NMR spin relaxation times have been an instrumental tool in deciphering the local en-vironment of ionic species, the various interactions they engender and the effect of these interactions on their dynamics in conducting media. Of particular importance has been their application in studying the wide range of electrolytes for energy storage, on which this chapter is based. Here we highlight some of the research carried out on electrolytes in recent years using NMR relaxometry techniques. Specifically, studies on liquid electro-lytes, such as ionic liquids and organic solvent; on semi-solid-state electrolytes, such as ionogels and polymer gels, and solid electrolytes such as glasses, glass ceramics and polymers. Although this chapter focuses on a small selection of materials, we believe they demonstrate the breadth of application and the invaluable nature of NMR relaxometry.

An atomic-scale approach is employed to simulate the formation of precipitates with different lattice misfits in the early stages of aging of supersaturated aluminum alloys. Simulation results reveal that the increase of lattice misfit could significantly promote the nucleation rate of precipitates, which results in a larger number and smaller size of the precipitates. The morphologies of the precipitates also vary with the degree of lattice misfit. Moreover, the higher the lattice misfit, the earlier the nucleation of the second phase occurs, which can substantially inhibit the movement of dislocations. The research on the lattice misfit of precipitation can provide theoretical guidance for the design of high-strength aluminum alloy.

Spin valves with a synthetic antiferromagnet were fabricated by magnetron sputtering. It was shown that the fabricated spin valves had perfect microstructure of layers and smooth interfaces, therefore RKKY interaction dominates in coupling of ferromagnetic layers separated by a copper spacer. Rhombus-shaped microobjects were fabricated from a single spin valve film. The thermomagnetic treatment procedure was found, to form unidirectional anisotropy in the microobject so, that the values of the exchange bias fields in the rhombus’ nonparallel sides were opposite in sign. For the synthetic antiferromagnet CoFeNi/Ru/CoFeNi the difference between ferromagnetic layers thicknesses was found, at which the thermomagnetic treatment forms the same exchange bias all over the rhombus’ side. The sensor element was fabricated in which each side of the rhombus was a shoulder of a Wheatstone bridge. After the thermomagnetic treatment procedure each shoulder worked as an active magnetosensitive element, thus the device operated as the full Wheatstone bridge. The sensor output has the shape of a step, high sensitivity to field change and significant magnetic hysteresis. Such characteristics are suitable for switching devices.

Abstract: I present a generalization of quantum electrodynamics which includes Diracmagnetic monop oles and the Salam magnetic photon. This quantum electromagnetodynamics has many attractive features. (1) It explains the quantization of electric charge. (2) It describes symmetrized Maxwell equations. (3) It is manifestly covariant. (4) It describes local four-potentials. (5) It avoids the unphysical Dirac string. (6) It predicts a second kind of electromagnetic radiation which can be veried by a tabletop experiment. An eect of this radiation may have been observed by August Kundt in 1885. Furthermore I discuss a generalization of General Relativity which includes Cartan's torsion. I discuss the mathematical denition, concrete description, and physical meaning of Cartan's torsion. I argue that the electric-magnetic duality of quantum electromagnetodynamics is analogous to the spin-mass duality of Einstein-Cartan theory. A quantum version of this theory requires that the torsion tensor corresponds to a spin-3 boson called tordion which is shown to have a rest mass close to the Planck mass. Moreover I present an empirically satised fundamental equation of unied eld theory which includes the fundamental constants of electromagnetism and gravity. I conclude with the remark that the concepts presented here require neither Grand Unication nor supersymmetry.

Metal nanoparticles supporting plasmons are widely used to enhance electromagnetic fields, resulting in strong light-matter interactions at the nanoscale in a diverse range of applications. Recently, it has been shown that when metal nanorods are periodically arranged with proper lattice periods, surface lattice resonances (SLRs) can be excited and near fields can be greatly enhanced over extended volumes. In this work, we report significant near field enhancement over even larger volumes by placing the metal nanorod array within a Fabry-Pérot (F-P) microcavity. Results show that taking advantage of strong coupling between the SLR and the photonic F-P resonances, the electric field intensity of the bonding split mode can be enhanced by up to 1935 times, which is about three times of the enhancement of the SLR, and the greatly enhanced field can extend over most of the F-P microcavity. We further show that the F-P resonances of both odd and even orders can strongly couple to the SLR by varying the nanorods position from the middle of the microcavity. We expect that the proposed plasmonic-photonic coupling system will find promising applications in nanolasers, nonlinear optics and sensing.

There has been observational evidence about spin axes of quasars in large quasar groups correlated over hundreds of Mpc. This is seen in the radio spectrum as well as in the optical range. There is not yet a satisfactory explanation of this "spooky" alignment. This alignment cannot be explained by mutual interaction at the time that quasars manifest themselves optically. A cosmological explanation could be possible in the formation of superconducting vortices (cosmic strings) in the early universe, just after the symmetry-breaking phase of the universe. We gathered from the NASA/IPAC and SIMBAD extragalactic databases the right ascension, declination, inclination, position angle and eccentricity of the host galaxies of 3 large quasar groups to obtain the azimuthal and polar angle of the spin vectors. The alignment of the azimuthal angle of the spin vectors of quasars in their host galaxy is confirmed in the large quasar group U1.27 and compared with two other groups in the vicinity, i.e., U1.11 and U1.28. It is well possible that the azimuthal angle alignment fits the predicted azimuthal angle dependency in the theoretical model of the formation of general relativistic superconducting vortices, where the initial axially symmetry is broken just after the symmetry breaking of the scalar-gauge field.} \keyword{quasar groups; alignment spin vectors; host galaxy; cosmic strings; symmetry breaking; scalar-gauge field.

: The silicon single crystals for semiconductor application is usually grown by Czochralski (CZ) method. This paper researches 300mm silicon Czochralski (CZ) crystal growth with CUSP magnetic field for IGBTs substrate application. The different positions of Zero-Gauss plane (ZGP) under CUSP magnetic field are simulated and compared to numerical analysis, investigated melt convection, melt flow velocity near to quartz crucible wall, diffusion boundary layer and effect of initial oxygen concentration in the silicon crystal, and the shape of solid/liquid interface was discussed. The results show that the change of the ZGP of the CMF mainly affects the convection in the melt, which leads to the difference of the thickness of the boundary layer near to the wall of the quartz crucible, and was found to be the key to reduce the oxygen dissolution from the crucible wall and oxygen diffuse into the crystal, along with the differences in the shape of the crystal-melt interface. In addition, we have carried out actual industrial single crystal production under the three configurations. The results show that the experimental data of oxygen content and shape of the crystal-melt interfaces in silicon crystal are consistent with the numerical results.

The X-ray induced spin crossover transition of an Fe(II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior that is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

Functional dependence of the axial zero-field splitting parameter D with respect to a properly chosen geometrical parameter (Dstr) in metal complexes is termed the Magnetostructural D-Correlation. In mononuclear hexacoordinate Ni(II) complexes with the ground electronic term 3B1g (3A2g in the regular octahedron) it proceeds along two intercepting straight lines allowing to predict the sign and magnitude of the D-parameter by knowing the X-ray structure alone; Dstr is constructed from the metal-ligand bond lengths. In hexacoordinate Co(II) complexes it is applicable only in the segment of the compressed bipyramid where the ground electronic term 4B1g is orbitally non-degenerate so that the spin Hamiltonian formalism holds true. The D vs Dstr correlation is strongly non-linear and it is represented by a set of decreasing exponentials. In tetracoordinate Co(II) complexes, on the contrary, the angular distortion from the regular tetrahedron is crucial so that the appropriate structural parameter Dstr is constructed of bond angles. All of these empirical correlations originate in the electronic structure of metal complexes that can be modelled by the generalized crystal-field theory. As the barrier to spin reversal in the single-molecule magnets is proportional to the D-value, for a rational tuning and/or prediction of the single-molecule magnetic behavior knowledge/prediction of the D-parameter is beneficial. In this review, we present the statistical processing of an extensive set of structural and magnetic data of Co(II) and Ni(II) complexes, which were published over the past 15 years. Magnetostructural D-correlations defined for this data set are reviewed in detail.

As Cybercrimes continue to rise, researchers and industry players have continued to work hard to come up with solutions that could reduce and possibly eradicate these criminalities. This research has been able to discover the major factor that usually causes people to fall prey to these cyber criminals. This was why a school of thought came up with the Zero Trust Access model to strengthen the network framework. While previous network assets relied on the "trust but verify" philosophy, this technology's primary tenet is "never trust, always verify," which applies to every user and device connected to the network. This study interrogated the existing network models of the Integrative Trust Model (ITM) and Zero Trust Access (ZTA) in addition to the trust model (TA) to understand their concepts, implementation needs, strengths, and shortcomings. This made it possible for the study to establish the position of the ZTA model in repositioning the network security architectures vis-a-vis protecting the users

We propose a new theory beyond the standard model of elementary-particle physics. Employing the concept of a quantized spacetime, our theory demonstrates that the zero-point energy of the vacuum alone is sufficient to create all the fields, including gravity, the static electromagnetic field, and the weak and strong interactions. No serious undetermined parameters are assumed. Furthermore, the relations between the forces at the quantum-mechanics level is made clear. Using these relations, we quantize Einstein’s gravitational equation: Beginning with the zero-point energy of the vacuum, and after quantizing Newtonian gravity equation, we combine the energies of a static electromagnetic field and gravity in a quantum spacetime. Applying these results to the Einstein gravity equation, we substitute the energy density derived from the zero-point energy in addition to redefining differentials in a quantized spacetime. This is how we derive the quantized Einstein gravitational equation without assuming the existence of macroscopic masses. For the weak interaction, by considering plane-wave electron and the zero-point energy, we obtain a wavefunction that represents a β collapse. In this process, from a different point of view than Weinberg-Salam theory, we derive the masses of the W and Z bosons and the neutrino, and we calculate the radius and lifetime of the neutron. For the strong interaction, we previously reported an analytical theory for calculating the mass of a proton by providing a specific linear attractive potential obtained from the zero-point energy, which agrees well with the measurements. In the present study, we further calculate the strong interaction between two nucleons, i.e., the mass of the pi-meson. The resulting calculated quantities agree with the measurements, which verifies our proposed theory.

While the knowledge about the development of understanding positive integers is rapidly growing, the development of understanding zero is not well-known. Here we tested several components of preschoolers’ understanding zero: whether they can use empty sets in numerical tasks, whether they can use empty sets soon after they understand the cardinality principle, whether they know what the word “zero” refers to, and whether they categorize zero as a number. The results show that preschoolers can handle empty sets in numerical tasks as soon as they understand the cardinality principle or even earlier, and some of them know that these sets are labeled as “zero.” However, they are unsure whether zero is a number. These results identify three components of knowledge about zero: operational knowledge, linguistic knowledge, and meta knowledge. To account for these results we propose that preschoolers might understand numbers as the properties of items or objects in a set. In this view, zero cannot be a number, because an empty set does not include any items, and the missing items cannot have any property, excluding also the number property. This model might explain why zero is handled correctly in numerical tasks, while it is not regarded to be a number.

Zero-shot learning ability robotics enables robots to generalize their knowledge and perform tasks for which they have not been explicitly trained. This ability is extremely helpful because in classic learning approaches, robots are trained on specific tasks and require extensive data and labeled examples to perform accurately. However, in real-world scenarios, robots often encounter new or unseen tasks that were not part of their training data. We briefly survey works in this area to give the reader a perspective about progresses in this area.

While there is a coordinated effort around reaching zero dose children and closing existing equity gaps in immunization delivery, it’s important that there is agreement and clarity around how ‘zero dose status’ is defined and what is gained and lost by using different indicators for zero dose status. There are two popular approaches used in research, program design, and advocacy to define zero dose status: one uses a single vaccine to serve as a proxy for zero dose status, while another uses a subset of vaccines to identify children who have missed all routine vaccines. We provide a global analysis utilizing the most recent publicly available DHS and MICS data to compare the number, proportion, and profile of children 12 to 23 months who are ‘penta-zero dose’ (have not received the pentavalent vaccine), ‘truly’ zero dose (have not received the BCG, polio, pentavalent, and measles vaccines), and ‘misclassified’ zero dose children (those who are penta-zero dose but have received at least one other vaccine). Our analysis includes 194,829 observations from 82 low- and middle-income countries. Globally, 14.2% of children are penta-zero dose and 7.5% are truly zero dose, suggesting that 46.5% of penta-zero dose children have had at least one contact with the immunization system. While there are similarities in the profile of children that are penta-zero dose and truly zero dose, there are key differences between the proportion of key characteristics among truly zero dose and misclassified zero dose children, including access to maternal and child health services. By understanding the extent of connection zero dose children may have with the health and immunization system and contrasting it with how much the use of a more feasible definition of zero dose may underestimate the level of vulnerability in the zero dose population, we provide insights that can help immunization programs design strategies that better target the most disadvantaged populations. If the vulnerability profiles of the truly zero dose children are qualitatively different from that of the penta zero dose children, then failing to distinguish the truly zero dose populations, and how to optimally reach them, may lead to the development of misguided or inefficient strategies for vaccinating the most disadvantaged population of children.

The zero-catch problem is a key issue in CPUE(Catch Per Unit Effort) standardization, and previous studies have treated all zero-catch data uniformly, but this actually loses some correctly-labeled samples. On the other hand, for the main catches with few zero-catch samples, the problem of low performance of fisheries forecasting remains unsolved even though the forecasting model structure is updating constantly, since we cannot know whether the samples are correctly recorded. In this paper, we propose a method based on confident learning theory to detect anomalous samples in the datasets and unify zero-catch and non-zero samples as noise through an overarching framework of learning with noisy labels, which reveals the heterogeneity among zero-catch samples (as well as among non-zero samples) and the homogeneity between zero-catch samples and non-zero samples. Using three species of tuna in the tropical Atlantic Ocean with the spatial resolution of 0.5 ◦ × 0.5 ◦ and time resolution of days from 2016 to 2019 as experimental material, performance on all three classical machine learning models(Random forest, Support Vector Machine and XGBoost) is significantly improved compared to each baseline.This confirms that we propose a self-adaptive, effective method for detecting and repairing anomalous samples in the fishery dataset.

Zero-dose children, or children who have not received any routine vaccination, are a priority population for global health policy makers as these children are at high risk of mortality from vaccine-preventable illnesses. We conducted a narrative review to identify potential interventions, both within and outside of the health sector, to reach zero-dose children. We reviewed peer-reviewed and grey literature and identified 59 relevant resources. Additionally, we interviewed six key informants to enhance synthesis of our findings. Data were organized into three priority settings: (1) urban slums, (2) remote or rural communities, and (3) conflict settings. We found that zero-dose children in the three-priority settings face differing barriers to vaccina-tion and, therefore, require context-specific interventions, such as leveraging slum health commit-tees for urban slums or integrating with existing humanitarian response services for conflict set-tings. Three predominant themes emerged for grouping the various interventions: (1) community engagement, (2) health systems strengthening and integration, and (3) technological innovations. The barriers to reaching zero-dose children are multifaceted and nuanced to each setting, there-fore, no one intervention is enough. Technological interventions especially must be coupled with community engagement and health systems strengthening efforts. Evaluations of the suggested interventions are needed to guide scale up, as the evidence-base around these interventions is rel-atively small.

This paper analyses the viability of different solutions to passively augment the axial stiffness of a horizontal axis radial levitation passive magnetic bearing (PMB) with topology previously studied. The zero-field cooling (ZFC) of high-temperature superconductor (HTS) bulks promotes higher magnetic impulsion and levitation forces and lower electromagnetic losses than with the field-cooling (FC), but on the other hand, the guiding stability is much lower than with FC. Because of stability reasons, FC was adopted in most superconducting maglev systems. The trend of this research group has been to develop an HTS ZFC horizontal axis radial levitation PMB presenting notable levitation forces with reduced electromagnetic losses, defined by a topology that creates guiding stability. Previous work has shown that even optimizing the bearing geometry to maximize magnetic guidance forces, could not be enough to guarantee the axial stiffness required for many applications. First, the extent to which guidance forces are augmented by increasing the number of HTS bulks in the stator is evaluated. Then, the axial stiffness augmentation by passively adding two limiting permanent magnet (PM) rings is evaluated. Results show that the axial stiffness is highly augmented by adding limiting PM rings with no significant additional investment. This change enables using the studied ZFC superconducting PMB in high-precision axial stability applications, such as precision gyroscopes, horizontal axis propellers and turbines.

proposal for a fundamental theory is described in which classical and quantum physics as a representation of the universe as a gigantic dendrogram are unified. The latter is the explicate order structure corresponding to the purely number-theoretical implicate order structure given by p-adic numbers. This number field was zero-dimensional, totally disconnected, and disordered. Physical systems (such as electrons, photons) are sub-dendrograms of the universal dendrogram. Measurement process is described as interactions among dendrograms; in particular, quantum measurement problems can be resolved using this process. The theory is realistic, but realism is expressed via the the Leibnitz principle of the Identity of Indiscernible. The classical-quantum interplay is based on the degree of indistinguishability between dendrograms (in which the ergodicity assumption is removed). Depending on this degree, some physical quantities behave more or less in a quantum manner (versus classic manner). Ideologically, our theory is very close to Smolin’s dynamics of difference and Rovelli’s relational quantum mechanics. The presence of classical behavior in nature implies a finiteness of the Universe-dendrogram. (Infinite Universe is considered to be purely quantum.) Reconstruction of events in a four-dimensional space type is based on the holographic principle. Our model reproduces Bell-type correlations in the dendrogramic framework. By adjusting dendrogram complexity, violation of the Bell inequality can be made larger or smaller.

In our previous papers [1,3], using only the concepts of the zero-point energy and quantized space–times, all the fields including gravity were explained. However, the previous papers had the following limitations: First, the concept of the quantized space-time must be experimentally confirmed. Second, we should clarify the meaning of the quantized Einstein’s gravity equation, which is derived in [1]. Moreover, in another paper [2], we succeeded in describing the neutrinos’ self-energy and their oscillations. However, this paper assumes the rest energy of 3-leptons in advance, which is why we needed to uncover the reason why leptons have 3-generations. As mentioned, using the concepts of the zero-point energy and quantized space–times, we derived the quantized Einstein’s gravity equation in our previous paper [1]. The paper provides an analytical solution of this equalized Einstein’s equation, which implies the conservation of angular momentum in terms of quantized space–times. Employing this solution and without the standard big bang model, a unique form of acceleration equation for the acceleration-expansion universe is derived. Moreover, the temperature of the cosmic microwave background (CMB) emission is also obtained. Further, this solution results in an analytical (not numerical) derivation of the gravity wave. Moreover, based on the configuration of quantized space–times in terms of both electric and magnetic fields, we analytically attempted to calculate every equation in terms of electromagnetic and gravity fields, using the solution of the quantized Einstein’s gravity equation. As a result of this theory, first the calculated acceleration and temperature of CMB emission agree with the measurements. Furthermore, the analytical solution of the quantized Einstein’s gravity equation resulted in all the laws of electromagnetic and gravity fields in addition to the analytically derived gravity wave, which agrees well with the recent measurements. Moreover, the calculations of the energies in the basic configuration of the quantized space–times resulted in all 3-leptons’ rest energies. Considering this basic configuration is uniformly distributed everywhere in the universe, we can conclude that τ-particles or static magnetic field energy derived from the basic configuration of the quantized space–times is the identity of dark energy, which also distributes uniformly in the universe.

Energy market price volatility and an upward trajectory of prices per unit of electricity have sent all industrial sectors and many economies to the brink of recession. Alongside the urgent need for decarbonisation of all industries, achieving a higher level of energy independence across all sectors seems imperative. A multi-disciplinary approach with a proposed system of CO₂ emissions reduction and capture technologies has the potential for short-term emissions reduction to near-zero in absolute terms. The findings of this research showed CO₂ emissions reduction of ~30% from 977t of CO_2e to 684t in one single blast furnace production cycle, by switching the energy provider generating energy exclusively from renewable sources. Replacing coal with biomass (BECCS), resulted in an additional reduction of ~30%, to CO_2e to 479t CO_2e. Installing solar PV panels for energy generation on site resulted in a further ~30% reduction, to 335 tonnes CO_2e. Finally, the installation of CO₂ filters reduced the CO₂ emissions to near-zero. Simultaneously, energy-saving and process improvement measures implementation (up to 60% efficiency increase), excess heat recovery (<30% of energy savings), and retrofitting renewable energy technology resulted in an energy independence of 88%. Short-term engineering solutions, partly subsidised in the UK, are readily available.

Recently, the focus of entity linking research has centered on the zero-shot scenario, where the entity mention to be labeled at the time of testing was never observed during the training phase or may belong to a different domain than the source domain. Current studies have used BERT as the base encoder as it effectively establishes distributional links between source and target domains. The currently available negative sampling methods all use an extractive approach, which makes it difficult for the models to learn diverse and more challenging negative samples. To address this problem, we propose a generative negative sampling method, Adaptive_mixup_hard, which generates more difficult negative entities by fusing the features of both positive and negative samples on top of hard negative sampling and introduces a transformable adaptive parameter W to increase the diversity of negative samples. Next, we fuse our method with the Biencoder architecture and evaluate its performance under three different score functions. Ultimately, experimental results on the standard benchmark dataset Zeshel demonstrate the effectiveness of our method.

The global agricultural sector is increasingly pressured to adopt sustainable practices and reduce its environmental impact. In this context, greenhouses play a crucial role in enabling year-round crop production, ensuring food security, and minimizing reliance on traditional open-field farming. However, the energy consumption associated with greenhouse operations poses a significant challenge to achieving sustainability goals. As a result, there is a growing emphasis on transitioning greenhouses towards near-zero energy consumption. Near-zero energy consumption in greenhouses refers to the ambitious objective of minimizing energy usage to the greatest extent possible while maintaining optimal growing conditions for crops. This goal encompasses reducing energy consumption for heating, cooling, lighting, and other operational needs, as well as exploring renewable energy sources to power greenhouse operations. This review article offers a comprehensive overview of greenhouse energy consumption, with the main goal of analyzing the present situation, identifying key challenges, exploring potential opportunities, and proposing future perspectives for decreasing energy usage in greenhouse environments. As the focus on sustainable agricultural practices grows, the need to reduce energy consumption in greenhouses becomes increasingly important. The review critically examines current technological models and strategies applied in smart greenhouse applications, as well as the monitoring of microclimatic conditions inside the greenhouse, encompassing factors such as temperature, humidity, CO2 levels, soil quality, and crop cultivation. Moreover, it aims to present existing literature that investigates the advancement of greenhouses toward achieving significant reductions in energy consumption.

Epsilon-near-zero nanoantennas can be used to tune the far-field radiation pattern due to their exceptionally large intensity-dependent refractive index. Here, we propose hybrid optical antenna based on indium tin oxide (ITO) to optically tune the deflection of radiation. In particular, a hybrid structure antenna of ITO and dielectric material, which makes the deflection angle changes 17 ∘ as incident intensities increases. Finally, the array of ITO or hybrid nanodisks can enhance the unidirectionality to be needle-like, with the angular beam width α< 8∘ of main lobe. The deflection angle of radiation pattern response with needle-like lobe pave the way for further studies and applications in beam steering and optical modulation where dynamic control of the nanoantennas is highly desirable.

Through history, particular attention has been paid of the study of the relationship between the energy use and the city structure. Improving energy efficiency in modern agglomerations is the most promising means to mitigate climate change and its impacts. In this current context of globalisation, European Union proposes initiatives and policy targets to rethink the urban development strategies towards the ‘zero energy objectives’. Providing a methodological approach with a simulation district analysis, the present article summarizes how the ‘zero energy’ challenge is analyzed in an existing district (Epinlieu) to articulate the users’ requirements in energy. This study contributes to the scientific discussion of the districts’ urban structure and energy planning by establishing a linkage among the beneficial influence of the KPIs of the districts’ form to increase their energy efficiency and its application in a real case study in Belgium.

As we all know, contemporary electromagnetic theory is based on the macroscopic electromagnetic theory established by the 19th century. Because of the lack of microscopic cognition in that era, various electromagnetic phenomena could only be explained and described at the macro level, and their origins could not be explained at the micro level. And because of the microscopic understanding of atomic physics in the 20th century, new progress has been made. Considering that it is now the 21st century, this paper attempts to establish a new theory of microscopic interpretation of classical electromagnetic theory based on the new cognition of atomic physics in the 20th century. Starting from the general assumption, the current will be interpreted as the momentum flow produced by the directed collision between electrons; the charge will be interpreted as a form of expression of electron motion; the voltage is interpreted as the potential difference (energy level difference) of the electron orbit. In the end, this paper successfully developed a new microscopic electromagnetic theory by introducing microscopic atomic physics and rigid body mechanics models to Maxwell's macroscopic electromagnetic theory.

In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum differential games where the players' state dynamics solve backward stochastic differential equations (BSDEs) that depend on the marginal distributions of player states. Players try to minimize their individual cost functionals, also depending on the marginal state distributions. Under some regularity conditions, we derive necessary and sufficient conditions for existence of Nash equilibria. Player behavior is illustrated by numerical examples, and is compared to a centrally planned solution where the social cost, the sum of player costs, is minimized. The inefficiency of a Nash equilibrium, compared to socially optimal behavior, is quantified by the so-called price of anarchy. Numerical simulations of the price of anarchy indicate how the improvement in social cost achievable by a central planner depends on problem parameters.

Leveraging the open-world understanding capacity of large-scale visual-language pre-trained models has become a hot-spot in point cloud classification. Recent approaches rely on transferable visual-language pre-trained models, classifying point clouds by projecting them into 2D images and evaluating consistency with textual prompts. These methods benefit from the robust open-world understanding capabilities of visual-language pre-trained models and require no additional training. However, they face several challenges summarized as prompt ambiguity, image domain gap, view weights confusion, and feature deviation. In response to these challenges, we propose PointBLIP, a zero-training point cloud classification network based on the recently introduced BLIP-2 visual-language model. PointBLIP is adept at processing similarities between multi-images and multi-prompts. We separately introduce a novel method for point cloud zero-shot and few-shot classification, which involves comparing multiple features to achieve effective classification. Simultaneously, we enhance the input data quality for both the image and text sides of PointBLIP. In point cloud zero-shot classification tasks, we outperform state-of-the-art methods on three benchmark datasets. For few-shot classification tasks, to the best of our knowledge, we present the first zero-training few-shot point cloud method, surpassing previous works under the same conditions and showcasing comparable performance to full-training methods.

Background: Manoka Health District (MHD), an enclaved archipelago district in Cameroon, is home to about 1,732 under-2 children. Over 90% of these children have not received a single dose of any vaccine. In this paper, we explored the reasons for the high proportion of zero-dose children in this district so as to generate information that policymakers can use to develop context-specific interventions to boast coverage for routine immunization (RI) in this remote fishing island Methodology: We collected qualitative data via key informant interviews (KII) and focused group discussions (FGD) and analyzed it using thematic analysis. Participants for KII were selected using purposive sampling, and a snowballing approach helped to recruit an intermixed population of locals and immigrants for FGDs. Results: MHD is a hard-to-reach zone with a lone health facility that lack a functional cold chain equipment to cover the 47 islets of the district. Diurnal floods, long distance, sea turbulence, infrastructural and resource constraints, and immigrant population without residence permits hinders optimal childhood vaccination. Insufficient community health workers and lack of proper community engagement with feedback loops hamper effective communication and vaccine uptake during campaigns and outreaches. The reasons for vaccination hesitancy included hospital-based vaccination preference over home-based vaccination, fear of post-vaccination fever, rumors, repeated postponement of the vaccination schedules, and refusal by some ethnic group leaders. Conclusion: This study revealed context-specific reasons for zero-dose childhood vaccination status in MHD. These findings should be leveraged to design tailored interventions to raise RI in MHD and similar under-vaccinated communities. Keywords: zero-dose, childhood vaccination, missed communities, Cameroon

New setting is introduced to study failed zero-forcing number and failed zero-forcing neutrosophic-number. Leaf-like is a key term to have these notions. Forcing a vertex to change its color is a type of approach to force that vertex to be zero-like. Forcing a vertex which is only neighbor for zero-like vertex to be zero-like vertex but now reverse approach is on demand which is finding biggest set which doesn’t force. LetNTG : (V,E,σ,μ) be a neutrosophic graph. Then failed zero-forcing number Z(NTG) for a neutrosophic graph NTG : (V,E,σ,μ) is maximal cardinality of a set S of black vertices (whereas vertices in V (G) \ S are colored white) such that V (G) isn’t turned black after finitely many applications of “the color-change rule”: a white vertex is converted to a black vertex if it is the only white neighbor of a black vertex. Failed zero-forcing neutrosophic-number Zn(NTG) for a neutrosophic graphNTG : (V,E,σ,μ) is maximal neutrosophic cardinality of a set S of black vertices (whereas vertices in V (G) \ S are colored white) such that V (G) isn’t turned black afterfinitely many applications of “the color-change rule”: a white vertex is converted to a black vertex if it is the only white neighbor of a black vertex. Failed zero-forcing number and failed zero-forcing neutrosophic-number are about a set of vertices which are applied into the setting of neutrosophic graphs. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs namely path-neutrosophic graphs, cycle-neutrosophic graphs, complete-neutrosophic graphs, star-neutrosophic graphs, bipartite-neutrosophic graphs, and t-partite-neutrosophic graphs are investigated in the terms of maximal set which forms both of failed zero-forcing number and failed zero-forcing neutrosophic-number. Neutrosophic number is reused in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number to compare with other vertices. Summation of three values of vertex makes one number and applying it to a comparison. This approach facilitates identifying vertices which form failed zero-forcing number and failed zero-forcing neutrosophic-number. In path-neutrosophic graphs, the set of vertices such that every given two vertices in the set, have distance at least two, forms maximal set but with slightly differences, in cycle-neutrosophic graphs, the set of vertices such that every given two vertices in the set, have distance at least two, forms maximal set. Other classes have same approaches. In complete-neutrosophic graphs, a set of vertices excluding two vertices leads us to failed zero-forcing number and failed zero-forcing neutrosophic-number. In star-neutrosophic graphs, a set of vertices excluding only two vertices and containing center, makes maximal set. In complete-bipartite-neutrosophic graphs, a set of vertices excluding two vertices from same parts makes intended set but with slightly differences, in complete-t-partite-neutrosophic graphs, a set of vertices excluding two vertices from same parts makes intended set. In both settings, some classes of well-known neutrosophic graphs are studied. Some clarifications for each result and each definition are provided. Using basic set not to extend this set to set of all vertices has key role to have these notions in the form of failed zero-forcing number and failed zero-forcing neutrosophic-number. The cardinality of a set has eligibility to form failed zero-forcing number but the neutrosophic cardinality of a set has eligibility to call failed zero-forcing neutrosophic-number. Some results get more frameworks and perspective about these definitions. The way in that, two vertices don’t have unique connection together, opens the way to do some approaches. A vertex could affect on other vertex but there’s no usage of edges. These notions are applied into neutrosophic graphs as individuals but not family of them as drawbacks for these notions. Finding special neutrosophic graphs which are well-known, is an open way to pursue this study. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Theoretical analysis into the energetics of a novel putative electromagnetic field propulsion device by the author, found that it was able to impart momenergy to the ground state of the electromagnetic field; some rest-energy of the craft was converted to kinetic energy of the craft. Electrical analysis showed that the propulsor was always a net electrical load – if the device accelerated from one frame, then deaccelerated to the original frame, both processes would consume electrical work. The aim of this paper is to look further into this sinking of high-grade electrical energy into the field ground state and to show that an even more pernicious form of 2^nd Law of Thermodynamics exists.

There are given algebraic and integral identities for a pair or a triple of plane solenoidal fields. As applications, we obtain sufficient potentiality conditions for a plane vector field. The integral identities are also important for exact a priori estimates.

The photodegradation of azithromycin present was carried out in water using H2O2 under UV irradiation. The reaction variables considered in this study were the amount of H2O2 solution and the initial concentration of azithromycin to evaluate the performance of the photodegradation process. The azithromycin degradation was not observed in the dark during stirring for 20 minutes. The study showed efficient photodegradation of azithromycin using H2O2 as an oxidant in the presence of UV irradiation. The azithromycin degradation was affected significantly by the pH of the irradiated solution. The degradation was low at an acidic pH and showed an increasing trend as the pH changed to basic. The azithromycin degradation was increased with a higher amount (higher concentration) of H2O2. The degradation of azithromycin decreased with a higher concentration of azithromycin in the reacting solution. The highest degradation of AZT was achieved in 1 hour using a 1.0 ppm AZT solution containing 3 ml of H2O2. The experimental data obtained was well-fitted to zero-order reaction kinetics. The results of this study were found to be superior when compared with those reported in the literature, with photocatalysis using nanomaterials and photolysis using irradiation and H2O2. The UV/H2O2 system was found to be quite efficient for the photodegradation of azithromycin, and this system can be applied to degrade other organic pollutants present in industrial wastewater. To this point, such a study has not been reported specifically for AZT photodegradation.

This paper explores the potential of using the SAM segmentator to enhance the segmentation capability of known methods. SAM is a promptable segmentation system that offers zero-shot generalization to unfamiliar objects and images, eliminating the need for additional training. The open-source nature of SAM on GitHub allows for easy access and implementation. In our experiments, we aim to improve the segmentation performance by providing SAM with checkpoints extracted from the masks produced by DeepLabv3+, then merging the segmentation masks provided by these two networks. Additionally, we examine the \enquote{oracle} method (as upper bound baseline performance), where segmentation masks are inferred only by SAM with checkpoints extracted from ground truth. In addition, we tested in the CAMO datasets an ensemble of PVTv2 transformers; combining the ensemble and SAM yields state-of-the-art performance in that dataset. The results of our study provide valuable insights into the potential of incorporating the SAM segmentator into existing segmentation techniques. We release with this paper the open-source implementation of our method.

Valorization of food and fruit wastes has the potential for the production of sustainable energy and biochemicals. Approximately 70% of the weight of the original jackfruit (Artocarpus heterophyllus L.) fruit is lost during processing as waste in the form of peeled skin and core, both of which have not been utilized and, thus contribute to disposal as well as pollution issues. The major components, cellulose, and hemicellulose, can be biologically transformed easily into bioenergy sources like ethanol, methanol, and butanol; valuable phenolics and biotechnological products like pectin, citric acid, bromelain, ferulic acid, and vanillin; and many other products. These residues can also be utilized as essential sources for the biological transformation process leading to the production of numerous products with added value, such as phenolic antioxidants, phenolic flavor compounds, and organic acids. Thus, the value addition of jackfruit waste can support the sustainable solution towards food and nutritional security. In this way, zero waste can be achieved through novel biorefineries which are critically highlighted in this paper. Furthermore, novel technologies for the conversion of jackfruit wastes are summarized with recent findings.

Current State-of-the-Art (SotA) chatbots are able to produce high quality sentences, handling different conversation topics, and larger interaction times. Unfortunately, the generated responses highly depend on the data on which they have been trained, the specific dialogue history and current turn used for guiding the response, the internal decoding mechanisms, ranking strategies, among others. Therefore, it may happen that for semantically similar questions asked by users, the chatbot may provide a different answer, which can be considered as a form of hallucination or produce confusion in long-term interactions. In this research paper, we propose a novel methodology consisting of two main phases: a) hierarchical automatic detection of topics and subtopics in dialogue interactions using a Zero-Shot learning approach, and b) detecting inconsistent answers using K-Means and the Silhouette coefficient. To evaluate the efficacy of topic and subtopic detection, we used a subset of the DailyDialog dataset and real dialogue interactions gathered during the Alexa Socialbot Grand Challenge 5 (SGC5). The proposed approach enables detecting up to 18 different topics and 102 subtopics. For the purpose of detecting inconsistencies, we manually generate multiple paraphrased questions and employ several pre-trained SotA chatbot models to generate responses. Our experimental results demonstrate a weighted F-1 value of 0.34 for topic detection, a weighted F-1 value of 0.78 for subtopic detection in DailyDialog, then 81% and 62% accuracy for topic and subtopic classification in SGC5; finally, to predict the number of different responses, we obtained a mean squared error (MSE) of 3.4 when testing smaller generative models and 4.9 in recent large language models.

Despite the increase in popularity of Zero Waste (ZW) concept, the successful implementation of this concept in waste management is still facing many challenges. The plastic recycling rate in Australia is currently only about 9.4%, which could leave up to 90.6% of plastic consumption being sent to landfills. The state of Victoria (in Australia) has proposed an ambitious plan to upgrade its waste and recycling system and to divert about 80% of waste from landfills by 2030. The aim of this research is to study Victoria’s current waste management plan and to develop a simulation model to assess the feasibility of it achieving zero plastic waste by 2035. In this direction, a fundamental knowledge of global ZW implementation needs to be acquired in order to understand the challenges, obstacles, and uncertainties in achieving ZW target. A simulation model is established using a method called double baselines. This method was developed as an improvisation to address the limitation of data availability for the model development. The model will run on 4 scenarios including one from Victoria’s current plan. Outcomes from the model are produced in comparative charts covering 6 key considerations including the rates of plastic consumption, waste to landfill, diversion, recycling, relative accumulative cost and effort. The findings of this study pointed out that Victoria’s current plan are feasible for its goal and presented with opportunities for improvement especially towards zero plastic waste. Besides, study results also reveal that the Victoria’s current plan to achieve 80% diversion rate by 2030 is possible but the zero plastic waste target by 2035 is less likely to happen.

The zero velocity update(ZUPT) algorithm is the core of a foot-mounted pedestrian navigation system. The zero velocity detection method is the premise and guarantee of the effective application of the ZUPT algorithm. To make ZUPT work properly, it is necessary to detect zero velocity intervals correctly. The detection accuracy of the existing zero velocity detection methods is easy to be affected by users and environment. A novel zero velocity detection method based on the plantar pressure is proposed in this paper, which has higher detection accuracy and better environmental adaptability. First, the paper analyzes the motion characteristics of foot during walking. Second, the inherent relationship between the plantar pressure and the gait change during walking is studied based on the pressure sensor. Then, the model of the zero velocity detection method using the plantar pressure is established. Finally, the indoor and outdoor multi-scene experiments show that this method not only has a high detection accuracy, but also has good adaptability to users and walking environment.

We consider a real scalar field in de Sitter background and compute its thermal propagators. We propose that in a dS/CFT context, non-trivial thermal effects as seen by an `out' observer can be encoded in the anomalous dimensions of the d=3 Ising model. One of these anomalous dimensions, the critical exponent eta, fixes completely a number of cosmological observables, which we compute.

Memphis aquifer is the primary drinking water source in Shelby County (Tennessee, USA) and supplies industrial, commercial, and residential water. Memphis aquifer is separated from the Shallow aquifer by a clayey layer known as Upper Claiborne Confining Unit (UCCU). All of the production wells in the Memphis area are screened in the Memphis aquifer or even deeper in the Fort Pillow aquifer. Traditionally, it was assumed that the UCCU could fully protect the Memphis aquifer from the contaminated Shallow aquifer groundwater. However, recent studies show that at some locations the UCCU is thin or absent which possibly leads to the contribution of Shallow aquifer to the Memphis aquifer. Accurately locating the breaches demands expensive and difficult geological or geochemical investigations, especially within an urban area. Hence, a pre-field investigation to identify the locations where the presence of breaches is likely can significantly reduce the cost of field investigations and improve the their results. In this study, to identify the locations where the presence of breaches in the UCCU is likely we use three different analyses: (1) pilot point calibration (PPC), (2) velocity and flow budget (VFB), and (3) particle tracking (PT) to post-process the developed groundwater results. These pre-field numerical investigations provide relevant and defensible explanations for groundwater flow anomalies in an aquifer system for informed decision-making and future field investigations. In this study, we identify five specific zones within the broad study area which are reasonable candidates for the future field investigations. Finally, we test the results of each analysis against other evidence for breaches to demonstrate that the results of the numerical analyses are reliable and supported by previous studies.

We report the electrical characterization and the field emission properties of CVD-grown MoS₂ bilayers deposited on SiO₂/Si substrate. Current-voltage characteristics are measured in the back-gate transistor configuration, with Ti contacts patterned by electron beam lithography. We confirm the n-type character of as-grown MoS₂ and we report normally-on field effect transistors. Local characterization of field emission is performed inside a scanning electron microscope chamber with piezo-controlled tungsten tips working as the anode and the cathode. We demonstrate that an electric field of ~200 V/μm is able to extract current from the flat part of MoS₂ bilayers, which therefore can be conveniently exploited for field emission applications even in low field-enhancement configurations. We show that a Fowler-Nordheim model, modified to account for electron confinement in 2D materials, fully describes the emission process.

Aiming to reveal the kinetic characteristics of ceramic ball grinding of fine magnetite comprehensively, two types of ceramic balls ground with the same filling rate and total weight as steel balls were researched. The results show that the breakage rate of ceramic ball grinding is only half of that of steel ball grinding with the same media filling rate. With the same total media weight and the feed size less than 0.212 mm, the breakage rate of the ceramic ball grinding approaches the steel ball grinding and is 21.43% higher than that of the steel ball grinding. The main crushing form of magnetite changed from impact to abrasion in ceramic ball grinding compared with steel ball grinding, which significantly affected the value of the zero-order output constant a. Consequently, there is a noticeable difference in the variation of the parameter β related to the fines generation rate of the ceramic ball grinding compared with the steel ball grinding.

Internet of Things includes all connected objects from small embedded systems with low computational power and storage capacities to efficient ones, as well as moving objects like drones and autonomous vehicles. The concept of Internet of Everything expands upon this idea by adding people, data and processing. The adoption of such systems is exploding and becoming ever more significant, bringing with it questions related to the security and the privacy of these objects. A natural solution to data integrity, confidentiality and single point of failure vulnerability is the use of blockchains. Blockchains can be used as an immutable data layer for storing information, avoiding single point of failure vulnerability via decentralization and providing strong security and cryptographic tools for IoE. However, the adoption of blockchain technology in such heterogeneous systems, containing light devices, presents several challenges and practical issues that need to be overcome. Indeed, most of the solutions proposed to adapt blockchains to devices with low resources confront difficulty in maintaining decentralization or security. The most interesting are probably the Layer 2 solutions which build offchain systems strongly connected to the blockchain. Among these, zk-rollup is a promising new generation of Layer 2/off-chain schemes which can remove the last obstacles to blockchain adoption in IoT, or more generally, in IoE. Despite their promises illustrated by recent systems proposed by startups and private companies, very few scientific publications explaining or applying this barely-known technology have been published, especially for non-financial systems. In this context, the objective of our paper is to fill this gap for IoE systems in two steps. We first propose a synthetic review of recent proposals to improve scalability including onchain (consensus, blockchain organization, ...) and offchain (sidechain, rollups) solutions and we demonstrate that zk-rollups are the most promising ones. In a second step, we focus on IoE by describing several interesting features (scalability, dynamicity, data management, ...) that are illustrated with various general IoE use cases.

Mill scale is the by-product of iron and steel industry. It can be recycled via sinter plant or solid as sinter feed materials. 85 to 90% of the constituent particles are more than 0.008 inches. The iron content is near around 70 %, with a very small amount of alkaline compounds and non-ferrous metals. Mill scale is polluted and contaminated with lubricants, oils and greases from the equipment. In this experiment for recovering of oil from mill scale, it is treated with three different methods. Then all methods were compared according to the ability of oil elimination and iron recovered. After washing and boiling with surfactants, large amount of polluted waste water becomes a problem for environment so this wastewater was utilized for making of Microbial Fuel Cells (MFCs), production of electricity in MFC depends on the biodegradation of organic materials, so different waste were added in wastewater for making MFC. The remaining of MFC was converted in bioethanol, biodiesel and biofertilizer. So this research is economical and environmentally friendly and fulfilled the important aspect of green environment with zero waste. It will be a mile stone in the research of metallurgy, environmental engineering, recycling technology and zero waste management.

Zero-Knowledge Proofs ZKP provide a reliable option to verify that a claim is true without giving detailed information other than the answer. A classical example is provided by the ZKP based in the Graph Isomorphism problem (GI), where a prover must convince the verifier that he knows an isomorphism between two isomorphic graphs without publishing the bijection. We design a novel ZKP exploiting the NP-hard problem of finding the algebraic ideal of a multivariate polynomial set, and consequently resistant to quantum computer attacks. Since this polynomial set is obtained considering instances of GI, we guarantee that the protocol is at least as secure as the GI based protocol.

Geological structures such as joints and faults in rock mass have significant influence on open pit mining. Hence, it is critical to develop a understanding of dynamic joint behaviour under blasting loading. This in turn can provide both theoretical and practical guidance to improve blasting rock fragmentation and associated bucket excavating efficiency. In this paper, delayed blasting on the highwall bench at Baiyunebo open-pit mine was used as an example, a nonlinear joint blasting model was also constructed. By simplifying the blasting wave propagation velocity, the P-wave normal incidence to the joint was obtained. The peak vibration velocity was 0.33m/s at 3.0s. The S-wave reflected by the joint interface was first reflected backward and then forward, which the peak vibration velocity was 0.027 m/s. By combining the relevant stress and displacement theories of type I and II cracks, the equipotential diagrams of the stress and displacement field with the vibration velocity of the particle were obtained. σx was positive in the direction of 0~330° and subjected to tensile stress, whereas σy was positive in the direction of 0~180° and under tensile stress. The longitudinal σy along joint was low in compressive stress distribution area and did not affect surrounding rock at the time. The stress concentration appeared in the lower right corner. Based on the continuous behavior of stress wave in joints, the asymmetry and continuous changes reflected in the whole process could not be analysed by the contour diagram. Hence, ANSYS used to analyse distribution of the stress field. The intensity of the shock wave after detonation was greater than that of the rock strength. Subsequently, the sub-layer shock wave supplemented the shock wave energy that was not enough to break the rock and induced further cracking. This was able to be visualized by the degree of color change post-processing. It was concluded that with the attenuation of the detonation wave energy, the stress exhibited a decreasing trend in this process. According to distribution of the peak effective stress, it was found that the peak value first increased to 10-12 MPa and then showed a downward trend. Overall, the results were validated against the finite element simulation and mathematical analysis.

ARBTools is a Python library containing a Lekien-Marsden type tricubic spline method for interpolating three-dimensional scalar or vector fields presented as a set of discrete data points on a regular cuboid grid. ARBTools was developed for simulations of magnetic molecular traps, in which the magnitude, gradient and vector components of a magnetic field are required. Numerical integrators for solving particle trajectories are included, but the core interpolator can be used for any scalar or vector field. The only additional system requirements are NumPy.

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

Mass plays a strange multiple role in classical physics. This results in a difference between gravity and all other forces - a difference that stood at the beginning of Einstein's development of his general theory of relativity. The equivalence principle (EP) deals with homogenious gravitational fields, which, in fact, don‘t exist in nature. There is only an approximation for this field in Einstein-Lift possible for local situations. Nevertheless this EP can be true, because in classical formal binary logic there can be formulated a true conclusion from a wrong premise or assumption.

Field electron emission, or electron tunneling through a potential barrier under the influence of a strong electrostatic field, is of broad interest to the accelerator physics community. For example, it is the source of undesirable dark currents in resonant cavities, providing a limit to high-field operation. The classical approach to field electron emission is the Fowler-Nordheim (FN) framework, which incorporates a simplified surface potential and various assumptions. Here we build a more realistic model using the potential and charge densities derived from a density-functional theory (DFT) calculation. We examine the correction factors associated with each model assumption. Compared to the FN framework, our results can be extended up to 80 GV/m, a limit that has been reached in laser-induced strong field emission scenarios.

The pursuit of Artificial Intelligence (AI) that emulates human cognitive processes is a cornerstone of ethical AI development, ensuring that emerging technologies can integrate seamlessly into societal frameworks requiring nuanced understanding and decision-making. Zero-Shot Instance Retrieval (ZSIR) stands at the forefront of this endeavour, potentially providing a robust platform for AI systems, particularly large visual language models, to demonstrate and refine cognition-aligned learning without the need for direct experience. In this paper, we critically evaluate current cognition alignment methodologies within traditional zero-shot learning paradigms, using visual attributes and word embedding generated by large AI models. We propose a unified similarity function that quantifies the cognitive alignment level, bridging the gap between AI processes and human-like understanding. Through extensive experimentation, our findings illustrate that this similarity function can effectively mirror the visual-semantic gap, steering the model towards enhanced performance in zero-shot instance retrieval. This work not only benchmarks the cognition alignment of AI, but also sets a new precedent for the development of visual language models attuned to the complexities of human cognition.}

We study the coupling of two topologcal subsystems in distinct topological states, and show that it leads to a precursor behavior of the topological phase transition in the overall system. This behavior is solely determined by the symmetry classes of the subsystem Hamiltonians and coupling terms, and is marked by the persistent existence of subgap states within the bulk energy gap. By investigating the critical current of Josephson junctions involving topological superconductors, we also illustrate that such subgap states play crucial roles in physical properties of nanoscale devices or materials.

Super-resolution technology is important not only in bio-related fields but also in nanotechnology, particularly in the semiconductor industry, where fine patterning is required and super-resolution is essential. However, observing microstructures beyond the diffraction limit proposed by Abbe and Rayleigh is considered impossible because of diffraction in traditional optical microscopy ob-servation techniques. However, in recent years, it has been possible to observe microstructures beyond the Rayleigh criterion by analysing the phase distribution of light. This study investigated the physical reasons why phase analysis makes this new analysis technique possible using simula-tions. The results confirmed that the phase component of the zero-order diffracted light reflected from the microstructure and able to pass through the lens system contained the phase information related to the shape of the measured object. Analysis of this information demonstrates the possi-bility of realising super-resolution based on speckle interferometry.

We present three reduced integrable hierarchies of nonlocal integrable NLS type equations from a vector integrable hierarchy associated with a matrix Lie algebra, not being A type. Three similarity transformations are taken to keep the invariance of the transformed zero curvature equations. The key step is to formulate a solution to a reduced stationary zero curvature equation so that the zero curvature formulation works for a reduced case.

Thermoregulation is important for maintaining homeostasis of our body. It can be easily broken under anesthesia. An appropriate method to measure the core body temperature is needed, especially for elderly patients because the efficiency of thermoregulation gradually decreases with age. The aim of this study was to examine the accuracy and feasibility of using of SpotOn® sensor in lower extremity orthopedic surgery in elderly patients aged over 80 years by comparing a SpotOn® sensor with two other reliable minimal-invasive methods: a tympanic membrane thermometer and a bladder thermometer. This study enrolled 45 patients aged over 80 years who were scheduled to undergo a lower extremity surgery. Body temperature was measured using a SpotOn® sensor, tympanic membrane thermometer and bladder thermometer. Agreements between the SpotOn® sensor and the other two methods were assessed using Bland and Altman plots for repeated measures adjusted for unequal numbers of measurements per patient. Compared with TempBladder, bias and limits of agreement for TempZHF were 0.07℃ ± 0.58℃. Compared with TempTympanic, bias and limits of agreement for TempZHF were -0.28℃ ± 0.61℃. 3M SpotOn® sensor using ZHF method for patients aged over 80 years undergoing lower extremity surgery shows feasible measurement value and sensitivity.

This study reports an empirical analysis of an all-electric, Net Zero Energy Housing (NZEH) development located in a mixed-humid climate zone (4A, Virginia, USA). Circuit-level energy monitors were used to measure energy consumption and energy production data (solar photovoltaic) at 1-hr intervals in six identical apartments over 24 months. The study employs a multi-step case study methodology to a) empirically evaluate energy consumption and production data, b) identify the temporal variability of energy consumption and production data at different time scales, c) understand the impact(s) of weather and human-building interaction on energy consumption and production, and d) synthesize the study’s “lessons learned” toward data-driven recommendations for future NZEH researchers and practitioners. The study found that the development’s net zero energy goal was achieved in three of six case units and that NZEH housing performance was more influenced by human-building interaction than weather variability. The analysis also found the solar photovoltaic (PV) performance to be reliable across the sampled units over the periods of measurement, suggesting that solar PV could be oversized as an approach to overcome verifiability in HBI and achieve NZEH performance goals.

U-turns and left turns are sometimes forbidden even though it increases travel distances. The greater travel distances are sometimes outweighed by the improved movement through intersections due to there being fewer conflicting lanes of traffic. One can, further, forbid straight-throughs. Restricting a sufficient number of turns can make intersections free from crossing lanes of traffic (``zero traffic conflict,'' ``ZTC"), though there may still be merging lanes of traffic. It's possible to make \begin{it}all\end{it} intersections in a road \begin{it}network\end{it} ZTC. However, keeping all destinations accessible and travel distances moderate requires careful selection of allowed driving directions and turning directions. We demonstrate through numerical microscopic and macroscopic simulations that there are road networks and ranges of traffic loads for which, in comparison with conventional schemes, ZTC road network can carry approximately $50$\% more vehicular traffic without incurring gridlock.

This paper provides an open dataset of measured energy use, solar energy production, and building air leakage data from a 328 m² (3,531 ft²) all-electric, zero energy commercial building in Virginia, USA. Over two years of energy use data were collected at 1-hour intervals using circuit-level energy monitors. Over six years of solar energy production data were measured at 1-hour intervals by 56 microinverters. The building air leakage data was measured post-construction per ASTM-E779 Standard Test Method for Determining Air Leakage Rate by Fan Pressurization and the United States Army Corps (USACE) Building Enclosure Testing procedure; both pressurization and depressurization results are provided. The architectural and engineering (AE) documents are provided to aid researchers and practitioners in reliable modelling of building performance. The paper describes the data collection methods, cleaning, and convergence with weather data. This dataset can be employed to predict, benchmark, and calibrate operational outcomes in zero energy commercial buildings.

Controversial hypotheses to explain consciousness exist in many fields of science, psychology and philosophy. Recent experimental findings in quantum cognition and magnetic resonance imaging have added new controversies to the field, suggesting that the mind may be based on quantum computing. Quantum computers process information in quantum bits (qubits) using quantum gates. At a first glance, it seems unrealistic or impossible that the brain can meet the challenges to provide either of these. Nevertheless, we show here why the brain has the incredible ability to perform quantum computing and how that may be realized.

We present a discussion and analysis regarding the benefits and limitations of open and non-anonymized peer review based on literature results and responses to a survey on the reviewing process of alt.chi, a more or less open-review track within the CHI conference, the predominant conference in the field of human-computer interaction (HCI). This track currently is the only implementation of an open-peer-review process in the field of HCI while, with the recent increase in interest in open science practices, open review is now being considered and used in other fields. We collected 30 responses from alt.chi authors and reviewers and found that, while the benefits are quite clear and the system is generally well liked by alt.chi participants, they are reluctant to see it used in other venues. This concurs with a number of recent studies that suggest a divergence between support for a more open review process and its practical implementation. The data and scripts are available on https://osf.io/vuw7h/, and the figures and follow-up work on http://tiny.cc/OpenReviews.

The world is facing several global issues such as food and energy crisis, climate change and greenhouse gases emissions. To subdue these issues, many entities from academia and industries have innovated alternate techniques of performing regular activities which cause such problems. One of these innovations is the introduction of vertical and zero acreage farming in the field of sustainability. These carry the potential to solve one of the most important affairs of food security in most countries of the world. But, this technology has been in its nascent stage for many years. This paper uses a comprehensive framework proving the feasibility of initiating vertical farming on university campuses to feed the staff and students, which could also set an example to the rest of the world into using this technique on a wider scale. The study chose Huazhong University of science and technology (HUST) in Wuhan city, China for accessing the return on investment and food sufficiency if vertical farming is implemented. Using Central Limit Theorem, a statistical model was developed, and various scenarios were analyzed. The results indicated that if a separate vertical farm is constructed, the breakeven can be achieved in a range of 10-20 depending on parameters such as type of operation, number of floors and amount of vegetation. The study has shown that the use of vertical farming cannot only bring in revenue for the campus but also aid in mitigating climate change.

The spectral properties of a one-dimensional photonic crystal bounded by a resonant absorbing nanocomposite layer with the near-zero permittivity have been studied. The problem of calculating the transmittance, reflectance, and absorptance spectra of such structures at the normal and oblique incidence of light has been solved. It is shown that, depending on the permittivity sign near zero, the nanocomposite is characterized by either metallic or dielectric properties. For the first time, the possibility of simultaneous formation of the Tamm plasmon polariton at the photonic crystal/metallic nanocomposite interface and the localized state similar to the defect mode with the field intensity maximum inside the dielectric nanocomposite layer is demonstrated. Specific features of field localization at the Tamm plasmon polariton and defect mode frequencies are analyzed.

Hybrid reverse osmosis electrodialysis systems make it possible to obtain solutions with a higher concentration of components compared to single electrodialysis treatment, i.e. more efficient separation of brine and pure water. The article proposes experimental and pilot-industrial studies of a hybrid membrane system operation using industrial wastewater for the disposal of liquid waste from an ion-exchange chemical-desalting water treatment plant of a thermal power plant, followed by a calculation of economic efficiency and an analysis of the environmental feasibility of their use. The developed technological scheme offers separate processing of acidic and alkaline waste regeneration solutions using calcium carbonate reagent and desalination on baromembrane and electromembrane units to obtain clean water and dry residue. The hybrid system includes a booster filter press and an evaporator. The hybrid system makes it possible to provide a thermal power plant with a "zero discharge" with a minimum consumption of reagents and electricity, as well as return all water from wastewater to the power plant cycle.

This interdisciplinary work presents a novel patent pending method of inertial electrostatic confinement (IEC) fusion called the Nuclear Electromagnetic Shaping Accelerator Reactor (NESAR) that addresses all of the major failure problems with currently known methods of IEC fusion. A brief background of previous IEC methods that generate a negative potential well to accelerate ions for fusion will be reviewed and compared to the NESAR method of magnetic confinement. In addition, a direct comparison will be presented between the NESAR and the tokamak method of fusion. The NESAR method of fusion obtains the plasma oscillation and compression capabilities of a tokamak without producing the catastrophic magnetic reconnection disruptions that currently plague tokamaks. Since the NESAR can oscillate charged particles comparable to the tokamak, this work will briefly review the history of the tokamak, how sawtooth magnetic reconnection occurs, and how the NESAR precludes the occurrence of magnetic reconnection. This work will also review the beginnings of a novel unified field theory that has obtained interest from the Defense Advanced Research Projects Agency (DARPA). This unified field theory is based upon the trajectory of charged particle movements within the NESAR, which is the only concept of magnetic confinement in the world that may allow charge particles to collectively interact relatively to a solitary location. Due to this possible capability, the confined charged particles have the potential to experience curved trajectories; allowing for the effects of curvature deviation to be placed upon the charged particle within the magnetic confines of the NESAR. If charged particles can experience curvature deviation then deviated acceleration is generated; allowing the electromagnet field to be propelled to a higher spatial dimension that could influence spacetime. Finally, this work will review another theory that explains how magnetic pole reversals are observed by the National Aeronautics and Space Administration’s (NASA) coiled magnetic field detectors. This theory requires little to no postulations to be framed and it is purely based upon the trajectory of charged particles within the NESAR, Michael Faraday’s law of induction, and experimental observations of rotating plasmas.

We show that the Einstein field equations for a five-dimensional warped spacetime, where only gravity can propagate into the bulk, determine the dynamical evolution of the warp factor of the four-dimensional brane spacetime. This can be explained as a holographic manifestation. The warped 5D model can be reformulated by considering the warp factor as a dilaton field ($\omega$) conformally coupled to gravity and embedded in a smooth $M_4 \otimes R$ manifold. On the brane, where the U(1) scalar-gauge fields live, the dilaton field manifests itself classically as a warp factor and enters the evolution equations for the metric components and matter fields. We write the Lagrangian for the Einstein-scalar-gauge fields in a conformal invariant setting. However, as expected, the conformal invariance is broken (trace-anomaly) by the appearance of a mass term and a quadratic term in the energy-momentum tensor of the scalar-gauge field, arising from the extrinsic curvature terms of the projected Einstein tensor. These terms can be interpreted as a constraint in order to maintain conformal invariance. By considering the dilaton field and Higgs field on equal footing on small scales, there will be no singular behavior, when $\omega\rightarrow 0$ and one can deduce constraints to maintain regularity of the action. Our conjecture is that $\omega$, alias warp factor, has a dual meaning. At very early times, when $\omega \rightarrow 0$, it describes the small-distance limit, while at later times it is a warp (or scale) factor that determines the dynamical evolution of the universe. We also present a numerical solution of the model and calculate the (time-dependent) trace-anomaly. The solution depends on the mass ratio of the scalar and gauge fields, the parameters of the model and the vortex charge $n$.

Using the principle of equivalence, it has recently been shown that the electrostatic field lines of a charge, stationary in the gravitational field, bend exactly like the trajectories of photons emitted isotropically from a source at the charge location and that the fraction of electric flux crossing a surface `below' or `above' the charge is exactly similar to the fraction of photon trajectories intersecting these surfaces, with more flux in the downward direction than upward. As one goes much deeper in the gravitational field, all electric field lines increasingly point in the vertically downward direction as is also the case for a stream of photons. Since photon trajectories as well as electric field lines, at any location in the gravitational field, are affected by the local space-time curvature an inference can be drawn that this parallel between the photon trajectories and the electric field lines is a general result. We could then apply these results in the external gravitational field of a black hole, where the trajectories of photons in the gravitational field are already well-known and the behaviour of electric field lines of a stationary charge could be inferred therefrom. Accordingly, we show that the electric field through an external spherical surface surrounding the black hole steadily reduces as the charge location approaches the event horizon (Schwarzschild radius), and like photons from a source inside the Schwarzschild radius cannot escape outside, the electric field lines of a charge within the black hole too remain trapped inside the event horizon. From this one arrives at a conclusion that, contrary to the conventional wisdom, the electric charge contained inside a static black hole cannot be detected or inferred by an external observer. A black hole, said to have no hair with the only external identifying characteristics being mass, electric charge, and angular momentum, is therefore all the more `hairless', as even its charge cannot be ascertained. The derivation of the Reissner-Nordström metric, supposedly describing the gravitational field of a static charged black hole, presumes an external stress-energy tensor of the electrostatic field, as per Gauss law, even for the charges contained within the black hole. However, the absence of electric flux external to a static charged black hole implies that such a charged black hole is not described correctly by the Reissner-Nordström metric and the consequential peculiarities of the space-time geometry, leading in specific cases to the idea of a naked intrinsic singularity and a need for the ``cosmic censorship'' hypothesis, also do not arise here.

Wide-field (WF) retinal imaging is becoming a standard diagnostic tool for diseases involving the retinal periphery. Technological progress elicited the advent of wide-field optical coherence tomography (WF-OCT) and WF-OCT angiography (WF-OCTA) examinations. This review presents the results of studies that analyzed the implementation of these procedures in clinical practice and refers to them as traditional and ultra-wide-field fluorescein angiography (UWF-FA). The PUBMED search was performed using the terms WF-OCT OR WF-OCTA OR UWF-FA AND the specific clinical entity, including diabetic retinopathy (DR), retinal vein occlusion (RVO), Coats disease, peripheral retinal telangiectasia, peripheral retinal degeneration, lattice degeneration, and posterior vitreous detachment. The analysis only included the studies in which the analyzed field of view for the OCT or OCTA exam was larger than 55 degrees. The evaluation of the extracted studies indicates that WF imaging with OCT and OCTA provides substantial information on retinal disorders involving the retinal periphery. Vascular diseases, such as DR or RVO, can be reliably evaluated using WF-OCTA with results superior to standard-field fluorescein angiography. Nevertheless, UWF-FA provides a larger field of view and still has advantages over WF-OCTA concerning the evaluation of areas of non-perfusion and peripheral neovascularization. Detailed information on the vascular morphology of peripheral changes should be obtained via WF-OCTA, not angiographic examinations. WF-OCT can serve as a valuable tool for the detection and evaluation of vitreoretinal traction, posterior vitreous detachment, and peripheral retinal degeneration, and guide therapeutic decisions on a patient’s eligibility for surgical procedures.

Owing to the growing concerns due to dwindling fossil fuel reserves, increasing energy demand and climate emergency, it is imperative to develop and deploy sustainable energy technologies to ensure future energy supply as well as transition to the net zero world. In this context, there is great potential in the biorefinery concept for supplying drop in biofuels in the form of biodiesel. Biodiesel as a fuel can certainly bridge the gap where electrification or the use of hydrogen is not feasible, for instance heavy vehicles, farm and marine transportation sector. However, biodiesel industry also leads to formation of large amount of crude glycerol as the byproduct. Crude glycerol due to presence of several impurities may not be a suitable feedstock for all high value products derived from glycerol but fits well with glycerol esterification for producing glycerol acetins, which have numerous applications. This review critically looks at the processes using nanostructured solid/liquid acid catalysts for glycerol esterification including the economic viability of the scale up.

The UK government and many international experts have pointed out that nuclear energy has an important role to play in the transition towards a decarbonized energy system since it is the only freely manageable very low-carbon energy technology with 24/7 availability to complement renewables. Besides current investments in light water reactor technologies, we need innovation for improved fuel usage and reduced waste creation, like offered by iMAGINE, for the required broad success of nuclear technologies. To allow quick progress into innovative technologies like iMAGINE and their regulation, a timely investment into urgently needed experimental infrastructure and expertise development will be required to assure the availability of capacities and capabilities. The initial steps to start the development of such a new reactor physics experimental facility to investigate molten salt fast reactor technology are discussed and a stepwise approach for the development of the experimental facility is described. The down selection to the choice for a diverse control and shutdown system is described through manipulating the reflector (control) and splitting the core (shutdown). The developed innovative core design of having the two core parts in two different rooms opens completely new opportunities and will allow to manifest the request for separated operational and experimental crews, as nowadays requested by regulators into the built environment. The proposed physical separation of safety relevant operational systems from the experimental room should on the one hand help to ease the access to the facility for visiting experimental specialists. On the other hand, the location of all safety relevant systems in a now separated access-controlled area for the operational team will limit the risk of misuse through third party access. The planned experimental programme described with the major steps: core criticality experiments, followed by experiments to determine the neutron flux, neutron spectrum, and power distribution as well as experiments to understand the effect of changes in reactivity and flux as a function of salt density, temperature and composition change.

Batch and transport experiments were used to investigate the remediation of a loamy sand soil contaminated with Cr(VI) using zero valent iron nanoparticles (nZVI) stabilized by the carboxy methyl cellulose (CMC-nZVI). The effect of pH, ionic strength (IS), and flow rate on the removal efficiency of Cr(VI) were investigated under equilibrium (uniform transport) and non-equilibrium (Two-site sorption) transport using the Hydrus-1D model. The overall removal efficiency ranged from 70 to over 90% based on the chemical characteristics of the CMC-nZVI suspension and the transport conditions. The concentration and pH of the CMC-nZVI suspension had the most significant effect on the removal efficiency and transport of Cr(VI) in the soil. The average removal efficiency of Cr(VI) was increased from 24.1 to 75.5% when the concentration of CMC-nZVI nanoparticles was increased from 10 to 250 mg L-1, mainly because of the increased total surface area at larger particle concentration. Batch experiments showed that removal efficiency of Cr(VI) was much larger under acidic conditions. The average removal efficiency of Cr(VI) reached 90.1 and 60.5 % at pH 5 and 7, respectively. The Two-site sorption model described quite well (r2 = 0.96-0.98) the transport of Cr(VI) in soil as compared to the uniform transport model (r2 = 0.81-0.98). The average retardation of Cr(VI) was 3.51 and 1.61 at pH 5 and 7, respectively, indicating earlier arrival for the breakthrough curves and shorter time to reach maximum relative concentration at lower pH. The Hydrus-1D model has proven to be an efficient tool for assessing the removal of Cr(VI) pollutants, offering innovative, cost-effective, and environmentally friendly remediation methodologies.

(1) Background: “Zero-dose” (ZD) refers to a child not receiving any doses of the pentavalent (diphtheria-tetanus-pertussis-Haemophilus influenzae type b (Hib)-Hepatitis B) vaccine in the routine national immunization schedule. These children are vulnerable to vaccine-preventable diseases (VPDs), and are often already disadvantaged due to poverty, conflict, and lack of access to basic health services. The Luambo health district (HD) is one of the 26 HDs in the Kasai Central Province and has the largest number of ZD children. This study was conducted to examine the factors associated with ZD status in the Luambo HD; (2) Methods: We conducted a mixed study of children aged 12-23 months in the Luambo HD in the Kasai Central Province; (3) Results: A total of 445 children aged 12-23 months were included in the study, including 89 cases and 356 controls. Correlates of zero dose (ZD) status in children aged 12-23 months were mothers who were not receiving Antenatal Care (ANC), of not knowing any VPD, the fact of the children being born in Angola and the fact of the children being born at home. In addition, the perceptions of children’s parents influenced child immunization; (4) Conclusions: Missing ANC services during pregnancy leads to home delivery with consequences being lack of knowledge on childhood’s VPD and subsequently children not being vaccinated.

This research explores the intricate relationship between gravitational and cosmic redshift phenomena, unveiling a profound understanding of how light behaves as it traverses the cosmos. The study begins with an examination of gravitational redshift, a well-established concept occurring when photons move away from massive gravitational sources, such as stars within galaxies. Gravitational redshift, expressed as λ/λ₀, manifests within the gravitational influence and extends to the boundary of the observed "zero-gravity sphere" enveloping galaxies. Within this remarkable zero-gravity sphere, gravitational effects persist, while the antigravity influence of dark energy remains negligible. As a result, gravitational redshift dominates, and cosmic redshift is notably absent within the sphere. Photons within this sphere maintain their constant speed 'c' and undergo gravitational redshift exclusively. However, as photons exit the zero-gravity sphere at a distance 'r' equivalent to the source star's radius, they encounter the onset of cosmic redshift, quantified as {(λ_obs - λ_emit)/ λ_emit}. Cosmic redshift blends with gravitational redshift, forming the effective redshift of the photon. Critically, the effective cosmic redshift surpasses gravitational redshift, illuminating a profound revelation: photons traverse a greater "light-traveled distance" than their proper distance from the source. In essence, cosmic redshift signifies that photons move across their intended distances at their intrinsic speed c, while the expanding universe introduces a relative distance expansion, influenced by antigravity. This research delves into the intricate dance between gravitational and cosmic redshift, shedding light on their remarkable implications for our comprehension of the expanding universe.

In the broad context of vulnerability detection, deep learning has achieved considerable progress but faces generalization challenges in multilingual environments . We introduce a novel approach named AST-FMVD, which leverages transfer learning and abstract syntax trees. By employing semantic similarity clustering and context-aware technology, the method constructs node mapping relationships between different languages, enabling zero-shot learning in vulnerability detection. The method was validated by applying Java's vulnerability detection model in the Python domain, successfully demonstrating that AST-FMVD retains the original model's detection capabilities in the target domain. In conclusion, the proposed method offers a promising solution to the inherent problems in multi-language vulnerability detection, signifying a potential leap in the application of deep learning, transfer learning, and abstract syntax trees for improved cross-domain performance.

The operating theatre represents a key contributor to healthcare-derived emissions. Here, we outline the carbon footprint of a lumbar microdiscectomy at our regional unit in Greater Manchester, with the use of AI technology. In doing so, we aim to define the extent of the environmental impact and identify carbon hotspots for sustainable change. Our unit of analysis covered the start of the patient journey into hospital through to the final outpatient appointment. Publicly available and locally sourced data was used. An inventory analysis of two lumbar microdiscectomies was conducted. Each item was categorised reconciled against our AI-powered ‘CO2 analysis’ database. Kilograms of carbon dioxide equivalent (kg CO2e) was chosen as the primary measure of impact. An average lumbar microdiscectomy at our trust generates 477.73kg CO2e. The operation (173.89kg CO2e, 36.40%) and the inpatient stay (144.67kg CO2e, 30.28%) constituted the biggest contributors. Single-use intraoperative equipment contributed to over three-quarters of the total emissions from the operation. By defining the environmental burden of elective spinal surgery, we have identified carbon hotspots to target for sustainable change. Substituting polluting elements for carbon-friendly alternatives and challenging the single-use culture, modern healthcare systems can help pave the way to a ‘net zero’ healthcare system.

A common challenge in real-world classification scenarios with sequentially appending target domain data is insufficient training datasets during the training phase. Therefore, conventional deep learning and transfer learning classifiers are not applicable especially when individual classes are not represented or are severely underrepresented at the outset. Domain Generalization approaches reach their limits when domain shifts become too large, making them occasionally unsuitable as well. In many (technical) domains, however, it is only the defect/ worn/ reject classes that are insufficiently represented, while the non-defect class is often available from the beginning. The proposed classification approach addresses such conditions and is based on a CNN encoder. Following a contrastive learning approach, it is trained with a modified triplet loss function using two datasets: Besides the non-defective target domain class (= 1st dataset), a state-of-the-art labeled source domain dataset that contains highly related classes (e.g., a related manufacturing error or wear defect) but originates from a (highly) different domain (e.g., different product, material, or appearance) (= 2nd dataset) is utilized. The approach learns the classification features from the source domain dataset while at the same time learning the differences between the source and the target domain in a single training step, aiming to transfer the relevant features to the target domain. The classifier becomes sensitive to the classification features and – by architecture – robust against the highly domain-specific context. The approach is benchmarked in a technical and a non-technical domain and shows convincing classification results. In particular, it is shown that the domain generalization capabilities and classification results are improved by the proposed architecture, allowing for larger domain shifts between source and target domains.

According to the World Food Programme (WFP), the projected increase in the human population stands at 2 billion people by 2050. At the same time, world food production is witnessing a declining trend over recent years, and 690 million (8.9%) of the world's population are already in severe starvation. Climate variability and climate change impacts on food security are very eminent today. For this reason, this study explored the real effects of climate variability and change on food security in Africa by applying the system Generalized Method of Moments (GMM) and the Panel Corrected Standard Errors (PCSEs) estimators on data from 2001–2018 for 38 selected African countries. The findings reveal that higher amounts of precipitation positively influence food security along two dimensions (food availability and utilization). Hotter temperatures negatively impact food availability and utilization. However, it aids food accessibility in Africa. Similarly, carbon dioxide emissions improve food availability and are harmful to food accessibility and food utilization in Africa. Consequently, the effects of climate variability and change on food security in Africa are undesirable, thereby putting the continent at risk of food insecurity over the long run. Given these findings, the study made appropriate recommendations for policy change to address the negative effects of climate variability and change on food security in Africa.

General relativity is a theory for gravitation based on Riemannian geometry, difficult to compatibilize with quantum mechanics. This is evident in relativistic problems in which quantum effects cannot be discarded. For example in quantum gravity, gravitation of zero-point energy or events close to a black hole singularity. Here, we set up a mathematical model to select general relativity geodesics according to compatibility with the uncertainty principle. To achieve this, we derived a geometric expression of the uncertainty principle (GeUP). This formulation identified proper space-time length with Planck length by a geodesic-derived scalar. GeUP imposed a minimum allowed value for the interval of proper space-time which depended on the particular space-time geometry. GeUP forced the introduction of a “zero-point” curvature perturbation over flat Minkowski space, caused exclusively by quantum uncertainty but not to gravitation. When applied to the Schwarzschild metric and choosing radial-dependent geodesics, our mathematical model identified a particle exclusion zone close to the singularity, similar to calculations by loop quantum gravity. For a 2 black hole merger, this exclusion zone was shown to have a radius that cannot go below a value proportional to the energy/mass of the incoming black hole multiplied by Planck length.

The sustainability of irrigated agriculture depends on the quality of irrigation water used. The electrolyte concentration (EC) of irrigation water may lead to the accumulation of salts in the root zone layers and affect the physiological functions of the crop by osmotic and ion toxicity effects. Further, the cationic and anionic composition of the water may alter the exchangeable cation composition of the soil and as well as its pH. Because of the dominance of sodium salts in many sources of irrigation water, parameters related to sodium such as exchangeable sodium percentage (ESP) of soils and sodium adsorption ratio (SAR) of soil solutions have been commonly used to study the effects of sodium in irrigation water on soil structural stability. Quirk and Schofield concept of ‘threshold electrolyte concentration’ (TEC) has shown the importance of electrolytes in preventing the effects of sodium on soil structure. Based on this concept, several models have been proposed to relate ESP or SAR with EC to predict the possible impacts of irrigation water on soil structural stability. However, many research reports indicate that this relationship varies with soils and a given model is not suitable for all types of soils. Further, the effects of potassium and magnesium in the processes leading to clay dispersion are disregarded in these models. This essay analyses all the factors involved in the structural failure of soils with different cationic composition, identify the defects in these TEC models and re-defines TEC on the basis of new insights on dispersive and flocculating charges of soils. This review does not deal with EC effects on crops and also the role of contaminant ions not involved with soil structural stability.

With the aim to improve cladding coating quality and prevent cracking, this paper established an extreme high-speed laser cladding thermo-mechanical coupling simulation model to study the evolution of the temperature field and residual stress distribution. Process parameters that impacted the macroscopic morphology of single-pass coatings were investigated. Numerical calculations and temperature field simulations were performed based on the process parameter data to validate the effect of the temperature gradient and cooling rate on the coating structure and the residual stress distribution. The results showed that a good coating quality could be achieved using a laser power of 2400 W, a cladding rate of 20 m/min, and a powder feeding rate of 20.32 g/min. The coatings’ cross-sectional morphology corresponded well with the temperature distribution predicted by numerical modeling of the melt pool. The microstructure of the molten coatings is affected by the temperature gradient and cooling rate, which vary greatly from the bottom to the middle to the top. Maximum residual stress appears between the bonding region of the coatings and the substrate, and the coatings themselves have significant residual stress in the form of tensile strains that are mostly distributed in the direction of the laser cladding speed.

The well-known coupling between the magnetic and electric fields in electromagnetic radiation is revisited in light of the recent introduction of a microscopic theory for the Ørsted magnetic field induction. I argue that, if the Ørsted magnetic field induction does indeed have a microscopic origin rather than the continuum solution offered by the Maxwell-Ampere equation, the "electromagnetic wave"' propagating in vacuum will not have a magnetic component.

In this work, a small-strain phase-field model is presented, which is able to predict crack propagation in systems with anisotropic brittle and ductile constituents. To model the anisotropic brittle crack propagation, an anisotropic critical energy release rate is used. The brittle constituents behave linear-elastically, in a transversely isotropic manner. Ductile crack growth is realised by a special crack degradation function, depending on the accumulated plastic strain, which is calculated by following the J2-plasticity theory. The mechanical jump conditions are applied in solid-solid phase transition regions. The influence of the relevant model parameters on a crack, propagating through a planar brittle-ductile interface, and furthermore a crack developing in a domain with a single anisotropic brittle ellipsoid, embedded in a ductile matrix, is investigated. We demonstrate that important properties, concerning the mechanical behaviour of grey cast iron, such as the favoured growth of cracks along the graphite lamellae and the tension-compression load asymmetry of the stress-strain response, are covered by the model. The behaviour is analysed on basis of a simulation domain consisting of three differently oriented elliptical inclusions, embedded in a ductile matrix, which is subjected to tensile and compressive load. The used material parameters correspond to graphite lamellae and pearlite.

It is well known that the photon trajectories follow a curved path in a gravitational field. We explore here the gravitational bending of electric field lines. It seems that the electric field lines of a charge, supported in a gravitational field, follow exactly the trajectories of photons emitted isotropically from a source situated at the charge location. From a detailed examination of the electrostatic field of a charge accelerated uniformly in the instantaneous rest frame, exploiting the strong principle of equivalence, one can determine the bending of the electric field lines of a charge in a gravitational field. The fraction of electric field lines crossing a surface, stationary above or below the charge in the gravitational field, is shown to be exactly similar to the fraction of photon trajectories, emitted from a source placed at the charge location, intersecting that surface. On the other hand, for a freely falling charge in the gravitational field there is no such bending of electric field lines. The field lines continue to extend in radial straight lines from the instantaneous 'present' position of the charge, as do the trajectories of photons streaming away from the instantaneous position of a freely falling source in the gravitational field. The electric field configuration of a freely falling charge in the gravitational field is shown to be exactly the same as that of a charge moving uniformly in an inertial frame with velocity equal to the instantaneous ``present'' velocity of the freely falling charge.

This article studies electrostatic fields and potentials in the presence of conductors and point charges under the framework of solving Laplace’s equation with specifi ed boundary conditions. The results demonstrate that many problems posed and solved in elementary electrostatics through various heuristics such as the method of images, can be more rigorously treated under the solution framework of Laplace’s equation.

In a recent article we showed that the analog of the cosmological constant in two spacetime dimensions for a wide variety of integrable quantum field theories has the form ρvac = −m2/2g where m is a physical mass and g is a generalized coupling, where in the free field limit g → 0, ρvac diverges. We speculated that in four spacetime dimensions ρvac takes a similar form ρvac = −m4/2g, but did not support this idea in any specific model. In this article we study this problem for λφ4theory in d spacetime dimensions. We show how to obtain the exact ρvac for the sinh-Gordon theory in the weak coupling limit by using a saddle point approximation. This calculation indicates that the cosmological constant can be well-defined, positive or negative, without spontaneous symmetry breaking. We also show that ρvac satisfies a Callan-Symanzik type of renormalization group equation. For the most interesting case physically, ρvac is positive and can arise from a marginally relevant negative coupling g and the cosmological constant flows to zero at low energies.

The translocator protein (TSPO) is a transmembrane protein present in the three domains of life. Its functional quaternary structure consists of one or more subunits. In mouse, the dimer-to-monomer equilibrium is shifted in vitro towards the monomer by adding cholesterol, a natural component of mammalian membranes. Here, we present a coarse-grained molecular dynamics study on the mouse protein in the presence of a physiological content and of an excess of cholesterol. The latter turns out to weaken the interfaces of the dimer by clusterizing mostly at the inter-monomeric space and pushing the contact residues apart. It also increases the compactness and the rigidity of the monomer. These two factors might play a role for the experimentally observed incremented stability of the monomeric form with increased content of cholesterol. Comparison with simulations on bacterial proteins suggests that the effect of cholesterol is much less pronounced for the latter than for the mouse protein.

Framed experiments and games are a useful medium to understand how context affects individual and group decision-making. They are particularly relevant for field research in agriculture, where alternative experimental designs can be costly and unfeasible. After a systematic review of the literature, we found that the volume of published studies employing coordination and cooperation games increased during the 2000-2020 period. In recent years, there has been greater attention given to natural resource management, conservation, and ecology areas, especially in strategic regions for agriculture sustainability. Other games, such as trust and risk games, have come to be regarded as standards of framed field experiments in agriculture. Regardless of sectoral focus, most games' results are subject to internal and external validity criticism. In particular, a significant portion of the games showed potential recruitment biases against women and no opportunities for a continued impact assessment. However, games' validity should be judged on a case-by-case basis. Specific cultural aspects of games might reflect the real context, and generalizing games' conclusions to different settings is often constrained by cost and utility. Overall, games in agriculture could benefit from more significant, frequent, and inclusive experiments and data – all possibilities offered by digital technology. Present-day physical distance restrictions may accelerate this shift. New technologies and engaging ways to approach farmers might represent a turning point for games in agriculture in the 21st century.

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.

Team spirit is often considered a peculiar characteristic of sportspersons. While the importance of unity among athletes is evident in team games, its relevance in the training of sportspersons of individual sports, especially track and field athletics, is often not recognized. The purpose of this study is to review how team cohesion impacts athletes of various sports and understand how it could contribute to the overall performance of track and field athletes, who mainly compete individually.

Ovariectomy appears to be the best method to control the density of wild ungulate populations. The aim of the present study was to compare two surgical approaches, via the flank and midline, in mouflon’s ovariectomy in field conditions. Twenty female mouflons were enrolled in the study. The animals were divided randomly in two groups, Group F animals were gonadectomized via flank approach, while Group A animals were sterilized via linea alba access. The parameters evaluated were duration of surgery, duration of anaesthesia, recovery time, intra- and post-operative complications, intra-operative nociception and pain in the post-operative period. There were no intra- and post-operative complications. The evaluated parameters showed a very similar trend in both groups. Both techniques are found to be effective and safe in execution.

This study conducted experiments to optimize the electro-dewatering of sludge using a dynamic model calculation method and the Wild Horse optimizer. Specifically, we explored two factors that might influence dewatering: the composition of the electrode materials and the strength of the electrical field. Compared to other electrodes commonly used in electro-dewatering—such as RuO2/Ir2O3-Ti, graphite, Ir2O3/Ta2O5-Ti, and Ti—the Electro-kinetic Geosynthetics (EKG) electrode exhibited superior performance. This was determined by considering both energy consumption and model establishment. Our findings also identified electric-field strength as a crucial factor determining the final moisture content. As the electrical intensity increased, the dewatering effect improved, aligning with our model calculations. However, we observed a steep increase in energy consumption per kilogram of filtrate when the electric-field strength exceeded a certain threshold. To optimize the energy consumption of the dehydration process, we constructed a multi-factor model. The simulation results from this model confirmed that electric-field intensity is the primary factor affecting dehydration. It was established that 10 V/cm is a critical threshold for the process.

The olfactory system is capable of distinguishing individual odorants from among a virtually unlimited number. Fish, for example, detect changes in the electric field environment induced by prey and other sources. Floral electric fields exhibit variations in pattern and structure, which can be discriminated by bumblebees. We have constructed an electric field sensor, which, in the course of focussing on achieving maximum sensitivity and consistency, ultimately resembles features of the insect sensorium. A “fingerprint” 3D plot ( time, frequency range, voltage amplitude), representing the emitted electric field profile, is presented for each of a variety of odorants and other chemicals. The substance-specific electric-field emission and identification is not impeded by containers or barriers or distance.

Generalized zero-shot learning (GZSL) aims to simultaneously recognize both seen classes and unseen classes by training only on seen class samples and auxiliary semantic descriptions. Recent state-of-the-art methods infer unseen classes based on semantic information or synthesize unseen classes using generative models based on semantic information, all of which rely on the correct alignment of visual-semantic features. However, they often overlook the inconsistency between original visual features and semantic attributes. Additionally, due to the existence of cross-modal dataset biases, the visual features extracted and synthesized by the model may also mismatch with some semantic features, which could hinder the model from properly aligning visual-semantic features. To address this issue, this paper proposes a GZSL framework that enhances the consistency of visual-semantic features using self-distillation and disentanglement network (SDDN). The aim is to utilize self-distillation and disentanglement network to obtain semantically consistent refined visual features and non-redundant semantic features to enhance the consistency of visual-semantic features. Firstly, SDDN utilizes self-distillation technology to refine the extracted and synthesized visual features of the model. Subsequently, the visual-semantic features are then disentangled and aligned using a disentanglement network to enhance the consistency of the visual-semantic features. Finally, the consistent visual-semantic features are fused to jointly train a GZSL classifier. Extensive experiments demonstrate that the proposed method achieves more competitive results on four challenging benchmark datasets (AWA2, CUB, FLO, and SUN).

The modern supply chain (SC) is growing in terms of data, devices, users, and stakeholders, which introduced new security challenges and threats, especially with the reliance on centralized servers or cloud platforms. In addition, increased trust among system participants exposes the SC to a higher risk of vulnerabilities which require strong security measures. This article proposes a hybrid security framework for SC systems, BC-DRLzSC, that integrates Blockchain (BC) and Deep Reinforcement Learning (DRL) designed to operate in a zero trust (ZT) environment. In particular, we propose a decentralized BC-based approach integrated with smart contracts to manage system participant registration and authentication and to control access to system resources. BC-DRLzSC adopts a ZT architecture to reinforce SC security, which can be achieved with an advocate to verify each entity’s trustworthiness before granting or retaining access to system resources. Incorporating the ZT architecture, with BC and DRL, can potentially and significantly bolster SC system security. DRL is employed to develop a proactive attack detection model that continuously monitors the incoming traffic from authenticated nodes within the network and predicts any malicious actions. Finally, we evaluate the performance of our proposed DRL solution using the NSL-KDD dataset.

When overhead lines are impacted by lightning, the traveling wave of the fault contains a wealth of fault information. The accurate extraction of feature quantities from transient components and their classification is fundamental to the identification of lightning faults. The extraction process may involve modal aliasing, optimal wavelet base issues, and inconsistencies between the lightning strike distance and the fault point, which have the potential to impact the effectiveness of recognition. This paper presents a method for identifying lightning strike faults by utilizing Kullback-Leibler (KL) divergence enhanced Variational Mode Decomposition (VMD) and Symmetric Geometry Mode Decomposition (SGMD) improved with Permutation Entropy (PE) to address the aforementioned issues. A model of a 220 kV overhead line is constructed using real faults to replicate scenarios of winding strike, counterstrike, and short-circuit. The three-phase voltage is chosen and then sub-jected to Karenbaren decoupling in order to transform it into zero mode, line mode 1, and line mode 2. The zero mode voltage is decomposed using KL-VMD and PE-SGMD methods, and lightning identification criteria are developed based on various transient energy ratios. The research findings demonstrate that the criteria effectively differentiate between winding strike, counterstrike, and short-circuit faults, thus confirming the accuracy and efficacy of the lightning fault identification criteria utilizing KL-VMD and PE-SGMD.

Implementing net-zero building design is a crucial step towards decarbonizing the built environment during the entire lifecycle of a building, encompassing both embodied and operational carbon. This paper presents a novel computational approach to design Life Cycle Zero-Carbon Building (LC-ZCB), utilizing parametric integrated modeling through the versatile Grasshopper platform and its plug-ins. The Department of Energy’s prototype residential building at New York Institute of Technology, optimized to fulfill the LC-ZCB target, serves as the base building for this comprehensive study. Four main influencing design parameters, namely geometry, construction technology, thermal resistance of the envelope, and on-site renewable energy production, are defined and three-hundred design combinations are evaluated through the assessment of the operational carbon (OC) and embodied carbon (EC). By incorporating bio-based materials in the design options, the influence of biogenic carbon on the whole carbon footprint of the building case study is addressed by utilizing the GWPbio dynamic method, which assumes 100-year time horizon and incorporates dynamic characterization factors based on time of pulse emissions and two variables: rotation of the biomass and storage period of carbon in products. Finally, to account for potential climate changes, future climate data and 2099 weather conditions are considered during the scenarios assessment. The results demonstrate the potential for achieving LC-ZCB when fast growing biobased materials are largely used as construction materials, fostering a more environmentally responsible future for the construction industry.

A layout of urban waste fired zero emission power plant is described in this paper. The principle of layout, which comes from similar coal-fired plants retrieved from the literature, integrates gasification with a power generation section, and implements two parallel conversion processes, one supplied by the heat of the gasifier consisting of a thermoacousticmagnetohydrodynamic (TAMHD) generator, while in the second one the syngas is treated in order to obtain almost pure hydrogen, which is fed to fuel cells. The CO2 deriving from the oxidation of Carbon base is stocked in liquid form. The novelty of the proposed layout lies in the fact that the entire conversion is performed without solid moving parts. The resulting plant avoids any type of emissions in the atmosphere, increases mechanical efficiency as compared to traditional plants, thanks to the absence of moving parts, nonetheless, resolving at its root the ever-increasing waste-related pollution problems.

Transitioning towards net zero emissions is critical in the chemical and process industries to combat climate change and ensure environmental sustainability. Key focus areas of this review include the reduction of carbon emissions, the efficient utilization of energy resources, and the adoption of sustainable practices. Cutting-edge technologies such as biomass utilization, biotechnology applications, and waste management strategies are crucial in achieving this transition. Industries, including cement production, encounter unique challenges in their quest for sustainability and must actively seek innovative solutions to mitigate their carbon footprint effectively. The role of hydrogen as a clean fuel and its potential to revolutionize the chemical and process sectors is also discussed. The European Green Deal and Sustainable Development Goals (SDGs) are significant for the chemical industry. They provide a clear roadmap and framework for promoting sustainability, driving innovation, and reducing the industry's environmental impact. By aligning with these initiatives, the chemical industry can enhance its competitiveness, contribute to societal well-being, and foster collaboration across sectors to achieve shared sustainability objectives.

Abstract: Establishing carbon neutrality (or Net Zero) in cities appears to be an ambitious challenge, which drives urban transformation efforts around the world to enhance people-centric living. Cities launch corresponding strategies focusing mainly on the United Nations 2030 goals to form their climate-neutral future. This paper provides practical guidance on city digital transformation to achieve carbon net zero. These guidelines illustrate actionable recommendations to reduce their carbon footprint using digital technologies. Following a multi-method research approach, findings from a bibliometric literature and a standards’ gap analysis were combined with practical evidence and circulated with focus group experts to conclude to these guidelines, which are the foundation for further standardization. The outcomes provide concrete guidelines to policymakers, planners, and other stakeholders for city digital transformation to establish carbon neutrality, via emphasizing the need for digital technologies to enhance efficiency in several areas and via leveraging green ICTs for city economic growth while also transforming citizen behavior.

Semi-structured complex numbers H was a number set developed to enable division by zero in ordinary algebraic equations. Its utility has been shown in mathematics and engineering. However, very little has been done to show its usefulness in computer science. Consequently, the aim of this paper was to show the utility of semi-structured complex numbers in computer science by developing a division by zero calculator. First two computer programs were written, one for a standard (STD) calculator and the other for a division by zero (DBZ) calculator. The programs were fed 20000 randomly generated arithmetic equations of varying lengths and the space and time complexity associated with processing these equations were measured and compared to determine the efficiency of each calculator. In the process, three major contributions were made: (1) A representation for semi-structured complex numbers that enables it to be easily used by a computer was developed; (2) It was demonstrated that the DBZ calculator outperforms the STD calculator in terms of efficiency; and, (3) It was shown that the number set H reduced the amount of error handling required to run a computer program. These results provide a firm foundation to advance the number set as a useful tool in computer science.

The relation between CO2 emissions and atmospheric CO2 concentration has traditionally been treated with more or less complex models with several boxes. Our approach is motivated by the question of how much CO2 must necessarily be absorbed by sinks. Observations lead to the model assumption, that carbon sinks like oceans or biosphere are linearly dependent on CO2 concentration on a decadal scale. In particular this implies the falsifiable hypothesis that oceanic and biological CO2 buffers have not significantly changed in the past 50 years and are not saturated in the forseeable future. The simple model with 2 parameters explains very well the CO2 emission and historical CO2 concentration data. The model gives estimates of the natural emissions, the pre-industrial CO2 equilibrium concentration levels, the half-life time of an emission pulse, and the future CO2 concentration level from a given emission scenario. This is validated by an ex-post forecast of the last 20 years. The important result is that with the stated polices scenario of the IEA future CO2 concentrations will not rise above 475 ppm. The model is compared with the Carbon modul of the Bern model, mapping their complex IRFs to a single time variant parameter.

In this study, we discuss the properties of absolute vacuum space and how these properties can play a vital role in creating a mechanism in which the very first particle gets created simultaneously everywhere and we find the limit in which when the absolute vacuum volume reaches will lead to the collapse that leads to the creation of the first particle. This discussion is made following to the elementary dimensions theory study that was peer-reviewed at the end of 2020, everything in the universe is made from four elementary dimensions, these dimensions are the three spatial dimensions (X, Y, and Z) and the Vacuum resistant as the factor of change among the four, time itself wasn’t considered as the fourth dimension, rather time corresponds to a factor of change, and during the research it was found out that the Vacuum resistant is the factor of change in the Absolute Vacuum space, where time is a hypothetical concept, that represents changes during certain events compared to a constant change rate event.Therefore, time does exist, but as a factor of change, and as the Vacuum resistant in the absolute vacuum space, Time= factor of change= Vacuum resistant. In the study, the internal and external vacuum resistant volume equivalent is found, External Vacuum resistant=3.2857602*10^15 *mass. This equation is used to identify the amount of Free external vacuum resistant created during nuclear fission and fusion: Initial mass of the excited nucleuses mass of the created new nucleuses+ 3.2857602*10^15 * the lost Mass. In elementary dimensions, the energy created during nuclear reactions is equivalent to the free External vacuum resistant created through nuclear reactions, and mass is equivalent to the internal Vacuum resistant.