changes in the pH-value modifies the average macromolecular charge and conformational equilibria. A second effect is that, for a given average charge per site, fluctuations can alter the intensity of the interactions by means of correlation between binding sites. We investigate both effects by means of Monte Carlo simulations at constant pH-value, so that the charge is a fluctuating quantity. Once the average charge per site is available, we turn off the fluctuations by assigning the same average charge to every site. A constant charge MC simulation is then performed. We make use of a model which accounts for the main fundamental aspects of a linear flexible polyelectrolyte i.e. proton binding, angle internal rotation, bond stretching and bending. Steric excluded volume and differentiated treatment for short-range and long-range interactions are also included in the model. It can be regarded as a kind of "minimal'' model in the sense that contains a minimum number of parameters but still preserving the atomistic detail. It is shown that, if fluctuations are activated, gauche state bond probabilities increase, and the persistence length decreases, so that the polymer becomes more folded. Macromolecular stretching is also analyzed in presence of CR (the charge depends on the applied force) and without CR (the charge is fixed to the value at zero force). The analysis of the low force scaling behavior concludes that Pincus exponent becomes pH-dependent. Both with and without CR, a transition from 1/2 at high pH-values (phantom chain) to 3/5 to low pH-values (Pincus regime), is observed. Finally, the intermediate force stretching regime is investigated. It is found that CR induces a moderate influence in the force-extension curves and persistence length (which in this force regime becomes force-dependent). It is thus concluded that the effect of CR on the stretching curves is mainly due to changes in the average charge at zero force. It is also found that, for the cases studied, the effect of steric excluded volume is almost irrelevant compared to electrostatic interactions.

Evaluating new, promising organic molecules to make next-generation organic optoelectronic devices necessitates the evaluation of charge carrier transport performance through the semi-conducting medium. In this work, we utilize quantum chemical calculations (QCC) and kinetic Monte Carlo (KMC) simulations to predict the zero-field hole mobilities of ~100 morphologies of the benchmark polymer poly(3-hexylthiophene), with varying simulation volume, structural order, and chain-length polydispersity. Morphologies with monodisperse chains were generated previously using an optimized molecular dynamics force-field and represent a spectrum of nanostructured order. We discover that a combined consideration of backbone clustering and system-wide disorder arising from side-chain conformations are correlated with hole mobility. Furthermore, we show that strongly interconnected thiophene backbones are required for efficient charge transport. This definitively shows the role "tie-chains" play in enabling mobile charges in P3HT. By marrying QCC and KMC over multiple length- and time-scales, we demonstrate that it is now possible to routinely probe the relationship between molecular nanostructure and device performance.

This study investigates the long-term stability of the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate-resolution Thermal Emissive Bands (M TEBs; M12 – M16) covering a period from February 2012 to August 2020. It also assesses inter-sensor consistency of the VIIRS M TEBs among three satellites-S-NPP, NOAA-20, and NOAA-21 over eight months spanning from March 18 to November 30, 2023. The field of interesting is limited to the ocean surface between 60°S and 60°N, specifically under clear-sky conditions. Taking radiative transfer modeling (RTM) as the transfer reference, we employed the Community Radiative Transfer Model (CRTM) to simulate VIIRS TEB brightness temperature (BTs), incorporating European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data as inputs. Our results reveal two key findings. Firstly, the reprocessed S-NPP VIIRS TEBs exhibit a robust long-term stability, as demonstrated through analyses of the observation minus background BT differences (O-B ∆BTs) between VIIRS measurements (O) and CRTM simulations (B). The drifts of the O-B BT differences are consistently less than 0.105 K/Decade across all S-NPP VIIRS M TEB bands. Notably, observations from VIIRS M14 and M16 stand out with drifts well within 0.04 K/Decade, reinforcing their exceptional reliability for climate change studies. Secondly, excellent inter-sensor consistency among these three VIIRS instruments is confirmed through the double-difference analysis method (O-O). This method relies on the O-B BT differences obtained from daily data. The mean inter-VIIRS O-O BT differences remain within 0.08 K for all M TEBs, except for M13. Even in the case of M13, the O-O BT differences between NOAA-21 and NOAA-20/S-NPP have values of 0.312 K and 0.234 K, respectively, which are comparable to the 0.2 K difference between some TEBs among VIIRS and MODIS. These disparities are primarily attributed to the significant differences in the Spectral Response Function (SRF) of NOAA-21 compared to NOAA-20 and S-NPP. Our study confirms the RTM-based TEB quality evaluation method’s versatility and effectiveness in assessing long-term sensor stability and inter-sensor consistency. The double-difference approach effectively mitigates uncertainties and biases inherent to CRTM simulations, establishing itself a robust mechanism for assessing inter-sensor consistency. In addition, we’ve observed that, except for M13, M12 always exhibits larger spatial variations of O-O BT differences with greater uncertainties compared to the other M TEBs. The influence of solar contribution through sea surface reflection on the Top of Atmosphere (TOA) radiance measurements during daytime in M12 should not be underestimated.

A human brain can communicate with another one’s brain using quantum entanglement. Similar particles can entangle without interaction. Sensory communication between two individuals from far distances is still not known. Former studies primarily have been performed regarding brain neurons' quantum behavior. The test was performed on two individuals far from each other. These individuals were put under the same music on the basis of brain neuroplasticity property. By activating the brain reward system, aligned thinking was time scheduled in these individuals’ brains. On the basis of entanglement, compressed information was sent and received between these two individuals.

Quantum cryptography is the field of cryptography that explores the quantum properties of matter. Its aim is to develop primitives beyond the reach of classical cryptography or to improve on existing classical implementations. Although much of the work in this field has been dedicated to quantum key distribution (QKD), some important steps were made towards the study and development of quantum oblivious transfer (QOT). It is possible to draw a comparison between the application structure of both QKD and QOT primitives. Just as QKD protocols allow quantum-safe communication, QOT protocols allow quantum-safe computation. However, the conditions under which QOT is actually quantum-safe have been subject to a great amount of scrutiny and study. In this review article, we survey the work developed around the concept of oblivious transfer in the area of theoretical quantum cryptography, with an emphasis on some proposed protocols and their security requirements. We review the impossibility results that daunt this primitive and discuss several quantum security models under which it is possible to prove QOT security.

Hydrogenases are iron-sulfur enzymes that catalyze proton reduction and H₂ oxidation with outstanding efficiency. They are considered blueprints for the design of transition metal complexes, e.g. as heterogenous catalysts in the context of H₂ production from water. Moreover, hydrogenases are biological model systems for metal hydride chemistry and proton-coupled electron transfer. Depending on the composition of the active site cofactor, [NiFe]-hydrogenases are distinguished from [FeFe]-hydrogenases. The former binds a hetero bimetallic nickel/iron site, embedded in the protein by four cysteine ligands. The later, by contrast, carries a homo bimetallic iron/iron site attached to the protein by only a single cysteine. Carbon monoxide and cyanide ligands (CO/CN) at the active site facilitated detailed investigations of hydrogenase catalysis by infrared spectroscopy, owing to strong signals and redox-dependent frequency shifts. However, the details of proton transfer have not been addressed experimentally.We found that specific redox state transitions in [NiFe]- and [FeFe]-hydrogenase can be triggered by visible light to record extremely sensitive ‘light-minus-dark’ infrared difference spectra monitoring key amino acid residues as shown in the ToC figure. As these transitions are coupled to protonation changes, our data allowed investigating dynamic hydrogen-bonding changes that go well beyond the resolution of protein crystallography. In [NiFe]-hydrogenase, photolysis of the bridging hydride ligand in the ‘Ni-C’ state was followed by rapid accumulation of the ‘Ni-SI_a’ state and/or ‘Ni-L’ state. Infrared difference spectra in various isotopic media clearly indicated the formation of a protonated cysteine residue as well as hydrogen-bonding changes involving the COOH group of a glutamic acid residue and a ‘dangling water’ molecule. These findings are in excellent agreement with crystallographic analyses of [NiFe]-hydrogenase in the Ni-R state and allowed devising a molecular precise model of catalytic proton transfer. In [FeFe]-hydrogenase, an external redox dye was used to accumulate the ‘Hred’ state over the oxidized resting state ‘Hox’. Infrared difference spectra of wild-type enzyme and numerous amino acid variants indicated hydrogen-bonding changes involving the COOH groups of two glutamic acid residues. Moreover, we noted the deprotonation of an arginine residue. Crystallographic analyses of [FeFe]-hydrogenase in the Hox state failed to explain the rapid proton transfer due to a ‘breach’ in the succession of residues. To this end, our findings facilitated a molecular precise model of ‘discontinued’ proton transfer.The comparison of catalytic proton transfer in bimetallic hydrogenases emphasizes the role of the outer coordination sphere. We suggest that the stable protonation of a nickel-ligating cysteine in [NiFe]-hydrogenase has a crucial influence on the preferred direction of proton flow and catalysis (i.e., H₂ oxidation). On the contrary, proton transfer in [FeFe]-hydrogenase involves an adjacent cysteine as a relay group that promotes both proton release and proton uptake. We presume that this causes the notable bidirectionality of [FeFe]-hydrogenase. These observations must guide the design of biomimetic compounds for the production or consumption of H₂.

This paper proposes a circuit model of Cross-Coupled CMOS AC – DC Charge Pump (XC – CP) operating in subthreshold region. The aim is improving the efficiency to design XC – CPs with variety of specifications, e.g., input and output voltages and AC input frequency. First, it is shown that the output resistance (Ro) of XC – CP is much higher than those of CPs with single diodes (SD – CP) and ultra-low-power diodes (ULPD – CP) as charge transfer switches (CTSs). Second, the reason behind the above feature of XC – CP is identified by a simple model that the gate-to-source voltages of CTS MOSFETs are independent of the output voltage of the CP. Third, high but finite Ro of XC – CP is explainable with a more accurate model that includes the dependence of the saturation current of MOSFETs operating in subthreshold region on the drain-to-source voltage which is a function of the output voltage of CP. The model was in good agreement with measured and simulated results of XC – , SD – and ULPD – CPs fabricated in 250 nm CMOS.

This paper presents an improved SOC estimation method for lithium ion batteries in Electric Vehicles using Bayesian optimized feedforward network. This innovative bayesian optimized neural network method attempts to minimize a scalar objective function by extracting hyperpa-rameters (hidden neurons in both layers) using a surrogate model. Furthemore, the hyperparameters are built and data samples are trained and validated. The performance of the proposed deep learning neural network is evaluated. Two reasonable size data samples are ex-tracted from Panasonic 18650PF Li-ion Mendeley datasets that are used for training and valida-tion. RNN and LSTM neural network algorithms offer the common core property of retaining past information and/or hidden states for better SOC estimation. However, the feature of this pro-posed method is the inclusion of Bayesian optimization that chooses optimal double layer hidden neurons. Analysis of results shows that Bayesian optimized feedforward algorithm with average MAPE (0.20%) is the lowest and is the best selection compared with average MAPE for other five deep learning algorithms. In the last quarter of fuel gauge, where fuel anxiety is severe, feed-forward with Bayesian Optimization algorithm is still the best selection (with MAPE of 0.64%).

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

Below T_CO=157 K the quasi-one-dimensional charge-transfer salt (TMTTF)_2SbF_6 undergoes a pronounced phase transition to a charge-ordered ground state. We have explored the non-linear and photoconductive behavior as a function of applied voltage, laser pulse energy and temperature. Besides a decay of the photoconductive signal in a double exponential fashion in the millisecond range, we discover current oscillations in the kHz range induced by the application of short laser pulses. While the resonance frequencies do not depend on voltage or laser intensity and vary only slightly with temperature, the amplitude changes linearly with the laser intensity and voltage. The findings are discussed and compared to comparable phenomena in other low-dimensional electron systems.

An exposition of entropy applications to highlight some potential entropic applications to artificial intelligence and knowledge transfer. Entropy is a basic idea in artificial intelligence that is applied to many different tasks, such as reinforcement learning, data compression, and decision-making. By quantifying uncertainty and information content, it helps artificial intelligence models provide predictions and decisions that are well-informed. Therefore, this paper shines on spotlighting the significance of entropy to attract the attention of artificial intelligence research community to entropy as a powerful tool to advance artificial intelligence.The significance of knowledge transfer (KT), particularly intergenerational knowledge transfer (IGT), in knowledge management is also covered in this paper. To quantify the complexity of knowledge distribution inside an organisation and assess the efficacy of knowledge transfer (KT) initiatives, the notion of knowledge entropy (KE) is presented. Additionally, the KT model—which is based on the conceptions of tacitness and information content—is introduced. It combines personalisation and codification methodologies. Future research directions are offered alongside a few difficult open problems.

Recently, the use of drones/unmanned aerial vehicles (UAVs) has notably increased due to their broad commercial spread and low cost. The wide diffusion of drones increases the hazards of their misuse in illegitimate actions such as drug smuggling and terrorism. Thus, the surveillance and automated detection of drones are crucial for safeguarding restricted regions or special zones from illegal drone interventions. One of the most challenging issues in drone detection in surveillance videos is the apparent similarity of drones and birds against complex backgrounds. In this work, an automated image-based drone-detection system utilizing an advanced deep-learning-based object-detection method known as you only look once (YOLOv5) is introduced for protecting restricted regions or special zones from unlawful drone interventions. Due to the lack of sufficient data, transfer learning was utilized to pretrain the object-detection method to increase the performance. The experiments showed outstanding results, and an average precision of 94.7% was accomplished.

We study the brain segmentation by dividing the brain into multiple tissues. Given possible brain segmentation by deep, machine learning can be efficiently exploited to expedite the segmentation process in the clinical practice. To accomplish segmentation process, a MRI and tissues transfer using generative adversarial networks is proposed. Given the better result, we propose the transfer model using GAN. For the case of the brain tissues, white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) are segmented. Empirical results show that this proposed model significantly improved segmentation results compared to the stat-of-the-art results. Furthermore, a dice coefficient (DC) metric is used to evaluate the model performance.

In this review, we provide an overview of the most common majority and minority charge carrier traps in n-type 4H-SiC material. We focus on the results obtained by different applications of junction spectroscopy techniques. The basic principles behind the most common junction spectroscopy techniques are given. These techniques, namely, deep level transient spectroscopy (DLTS), Laplace DLTS (L-DLTS) and minority carrier transient spectroscopy (MCTS) have led to recent progress in identifying and better understanding of the charge carrier traps in n-type 4H-SiC material.

We examine here the discrepancy between the radiated power, calculated from the Poynting flux at infinity, and the power loss due to radiation reaction for an accelerated charge. It is emphasized that one needs to maintain a clear distinction between the electromagnetic power received by distant observers and the mechanical power loss undergone by the charge. In literature both quantities are treated as almost synonymous, the two in general could, however, be quite different. It is shown that in the case of a periodic motion, the two formulations do yield the power loss in a time averaged sense to be the same, even though, the instantaneous rates are quite different. It is demonstrated that the discordance between the two power formulas merely reflects the difference in the power going in self-fields of the charge between the retarded and present times. In particular, in the case of a uniformly accelerated charge, power going into the self-fields at the present time is equal to the power that was going into the self-fields at the retarded time plus the power going in acceleration fields, usually called radiation. From a comparison of the far fields with the instantaneous location of the uniformly accelerated charge, it is shown that all its fields, including the acceleration fields, remain around the charge and are not radiated away from it.

This computational research study analyzes the increase of the specific charge capacity that comes with the reduction of the anisotropic volume expansion during lithium ion insertion within silicon nanowires. This research paper is a continuation from previous work that studied the expansion rate and volume increase. It has been determined that when the lithium ion concentration is decreased by regulating the amount of Li ion flux, the lithium ions to silicon atoms ratio, represented by x, decreases within the amorphous lithiated silicon (a-LixSi) material. This results in a decrease in the volumetric strain of the lithiated silicon nanowire as well as a reduction in Maxwell stress that was calculated and Young’s elastic module that was measured experimentally using nanoindentation. The conclusion as will be seen is that as there is a decrease in lithium ion concentration there is a corresponding decrease in anisotropic volume and a resulting increase in specific charge capacity. In fact the amplification of the electromagnetic field due to the electron flux that created detrimental effects for a fully lithiated silicon nanowire at x = 3.75 which resulted in over a 300% volume expansion becomes beneficial with the decrease in lithium ion flux as x approaches 0.75 which leads to a marginal volume increase of ~25 percent. This could lead to the use of crystalline silicon, c-Si, as an anode material that has been demonstrated in many previous research work to be ten times greater charge capacity than carbon base anode material for lithium ion batteries.

Abstract: This computational research study analyzes the increase of the specific charge capacity that comes with the reduction of the anisotropic volume expansion during lithium ion insertion within silicon nanowires. This research paper is a continuation from previous work that studied the expansion rate and volume increase. It has been determined that when the lithium ion concentration is decreased by regulating the amount of Li ion flux, the lithium ions to silicon atoms ratio, represented x, decreases within the amorphous lithiated silicon (a-LixSi) material. This results in a decrease in the volumetric strain of the lithiated silicon nanowire as well as a reduction in Maxwell stress that was calculated and Young’s elastic module that was measured experimentally using nanoindentation. The conclusion as will be seen is that as there is a decrease in lithium ion concentration there is a corresponding decrease in anisotropic volume and a resulting increase in specific charge capacity. In fact the amplification of the electromagnetic field due to the electron flux that created detrimental effects for a fully lithiated silicon nanowire at x=3.75 which resulted in over a 300% volume expansion becomes beneficial with the decrease in lithium ion flux as x approaches 0.75 which leads to a marginal volume increase of ~25 percent. This could lead to the use of crystalline silicon, c-Si, as an anode material that has been demonstrated in many previous research work to be ten times greater charge capacity than carbon base anode material for lithium ion batteries.

Since the turn of the 21^st Century Chian has enacted a range of policies to improve its water ecosystem. Some of these measures include (but are not limited to) the creation of Seven River Conservancy Commissions to engage in river basin management and the development (combination and recombination) of series of ministries and departments to address environmental pollution and degradation. The most recent attempt to address the nations polluted waterways and lakes occurred in December 2016, when the General Office of the Chinese Central Committee and the State Council issued The Options on Full Implementation of the River Chief System (RCS) Across the Country. The intent behind Options was not only to fully implemented he river chief system but to bring the nations drinking water supply quality to no worse than category III. Based on the Options Erik Solheim, UN Under Secretary General and Executive Director of the UN Environment Programme, commented ‘I'm convinced that what I have seen in Pujiang County and Anji County will be the future of China, even the future of the world’ (cited in Xianqiang 2021, 435; emphasis added). It is to this observation that the reminder of this article will be directed.

We propose a new methodology for long-time biopotential recording based on MEMS multisensor integrated platform featuring a commercial electrostatic charge transfer sensor. That family of sensors was originally intended for presence tracking in automotive, so the existing setup has been engineered for the acquisition of electrocardiogram, electroencephalogram, electrooculogram and electromyography, designing a dedicated front-end and writing a proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in domestic environment will be discussed in detail. The excellent results candidate this technology to provide a low power, unexplored solution to biopotentials acquisition. The technology breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, they open to additional possibilities for wearable sensing and strengthen the role of MEMS technology in medical wearable applications for long time synchronous acquisition of a wide range of signals.

Luminophores featuring thermally activated delayed fluorescence (TADF luminophores) are the workhorse of the third- and fourth-generation OLEDs. While these compounds had usually been used as dopants embedded in the host, non-doped TADF OLEDs have recently shown significant progress as well reaching the performance comparable to the host-dopant ones. For efficient operation of the non-doped OLEDs, charge transport in neat films and single crystals of TADF luminophores is important; however, this issue was nearly unexplored theoretically. In the current study, we calculated charge mobilities in four TADF single crystals, which have different molecular packing motifs. Specifically, in one of them both donor and acceptor moieties form uniform π-stacks, while in the others donors (acceptors) show alternating lateral shifts along the stacks; the difference in molecular packing results in the difference of transfer integral between the molecules. Reorganization energies differ as well up to four times for the studied crystals. As a result, charge mobilities vary from 0.001 to ~0.3 cm2/(V∙s), the largest being predicted for the crystal of the luminophore consisting of rigid donor and acceptor. We anticipate that the results obtained can be useful for the design of TADF luminophores for non-doped OLEDs, OLETs and other organic light-emitting devices.

As one of the critical state parameters of the battery management system, lithium battery state of charge (SOC) can provide an essential reference for battery safety management, charge/discharge control, and energy management of electric vehicles. To analyze the application of deep learning in electric vehicle power battery SOC estimation, this study reviewed the technical process, common public datasets, and the neural networks used, structural characteristics, advantages and disadvantages of lithium battery SOC estimation in deep learning method. First, the specific technical processes of the deep learning method for SOC estimation were analyzed, including data collection, data preprocessing, feature engineering, model training, and model evaluation. Secondly, the current commonly and publicly used lithium battery dataset was summarized. Then, the input variables, data sets, errors, and advantages and disadvantages of four types of deep learning methods, were concluded using the structure of neural network used for training as the classification criterion. Finally, the challenges and future development directions of lithium battery SOC estimation in deep learning method were explained.

During last decades, production and consumption of small ruminant milk has been increased. As a result of it, sheep and goat farming has been developing and scientists are focused on these animal researches both clinical and feeding strategies. By the evolutionary challenges and adaptations, colostrum has a crucial role of immune complementation for litter. As a result of these challenges and adaptations neonatal life is especially more important in ruminants because of it affects their whole life and future of livestock. Passive immune transfer is the main mechanism that explained by biological evolution between dam and lamb and also it is effected by factors up to dam and up to the litter. Today importance of passive immune transfer is well known for the future of livestock economy and animal welfare. In the literature, researchers are focused on correlation between colostrum quality (especially immunoglobulin amounts) and blood serum levels of newborns. Aims of present review are to discuss datas of recent studies, point out different effecting factors in colostrum quality and passive immune transfer, enlighten and give new ideas to researchers.

Transformers are increasing replacing older generation of deep neural networks due to their success in a wide range of application. The dominant approach of using transformers is to pre-train them on a large training dataset and then fine-tune them on a downstream task. However, as transformers becoming larger, the fine-tuning approach is become an infeasible approach for transfer learning. In this short survey, we list a few recent methods that makes using transformers based on transfer learning more efficient.

Graph neural networks (GNNs) build on the success of deep learning models by extending them for use in graph spaces. Transfer learning has proven extremely successful for traditional deep learning problems: resulting in faster training and improved performance. Despite the increasing interest in GNNs and their use cases, there is little research on their transferability. This research demonstrates that transfer learning is effective with GNNs, and describes how source tasks and the choice of GNN impact the ability to learn generalisable knowledge. We perform experiments using real-world and synthetic data within the contexts of node classification and graph classification. To this end, we also provide a general methodology for transfer learning experimentation and present a novel algorithm for generating synthetic graph classification tasks. We compare the performance of GCN, GraphSAGE and GIN across both the synthetic and real-world datasets. Our results demonstrate empirically that GNNs with inductive operations yield statistically significantly improved transfer. Further we show that similarity in community structure between source and target tasks support statistically significant improvements in transfer over and above the use of only the node attributes.

Three-dimensional transfer functions (3D TFs) are generally assumed to fully describe the transfer behavior of optical topography measuring instruments such as coherence scanning interferometers in the spatial frequency domain. Therefore, 3D TFs are supposed to be independent of the surface under investigation resulting in a clear separation of surface properties and transfer characteristics. In this paper we show that the 3D TF of an interference microscope differs depending on whether the object is specularly reflecting or consists of point scatterers. In addition to the 3D TF of a point scatterer, we will derive an analytical expression for the 3D TF corresponding to specular surfaces and demonstrate this as being most relevant in practical applications of coherence scanning interferometry (CSI). We additionally study the effects of temporal coherence and disclose, that in conventional CSI temporal coherence effects dominate. However, narrowband light sources are advantageous if high spatial frequency components of weak phase objects are to be resolved, whereas for low-frequency phase objects of higher amplitude the temporal coherence is less affecting. Finally, we present an approach that explains the different transfer characteristics of coherence peak and phase detection in CSI signal analysis.

When a microgrid is grid-tied to a distribution system, it can provide surplus power generation to the distribution system, if any abnormality or interruption occurs in the distribution system, the microgrid can operate in standalone mode to isolate the impact of the abnormality or interruption. However, if the microgrid can not collect enough information from the distribution system, it may cause the failure of generation transferring of distribution feeders, or even further influence the stability of the distribution system. In this paper, a strategy for the resilient control of a microgrid is proposed. It can solve the above-mentioned problem, reduce the duration of the outage of loads. This strategy is experimented in the microgrid in the Institute of Nuclear Energy Research (INER), the reliability is also analyzed to evaluate the unavailability of the microgrid in INER, and it is verified that the proposed strategy can reduce the duration of the outage of loads, and hence the reliability of a microgrid can be upgraded.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

Accurate transfer learning of clinical outcomes, e.g., of the effects and side effects of drugs or other interventions, from one cellular context to another (in-vitro versus ex-vivo versus in-vivo, or across tissues), between cell-types, developmental stages, omics modalities or species, is considered tremendously useful. Ultimately, it may avoid most drug development failing in translation, despite large investments in the preclinical stages, which includes animal experiments requiring careful justification. Thus, when transferring a prediction task from a source (model) domain to a target domain, what counts is the high quality of the predictions in the target domain, requiring molecular states or processes common to both source and target that can be learned by the predictor, reflected by latent variables. These latent variables may form a compendium of knowledge that is learned in the source, to enable predictions in the target; usually, there are few, if any, labeled target training samples to learn from. Transductive learning then refers to the learning of the predictor in the source domain, transferring its outcome label calculations to the target domain, considering the same task. Inductive learning considers cases where the target predictor is performing a different yet related task as compared to the source predictor, making some labeled target data necessary. Often, there is also a need to first map the variables in the input/feature spaces (e.g. of gene names to orthologs) and/or the variables in the output/outcome spaces (e.g. by matching of labels). Transfer across omics modalities also requires that the molecular information flow connecting these modalities is sufficiently conserved. Only one of the methods for transfer learning we reviewed offers an assessment of input data, suggesting that transfer learning is unreliable in certain cases. Moreover, source domains feature their very own particularities, and transfer learning should consider these, e.g., as differences in pharmacokinetics, drug clearance or the microenvironment. In light of these general considerations, we here discuss and juxtapose various recent transfer learning approaches, specifically designed (or at least adaptable) to predict clinical (human in-vivo) outcomes based on molecular data, towards finding the right tool for a given task, and paving the way for a comprehensive and systematic comparison of the suitability and accuracy of transfer learning of clinical outcomes.

In this paper, we revisit a modified version of the classical Whitehead's theory of gravity in which all possible bilinear forms are considered to define the corresponding metric. Although, this is a linear theory that fails to give accurate results for the most sophisticated predictions of general relativity, such as gravity waves, it can still provide a convenient framework to analyze some new phenomena in the Solar System. In particular, recent development in the accurate tracking of spacecraft and the ephemerides of planetary positions have revealed certain anomalies in relation with our standard paradigm for celestial mechanics. Among them the so-called flyby anomaly and the anomalous increase of the astronomical unit play a prominent role. In the first case the total energy of the spacecraft changes during the flyby and a secular variation of the semi-major axis of the planetary orbits is found in the second anomaly. For this to happen it seems that a net energy and angular momentum transfer is taken place among the orbiting and the central body. We evaluate the total transfer per revolution for a planet orbiting the Sun in order to predict the astronomical unit anomaly in the context of Whitehead's theory. This could lead to a more deeply founded hypothesis for an extended gravity model.

The role of initial state (ISI) and final state (FSI) ion–ion interactions in heavy ion double charge exchange (DCE) reactions A(Z,N)→A(Z±2,N∓2) are studied in the context of double single charge exchange (DSCE) reactions given by sequential actions of the isovector nucleon–nucleon (NN) T–matrix. The second order DSCE reaction amplitude is investigated in momentum representation in a formulation, focused on the extraction of nuclear matrix elements under the conditions of strong initial state (ISI) and final state (FSI) interactions. In closure approximation and using the momentum representation, the reaction amplitude is finally separated into ISI/FSI distortion coefficients and reaction kernels and nuclear matrix elements. The ISI/FSI reaction kernels emerge as the result of the repeated scattering on the avoided volume, introduced by the imaginary parts of the ion–ion optical potential and acting as sinks for the quantal probability current. The closure approximation allows derive a set of induced effective two–body isotensor interactions, given by products of spin–scalar, spin–vector central and rank–2 spin–tensor interactions. The intermediate propagator plays a key role in establishing correlation between the DCE transitions in the projectile and target nucleus. The presented approach emphasizes the special features of DSCE reaction dynamics as proceeding like a system of two coupled isospin dipoles whose strengths are determined by the momentum-space form factors of the NN isovector interaction. The properties of the DSCE interaction form factors are investigated and the approach is applied to data.

Towards smart batteries for electric vehicles (EVs) smart algorithms to control battery packs, mainly reconfigurable batteries, have to be developed. This work proposes a reinforcement learning (RL) algorithm to balance the State of Charge (SoC) of reconfigurable batteries based on the topologies half-bridge and battery modular multilevel management (BM3). As RL algorithm, Amortized Q-learning (AQL) is implemented, which allows enourmous numbers of possible configurations of the reconfigurable battery to be controlled, as well as the combination of classical controlling approach and machine learning methods. This enables safety mechanisms in control. As a neural network of the AQL a Feedforward Neuronal Network (FNN) is implemented consisting of three hidden layers. The experimental evaluation using a 12-cell hybrid cascaded multilevel converter illustrates the applicability of the method to balance the SoC and maintain the balanced state during discharge. The evaluation shows a 20.3% slower balancing compared to the classical. Nevertheless, AQL shows great potential to be applied for multiobjective optimizations as an applicable RL algorithm for control in power electronics.

Exposure to quasi-electrostatic field induced currents is a hazard of live-line transmission work. These steady-state induced currents are typically less than 1 mA, and their sensory effects range from imperceptible to painful depending on the person and conditions such as contact area and duration. Permanent injury from these currents is unlikely but they can distract workers, increasing the risk of injury from falls or other dangers. Identifying contact current severity and training workers can help reduce risk of accidents. Measuring induced currents along a climbing route is time consuming and simulation is challenging because of geometric complexity of the worker, transmission structure, conductor bundles, and electric fields in the climbing space. This research explores calculation of worker contact current using a recently developed adaptation of the charge simulation method. The method uses Fourier principles to improve computational efficiency when explicitly modeling all bundle subconductors. The research also examines reasonable simplifications for modeling lattice structures and human geometry. Calculated results compare well to measured currents for a worker climbing a 400 kV lattice structure. This indicates the method is a practical option for calculating the severity of steady-state contact currents. A simple calculation is suggested for estimating these currents.

The diffusion coefficients of ions are measured in a microchip filled with a cationic charged 3D hydrogel in order to study the effect of cationic charged 3D hydrogel on the diffusivity of ions. In this study, poly-diallyl-dimethyl-ammoniumchloride (poly-DADMAC) is used to produce a 3D hydrogel. Four different fluorophores are used in the 3D hydrogel rhodamine 6G, rhodamine-BSA, fluorescein isothio-cyanate (FITC) and FITC-BSA. The rhodamine 6G and rhodamine-BSA are positively charged (cations), while fluorescein isothio-cyanate (FITC) and FITC-BSA are negatively charged (anions). Two widely used techniques which are short time diffusivity measurement technique and long time diffusivity measurement techniques are used to measure the diffusion coefficients. For the short time measurement, Fluorescence recovery after photo-bleaching (FRAP) is used by a 3D confocal microscope. For the long time measurement, fluorescence images are taken for 11 days to observe a pure diffusivity without any convective movement. As a result, the diffusivity of the cations was found to be lower than that of the anions in the cationic charged hydrogel.

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

Using machine learning or deep learning to solve the problem of garbage recognition and classification is an important application in computer vision, but due to the incomplete establishment of garbage datasets and the poor performance of complex network models on smart terminal devices, the existing garbage classification models The effect is not good.This paper presents a waste classification and identification method base on transfer learning and lightweight neural network. By migrating the lightweight neural network MobileNetV2 and rebuild it, The reconstructed network is used for feature extraction, and the extracted features are introduced into the SVM to realize the identification of 6 types of garbage. The model was trained and verified by using 2527 pieces of garbage labeled data in the TrashNet dataset, which ultimately resulted in a classification accuracy of 98.4% of the method, which proves that the method can effectively improve the classification accuracy and time and overcome the problem of weak data and less labeling. The over-fitting phenomenon encountered by small data sets in deep learning makes the model robust.

Contactless charging is evolving fast in many domains and applications such as the electrical vehicles (EV). The principle consists of transferring energy between two systems without having any electrical connection between them. This power transfer can be realized by emitting a magnetic field for Inductive Power Transfer (IPT). In the automotive domain, the application of contactless charging to supply power to the vehicle while driving is one of the solutions envisaged to solve the limited autonomy range of EV and reduced its cost but the system must comply with existing standards (e.g., allocated frequency range and radiated electromagnetic emissions), as summarized in this paper.

Conventional text style transfer (TST) methodologies primarily utilize style classifiers to segregate the content and stylistic elements of text for effective style transformation. Despite the pivotal role of these classifiers, their influence on TST techniques remains largely unexplored. This study embarks on a detailed exploration of the limitations inherent in style classifiers within current TST frameworks. We reveal that these classifiers often inadequately comprehend sentence syntax, leading to diminished performance in TST models. In response, we introduce the Syntax-Enhanced Style Transfer (SEST) model, a groundbreaking approach incorporating a syntax-sensitive style classifier. This classifier ensures that the extracted style representations robustly encapsulate syntax nuances, enhancing TST effectiveness. Rigorous evaluations across diverse TST benchmarks demonstrate that SEST significantly surpasses contemporary models in performance. Additionally, our case studies highlight SEST's proficiency in producing syntactically coherent sentences that aptly retain original content.

In this review, photoinduced electron transfer processes in specifically designed assembled ar-chitectures have been investigated on the basis of recent results reported from our laboratories. A convenient and useful way to study these kinds of systems has been described in order to under-stand the rules that drive to a light induced charge separation and its subsequent decay to the ground state, also with the aim of offering a tutorial for young researchers. Assembled systems of covalent or supramolecular nature have been presented and some functional multicomponent systems for the conversion of light energy into chemical energy have been discussed.

The paper concludes the first research on mouth-based Emotion Recognition (ER), adopting a Transfer Learning (TL) approach. Transfer Learning results paramount for mouth-based emotion ER, because a few data sets are available, and most of them include emotional expressions simulated by actors, instead of adopting a real-world categorization. Using TL we can use fewer training data than training a whole network from scratch, thus more efficiently fine-tuning the network with emotional data and improving the convolutional neural network accuracy in the desired domain. The proposed approach aims at improving the Emotion Recognition dynamically, taking into account not only new scenarios but also modified situations with respect to the initial training phase, because the image of the mouth can be available even when the whole face is visible only in an unfavourable perspective. Typical applications include automated supervision of bedridden critical patients in an healthcare management environment, or portable applications supporting disabled users having difficulties in seeing or recognizing facial emotions. This work takes advantage from previous preliminary works on mouth-based emotion recognition using CNN deep-learning, and has the further benefit of testing and comparing a set of networks on large data sets for face-based emotion recognition well known in literature. The final result is not directly comparable with works on full-face ER, but valorizes the significance of mouth in emotion recognition, obtaining consistent performances on the visual emotion recognition domain.

Structure based biological and chemical properties of 4-(carboxyamino)-benzoic acid has been studied by quantum chemical methods. The revamped geometric structure and its quantum chemical parameters were obtained by DFT-B3LYP/6-311G method. Normal mode analysis is performed to assign the fundamental vibrational frequencies as per the potential energy distribution (PED) by using the VEDA program. Simulation of IR and Raman spectral patterns are observed by refinement of scale factors. TD-DFT approach is used to explore the excited states of molecule and prediction of electronic absorption spectra. NMR chemical shifts of the molecule are determined by the gauge independent atomic orbital method. The molecular docking is performed to recognize the binding energy of the ligand with the dynamic site of protein. In our docking analysis, the protein 5DT6 shows the best results than other three proteins which could be used for further analysis. Further inter and intra molecular interactions, electrophilic, nucleophilic and chemical reactivity sites are found by molecular electrostatic potential, HOMO-LUMO and Global chemical reactivity descriptors. Thermodynamic property of the title compound is also reported. The determined quantum chemical parameters show high reactivity and the dipole moment was sufficiently high enough to induce nonlinear characteristics which are required for applications in optoelectronic devices.

The study of interactions between polyelectrolytes (PE) and surfactants is of great interest for both fundamental and applied research. These mixtures can represent, for example, models of self-assembly and molecular organization in biological systems, but they are also relevant in industrial applications. Amphiphilic block polyelectrolytes represent an interesting class of PE, but their interactions with surfactants have not been extensively explored so far, most studies being restricted to non-associating PE. In this work, interactions between an anionic amphiphilic triblock polyelectrolyte and different types of surfactants bearing respectively negative, positive and no charge, are investigated via surface tension and solution rheology measurements for the first time. It is evidenced that the surfactants have different effects on viscosity and surface tension, depending on their charge type. Micellization of the surfactant is affected by the presence of the polymer in all cases; shear viscosity of polymer solutions decreases in presence of same charge or nonionic surfactants, while the opposite charge surfactant cause precipitation. This study highlights the importance of the charge type, and the role of the associating hydrophobic block in the PE structure, on the solution behavior of the mixtures. Moreover, a possible interaction model is proposed, based on the obtained data.

The purpose of this paper is to propose a novel transfer learning regularization method based on knowledge distillation. Recently, transfer learning methods have been used in various fields. However, the problems such as knowledge loss still occur during the process of transfer learning to a new target dataset. To solve these problems, there are various regularization methods based on knowledge distillation techniques. In this paper, we propose a transfer learning regularization method based on feature map alignment used in the field of knowledge distillation. The proposed method is composed of two attention based submodules: self-pixel attention (SPA) and global channel attention (GCA). The self-pixel attention submodule utilizes both the feature maps of the source and target models, so that it provides an opportunity to jointly consider the features of the target and the knowledge of the source. The global channel attention submodule determines the importance of channels through all layers, unlike the existing methods that calculate these only within a single layer. Accordingly, transfer learning regularization is performed by considering both the internal of each single layer and the depth of the entire layer. Consequently, the proposed method using both of these submodules showed overall improved classification accuracy than the existing methods in classification experiments on commonly used dataset.

We aimed to investigate the clinical results following poor-quality embryo transfer and the parameters to foresee the prognosis. In this study, 2123 cycles that had day 3 and day 5 single-fresh embryo with a poor-quality embryo transfers and a good-quality embryo transfers were compared. The cycles according to transfer day were evaluated by conducting a subgroup analysis. The correlation between all the obtained demographic characteristics, controlled ovarian stimulation parameters and cycle results were analysed. Clinical pregnancy was established in 53 patients that underwent transfer in the poor-quality embryo group (14.9%). Of these patients, 36 had live birth (live birth rate per clinical pregnancy 67.9%). In cleavage-stage embryos, live birth rates per clinical pregnancy were higher in poor-quality blastocyst transfer. When analysing the factors affecting live births in poor-quality embryo group, as the total gonadotropin dose increases, the probability of live birth decreases, as in the probability of hCG positivity. In conclusion; although the probability of pregnant is low, when clinical pregnancy is established, there is a high chance of having a live birth after poor-quality embryo transfers. This could be regarded as an acceptable option in cycles when only poor-quality embryos were available.

Indoor localization (IL) is a significant topic of study with several practical applications. The area of IL has evolved greatly in recent years due to the introduction of numerous technologies such as WiFi, Bluetooth, cameras, and other sensors. Despite the growing interest in this field, there are numerous challenges and drawbacks that must be addressed to develop more accurate and sustainable systems for IL and its real-life applications. This review study gives an in-depth look into IL, covering the most promising artificial intelligence-based and hybrid strategies that have shown excellent potential in overcoming some of the limitations of classic methods. In addition, the paper investigates the significance of high-quality datasets and evaluation metrics in the design and assessment of IL algorithms. Furthermore, this overview study emphasizes the crucial role that machine learning techniques, such as deep learning and transfer learning, play in the advancement of IL. A focus on the importance of IL and the various technologies, methods, and techniques that are being used to improve it. Finally, The survey highlights the need for continued research and development to create more accurate and scalable techniques that can be applied across a range of industries, such as evacuation-egress routes, hazard-crime detection, smart occupancy-driven energy reduction and asset tracking and management.

Demand for development of the convergence industry, research studies on electrical conductivity, thermal characteristics, semiconductors, motors, and batteries using special materials have come to the fore. Meanwhile, molybdenum (Mo) exhibits relatively small inorganic qualities, and the thermal conductivity rate is applied to various fields. In this study, in-depth characteristics were considered regarding the concentration of thermal characteristics, IR car terminal characteristics, and IR ve-hicles. This study calculated each phase temperature of the molybdenum sputtered specimens in the steady state according to the heat transfer theory. When the molybdenum-sputtered fabric’s metal layer pointed to the outside air, the heat transfer rate (Q) was high at 5748.3W, In contrast, if the molybdenum sputtered film’s metal layer of the pointed toward the heat source, the heat transfer rate (Q) was low at 187.1W. As a result of measuring the IR transmittance, the infrared transmit-tance of the molybdenum sputtering-treated sample was significantly reduced compared to the untreated sample. In the case of untreated samples, the transmittance ranged from 92.7 to 42.0%. When only the cross part was treated with molybdenum sputtering and the molybdenum surface was directed toward the IR irradiator, the IR transmittance was 66.8~0.7%. It is believed that the molybdenum sputtering polyamide samples produced in this study can be applied to multifunc-tional military wear, biosignal detection sensors, semiconductor products, batteries, etc., by utilizing excellent electrical properties, stealth functions, IR blocking properties, and lightness for infrared thermal imaging detectors.

Skin cancer is an uncommon but serious malignancy. Dermoscopic images examination and biopsy are required for cancer detection. Deep learning (DL) is extremely effective in learning characteristics and predicting malignancies. However, DL requires a large number of images to train. Image augmentation and transferring learning were employed to overcome the lack of images issue. In this study we divided images into two categories: benign and malignant. To train and test our models, we used the public ISIC 2020 database. Melanoma is classified as malignant in the ISIC 2020 dataset. Along with categorization, the dataset was studied to demonstrate variation. The performance of three top pretrained models was then benchmarked in terms of training and validation accuracy. Three optimizers were employed to optimize the loss: RMSProp, SGD, and ADAM. Using ResNet, VGG16, and MobileNetV2, we obtained training accuracy of 98.73%, 99.12%, and 99.76%, respectively. Using these three pretrained models, we attained a validation accuracy of 98.39%.

The organo-catalyzed enantioselective benzylation reaction of α-trifluoromethoxy indanones afforded α-benzyl-α-trifluoromethoxy indanones with a tetrasubstituted stereogenic carbon center in excellent yield with moderate enantioselectivity (up to 57% ee). Cinchona alkaloid-based chiral phase transfer catalysts were found to be effective for this transformation, and both enantiomers of α-benzyl-α-trifluoromethoxy indanones were accessed, depended on the use of cinchonidine and cinchonine-derived catalyst. The method was extended to the enantioselective allylation reaction of α-trifluoromethoxy indanones to give the allylation products in moderate yield with good enantioselectivity (up to 76% ee).

Transfer factor is the name given to material derived from activated lymphocytes that is probably composed of a complex of a peptide and a short segment of RNA and which has the reported ability to transfer specific T cell immunity to uncommitted lymphocytes. Many independent groups around the world reported isolating transfer factors between 1955 and 1990 and demonstrating their ability to transfer passive immunity from one animal or individual to another, often within 24 hours of inoculation. Such activity is potentially revolutionary both in making T cell vaccines readily manufacturable and also because the existence of transfer factors would undermine the basic assumptions of the clonal selection theory, which currently dominates immunological theory. Unfortunately, lack of the microanalytical and synthetic techniques required to properly identify transfer factors, combined with safety factors associated with it derivation from blood sources susceptible to HIV and prion infections, put an end to transfer factor research after 1990. This paper reviews the evidence supporting transfer factor activity and suggests that this potentially revolutionary concept be resurrected and subjected to renewed scrutiny in light of CRISPR-Cas mechanisms and because of its potential to make possible T cell vaccination and provide a novel basis for understanding immunological function.