We prove the continuous non-Archimedean (resp. p-adic) Banach space and Hilbert space versions of non-Archimedean (resp. p-adic) Welch bounds proved by M. Krishna. We formulate continuous non-Archimedean and p-adic functional Zauner conjectures.

We prove the non-Archimedean (resp. p-adic) Banach space version of non-Archimedean (resp. p-adic) Welch bounds recently obtained by M. Krishna. More precisely, we prove following results. \begin{enumerate}[\upshape(i)] \item Let $\mathbb{K}$ be a non-Archimedean (complete) valued field satisfying $\left|\sum_{j=1}^{n}\lambda_j^2\right|=\max_{1\leq j \leq n}|\lambda_j|^2$ for all $ \lambda_j \in \mathbb{K}, 1\leq j \leq n$, for all $n \in \mathbb{N}.$ Let $\mathcal{X}$ be a $d$-dimensional non-Archimedean Banach space over $\mathbb{K}$. If $\{\tau_j\}_{j=1}^n$ is any collection in $\mathcal{X}$ and $\{f_j\}_{j=1}^n$ is any collection in $\mathcal{X}^*$ (dual of $\mathcal{X}$) satisfying $f_j(\tau_j) =1$ for all $1\leq j \leq n$ and the operator $S_{f, \tau} : \text{Sym}^m(\mathcal{X})\ni x \mapsto \sum_{j=1}^nf_j^{\otimes m}(x)\tau_j^{\otimes m} \in \text{Sym}^m(\mathcal{X})$, is diagonalizable, then \begin{align}\label{NONFUNCTIONALWELCH} \max_{1\leq j,k \leq n, j \neq k}\{|n|, |f_j(\tau_k)f_k(\tau_j)|^{m} \}\geq \frac{|n|^2}{\left|{d+m-1 \choose m}\right| }. \end{align} We call Inequality (\ref{NONFUNCTIONALWELCH}) as non-Archimedean functional Welch bounds. \item For a prime $p$, let $\mathbb{Q}_p$ be the p-adic number field. Let $\mathcal{X}$ be a $d$-dimensional p-adic Banach space over $\mathbb{Q}_p$. If $\{\tau_j\}_{j=1}^n$ is any collection in $\mathcal{X}$ and $\{f_j\}_{j=1}^n$ is any collection in $\mathcal{X}^*$ (dual of $\mathcal{X}$) satisfying $f_j(\tau_j) =1$ for all $1\leq j \leq n$ and there exists $b \in \mathbb{Q}_p$ such that $ \sum_{j=1}^{n}f_j^{\otimes m}(x) \tau_j^{\otimes m} =bx$ for all $ x \in \text{Sym}^m(\mathcal{X}),$ then \begin{align}\label{PADICFUNCTIONALWELCH} \max_{1\leq j,k \leq n, j \neq k}\{|n|, |f_j(\tau_k)f_k(\tau_j)|^{m} \}\geq \frac{|n|^2}{\left|{d+m-1 \choose m}\right| }. \end{align} We call Inequality (\ref{PADICFUNCTIONALWELCH}) as p-adic functional Welch bounds. \end{enumerate} We formulate non-Archimedean functional and p-adic functional Zauner conjectures.

The paper introduces and describes the recent and still ongoing development activities performed in Luxembourg for In-Orbit Attach Mechanisms for (Drag) Sails Modules to be operated from Space Tugs. After some preparatory work aiming at understanding the possible operational aspects, three designs have been completed for their 3D (Metal and Plastic) Printing. The Plastic-printed prototype underwent a series of automated tests where a robotic arm, equipped with an advanced force sensor, replicated four docking scenarii in ideal and degraded modes. The observation of the forces and torques behaviors at and after impact allowed to characterize the typical patterns for the various contacts but also, to identify a type of impact potentially dramatic for the safety of the docking and its equipment: in case of off-axis approach, “point” contacts shall be avoided as they instantaneously transfer the total kinetic energy in a small area that could break.

Chipman contends, in stark contrast to the conventional view, that utility is not a real number but a vector and is inherently lexicographic in nature. According to these views, it will be proved that, for every preordered topological space (X,≾,t), the assumption t to be finer than the order topology t≾ on (X,t), i.e. t⊇t≾, and the assumption the quotient topology t∣∼≾ that is defined on the preordered set (X∣∼,≾∣∼) of indifference classes of ≾ to be Hausdorff imply that a cardinal number κ and a (complete) preorder ≲ on {0,1}κ that is coarser than the lexicographical ordering ≤lex on {0,1}κ, i.e. ≤lex⊂≲, can be chosen in such a way that there exists a continuous order-embedding ϑ:(X,≾,t)⟶({0,1}κ,≲,t≤lex). This theorem will be compared with a theorem that, in particular, describes necessary and sufficient conditions for ≾ to have a continuous multi-utility representation.

On the basis of the findings of this paper, the theories of quantum mechanics and general relativity can be expressed in a comprehensive theory. The events were surveyed length of the time, in the Euclidean six-dimensional space-time (R6=x1+x2+x3+t1+t2+t3). Previous studies have not studied the relationship between the origin of matter's inherent properties, fundamental constants, and quantum mechanics phenomenon with space-time geometry. This theory prediction the with certainty obtained probabilistic results of quantum mechanics. This prediction is on the basis of metric resulting from the Eccentricity of the Ellipse due to the object density, in the length of time. The cause and nature of dark matter and dark energy are the findings of this article.

The unexploited unification of quantum physics, general relativity and biology is a keystone that paves the way towards a better understanding of the whole of Nature. Here we propose a mathematical approach that introduces the problem in terms of group theory. We build a cyclic groupoid (a nonempty set with a binary operation defined on it) that encompasses the three frameworks as subsets, representing two of their most dissimilar experimental results, i.e., 1) the commutativity detectable both in our macroscopic relativistic world and in biology; 2) and the noncommutativity detectable both in the microscopic quantum world and in biology. This approach leads to a mathematical framework useful in the investigation of the three apparently irreconcilable realms. Also, we show how cyclic groupoids encompassing quantum mechanics, relativity theory and biology might be equipped with dynamics that can be described by paths on the twisted cylinder of a Möbius strip.

Room-temperature phosphorescent (RTP) materials have been attracted tremendous interest owing to their unique material characteristics and potential applications for state-of-the-art optoelectronic devices. Recently, we have reported a synthesis and fundamental photophysical properties of new RTP materials based on benzil, i.e., fluorinated monobenzil derivative and fluorinated and non-fluorinated bisbenzil derivative analogues [Yamada, S. et al, Beilstein J. Org. Chem. 2020, 16, 1154–1162.]. To further understand their RTP properties, here we investigated the excited-state dynamics and photostability of the derivatives by means of time-resolved and steady-state photoluminescence spectroscopies. For these derivatives, clear RTP emissions with lifetimes on the microsecond timescale were identified. Among them, the monobenzil derivative was found to be the most efficient RTP material, showing both the longest lifetime and highest amplitude RTP emission. Time-resolved photoluminescence spectra measured at 77 K and density functional theory calculations revealed the existence of a second excited triplet state in the vicinity of the first excited singlet state for the monobenzil derivative, indicative of the presence of a fast intersystem crossing pathway. A discussion of the correlation between the excited state dynamics, emission properties, and conformational flexibility of the three derivatives is presented.

The excited-state lifetimes of the anticoagulant drug warfarin (W) in water and in the absence and presence of methyl-β-cyclodextrins (Me-β-CD) were recorded using time-resolved fluorescence measurements. Selective excitation of the open and cyclic protonated isomers of W were acquired with laser emitting diodes (LED) producing 320 and 280 nm excitation pulses, respectively. Formation of the inclusion complex was checked by UV–visible absorption spectroscopy, and the values of binding constants (2.9 × 10³ M^–1 and 4.2 × 10² M^–1 for protonated and deprotonated forms, respectively) were extracted from the spectrophotometric data. Both absorption and time-resolved fluorescence results established that the interior of the macromolecular host binds preferentially the open protonated form, red shifts the maximum of its absorption of light at ~305 nm, extends its excited-state lifetime, and decreases its emission quantum yield (ФF). Collectively, sequestration of the open guest molecules decreases markedly their radiative rate constants (kr), likely due to formation of hydrogen-bonded complexes in both the ground and excited states. Due to lack of interactions, no change was observed in the excited-state lifetime of the cyclic form in the presence of Me-β-CD. The host also increases the excited-state lifetime and ФF of the drug deprotonated form (W¯). These later findings could be attributed to the increased rigidity inside the cavity of Me-β-CD. The pKa values extracted from the variations of the UV–visible absorption spectra of W versus the pH of aqueous solution showed that the open isomer is more acidic in both ground and excited states. The positive shifts in pKa values induced by three derivatives of cyclodextrins: HE-β-CD, Ac-β-CD, and Me-β-CD supported the preferential binding of these hosts to open isomers over cyclic.

We delve into the axion-dilaton model within the supergravity framework, with a specific focus on the intricacies of domain wall construction and stability. Employing holographic vitrification, we unravel the dynamics of domain wall formation in gauge theories featuring periodic vacuum structures. Our model, incorporating a QCD-like axion term and a stabilizing dilaton, undergoes scrutiny for conductivity variations under weak disorder. The investigation reveals the model's resilience, manifesting near-perfect conductivity under mild disorder conditions. However, the rigorous mathematical motivation for the holographic setup demands further elucidation. The scattered nature of our results prompts the necessity for a more systematic interpretation of QCD phenomena and conductivity transitions. This study contributes to the mathematical understanding of the axion-dilaton model's behavior, highlighting the imperative for a refined holographic framework and a more coherent interpretation of observed phenomena.

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modelling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modelling frameworks have proved useful for explaining ecosystem response to perturbations, while requiring fewer information and providing more general predictions. However, current qualitative methods have some shortcomings which may limit their utility for specific issues. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modelling framework based on "if-then" rules which generates many alternative event sequences (trajectories). Based on expert knowledge, observations and literature, we use this framework to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups had highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modelling.

This paper presents a novel method to extract local features, which instead of calculating local extrema computes global maxima in a discretized scale-space representation. To avoid obtaining precise scales by interpolation and to achieve perfect rotation invariance, two essential techniques, increasing the width of kernels in pixel and utilizing disk-shaped convolution template are adopted in this method. Since the size of a convolution template is finite and finite templates can introduce computational error into convolution, we sufficiently discuss this problem and work out an upper bound of the computational error. The upper bound is utilized in the method to ensure that all features obtained are computed under a given tolerance. Besides, the technique of relative threshold to determine features is adopted to reinforce the robustness for the scene of changing illumination. Simulations show that this new method attains high performance of repeatability in various situations including scale change, rotation, blur, JPEG compression, illumination change and even viewpoint change.

When an earthquake or a large fire has occurred, it is difficult to secure communication networks for rescue in the building due to the destruction of commercial communication networks. Although analog radio systems such as VHF (very high frequency) and UHF (ultra-high frequency) are used for rescue operation in general, communication failure occurs in closed spaces, causing difficulties in smooth rescue operations. When the communication infrastructures have been destroyed in a building in the disaster, an emergency wireless telecommunication environment should be constructed to secure a safer disaster response environment. In this study, along with comparison of the performances of diverse communication frequencies, UWB (Ultra-Wide Band) wireless telecommunication networks were evaluated under five building indoor environment conditions including open spaces. UWB communication modules were fabricated to satisfy the IEEE (The Institute of Electrical and Electronics Engineers) 802.15.4a standard performance to measure distances in which communications are possible according to the indoor environment for each of six channels with different UWB communication frequencies. The results indicated that the distances in which communications are possible for each the six channels were average 15.5 m, maximum 20 m in open spaces; average 17.33 m, maximum 20 m in corridors; average 15.3 m, maximum 20 m in indoor office environments with office fixtures; average 4.33 m, maximum 6 m in vertical spaces of stairs; and average 6.5 m, maximum 17 m in closed horizontal spaces with a fire door. In this case, the communication performance and distance performance were shown to be the most excellent at a frequency (Centre Frequency) of 6489.6 and a band of 5980.3 – 6998.9 MHz, which is UWB 7ch. In conclusion, it is judged that if UWB communication modules are installed in the disaster area at intervals of 20 m and multi-channels are used, communication environments can be constructed even in closed spaces

Hydrogenated amorphous silicon (a-Si:H) can be produced by plasma-enhanced chemical vapour deposition (PECVD) of SiH4 (Silane) mixed with Hydrogen. The resulting material shows outstanding radiation resistance properties and can be deposited on a wide variety of different substrates. These devices have been used to detect many different kinds of radiation namely: MIPs, x-rays, neutrons and ions as well as low energy protons and alphas. However, MIP detection using planar diodes has always been difficult due to the unsatisfactory S/N ratio arising from a combination of high leakage current, high capacitance and a limited charge collection efficiency (50% at best for a 30 µm planar diode). To overcome these limitations the 3D-SiAm collaboration proposes to use a 3D detector geometry. The use of vertical electrodes allows for a small collection distance to be maintained while conserving a large detector thickness for charge generation. The depletion voltage in this configuration can be kept below 400 V with consequent reduction in the leakage current. In this paper, following a detailed description of the fabrication process, the results of the tests performed on the planar p-i-n structures made with ion implantation of the dopants and with carrier selective contacts will be illustrated.

State legitimacy and effectiveness could be seen by the way to deliver welfare to citizens to mitigate social grievances, that could eventually lead to conflicts (Kivimäki, 2021). Social security systems in Maghreb countries are quite similar in their architecture and aims to provide social insurance to all the workers in the labor market. However, they suffer from the same main problem: the low rate of enrollment of workers. Many workers (employees and self-employed) work informally without any social security coverage. The issue of whether informal jobs are chosen voluntarily by workers or as a strategy of last resort is controversial. Many authors recognize that the informal sector is heterogeneous and it is made up of workers who voluntary choose it and others who are pushed inside because of entry barriers to the formal sector (Günther & Launov, 2012). Using the SAHWA survey and discrete choice models, this article confirms the heterogeneity of the informal labor market in three Maghreb countries: Algeria, Morocco, and Tunisia. Furthermore, this article highlights the profiles of workers who voluntarily choose informality, which is missing from previous studies. Finally, this article proposes policy recommendations in order to extend social security to informal workers and to include them in the formal labour market.

We are using the book “Towards Quantum Gravity with an article by Claus Kiefer as to a quantum gravity interpretation of the density matrix in the early universe. The density matrix we are using is a one loop approximation, with inflaton value and potential terms, like V(phi) using the Padmanabhan values one can expect if the scale factor is a ~ a(Initial) times t ^ gamma , from early times . In doing so, we isolate out presuming a very small initial time step candidates initial time values which are from a polynomial for time values due to the Kiefer Density value.

The study of the area model of Pinus tabulaeformis forest provides an important reference for improving the management of Pinus tabulaeformis and revealing the growth law of Pinus tabulaeformis. According to the classification method proposed by Munro, stand growth and harvest prediction models are divided into three categories: full stand model, single wood model and diameter distribution model. Based on the fixed sample data of Shangluo Pinus tabulaeformis, the spatial instead of time method is used to process the data, and the weight coefficient of each model in the combined prediction model is calculated by using the optimal weighting method. The single wood model, the whole forest model and the diameter distribution model are combined by the combined prediction method to integrate the fault area prediction of Pinus tabulaeformis forest. The results show that the combined prediction method is more accurate than the single model (single wood model, whole forest model and diameter distribution model). At the same time, the method can improve the compatibility of the forest break area prediction model, ensure the consistency of the forest break area prediction, and provide a new direction for the research of forest resource monitoring and investigation.

In the study of rough sets, there are many covering approximation spaces, how to classify covering approximation spaces has become a hot issue. In this paper, we propose concepts covering approximation $T_{1}$-space, $F-$symmtry, covering rough continuous mapping, covering rough homeomorphism mapping to solve this question. We also propose a new method for constructing topology in Theorem 5.1, and get the following properties: (1) For each $x\in U$, $\{X_{i}:i\in I\}\subseteq \mathcal{P}(U)$ is all the subsets of $U$ which contains $x$ and $*$ is a reflexive relation on $U$. If $V\in \tau$ is a subset of $U$ and $x\in V$, then $\underline{*}(\bigcap \limits_{i\in I}X_{i})$ is the smallest subset of $U$ and $x \in \underline{*}(\bigcap \limits_{i\in I}X_{i})\subseteq V$. Denoted by $C(x)=\bigcap \{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$. (2)If $V\in \tau$ is a subset of $U$, then $V =$ $\bigcup \limits_{x\in V} C(x)$. (3) Let $\{\underline{*}(X_{i}):x\notin \underline{*}(X_{i}), i\in I\}$, then $\overline{\{x\}}$ $=$ $U \setminus \bigcup \limits_{x\notin \underline{*}(X_{i}), i\in I}\underline{*}(X_{i})$; (4) Let $*$ be a reflexive relation on $U$. For every $X\subseteq U$, we have $int(\underline{*}(X))=\underline{*}(X)$. Where $int(\underline{*}(X))$ represents the interior of $\underline{*}(X)$. (5) Let $\{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$ be a family subsets of $U$, then $\{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$ is a base for $(U,\tau)$ at the point $x$. \\

Along with environmental pollutions, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, the consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and consequently, the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.

The purpose of this study was to evaluate the bioactivity and cell response of a well-characterized Nurse´s A-phase (7CaO•P2O5•2SiO2) ceramic and his effect compared to a control (tissue culture polystyrene-TCPS) on the adhesion, viability, proliferation and osteogenic differentiation of ahMSCs in vitro. Cell proliferation (Alamar Blue Assay), Alizarin Red-S (AR-s) staining, alkaline phosphatase (ALP) activity, osteocalcin (OCN) and collagen I (Col I) were evaluated. Also, field emission scanning electron microscopy (FESEM) images were acquired in order to visualise the cells and the topography of the material. The proliferation of cells growing in a direct contact with the material was slower at early stages of the study because of the new environmental conditions. However, the entire surface was colonized after 28 days of culture in growth medium (GM). Osteoblastic differentiation markers were significantly enhanced in cells growing on Nurse´s A phase ceramic and cultured with osteogenic medium (OM), probably due to the role of silica to stimulate the differentiation of ahMSCs. Moreover, calcium nodules were formed under the influence of ceramic material. Therefore, it is predicted that Nurse´s A-phase ceramic would present high biocompatibility and osteoinductive properties being a good candidate to be used as a biomaterial for bone tissue engineering.

SiOx films, frequently derived from amino silane precursors, have found several applications with high added value. Although frequently used, the deposition of coatings from Tris(dimethyl amino)silane (TDMAS) has been reported to demand considerable amounts of energy, mainly due to the difficulty of oxidizing such compound. As it is well known, Plasma-enhanced atomic layer deposition (PEALD) is able to improve the oxidation efficiency even under low process temperatures. Owing to that, PEALD can be considered as a very promising technique for the deposition of SiOx coatings. In this work, it has been investigated the deposition of silicon oxide films using TDMAS at 150°C. It has been evaluated the effect of the plasma oxidation time (6 to 18 s) and of the atmosphere composition (pure O2 or O2+Ar) on the chemical structure, elemental composition and chemical bonding state of the films. Increasing the plasma oxidation time in pure O2 resulted in larger proportion of retained C (Si-CH3) whereas N was preserved in the structure (Si-N). on the other hand, the formation of SiOx films from TDMAS is favored in shorter oxidation times in O2 + Ar plasmas.

Thermodynamics and phase transitions of magnetic Anti-de Sitter black holes are studied. We consider an extended phase space thermodynamics with the cosmological constant being a thermodynamic pressure and the black hole mass is treated as a chemical enthalpy. The extended phase space thermodynamics of black holes mimics the behavior of the Van der Walls liquid. Quantities conjugated to the coupling of nonlinear electrodynamics (NED) and a magnetic charge are obtained. Thermodynamic critical points of phase transitions are investigated. It is demonstrated that the first law of black hole thermodynamics and the generalized Smarr relation take place. The Joule--Thomson adiabatic expansion of NED-AdS black holes is studied. The dependence of inversion temperature on pressure and the minimum of inversion temperature are found.

Lack of due attention to the orientation of streets and establishment of urban blocks without regard for climatic characteristics and conditions of the environment have an adverse effect on thermal comfort in open urban spaces. Construction of new settlements without taking into account climatic requirements undermines thermal comfort for pedestrians and other users, especially in cold regions. Considering the coldness of the region under study and the significance of the orientation of streets in absorbing radiation and providing heat to outdoor urban spaces, this study investigates the effect of the orientation of streets on microclimatic comfort in one of the residential towns of Hamadan City in Iran. For this purpose, microclimate simulation was performed using ENVI-met software. A residential block with four different orientations (the most common orientations of its surrounding buildings) were simulated in the coldest day of winter and the hottest day of summer. The results suggest that streets have different thermal behavior in different orientations. Orientation affects mean radiant temperature (Tmrt), the duration of exposure to direct sunlight, wind speed, and physiological equivalent temperature (PET), which are all important factors in thermal comfort. Based on these findings, north-south streets in Hamedan receive more radiant temperature during winter compared to other simulated orientations and provide more desirable thermal comfort. The average PET value on a winter day at a point on the north-south passage was 4.5-8 °C warmer than other orientations. In summer, streets with intercardinal orientations (i.e., northeast-southwest and northwest-southeast) provided the lowest PET (about 2 °C cooler than other orientations) and better thermal comfort

A mathematical model given by a two - dimensional differential system is introduced in order to understand the transition process from the normal hematopoiesis to the chronic and accelerated acute stages in chronic myeloid leukemia. A previous model of Dingli and Michor is refined by introducing a new parameter in order to differentiate the bone marrow microenvironment sensitivities of normal and mutant stem cells. In the light of the new parameter, the system now has three distinct equilibria corresponding to the normal hematopoietic state, to the chronic state, and to the accelerated acute phase of the disease. A characterization of the three hematopoietic states is obtained based on the stability analysis. Numerical simulations are included to illustrate the theoretical results.

Background & Objectives: The global pandemic caused by novel coronavirus SARS-CoV-2 has claimed several lives worldwide. With the virus gathering rapid spread, the world has witnessed increasing number of confirmed cases and mortality rate, India is not far behind with approximately 37,000 affected individuals as on May 2, 2020. The ongoing pandemic has raised several questions which need to be answered by analysis of transmission of the infection. The data has been collected on daily basis from WHO and other sites. We have represented the data collated graphically using statistical packages, R and other online softwares. The present study provides a holistic overview of the spread of COVID-19 infection in India. Methods: Real-time data query was done based on daily observations using publicly available data from reference websites for COVID-19 and other government official reports for the period (15^th February, 2020 to April 28^th, 2020). Statistical analysis was performed to draw important inferences regarding COVID-19 trend in India. Results: A decrease in growth rate of cases due to COVID-19 in India post lockdown and improvement in recovery rate during the month of April was identified. The case fatality rate was estimated to be 3.22% of the total reported cases. State-wise analysis revealed a deteriorating situation in states of Maharashtra and Gujarat among others as cases continued to increase rapidly there. A positive linear correlation between the number of deaths and total cases and exponential relation between population density and number of cases reported per square km was established. Interpretation & Conclusions: Despite early preventive measures taken up by the Government of India, the increasing number of cases in India is a concern. This study compiles state-wise and district-wise data to report the daily confirmed cases, case fatalities and strategies adopted in the form of case studies. Understanding the transmission spread of SARS-CoV-2 in a diverse and populated country like India will be crucial in assessing the effectiveness of control policies towards the spread of COVID-19 infection.

(1) Background: The issue of human adaptation to the Arctic environmental factors is relevant. The adaptation can be assessed through dynamic monitoring of the functional state of a person during his/her stay there. The vitamin D level in blood is one of the markers of the functional reserves of the human body and can contribute to more successful adaptation in the Arctic. (2) Methods: The study involved 38 participants in the scientific and educational expeditionary project "Arctic Floating University-2021". Blood collection for determination of vitamin D content was carried out at the beginning of the expedition. A dynamic study was carried out for 20 days in the morning and in the evening during a marine scientific expedition to the Arctic. The main parameters of the functional state of the participants were assessed using instrumental psychophysiological, projective and questionnaire methods. Statistical methods: Mann-Whitney U-test, correlation analysis using the Spearman coefficient. (3) Results: It was found that at the beginning of the expedition, the functional state of participants with severe vitamin D deficiency is characterized by a shorter average duration of RR intervals and reduced SDNN values, which may indicate a higher level of regulatory mechanisms tension. The pronounced differences in the nature of the dynamic series of objective and projective working capacity parameters were manifested most clearly. According to the subjective questionnaire characteristics of well-being, activity and mood, no significant features of the participants with vitamin D deficiency were revealed. (4) Conclusion: The participants with vitamin D deficiency in blood are characterized by a reduced adaptive capacity during the expedition to the Arctic.

The theory of limited numbers says that the number is not infinite, that is, the number is limited in parts or completely. To reach a conclusion about the limited number, one must understand the meaning of mathematics and varied spaces, therefore, one must understand that mathematics and spaces interact. Mathematics has the function of describing the world precisely, where numbers represent elements or facts that rationally belong to space, and spaces have different intensities of specific physical concepts in each space; therefore, there is no infinite element or fact due to differences in the intensities of specific physical concepts in spaces that do not allow for the fact or fact in all spaces.

The detection of temporary color steel buildings and the analysis of their spatiotemporal patterns and characteristics are of great importance in many developing cities, because areas densely distributed with color steel buildings are usually problematic regions with high population density, sustainable development and risk level, which are challenging for local governments. Using the high-resolution satellite images of the Anning District, Lanzhou City, China as the case study, this paper first extracts the information of the color steel buildings for two different periods. Then the spatiotemporal distributional characteristics of the color steel buildings are analyzed, both at small scale (temporary buildings) and large scale (planthouses, warehouses, etc.). Finally, this paper utilizes kernel density estimation, Delaunay triangulation and Voronoi diagrams to examine the spatial distribution, aggregation and proximity characteristics of the color steel buildings. Our experiments show that the temporal and spatial differences of urban development, the phased characteristics and urban space are represented by various types of color steel buildings. Thus, there are some robust coupling relationship between color steel buildings, urban spatial form and urban development.

The formation of high-melting-point Cu₆Sn₅ interconnections is crucial to overcome the collapse of Sn-based micro-bumps and produce reliable intermetallic interconnections in three-dimensional (3D) package. However, because of the multiple reflows in 3D package manufacturing, Cu₆Sn₅ interconnections will experience the cyclic polymorphic transitions in the solid state. The repeated and abrupt change in the Cu₆Sn₅ lattice due to the cyclic polymorphic transitions can cause extreme strain oscillations, producing damages at the surface and in the interior of the Cu₆Sn₅ matrix. Moreover, because of the polymorphic-transition-induced grain splitting and superstructure phase formation, the reliability of Cu₆Sn₅ interconnections will thus face great challenges in 3D package. In addition, the Cu₆Sn₅ polymorphic transition is structure-dependent, and the η′↔η polymorphic transition will occur at the surface while the η′↔ηs↔η polymorphic transition will occur in the deep matrix. Our results can provide in-depth understandings of structural evolution and damage mechanism of Cu₆Sn₅ interconnections in real 3D package manufacturing.

Given a set of distinct non-negative integers X^n and a target certificate S in parametrized form: ∃X^k⊆X^n,∑_(x_i∈X^k)▒x_i =S (k=|X^k |,n=|X^n |). We present a polynomial solution of the subset sum problem with time complexity T≤O(kn)≤O(n^2) and space complexity S≤O(((n-1)n)/2)≤O(n^2 ), so that P = NP.

We study the resonant dipole-dipole interaction energy between two uniformly accelerated identical atoms, one excited and the other in the ground state, prepared in a correlated Bell-type state, and interacting with the scalar field or the electromagnetic field nearby a perfectly reflecting plate. We suppose the two atoms moving with the same uniform acceleration, parallel to the plane boundary, and that their separation is constant during the motion. We separate the contributions of vacuum fluctuations and radiation reaction field to the resonance energy shift of the two-atom system, and show that Unruh thermal fluctuations do not affect the resonance interaction, which is exclusively related to the radiation reaction field. However, nonthermal effects of acceleration in the radiation-reaction contribution, beyond the Unruh acceleration-temperature equivalence, affect the resonance interaction energy. By considering specific geometric configurations of the two-atom system relative to the plate, we show that the presence of the mirror significantly modifies the resonance interaction energy between the two accelerated atoms. In particular, we find that new and different features appear with respect to the case of atoms in the free space, related to the presence of the boundary and to the peculiar structure of the quantum electromagnetic field vacuum in the locally inertial frame. Our results suggest the possibility to exploit the resonance interaction between accelerated atoms, as a probe for detecting the elusive effects of atomic acceleration on radiative processes.

Our understanding of the diversity of life on our planet and the possibility of finding or sustaining life elsewhere in the universe plays a central role in supporting human space settling and exploration. Astrobiology and its outcomes require a multidisciplinary and comprehensive approach, in which the microbial, geological, chemical, astronomical, and physical domains of research are interlinked. An example of the applications of astrobiology and space microbiology is the use of extremophiles for in-situ resource utilization through biomining and bioleaching. To better understand the multidisciplinary research landscape in this area, we have quantitatively reviewed the global scientific literature on astrobiology with a focus on biomining and bioleaching through bibliometric network analysis, investigating patterns and trends in its development over time. The network analysis of the keywords co-occurrence highlights different connecting and overlapping clusters, illustrating the multidisciplinary character of astrobiology. Temporal analyses show a recent focus on topics related to microbiology and geomicrobiology, emphasizing the role that these fields will play in future astrobiology research. In conclusion, astrobiology, biomining, and bioleaching research are timely responding to the identification of these techniques as tools for biotechnological applications, expected to play a crucial role in long-term human space exploration.

Almost all single-family detached house in Canada consume huge electricity for space heating and domestic hot water (DHW) purposes. There are many possibilities to design an energy-efficient house. A solar water heating system can be used for domestic water and space heating. Water temperature can be kept constant always by connecting a heat pump or oil burner because solar energy is intermittent. Proper and optimized solar photovoltaic and collector design, tank design, heat pump selection, house insulation, total demand calculation in each section are essential. Energy-Efficient house design has been proposed with water heating and space heating system and compared with the existing system, solar PV based systems, and solar collector based system. The tracking and non-tracking based solar thermal collector based and the solar photovoltaic based system has been compared in this paper and investigate the suitable one for practically applicable and acceptable by the people. Simulation has been done by using the PolySun software. It found that by implementing the proposed PV based system with tracking is highly suitable considering lower cost, high output power, flexibility, easy installation.

We explore the possibility to form a physical theory in $C^4$. We argue that the expansion of our usual 4-d real space-time to a 4-d complex space-time, can serve us to describe geometrically electromagnetism and nuclear fields and unify it with gravity, in a different way that Kaluza-Klein theories do. Specifically, the electromagnetic field $A_\mu$, is included in the free geodesic equation of $C^4$. By embedding our usual 4-d real space-time in the symplectic 8-d real space-time (symplectic $R^8$ is algebraically isomorphic to $C^4$), we derive the usual geodesic equation of a charged particle in gravitational field, plus new information which is interpreted. Afterwards, we formulate and explore the extended special relativity and extended general relativity an $C^4$ or$R^8$. After embedding our usual 4-d space-time in $R^8$, two new phenomena rise naturally, that are interpreted as "dark matter" and "dark energy". A new cosmological model is presented, while the geometrical terms associated with "dark matter" and "dark energy" are investigated. Similarities, patterns and differences between "dark matter", "dark energy", ordinary matter and radiation are presented, where "dark energy" is a dynamic entity and "dark matter" reveal itself as a "mediator" betwen ordinary matter and "dark energy". Moreover, "dark matter" is deeply connected with "dark energy". Furthermore, the extended Hamilton-Jacobi equation of the extended space-time, is transformed naturally as an extended Klein-Gordon equation, in order to get in contact with quantum theories. By solving the Klein-Gordon equation analytically, we derive an eigenvalue for Higg's boson mass value at 125,173945 $Gev/c^{2}$. The extended Klein-Gordon equation, also connects Higg's boson (or vacuum) with Cosmology, due to the existence of our second "time" T (cosmological time), which serve us to connect quantum theories with Cosmology. Afterwards, in the general case, we explore the symmetries of the curved Hamilton-Jacobi equation locally, in order to investigate the consequences of a $C^4$ space-time in Standard Model. An extension to Standard Model is revealed, especially in the sector of strong nuclear field. The Stiefel manifold $SU(4)/SU(2)$ seems capable not only to describe the strong nuclear field but give us,as well, enough room to explore in the future, the possibility to explain quark confinment. Our extension, flavors firstly the unification of nuclear fields and afterwards the unification of nuclear fields with electromagnetic field. The desired grand unification, is achieved locally, through the symmetry group $GL(4,C)\simeq SO(4,4)\cap U(4)$ and we present a potential mechanism to reduce the existing particle numbers to just six. Afterwards,23 present the extended Dirac equation in $C^4$ space-time (Majorana-Weyl representation) plus a preliminary attempt to introduce a pure geometric structure for fermions. Finally, we consider a new geometric structure through n-linear forms in order to give geometric explanation for quantisation

Intratumoral heterogeneity can exist along multiple axes: Cancer Stem Cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple “attractors”. These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.

The use of natural stone has a historical and environmental value that makes it strategically valuable for landscape conservation in Europe. Marble, among others, is widely spread on Earth, and it offers high-performance features in architectural applications. However, the complexity of these formations and the rock variability in different ore bodies require detailed studies of the natural and induced stress state, the fracturing degree, and the influence of external factor (such as temperature and/or chemical agents) on the mechanical properties in order to optimize the exploitation processes by reducing extractive waste. This article shows a series of studies conducted by the authors over the last 20 years aimed at making the exploitation of marble blocks in the Carrara basin safer, more efficient, and, therefore, more sustainable. In particular, studies for increasing the knowledge on the natural and the induced stress state through on-site measurements and numerical modeling, studies to improve the quality of the exploited material through improvements of cutting technologies, studies to improve the knowledge of the mechanical behavior of the material under varying loads and temperature conditions and studies to improve the reuse of water materials and their reduction are reported.

The current regeneration mode of public space in the old city of Guangzhou is ineffective, thus necessitating supplementation with a more systematic methodology. The “plug-in design” targets sustainable regeneration while preserving the overall urban texture and context, i.e., has little impact on the spatial qualities of the old city. The ultimate goal is to activate the public space of the old city of Guangzhou point-to-area through the insertion of various plug-ins. In this study, the methodology is applied to Xudi Gaodi Street, the core area of the old city of Guangzhou, to explore its effects on sustainability. The internal public space is isolated and supplied with rigid and flexible plug-ins from multiple dimensions, which not only improves the spatial environment but also injects new urban formats. This work provides a specific solution for regeneration in Guangzhou’s old city while enhancing empirical knowledge of the plug-in design to support urban regeneration theory and further practical development.

Climate change is expected to affect the agricultural sector in ways that are often unclear to predict. If in the short- medium-terms farmers may adapt to climate change by adjusting agricultural practices, in the long-term these adjustments may become insufficient, forcing farmers to change their farming systems. The extent and direction in which these farming system transitions will occur is still a subject underexplored in the literature. We propose a new framework to explore the marginal effect of climate change on the choice of the farming system, while controlling the effect of other drivers known to also influence farming system choice. Using a spatial-explicit farming system choice-model developed by a previous study in an extensive agricultural region of southern Portugal, we applied a space-for-time approach to simulate the effect of climate change on the future dynamics of the farming systems in the study area. Results suggest that climate change will force many farmers to change the farming system in a foreseeable future. The extent of the projected changes in farming systems is likely to trigger significant social, economic, or environmental impacts, which should require early attention from policy makers.

This article presents the possibilities of using ferrite absorption material for shielding rooms with medical devices in order to additionally protect them against the limits of the electric component of the E field, which are up to 61 V/m. These values may appear in connection with the currently launched 5G system operating in the high-band frequency range, i.e. 28 GHz and 38 GHz, and may cause negative effects on the operation of medical devices. The possibilities of using ferrite absorption material for shielding rooms with medical devices were determined based on the results of measurements of the electrical properties of the ferrite material performed using two methods: the reflection method and the free space method. In the article, the complex electrical permittivity and complex magnetic permeability were determined for a ferrite plate based on measurements of the reflection coefficient and the transmission (attenuation) coefficient. The presented calculation and measurement results were used to show the properties of the ferrite material in the frequency range from 15 GHz to 45 GHz and to show the possibility of using it for shielding rooms as a material absorbing electromagnetic waves in this frequency range.

An information-theoretic data mining method is employed to analyze categorical spatiotemporal Geographic Information System land use data. Reconstructability Analysis (RA) is a maximum-entropy-based data modeling methodology that works exclusively with discrete data such as those in the National Land Cover Database (NLCD). The NLCD are organized into a spatial (raster) grid, and are available in consistent format for every five years from 2001 to 2021. An NLCD tool reports how much change occurred for each category of land use; for the study area examined the most dynamic class is Evergreen Forest (EFO), so the presence or absence of EFO in 2021 was chosen as the dependent variable that our data modeling attempts to predict. RA predicts the outcome with approximately 80% accuracy using a sparse set of cells from a spacetime data cube consisting of neighboring lagged-time cells. When the predicting cells are all Shrubs & Grasses there is a high probability for a 2021 state of EFO, while when the predicting cells are all EFO, there is a high probability that the 2021 state will be not-EFO. These findings are interpreted as detecting forest clear-cut cycles that show up in the data, and explain why this class is so dynamic. This study introduces a new approach to analyzing GIS categorical data and expands the range of applications that this entropy-based methodology can successfully model.

We provide methodology and numerical results for the Hattendorff differential equa- tion for the continuous time evolution of the variance of L(j)t , the loss at time t random variable for a multi-state process, given that the state at time t is j.

Background: Healthcare workers are exposed to several hazardous chemicals in the workplace that can result in numerous adverse health effects. Several published studies from many different countries have documented the presence of metabolites from antineoplastic drugs in the urine of healthcare workers and demonstrated contaminated working surfaces with these agents. This study is a literature review that aims to compare the prevalence and degree of exposure to cyclophosphamide (CP), ifosfamide (IFO), and methotrexate (MTX) in physicians, nurses, and pharmacists in the hospital setting. Methods: An extensive search was conducted on PubMed, Google Scholar, HINARI, OARE, and Science Direct where applicable research about healthcare workers and antineoplastic drugs exposure were identified. Medical Subject Headings (MeSH) keywords: occupational exposure, antineoplastic drugs (cytotoxic drugs, cyclophosphamide, ifosfamide, methotrexate), hazardous chemicals, healthcare workers (healthcare professionals, nurses, pharmacists, physicians), hospital setting, and adverse health outcomes were used. Thereafter, relevant articles from 2000 to 2020 were selected to perform this literature review. Results: Review of literature demonstrated that cyclophosphamide was the most prevalent contaminant in the hospital setting. Additionally, pharmacists are among the group of healthcare workers with the highest prevalence of antineoplastic agents in urine samples while nursing stations had the highest rate of surface contamination. Conclusion: There is an urgent need to develop a system to monitor and detect the pathway of environmental exposure to antineoplastic drugs in the healthcare setting, and to evaluate the effectiveness of the existing protective measures. Well designed studies focusing on improving the standard safety precautions is a priority to protect healthcare workers.

Energy supply interruptions or blackouts caused by faults in power distribution feeders entail several damages to power utilities and consumer units: financial losses, damage to power distribution reliability, power quality deterioration, etc. Most studies in the specialized literature concerning faults in power distribution systems present methodologies for detecting, classifying, and locating faults after their occurrence. In contrast, this study aims to prevent faults by estimating the city regions whose power grid is most vulnerable to them. This work incorporates the geographic space study to prevent faults in the distribution power grid through a spatial data analysis using local variables that increase the fault risk in feeders in some city regions. Geographically weighted spatial analysis is applied to data aggregated by regions to produce thematic maps with the city regions whose feeders are more vulnerable to failures. Spatial data analysis is developed in QGIS and R programming environments. It is applied in real data of electrical discharges in a medium-sized city with approximately 200,000 inhabitants. In this study, we highlight a moderate positive correlation between electrical discharge density and the percentage of faults in transformers by regions in the central and western areas of the city under study.

Recent successes in the field of evolutionary cancer cell biology (ECCB) have brought to a head two of the most important controversies regarding cancer origin. The first concerns the question of whether carcinogenesis is initiated only by genetic alterations, mutations, and driver genes, as the mutational theory teaches. The ECCB, claims that a large number of polyploidy-related cancers (PGCC cancers) are not due to mutations, but rather to inadequate ancient repair mechanisms used by DNA-damaged stem cells for their repair. Somatic mutations are merely secondary. The second controversy, described in the previous article, concerns the non-mutational theory itself: Are non-mutational polyploid cancers an atavism - as previously thought - or rather the effect of an ancient gene regulatory network aGRN that controls genome reprogramming in precancerous DNA-damaged cells as well in the transformed cells. Finally, the unicellular gene module of cancer, of which the aGRN is a part, has evolved along with the multicellular genome during the last 1000 My of evolution. and non-mutated cancer cell systems are under the control of the aGRN. The atavistic theory relies on phylostratigraphic evidence to determine the age of cancer genes. It states that most cancer-like genes arose during the transition period from unicellularity to multicellularity, but also during the early metazoan era. In our opinion, the atavistic theory is flawed and suffers from many misunderstandings. It provides little insight into the origin and coevolution of the cancer cell system and its control by the ancient gene regulatory network aGRN.

Diet modification may be a potential contributor in the prevention of age-related cognitive decline. The association between dairy product consumption and cognitive function remains unknown in older people. We investigated whether cheese intake is associated with lower cognitive function (LCF) in community-dwelling older adults. This cross-sectional study included 1503 adults aged over 65 years. Analyzed data were obtained from face-to-face interviews and functional ability measurement. Cognitive function was assessed using mini-mental state examination (MMSE), and a score ≤ 23 was defined as LCF. The prevalence of LCF was 4.6% and this group had smaller calf circumference, slower usual walking speed, and more frequent history of anemia than subjects with MMSE scores ≥ 24. After adjusting for confounding factors, logistic regression analysis revealed cheese intake (odds ratio (OR) = 0.404, 95% confidence interval (CI) = 0.198-0.824), age (OR = 1.170, 95% CI = 1.089-1.256), usual walking speed (OR = 0.171, 95% CI = 0.062-0.472) and calf circumference (OR = 0.823, 95% CI = 0.747-0.908) as significant factors associated with LCF. Although the present study was an analysis of cross-sectional data of Japanese community-dwelling older adults, the results suggest that cheese intake is inversely associated with LCF.

The evolution in the post shock nonequilibrium relaxation in a hypersonic plasma flow was investigated during a shock’s reflection off a thermal discontinuity. Within a transitional period, the relaxation zone parameters past both, the reflected and transmitted waves, evolve differently compared to that in the incident wave. In a numerical example for the non-dissociating N₂ gas heated to 5000 K/10,000 K across the interface and M = 3.5, the relaxation time for the transmitted wave is up to 50% shorter and the relaxation depth for both waves is significantly reduced, thus resulting in a weakened wave structure. The results of extension into larger values of heating strength and the shock Mach numbers are discussed. The findings can be useful in the areas of research involving strong shocks interacting with optical discharges or other heated media on the scale where the shock structure becomes important.

Aim. In the current study, we aimed at identifying resting-state brain networks, which are different in patients with depression compared to healthy individuals. Moreover, we analyzed the potential for clinical use of different network measures that could discriminate the two groups and thus help the diagnostic process. Method and subjects. We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed to investigate functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were made at the functional networks level, using false discovery rate method. Independent samples t-test was performed on the network measures mean values to reveal differences between HC and MDE groups. Permutation-based statistical testing was used to test the significance of the difference between the distributions of the network measures by nodes for HC and MDE groups. Linear discriminant analysis was used to differentiate between the groups. Results and discussion. Significant differences in FC between depressed patients and healthy controls were found with the most prominent changes encompassing within-region as well as between-region connectivity of occipital lobe areas such as precuneus (PreCu), cuneus (Cu), superior occipital gyrus (SOG), lingual gyrus (LG), fusiform gyrus (FG), cerebellum, along with limbic structures including the hippocampus (Hipp) and cingulate gyrus. Linear discriminant analysis demonstrated that the full connectivity matrices, as well as those with only the significant connections identified in advance, were the most precise in differentiating between depression and health. These measures reached precision levels of 97% and 94%, respectively. Conclusion. Our study delivered further evidence about impairment of functional connectivity networks in MDE that may contribute to differentiate patients with depression from healthy subjects.

In this paper, a metal cutting machine position control have been designed and simulated using Matlab/Simulink Toolbox successfully. The open loop response of the system analysis shows that the system needs performance improvement. Static output feedback and full state feedback H₂ controllers have been used to increase the performance of the system. Comparison of the metal cutting machine position using static output feedback and full state feedback H₂ controllers have been done to track a set point position using step and sine wave input signals and a promising results have been analyzed.

To embrace the special theory of relativity with classical thermodynamics correct Lorentz transformations of thermodynamic state functions are formulated. All of these Lorentz transformations of state functions equally support the time dilation phenomenon which is experimentally verified fact. Relativistic Boltzmann constant proves entropy to be the Lorentz variant. Twin paradox thought experiments for heat engines prove heat flux to be Lorentz variant. Lorentz transformation of entropy and heat flux proves temperature Lorentz invariant. All thermodynamic state functions are proved to be Lorentz variant which is shown in accord with Lorentz transformation of thermodynamic work.

Smart cities and smart technologies have been incorporated into several axes to increase the comfort of life. The connected building's concept was introduced for this reason. However, it was utilized in power management for better organizing, greater buildings management, and monetary savings. Cars technologies and the number of vehicles are also involved; Nowadays, each house has at least one car. Technological evolution helped to make those cars intelligent and connected. In the latest versions, the majority of those cars were equipped with several sensors, several communication protocols and a principal electrical control unit (ECU), especially for the electric vehicle model. This type of architecture was an essential element in a smart city, thus, it helps to manage power and decide when a vehicle needs to be charged. Based on the smart city concept and using possible network communication between buildings and vehicles, EVs can share their own information related to the powerful experience on a specific path. This information can be gathered in a gigantic database and used for managing the power inside these vehicles. In this field, we propose in this paper a new approach for power management inside an electric vehicle based on bi-communication between vehicles and buildings. The proposed approach is founded on two essential parts; the first is related to vehicles’ classification and buildings’ recommendation according to different car positions. Two algorithms, related to the SVC and neural network was employed in this work for implementing the final process. Different possibilities and situations were discussed for this approach. The proposed method was tested and validated using Simulink/Matlab application. The state of charge of the used battery was compared at the end of this work, for two specified cases, for showing the contribution of this approach.

Information-theoretically provable unique true random numbers, which cannot be correlated or controlled by an attacker, can be generated based on quantum measurement of vacuum state and universal-hashing randomness extraction. Quantum entropy in the measurements decides the quality and security of the random number generator (RNG). At the same time, it directly determines the extraction ratio of true randomness from the raw data, in other words, it obviously affects quantum random bits generating rate. In this work, we commit to enhancing quantum entropy content in the vacuum noise based quantum RNG. We have taken into account main factors in this proposal to establish the theoretical model of quantum entropy content, including the effects of classical noise, the optimum dynamical analog-digital convertor (ADC) range, the local gain and the electronic gain of the homodyne system. We demonstrate that by amplifying the vacuum quantum noise, abundant quantum entropy is extractable in the step of post-processing even classical noise excursion, which may be deliberately induced by an eavesdropper, is large. Based on the discussion and the fact that the bandwidth of quantum vacuum noise is infinite, we propose large dynamical range and moderate TIA gain to pursue higher local oscillator (LO) amplification of vacuum quadrature and broader detection bandwidth in homodyne system. High true randomness extraction ratio together with high sampling rate is attainable. Experimentally, an extraction ratio of true randomness of 85.3% is achieved by finite enhancement of the laser power of the LO when classical noise excursions of the raw data is obvious.

This paper presents a state machine based architecture which enhances flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating presented approach versus traditional robot programming techniques.

Li-rich layered oxide cathode materials have become one of the most promising cathode materials for high-energy-density lithium-ion batteries owning to its high theoretical specific capacity, low cost, high operating voltage and environmental friendliness. Yet they suffer from severe capacity and voltage attenuation during prolong cycling, which blocks their commercial application. To clarify these causes, we synthesize 0.5Li2MnO3·0.5LiNi0.8Co0.1Mn0.1O2 (LL-811) with high-nickel-content cathode material by a solid-sate complexation method, and it manifests a lot slower capacity and voltage attenuation during prolong cycling compared to LL-111 and LL-523 cathode materials. The capacity retention at 1C after 100 cycles reaches to 87.5% and the voltage attenuation after 100 cycles is only 0.460 V. Combining X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscopy (TEM), it indicates that increasing the nickel content not only stabilizes the structure but also alleviates the attenuation of capacity and voltage. Therefore, it provides a new idea for designing of Li-rich layered oxide cathode materials that suppress voltage and capacity attenuation.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

Solid-state fermentation (SSF) is the bioprocess where microorganisms are cultivated in the absence of free water under control conditions. Lactic acid can be produced by fermenting grape stalks with Rhizopus oryzae in SSF. During the microorganism growth, the temperature and water content of the solid bed fluctuate, leading to areas of either dry or excessive moisture in the solid substrate. Therefore, it's crucial to control the supply of water to the matrix. In this work, we obtain lactic acid through SSF of grape stalks using Rhizopus oryzae NCIM 1299. The SSF was conducted at a fixed temperature of 35 °C, with three constant relative humidity levels: 50, 65, and 80 %RH. Mathematical models, including the Logistic and First Order Plus Dead Time models for fungal biomass growth and the Luedeking and Piret with Delay Time model for lactic acid production, were adjusted to kinetic curves. Growth kinetic parameters (Xmax, μmax, Tp, T0, Yp/x and td) were determined for all conditions. These kinetic parameters were then correlated with relative humidity using a second-degree polynomial relationship. We observed a decrease in Xmax with increasing %RH, while the value of Yp/x increased at higher %RH. Finally, the optimal variable relative humidity profile was obtained by applying the Dynamic Optimization Technique, resulting in a 15.30% increase in lactic acid production.

Similarly to his special theory of relativity, Einstein's special principle of relativity extends beyond the limits currently known to it. Up to now, the principle has not been suspected to have the potential to translate laws. However, the principle holds an inherent capacity to translate physical laws and, in so doing, speeds up our understanding and control of physical reality. Such a translation of laws leads to the faster discovery of other laws, such as the Laws of Electronic Motion, characterizing the motion of electrons around the atomic nucleus, and the Third Law of Biological Resistance, facilitating the successful control of drug resistance in medicine. The ability of the special principle of relativity to translate laws shines forth once the said principle is duly interpreted. This interpretation exposes a parallelism between experimental frames of reference and justifies the applicability of the laws of one frame of reference in other parallel frames of reference. This process opens the door to our faster discovery of the laws governing a multiplicity of frames parallel to a frame we already know the laws of. In practice, the interpretation of Einstein's special principle of relativity speeds up our understanding of the workings of physical reality and strengthens our capacity to subdue matter.

A scientific investigation into visual preferences of rural recreation path landscapes is crucial for enhancing visual qualities and visitors' experience. Taking Baofeng, a representative traditional village in Yunlong, as an example, this study analyzed the visual preference of three typical linear recreational paths with different landscape attributes. We used eye-tracking technology to collect eye movement data and conducted a subjective semantic differential evaluation. Our findings manifest a general inclination amongst individuals to favor closer views and paths with clear trajectories and rich elevation changes while walking, despite preference differences on different types of paths. Regarding group diversity, more inclusive design should be made to meet the sensory needs of different groups. Moreover, despite the limited level of correlation between subjective and objective evaluation methods, combining these two approaches remains indispensable. This synthesis advances prior quantitative landscape evaluation with a specific focus on rural path landscapes and upholds the integrity of results by combining objectivity with subjectivity. It also provides relevant design suggestions for further rural renewal and path planning of Baofeng village.

Urban rivers and waterfronts play a vital role in the ecological, social, and economic fabric of cities, providing not only aesthetic value but also serving as important ecosystems that contribute to the overall well-being of urban environments. However, many urban rivers, including the Beirut River in Lebanon, face challenges such as pollution, neglect, and the loss of recreational and ecological value due to urbanization and industrialization. According to the Lebanese MOE (Ministry of Environment), almost 70% of Lebanese rivers are polluted due to untreated waste management systems and which leads to undrinkable water and possible flooding disasters if not treated. This study addresses the problem of abandoned and degraded spaces along the Beirut River riverside through the application of urban acupuncture, a strategic approach that targets specific points in the urban environment to stimulate positive change and regeneration. The aim of the study is to assess the effectiveness of implementing small-scale ‘sensitive urban points’ known as urban acupuncture as the method for regenerating the Beirut River riverside, with the hypothesis that targeted interventions through Blue Urban Acupuncture or Aqua-puncture- can lead to significant improvements in the ecological, social, and economic aspects of the area that re-connect the people of Beirut with its river. The methodology involves a multidisciplinary approach that integrates urban design, and community engagement, and analysing similar examples of different approaches through creating a comparative table. Data collection includes environmental assessments of water quality, biodiversity, and ecosystem health, as well as social surveys to understand community needs and perceptions. By applying urban acupuncture principles to the Beirut River riverside, this study seeks to demonstrate how strategic interventions can lead to the regeneration of abandoned spaces, improve the overall quality of the urban environment, and create sustainable and inclusive riverside landscapes that benefit both the environment and the community.

The concept of "Eco-authoritarianism", although appeared in the 1970s, through the writings of Robert Heilbroner, William Ophuls etc., but Eco-authoritarianism as a theory has emerged very recently [1]. In this era of global environmental degradation and rampant defacement of green space in the rapidly expanding cities of developing countries especially in India, historical sites of green belts, or eco-space developed by royal dynasties or colonial rulers are still preserved by eco-authoritarianism and cultural praxis. A lot of such heritage sites and built-up eco-spaces have faded out over time but at the same time, huge numbers are still present due to the imposition of restrictions by the state or national government or statutory organizations. Built up eco-space under Burdwan Raj Dynasty during the 18th and 19th centuries is still preserved almost in its original form due to the eco-authoritarianism outlook of the present stakeholder (The University authority mainly and the Forest Department). People of this urban unit not only feel proud of such built up eco-space; they also give credit to the university authority for maintaining the legacy of the Raj Dynasty. This investigation attempts to capture not only the role of authoritarian legacy for the preservation and conservation of eco-space in the urban context but also clarify the benefits of this eco-space regarding the cultural ecosystem services and outlook of urbanites towards nature. To portray this, both the qualitative and quantitative methods have been applied to glean the whole perspective.

Given any sequence a = (an)n1 of positive real numbers and any set E of complex sequences, we write Ea for the set of all sequences y = (yn)n1 such that y=a = (yn=an)n1 2 E. In this paper, we use the spaces w1, w0 and w of strongly bounded, summable to zero and summable sequences, that are the sets of all sequences y such that ? n?1Pn k=1 jykj
n is bounded, tends to zero and such that y ? le 2 w0, for some scalar l, respectively, (cf. [24, 22]). These sets where used in the statistical convergence, (cf. [17, Chapter 4]). Then we deal with the solvability of each of the (SSIE) F
 E + F0x where E is a linear space of sequences, F = c0, c, `1, w0, w, or w1 and F0 = c0, c, or `1. For instance, the solvability of the (SSIE) w
 w0+s(c) x consists in determining the set of all sequences x = (xn)n1 2 U+ that satisfy the following statement. For every sequence y that satisfy the condition limn!1 n?1Pn k=1 jyk ? yk?1 ? lj = 0, there are two sequences u and v, with y = u+v such that limn!1 n?1Pn k=1 jukj = 0 and limn!1 (vn=xn) = L for some scalars l and L. These results extend those stated in [11, 12, 10].

The Hertzian contact theory, as well as most of the other classical theories of normal and tangential contact, provides displacements and the distribution of normal and tangential stress components directly in the contact surface. However, other components of the full stress tensor in the material may essentially influence the material behaviour in contact. Of particular interest are principal stresses and the equivalent von Mises stress, as well as the gradient of the hydrostatic pressure. For many engineering and biomechanical problems, it would be important to find these stress characteristics at least in the contact plane. In the present paper, we show that the complete stress state in the contact plane can be easily found for axially symmetric contacts under very general assumptions. We provide simple explicit equations for all stress components and the normal component of the gradient of hydrostatic pressure in the form of one-dimensional integrals.

Flexible energy storage devices, such as solid-state supercapacitors, are becoming increasingly attractive due to their characteristics of high electrochemical performance, reliability, light weight, flexibility, absence of electrolyte leakage, high power density, and long lifetime. For the optimization of the solid-state symmetrical supercapacitor proposed in this work, it was employed in sodium and lithium form Aquivion electrolyte membrane, which serves as the separator and electrolyte. As electrode materials, carbon xerogels, synthesized by microwave-assisted sol-gel methodology, with designed and controlled properties were obtained. Commercial activated carbon (YP-50F, 'Kuraray Europe' GmbH) was used for comparison. Specifically, the developed solid-state symmetrical supercapacitors deliver sufficient high specific capacitances of 105−110 F g−1 at 0.2 A g−1, along with an energy density of 4.5 Wh kg−1 at 300 W kg−1, and in a voltage window of 0-1.2 V in an aqueous environments, also demonstrating excellent cycling stability up to 10,000 charge/discharge cycles. These results can demonstrate the potential applications of carbon xerogel as an active electrode material and cation exchange membrane as the electrolyte in the development of solid-state supercapacitor devices

The induced draft (ID) fan is important auxiliary equipment in the thermal power plant. It is of great significance to monitor the operation of the ID fan for safe and efficient production. In this paper, an adaptive warning model is proposed to detect early faults of ID fans. First, a non-parametric monitoring model is constructed to describe the normal operation states with the multivariate state estimation technique (MSET). Then, an early warning approach is presented to identify abnormal behaviors based on the results of the MSET model. As the performance of the MSET model is heavily influenced by the normal operation data in the historic memory matrix, an adaptive strategy is proposed by using the samples with a high data quality index (DQI) to manage the memory matrix and update the model. The proposed method is applied to a 300 MW coal-fired power plant for early fault detection, and it is compared with the model without an update. Results show that the proposed method can detect the fault earlier and more accurately.

The 21st century has seen the launch of new space-borne sensors based on LiDAR (light detection and ranging) technology developed in the second half of the 20th century. LiDAR was initially developed to integrate laser-focused imaging with the capability to determine distances through the measurement of signal return times, utilizing suitable sensors and data acquisition electronics. Nowadays, these sensors have transformed into robust instruments, offering novel opportunities for mapping terrain, canopy heights, and estimating above-ground biomass (AGB) across local to regional scales. This work aims to analyze the scientific impact of these sensors on large-scale for-est mapping to retrieve 3D canopy information, monitor forest degradation, estimate AGB, and model key ecosystem variables such as primary productivity and biodiversity. In this way, a worldwide bibliometric analysis of this topic was carried out based on up to 412 publications in-dexed in the Scopus database during the period 2004-2022. The results showed that the number of published documents increased exponentially in the last five years, coinciding with the commis-sioning of two new LiDAR space missions: Ice, Cloud and Land Elevation Satellite (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI). These missions are providing data since 2018 and 2019, respectively. The journal that demonstrated the highest productivity in this field was "Remote Sensing," and among the leading contributors, the top five countries in terms of publica-tions were the USA, China, the UK, France, and Germany. In the realm of prominent research in-stitutions, France boasted six, the USA had four, China had three, while the UK and Canada each had one. The upward trajectory in the number of publications recorded from 2004 to 2022 catego-rizes the subject under investigation as a highly trending research topic, particularly within the context of enhancing the administration of forest resources and engaging in global climate treaty frameworks mandating the surveillance and reporting of carbon stocks in forests. The recent launch in August 2022 of the Terrestrial Ecosystem Carbon Monitoring Satellite (TECMS; China State Administration of Forestry and Grassland), along with the planned launch in the coming years of up to three new space sensors, such as the Multi-footprint Observation LiDAR and Im-ager (Japan Aerospace Exploration Agency), the BIOMASS P-band Synthetic Aperture Radar (SAR) (European Space Agency), and the LiDAR Surface Topography (LIST; NASA), will greatly contribute to expanding the ability to map and monitor forest systems at very large scales. In this context, the integration of space-borne data, including imagery, SAR, and LiDAR, is anticipated to steer the trajectory of this research in the upcoming years.

Advances of Relativity Theory are in the replacement of the space-time model with time-invariant universal space that has a variable energy density. Every physical object with mass m and energy E is diminishing the energy density of space exactly for the amount of its energy. Lorentz factor has its origin in the variable energy density of universal space, we call it "superfluid quantum space" - SQS that is the primordial energy of the universe. Universal SQS is the absolute frame of reference for all observers as confirmed experimentally by the GPS system, which demonstrates that the relative rate of clocks is valid for all observers. A planet's perihelion precession and the Sagnac effect are the results of the SQS dragging effect.

As operations in Cislunar space continue to expand, the sustainability of operations in orbital environments beyond GEO has become a critical concern. The Cislunar region is known to have a higher non-linear chaotic component in the dynamics compared to the low-Earth environment. This research is focused on producing simulations to model debris trajectories and dispersion from spacecraft mishaps across various identified key Cislunar orbits. By varying initial conditions, simulations of explosions at different locations of the orbits are carried out and the debris propagation is analyzed. This research emphasizes the creation of a robust debris propagation scheme and the development of a comprehensive database to address the computational costs associated with debris propagation. The resulting codes and databases documenting the historical evolution of debris are published as open-source resources, aiming to aid in solving the Cislunar space debris and traffic problem and in forecasting future needs and policies.

Solar flares are characterized by sudden bursts of electromagnetic radiation from the Sun’s surface, and caused by the changes in magnetic field states in solar active regions. Earth and its surrounding space environment can suffer from various negative impacts caused by solar flares ranging from electronic communication disruption to radiation exposure-based health risks to the astronauts. In this paper, we address the solar flare prediction problem from magnetic field parameter-based multivariate time series (MVTS) data using multiple state-of-the-art machine learning classifiers that include MINImally RandOm Convolutional KErnel Transform (MINIROCKET), Support Vector Machine (SVM), Canonical Interval Forest (CIF), Multiple Representations SEQuence Learner (Mr-SEQL), and Long Short-Term Memory (LSTM)-based deep learning model. Our experiment is conducted on the on the Space Weather ANalytics for Solar Flares (SWAN-SF) benchmark data set, which is a partitioned collection of MVTS data of active region magnetic field parameters spanning over 9 years of operation of the Solar Dynamics Observatory (SDO). The MVTS instances of the SWAN-SF dataset are labeled by GOES X-ray flux-based flare class labels, and attributed to extreme class imbalance because of the rarity of the major flaring events (e.g., X and M). As a performance validation metric in this class-imbalanced dataset, we used the true skill statistic (TSS) score. Finally, we demonstrate the advantages of the MVTS learning algorithm MINIROCKET, which outperformed the aforementioned classifiers without the need for essential data preprocessing steps such as normalization, statistical summarization, and class imbalance handling heuristics.

Quantum logic is a well-structured theory, which has recently received some attention because of its fundamental relation to quantum computing. However, the complex foundation of quantum logic borrowing concepts from different branches of mathematics as well as its peculiar settings have made it a non-trivial task to device suitable applications. This article aims to propose for the first time an approach to use quantum logic in image processing at hand of a process for shape classification. We show how to make use of the principal component analysis to realize quantum logical propositions. In this way we are able to assign a concrete meaning to the rather abstract quantum logical concepts, and we are able to compute a probability measure from the principal components. For shape classification we consider encrypting given point clouds of different objects by making use of specific distance histograms. This enables to initiate the principal component analysis. At hand of experiments, we explore the possibility to distinguish between different geometrical objects and discuss the results in terms of quantum logical interpretation.

A question of physical importance is whether finite-energy spatiotemporally localized (i.e., pulsed) generalizations of monochromatic accelerating Airy beams are feasible. For luminal solutions, this question has been answered affirmatively by Saari, Valdmann, Piksarv, Valta-Lukner and Saari, and Kaganovsky and Heyman within the framework of the paraxial geometry. The time-diffraction technique introduced by Porras recently has been motivated by Besieris and Shaarawi in terms of the Lorentz invariance of the equation governing the narrow angular spectrum and narrowband temporal spectrum paraxial approximation and has been used to derive finite-energy spatiotemporally confined subluminal, luminal, and superluminal Airy wave packets. The goal in this article is to provide exact finite-energy broadband spatiotemporally localized Airy solutions (a) to the scalar wave equation in free space; (b) in a dielectric medium moving at its phase velocity; (c) in a lossless second order temporally dispersive medium.

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.

In this paper, we investigate an exact Universe which is observational viable and filled with binary mixture of perfect fluid and cosmological constant $\Lambda$. Owning the non-uniform expansion of cosmos, we have considered redshift drift $\dot{z} = -(1+z)H_{0}+H(z)$ and performed statistical test to obtain the best fit value of model parameters of derived Universe with its observed values. Here $H_{0}$ and $z$ denote the present value of Hubble constant and redshift respectively. We estimate the best fit values of Hubble constant and density parameters are $H_{0} = 68.58 \pm 0.84$ km/s/Mpc, $(\Omega_{m})_{0} = 0.26 \pm 0.010$ and $(\Omega_{\Lambda})_{0} = 0.71 \pm 0.025$ by bounding the derived model with latest observational Hubble data (OHD) while with joint Pantheon data and OHD, its values are $H_{0} = 71.93 \pm 0.58$ km/s/Mpc, $(\Omega_{m})_{0} = 0.272 \pm 0.06$ and $(\Omega_{\Lambda})_{0} = 0.74 \pm 0.09$. The analysis of deceleration parameter and jerk parameter show that the Universe in derived model is compatible with $\Lambda$CDM model.

One of the most popular techniques for determining electrical properties of material is the free-space measurement technique. With the potential for new applications requiring efficient, accurate and broadband material measurement systems using higher millimeter-wave and terahertz frequencies, the free-space measurement method has received renewed interest. This is mainly due to its simplicity, favorable properties as a non-destructive method, and it allows transmission and reflection measurements without any physical contact with the sample. This paper reviews and discusses state- of-the-art free space material measurement systems, starting with the different measurement techniques available for material characterization, their important concepts, post-processing in determining their properties, and progress towards expanding their use at higher frequencies. Also, this paper reviews dielectric material characterization using the free space method focusing on their application extension towards the higher frequencies. Besides, the algorithms for conversion methods and usage of lens in free space material measurement system was discussed in this paper. Finally, a future perspective on the outlook of this free space method is presented prior to the conclusion.

In humankind’s endeavor to explore beyond our planet and travel further into space, we are now at the threshold of an era in which it is possible to move to and from low Earth orbit (LEO) with increasing ease and reduced cost. Through the International Space Station (ISS) U.S. National Laboratory, investigators from industry, academia, and government can easily access the unique LEO environment on the ISS to conduct research and development (R&D) activities in ways not possible on Earth. A key advantage of the LEO environment for life sciences research is the ability to conduct experiments in sustained microgravity conditions. The ability to conduct long-term research in microgravity enables opportunities for novel, fundamental studies in tissue engineering and regenerative medicine, including research on stem cell proliferation and differentiation, biofabrication, and disease modeling using microphysiological systems (MPS) that build on prior research using simulated microgravity conditions (Grimm, D., et al. 2018). Over the last decade, space-based research has demonstrated that microgravity informs our knowledge of fundamental biology and accelerates advancements in health care and medical technologies (International Space Station 2019). The benefits provided by conducting biomedical research in LEO may lead to breakthroughs not achievable on Earth. We are now at a transition point, in which nations are changing their approach to space-based R&D. The focus is shifting from government-funded fundamental science toward the expansion of privately funded R&D with terrestrial application and economic value that will drive a robust marketplace for innovation and manufacturing in LEO. Making this long-term transition requires public-private participation and near-term funding to support critical R&D to leverage the benefits of the LEO environment and de-risk space-based research. Studies conducted on the ISS over the past several years have indicated that one area with potential significant economic value and benefit to life on Earth is space-based biomanufacturing, or the use of biological and nonbiological materials to produce commercially relevant biomolecules and biomaterials for use in preclinical, clinical, and therapeutic applications. We must take advantage of the remaining lifetime of the ISS as a valuable LEO platform to demonstrate this economic value and Earth benefit. By facilitating access to the space station, the ISS National Lab is uniquely positioned to enable the R&D necessary to bridge the gap between the initial discovery phase of space-based biomedical research and the development of a sustainable, investment-worthy biomanufacturing market in LEO supported by future commercial platforms. Through a joint effort, the Center for the Advancement of Science in Space (CASIS), which manages the ISS National Lab, and the University of Pittsburgh’s McGowan Institute for Regenerative Medicine brought together thought leaders from around the U.S. for a Biomanufacturing in Space Symposium that consisted of a series of working sessions to review data from past space-based tissue engineering and regenerative medicine research, discuss relevant current space-based R&D in this area, and consider potential future markets to address the questions: What are the most promising opportunities to leverage the ISS to advance space-based biomanufacturing moving forward? What are the current gaps or barriers that, if overcome, could clear pathways toward private investment in LEO as a valued site for research, development, and production activity? And, most importantly: For which opportunities do the most compelling value propositions exist? The goal of the Biomanufacturing in Space Symposium was to help identify the specific areas in which government and industry investment would be most likely to stimulate advancements that overcome barriers. This would lead to a more investment-ready landscape for private interests to enter the market and fuel exponential growth. The symposium was meant to serve as the first step in developing a roadmap to a sustainable market for biomanufacturing in space. The symposium identified and prioritized multiple key R&D opportunities to advance space-based biomanufacturing. These opportunities fall in the areas of disease modeling, stem cells and stem-cell-derived products, and biofabrication. Additionally, symposium participants highlighted the critical need for additional data to help validate and de-risk these opportunities and concluded that approaches such as automation, artificial intelligence (AI), and machine learning will be needed to produce and capture the required data. Symposium participants also came to a consensus that public-private partnerships and funding will be needed to advance the opportunities toward a biomanufacturing marketplace in LEO. This paper will summarize the current state of the science and technology on the ISS and in the fields of tissue engineering and regenerative medicine; provide an overview of biomanufacturing R&D in space to date; review the goals of the Biomanufacturing in Space Symposium; highlight the key commercial opportunities and gaps identified during the symposium; provide information on potential market sizes; and briefly discuss the next steps in developing a roadmap to biomanufacturing in space.

The wave-particle description of quantum mechanics is briefly reviewed to set an analogy between the quantum mechanics of particles and fields and quantum cosmology. It is shown that quantum cosmology can be seen as a quantum field theory developed in the space of three metrics (the metrics of the spatial sections of the spacetime), where the classical evolution of the universe corresponds to a definite trajectory and the quantum mechanics of matter fields emerges as the first order quantum correction. Like in a quantum field theory developed in an isotropic background, the universes are created in universe-antiuniverse pairs, which might provide us with an explanation for the matter-antimatter asymmetry observed in our universe without going beyond the standard model. Moreover, the states of the matter and the antimatter fields of the pair of universes are entangled and that makes that their initial states are in a non-vacuum state (presumably in a thermal state). That might open the possibility of looking for observable imprints of the creation of universes in pairs is the astronomical data.

To sample from complex, high-dimensional distributions, one may choose algorithms based on the Hybrid Monte Carlo (HMC) method. HMC-based algorithms generate nonlocal moves alleviating diffusive behavior. Here, I build on an already defined HMC framework, Hybrid Monte Carlo on Hilbert spaces [A. Beskos, F.J. Pinski, J.-M. Sanz-Serna and A.M. Stuart, Stoch. Proc. Applic. 121, 2201 - 2230 (2011); doi:10.1016/j.spa.2011.06.003] that provides finite-dimensional approximations of measures π which have density with respect to a Gaussian measure on an infinite-dimensional Hilbert (path) space. In all HMC algorithms, one has some freedom to choose the mass operator. The novel feature of the algorithm described in this article lies in the choice of this operator. This new choice defines a Markov Chain Monte Carlo (MCMC) method which is well defined on the Hilbert space itself. As before, the algorithm described herein uses an enlarged phase space Π having the target π as a marginal, together with a Hamiltonian flow that preserves Π. In the previous method, the phase space π was augmented with Brownian bridges. With the new choice for the mass operator, π is augmented with Ornstein-Uhlenbeck (OU) bridges. The covariance of Brownian bridges grows with its length, which has negative effects on the Metropolis-Hasting acceptance rate. This contrasts with the covariance of OU bridges which is independent of the path length. The ingredients of the new algorithm include the definition of the mass operator, the equations for the Hamiltonian flow, the (approximate) numerical integration of the evolution equations, and finally the Metropolis-Hastings acceptance rule. Taken together, these constitute a robust method for sampling the target distribution in an almost dimension-free manner. The behavior of this novel algorithm is demonstrated by computer experiments for a particle moving in two dimensions, between two free-energy basins separated by an entropic barrier.

In this paper the problem of sampling from uniform probability distributions is approached by means of space-filling curves (SFCs), a topological concept that has found a number of important applications in recent years. Departing from the theoretical fact that they are surjective but not necessarilly injective, the investigation focused upon the structure of the distributions obtained when their domain is swept in a uniform and discrete manner, and the corresponding values used to build histograms, that are approximations of their true PDFs. This work concentrates on the real interval [0,1], and the Sierpinski space-filling curve was chosen because of its favorable computational properties. In order to validate the results, the Kullback-Leibler distance is used when comparing the obtained distributions in several levels of granularity with other already established sampling methods. In truth, the generation of uniform random numbers is a deterministic simulation of randomness using numerical operations. In this fashion, sequences resulting from this sort of process are not truly random.

Due to the advantages such as low power consumption and higher concealment, deceptive jamming against synthetic aperture radar (SAR) receives extensive attention during the past decades. However, the large scene deception jamming is still a challenge because of the huge computing burden. In this paper, we propose a new large scene deceptive jamming algorithm. First, the time-delay and frequency-shift (TDFS) algorithm is introduced to improve the jamming processing speed. The system function of jammer (JSF) for a fake scatter is simplified to the multiplication of the scattering coefficient, a time-delay term in range dimension and a frequency-shift term in azimuth dimension. Then, in order to solve the problem that the effective region of the TDFS algorithm is limited, the scene deceptive jamming template is divided into several blocks according to the SAR parameters and imaging quality control factor. The JSF of each block is calculated by the TDFS algorithm and added together to achieve the large scene jamming. Finally, the correction algorithm in squint mode is derived. The simplification and parallel block processing could improve the calculation efficiency significantly. The simulation results verified the validity of the algorithm.

After astrochemistry and astrobiology, astrotoxicology is a further subfield of astroscience. Astrotoxicology is an interdisciplinary science that combines physics, biology, chemistry, astronomy, medicine and toxicology. Unlike toxicology on Earth, astrotoxicology in space must take into account the specific features of extreme conditions such as gravity, radiation, temperature or pressure and also consider the distinctions of extreme conditions on other celestial bodies. The field of action of astrotoxicology is, therefore, the influence of lower gravity on the toxicological characteristics of substances in the human body, the special dangers caused by increased radiation in space and on other planets and the special chemical changes caused by the extreme conditions in space on substances and the toxicological consequences associated with them. Despite growing space research, there are so far only a few pharmacokinetic, pharmacodynamic or toxicological investigations under conditions of microgravity and knowledge of toxicology under the extreme conditions in space in particular. Future studies will be the beginning of astrotoxicology, a previously unknown branch of toxicology.

We review recent progress in high-speed orbital angular momentum (OAM) multiplexed free-space optical communication systems. The outdoor atmospheric turbulence is emulated by an indoor turbulence emulator, which is based on split-step beam propagation method. Adaptive optics, channel coding, Huffman coding combined with LDPC coding, and spatial offset are used for turbulence mitigation; while OAM multiplexing and wavelength-division multiplexing (WDM) are applied to boost aggregate capacity.

We explores the relational, dynamic elements of Complex Buildings, a type of architecture designed to incubate uses, located in urban areas with high housing density. The uses of Complex Buildings concern different elements, including the network of agents using or managing them, the environment, and the activities and functions that take place occasionally, temporarily or permanently. Data was gathered through ethnographic research lasting 6 months and a chronotopian approach was used to describe time and space. We analyzed and discussed the interaction of the elements of Complex Buildings through a cellular automaton model, a computational method that simulates the growth of complex systems. It was used here to generate patterns that suggest configurations of uses that can optimize management and therefore increase economic and social capital. The cellular automaton model was also used to develop an abstraction of the Centquatre, a public cultural center in Paris. This center is a good example of a Complex Building, being based on a public-private partnership and having an architectural configuration designed to host a wide range of art, social and productive activities. The building includes a large central space used as an urban public area open to different types of people. The importance of this case study lies in its capacity to produce economic value by combining different uses, and also by welcoming different people to the public space. Regarding the building as a living organism, the cellular automaton model reveals the determinant nature of the concepts of configuration, compatibility of uses and economic value generated by the presence of people. We argue that this approach makes it possible to show that the space-time design and public space dimensions are determinant factors in Complex Buildings.

Edge detection is one of the key issues in the field of computer vision and remote sensing image analysis. Although many different edge-detection methods have been proposed for gray-scale, color, and multispectral images, they still face difficulties when extracting edge features from hyperspectral images (HSIs) that contain a large number of bands with very narrow gap in the spectral domain. Inspired by the clustering characteristic of the gravitation, a novel edge-detection algorithm for HSIs is presented in this paper. In the proposed method, we first construct a joint feature space by combining the spatial and spectral features. Each pixel of HSI is assumed to be a celestial object in the joint feature space, which exerts gravitational force to each of its neighboring pixel. Accordingly, each object travels in the joint feature space until it reaches a stable equilibrium. At the equilibrium, the image is smoothed and the edges are enhanced, where the edge pixels can be easily distinguished by calculating the gravitational potential energy. The proposed edge-detection method is tested on several benchmark HSIs and the obtained results were compared with those of three state-of-the-art approaches. The experimental results confirm the efficacy of the proposed method

The accurate state of health (SOH) estimation of lithium-ion batteries (LIBs) during operation is crucial to ensure optimal performance, prolonging battery life and preventing unexpected failure or safety hazards. This work presents a storage and performance optimised deep learning approach to predict the capacity based SOH of LIBs using raw sensor data from partial charging curves under constant current condition. The proposed model is based on a combination of a 1-dimensional convolutional and long-short term memory neural network and processes time, voltage and incremental capacity of partial charging curves as time series. The model is cross-validated on different aging scenarios reaching an overall MAE = 0.418% and RMSE = 0.531%, promising an accurate SOH estimation of LIBs under varying usage and environmental conditions in a real world application.

Spinors are used for the computation of probability in quantum mechanics. They are treated as elements of a complex vector space in contrast to a real vector space. Spinor theory is abstract mathematics with an ambiguous interpretation. The overall phase of spinors does not affect the computation of probability in quantum mechanics. If two spinors have an overall phase of imaginary number i, then they can be treated like vectors in a real vector space. The square of the magnitude of the number, which is the sum of dot product and the term having basis vector i of cross product of two such vectors, is equal to the probability computed using the corresponding spinors. Therefore, the geometry of such spinors can be easily depicted in a three-dimensional space like vectors in a real vector space. Spinors are not isotropic vectors in Hilbert space. The sum of dot product and cross product of two complex numbers is equivalent to the quotient of the division of one complex number by another. Similarly, the sum of dot product and cross product of two vectors is the quotient of the division of one vector by another. Using the rules of division of vectors, we can find the rules of multiplication of vectors. The rules of multiplication and division of basis vector i match the rules of multiplication and division of imaginary number i. Therefore, basis vector i is nothing but imaginary number i. Multiplication of dot and cross product of two vectors to the second vector will give us the components of the first vector that are parallel and orthogonal to the second vector. Vectors are also made up of complex numbers like spinors. The reason for finding dot product of complex numbers in the process of computing the probability is to ignore the overall phase in contrast to the phase difference. This is misconstrued as complex vector space in quantum mechanics. 3-D number which is nothing but a spinor with new notation is an extension of vector algebra. It can have a real number as a term in addition to the terms i, j and k. In all other respects, it is a vector. 3-D numbers are part of the number system like real numbers and complex numbers. The real numbers are one dimensional numbers, the complex numbers are two-dimensional numbers and the 3-D numbers as well as vectors and spinors are three-dimensional numbers. As polarisation and spin are one and the same, we can straight away apply 3-D numbers to polarisation of light. 3-D numbers will greatly simplify the study of areas of science where three-dimensional space is involved.

Sustainable urban design or planning is not a LEGO-like assembly of prefabricated elements, but an embryo-like growth with persistent differentiation and adaptation towards a coherent whole. The coherent whole has a striking character – called living structure – that consists of far more small substructures than large ones. To detect the living structure, natural streets or axial lines have been previously adopted to be topologically represent an urban environment as a coherent whole. This paper develops a new approach to detecting the underlying living structure of urban environments. The approach takes an urban environment as a whole and recursively decomposes it into meaningful subwholes at different levels of hierarchy or scale ranging from the largest to the smallest. We compared the new approach to natural street and axial line approaches and demonstrated, through four case studies, that the new approach is better and more powerful. Based on the study, we further discuss how the new approach can be used not only for understanding, but also for effectively designing or planning the living structure of an urban environment to be more living or more livable.

In this article, the geometry of pseudoparallel, Ricci-generalized pseudoparallel and 2-Ricci-generalized pseudoparallel invariant submanifolds of an almost $\alpha$-cosymplectic $(\kappa,\mu,\nu)$ space has been searched under the some conditions. We also give some characterizations for such submanifolds. I think that obtained new results contribute to differential geometry.

Three-phase to single-phase matrix converter (TSMC) is used as the transmitter for transient electromagnetic method (TEM) instrument, instead of an AC-DC converter and an H-bridge inverter. The transmitter produces excitation current for primary field. The output current has a waveform with a bipolar square of half duty cycle, which is required by TEM. The space vector PWM based on input currents is discussed in detail. The control method of input power factor is proposed for TSMC. The simulation model of TSMC is established and the simulations of different conditions are completed. The simulation results show the controllability of the input power factor is illustrated.

Microbial biofilms cause several environmental and industrial issues, even on the human health. Although they have represented a threaten due to their resistance to antibiotics, there are currently no approved antibiofilm agents for clinical treatments. The multi-functionality of antimicrobial peptides (AMPs) including the antibiofilm activity and their potentialities to target multiple mi-crobes motivated the synthesis of AMP relatives for developing antibiofilm agents for clinical purposes. Antibiofilm peptides (ABFPs) have been organized in databases that allowed the building of prediction tools which have assisted in the discovery/design of new antibiofilm agents. However, the complex network approach has been explored yet as an assistant tool for this aim. Herein, a kind of similarity networks, called the Half-Space Proximal Network (HSPN) is applied to represent/analyse the chemical space of the ABFPs aimed to identify promising scaf-folds for the development of next generation antimicrobials, able to target both planktonic and biofilm microbial forms. Such analyses also considered the metadata associated to the ABFPs such as origin, other activities, targets, etc. in which the relationships were projected by multilayer networks called metadata networks (METNs). From the complex networks mining, a reduced but informative set of 66 ABFPs representing the original antibiofilm space was extracted. This subset retained from the most central to atypical ABFPs, having some of them, desired properties for developing next generation antimicrobials. So, this subset is advisable for assisting the search/design both new antibiofilm/antimicrobial agents. The provided ABFP motifs list, dis-covered within the HSPN communities, is also useful for the same purpose.

Temperature field is an essential attribute of metal additive manufacturing in view of its bearings on the prediction, control, and optimization of residual stress, part distortion, fatigue, balling effect, etc. This work provides an analytical physics-based approach to investigate the effect of scan strategy parameters including time delay between two irradiations and hatching space on thermal material properties and melt pool geometry. This approach is performed through the analysis of the distribution of material properties and temperature profile in three-dimensional space. The moving point heat source approach is used to predict the temperature field. To predict the temperature field during the additive manufacturing process some important phenomena are considered. 1) Due to the high magnitude of temperature in the presence of the laser, the temperature gradient is usually high which has a crucial influence on thermal material properties. Consequently, the thermal material properties of stainless steel grade 316L are considered to be temperature-dependent. 2) Due to the repeated heating and cooling, part usually undergoes several melting and solidification cycles. This physical phenomenon is considered by modifying the heat capacity using the latent heat of melting. 3) The multi-layer aspect of metal AM process is considered by incorporating the temperature history from the previous layer since the interaction of the successive layers has an impact on heat transfer mechanisms. 4) Effect of heat affected zone on thermal material properties is considered by the superposition of material properties in regions where the temperature fields of two consecutive irradiations have an overlap since the consecutive irradiations change the behavior of the material properties. The goals are to 1) investigate the effects of temperature-sensitive material properties and constant material properties on the temperature field. 2) Study the behavior of thermal material properties under different scan strategies. 3) Study the importance of considering the effect of heat affected zone on thermal material through the prediction of melt pool geometry. 4) Investigate the effect of hatching space on melt pool geometry. This work is purely employed physics-based analytical models to predict the behavior of material properties and temperature field under different process conditions, and no finite element modeling is used.

Stroke is a major leading cause of chronic disability, often affecting patients’ motor and sensory functions. Functional magnetic resonance imaging (fMRI) is the most commonly used method of functional neuroimaging and allows the non-invasive study of brain activity. The time-dependent coactivation of different brain regions at rest is described as resting-state activation. As a non-invasive task-independent functional neuroimaging approach, resting-state fMRI (rs-fMRI) may provide therapeutically useful information on both the focal vascular lesion and the connectivity-based reorganization and subsequent functional recovery in stroke patients. Considering the role of prompt and accurate prognosis in stroke survivors along with the potential of rs-fMRI in identifying patterns of neuroplasticity in different post-stroke phases, this review provides a comprehensive overview of the latest literature regarding the role of rs-fMRI in stroke prognosis in terms of motor and sensory outcome. Our comprehensive review suggests that with the advancement of MRI acquisition and data analysis methods, rs-fMRI emerges as a promising tool to study the motor and sensory outcome in stroke patients and evaluate the effect of different interventions.

We aimed at analyzing Chlorophyll-a and CDOM dynamics from field measurements and at assessing the potential of multispectral satellite data for retrieving water-quality parameters in three small surface reservoirs in the Brazilian semiarid region. More specifically, this work comprises i) analysis of Chl-a and trophic dynamics; ii) characterization of CDOM; iii) estimation of Chl-a and CDOM from OLI/Landsat-8 and RapidEye imagery. The monitoring lasted 20 months within a multi-year drought, which contributed to water-quality deterioration. Chl-a and trophic state analysis showed a highly eutrophic status for the perennial reservoir during the entire study period, while the non-perennial reservoirs ranged from oligotrophic to eutrophic, with changes associated with the first events of the rainy season. CDOM characterization suggests that the perennial reservoir is mostly influenced by autochthonous sources, while allochthonous sources dominate the non-perennial ones. Spectral-group classification assigned the perennial as CDOM-moderate and highly eutrophic reservoir, whereas the non-perennial ones were assigned as CDOM-rich and oligotrophic-dystrophic reservoirs. The remote sensing initiative was partially successful: the Chl-a was best modelled using RapidEye for the perennial; whereas CDOM performed best with Landsat-8 for non-perennial reservoirs. This investigation showed high potential for retrieving water quality parameters in dry areas with small reservoirs.

We discuss the neutron skins of 48Ca and 208Pb. We review and critically examine modern predictions and empirical constraints, with special attention to the dierent interpretations of the ndings from the PREX-II experiment and the recently reported value of the neutron skin in 48Ca extracted from the CREX experiment. We argue that, in the spirit of the ab initio philosophy, the path to understanding the behavior of dense neutron-rich matter must not circumvent fundamental nuclear forces. Based only on that argument, a thick neutron skin in 208Pb is highly unlikely.

In a generalized topological space Tg = (Ω, Tg), ordinary interior and ordinary closure operators intg, clg : P (Ω) −→ P (Ω), respectively, are defined in terms of ordinary sets. In order to let these operators be as general and unified a manner as possible, and so to prove as many generalized forms of some of the most important theorems in generalized topological spaces as possible, thereby attaining desirable and interesting results, the present au- thors have defined the notions of generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, in terms of a new class of generalized sets which they studied earlier and studied their essen- tial properties and commutativity. The outstanding result to which the study has led to is: g-Intg : P (Ω) −→ P (Ω) is finer (or, larger, stronger) than intg : P (Ω) −→ P (Ω) and g-Clg : P (Ω) −→ P (Ω) is coarser (or, smal ler, weaker) than clg : P (Ω) −→ P (Ω). The elements supporting this fact are reported therein as a source of inspiration for more generalized operations.

It is shown that the representation theory of some finitely presented groups thanks to their $SL_2(\mathbb{C})$ character variety is related to algebraic surfaces. We make use of the Enriques-Kodaira classification of algebraic surfaces and the related topological tools to make such surfaces explicit. We study the connection of $SL_2(\mathbb{C})$ character varieties to topological quantum computing (TQC) as an alternative to the concept of anyons. The Hopf link $H$, whose character variety is a Del Pezzo surface $f_H$ (the trace of the commutator), is the kernel of our view of TQC. Qutrit and two-qubit magic state computing, derived from the trefoil knot in our previous work, may be seen as TQC from the Hopf link. The character variety of some two-generator Bianchi groups as well as that of the fundamental group for the singular fibers $\tilde{E}_6$ and $\tilde{D}_4$ contain $f_H$. A surface birationally equivalent to a $K_3$ surface is another compound of their character varieties.

It is time-consuming for acquiring complete data by fully phase encoding in two orthogonal directions along with one frequency encoding direction. Undersampling in the 3D k-space is promising in accelerating such 3D MRI process. Though 3D undersampling can be conducted according to predefined probability density, the density based method is not optimal. Because of the large amount of 3D data and computational cost, it is challenging to perform data-driven and learning-based 3D undersampling and subsequent 3D reconstruction. To tackle this challenge, this paper proposes a deep neural network called EEUR-Net, realized by optimizing specific undersampling patterns for the fully-sampled 3D k-space data. Innovatively, our undersampling algorithm employs an end-to-end deep learning approach to optimize phase encoding patterns and uses a 3D U-Net for image reconstruction of undersampled data. Through end-to-end training, we obtain an optimized 3D undersampling pattern, which significantly enhances the quality of the reconstructed image under the same acceleration factor. A series of experiments on a knee MRI dataset demonstrated that, in comparison to standard random uniform, radial, Poisson and equispaced Cartesian undersampling schemes, our end-to-end learned undersampling pattern considerably improves the reconstruction quality of undersampled MRI images.

Financial system is essentially chaotic and unstable if there is not any external inputs. By means of Lyapunov function method, design of switching law, novel fuzzy assumption, $L^p$ estimation technique and Laplace semigroup theory, the author presents the boundedness and LMI-based (globally) asymptotical input-to-state stability criteria of financial systems. Particularly, the globally asymptotical stability in the meaning of switching implies that when the time $t$ is big enough, the dynamic of any subsystem must approach its unique equilibrium point. Besides, the global financial crisis often erupts periodically, which illuminates that the global stability in the classical sense is actually meaningless. So the stability in the meaning of switching proposed in this paper is suitable and appropriate. Numerical examples illuminate the effectiveness of the obtained results.

Infrastructure monitoring, inspection, repair, and replacement in space is crucial for continued usage and safety, yet it is expensive, time-consuming, and technical very challenging. New robotics technologies and artificial intelligence algorithms are potentially novel approaches that may alleviate such demanding operations using existing or novel sensing technologies. Space structures must necessarily be very light weight due to high costs of placing robots in space. Several methods are proposed and compared to control highly flexible space robotics, where a key challenge is the presence of flexible resonant modes at frequencies so low as to reside inside typical feedback controller bandwidths. Such conditions imply the very action of sending control signals to the ultra-light weight robotics will cause structural resonance. Implementations of incrementally increasing order are offered, achieving over ninety percent performance improvement in trajectory tracking errors, while improvement using unshaped methods merely achieve twenty-four percent improvement in direct comparison (where the only modification is the proposed control methodology). Based on superior performance, single-sinusoidal trajectory shaping is recommended with a corollary benefit of preparing future research into applying deterministic artificial intelligence whose current instantiation relies on single-sinusoidal, autonomous trajectory generation.

Increasing the availability of alternative protein from insects is important to solving food shortages. Not only are insects a rich source of protein, the use of insect ingredi-ents can reduce food waste. Insects are thus a potentially valuable ingredient for food industries and even food eaten on deep-space missions. The three-dimensional produc-tion of food on space missions has gained attention owing to its potential to reduce au-tonomous food production and produce sustainable food for long-duration space mis-sions. This study investigated the printability and rheological properties of a high-protein food system derived from mealworms and guar gum used as a stabilizer to im-prove printability. Stability and rheological properties were analyzed for various print-ing parameters. The results indicate that as the guar gum concentration was increased from 0 to 1.75%, the yield stress of the mealworm paste increased from 39 to 1096 Pa. Increasing the guar gum concentration thus resulted in a mealworm paste that was more viscous, exhibited shear thinning behavior, could support itself and was thus more stable. In summary, introducing guar gum resulted in a mealworm paste with rheological properties more suitable for printing in terms of printability and stability.

This study investigated how fashion is expressed on social media platforms from a media ecology perspective of sustainable digital space-time, as society evolves into a digital ecosystem. Media ecology concerns how the media environment transforms human experience and impacts society and culture. A theoretical review of media ecology was conducted, and the Instagram account of global fashion influencer Susanna Lau (@susiebubble) was analyzed as a case study. In total, 300 fashion-related images were collected out of 5,817 uploaded to Lau’s Instagram between May 2012 and June 2019. These were analyzed—alongside their titles, content, hashtags, and commentaries—for visual phenomena conveying everyday divisions between spatiality and temporality, public and private, real and virtual, and geography and culture, which demonstrate ambiguous boundaries. The analysis revealed that the images reflect nuances of digital time and space as they emerge in social media, and represent a nonboundary of style across the binaries of work and leisure, public and private, real and virtual, and geography and culture—signifying a sustainable digital lifestyle. These findings illustrate how our changing daily lives are visualized through fashion on a sustainable digital platform, and suggest ongoing research into the practical impact of technological advances on fashion.

Political and legal debate about freedom of religion and belief (FoRB) in Australia has intensified since the Same-sex marriage postal survey in 2017. Central to this debate has been children, their parents and institutions (Schools). This paper outlines the place of children in the Australian FoRB since 2017, focusing on the Same-sex marriage postal survey debate and subsequent reviews into freedom of religion. In particular it highlights the links drawn between same-sex marriage or marriage equality and the Safe School Coalition Australia campaign, the emphasis on parental rights in relation to education about marriage in schools and the ongoing debate about potential reform to Australia’s suit of anti-discrimination laws

We show that the compound samarium hexaboride is a strong topological insulator using the eigenvalues of the space inversion operator in the low-energy limit of the periodic Anderson model. Additionally, we assume the presence of the ferromagnetic exchange interaction (M). A Dirac cone like feature in the surface state energy spectra is observed for M equals zero in a certain parameter range. For M not equal to zero, there is no Kramers degeneracy. We have been able to show that this phase corresponds to the quantum anomalous Hall state by calculating Berry curvature and the Chern number. Using Floquet theory, we further show that the access to a novel state with broken time reversal symmetry is possible due to the normal incidence of circularly polarized optical field on the surface of the compound despite M being absent.

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