Kinds Of Properties Research Articles

Molecular and Supramolecular Materials: From Light-Harvesting to Quantum Information Science and Technology.

The past two decades have witnessed immense advances in quantum information technology (QIT), benefited by advances in physics, chemistry, biology, and materials science and engineering. It is intriguing to consider whether these diverse molecular and supramolecular structures and materials, partially inspired by quantum effects as observed in sophisticated biological systems such as light-harvesting complexes in photosynthesis and the magnetic compass of migratory birds, might play a role in future QIT. If so, how? Herein, we review materials and specify the relationship between structures and quantum properties, and we identify the challenges and limitations that have restricted the intersection of QIT and chemical materials. Examples are broken down into two categories: materials for quantum sensing where nonclassical function is observed on the molecular scale and systems where nonclassical phenomena are present due to intermolecular interactions. We discuss challenges for materials chemistry and make comparisons to related systems found in nature. We conclude that if chemical materials become relevant for QIT, they will enable quite new kinds of properties and functions.

Short‐term origin‐destination demand forecasting in bus rapid transit based on dual attentive multi‐scale convolutional network

AbstractThe short‐term origin‐destination (OD) forecast in bus rapid transit (BRT) can provide future OD demand, which means that transport plan personnel can take measures in advance, such as adjusting the departure schedule, to avoid congestion. This emphasizes the importance of accurate and stable OD forecasting in real‐time. Deep learning methods have been widely applied due to their superior performance in capturing dynamic spatiotemporal and nonlinear features. However, current methods based on deep learning and data‐driven cannot simultaneously address the problems of data availability and sparsity, and their ability to capture dynamic spatiotemporal patterns is insufficient, which cannot provide satisfactory accuracy and stability. To address these problems, this paper proposes a method for forecasting the OD demand in BRT based on dual attention multi‐scale convolutional network (DAMSCN). Considering the three temporal properties of OD, that is, closeness, period and trend dependencies. DAMSCN uses multi‐scale convolution (MSC), dual attention mechanism (DAt) and stacked convolutional long short‐term memory networks (ConvLSTM) to model the three kinds of properties. The MSC module converts sparse OD information into dense useful features to solve the problem of data sparsity. The DAt and ConvLSTM module model the dependencies relationship in the spatial and temporal dimensions, which can improve the spatiotemporal features extraction ability. DAMSCN also combine inflow information to enhance data availability. The three properties are dynamically aggregated and further integrated with external influences (e.g. weather conditions etc.) to obtain the final forecasting result. The accuracy and stability are evaluated on the Xiamen BRT (XMBRT) and Shanghai Metro datasets (SHMetro). The experimental results show that the DAMSCN is superior to other method. Compared to the best baseline, on the XMBRT, MAE decreased by 8.60%, and RMSE decreased by 4.81%. On the SHMetro, MAE decreased by 7.22%, and RMSE decreased by 8.96%.

Multifaceted Role of Nanomaterials in Modulating In Vitro Seed Germination, Plant Morphogenesis, Metabolism and Genetic Engineering.

The agricultural practices of breeding, farm management and cultivation have improved production, to a great extent, in order to meet the food demands of a growing population. However, the newer challenges of climate change, global warming, and nutritional quality improvement will have to be addressed under a new scenario. Plant biotechnology has emerged as a reliable tool for enhancing crop yields by protecting plants against insect pests and metabolic engineering through the addition of new genes and, to some extent, nutritional quality improvement. Plant tissue culture techniques have provided ways for the accelerated clonal multiplication of selected varieties with the enhanced production of value-added plant products to increase modern agriculture. The in vitro propagation method has appeared as a pre-eminent approach for the escalated production of healthy plants in relatively shorter durations, also circumventing seasonal effects. However, there are various kinds of factors that directly or indirectly affect the efficiency of in vitro regeneration like the concentration and combination of growth regulators, variety/genotype of the mother plant, explant type, age of seedlings and other nutritional factors, and elicitors. Nanotechnology as one of the latest and most advanced approaches in the material sciences, and can be considered to be very promising for the improvement of crop production. Nanomaterials have various kinds of properties because of their small size, such as an enhanced contact surface area, increased reactivity, stability, chemical composition, etc., which can be employed in plant sciences to alter the potential and performance of plants to improve tissue culture practices. Implementing nanomaterials with in vitro production procedures has been demonstrated to increase the shoot multiplication potential, stress adaptation and yield of plant-based products. However, nanotoxicity and biosafety issues are limitations, but there is evidence that implies the promotion and further exploration of nanoparticles in agriculture production. The incorporation of properly designed nanoparticles with tissue culture programs in a controlled manner can be assumed as a new pathway for sustainable agriculture development. The present review enlists different studies in which treatment with various nanoparticles influenced the growth and biochemical responses of seed germination, as well as the in vitro morphogenesis of many crop species. In addition, many studies suggest that nanoparticles can be useful as elicitors for elevating levels of important secondary metabolites in in vitro cultures. Recent advancements in this field also depict the suitability of nanoparticles as a promising carrier for gene transfer, which show better efficiency than traditional Agrobacterium-mediated delivery. This review comprehensively highlights different in vitro studies that will aid in identifying research gaps and provide future directions for unexplored areas of research in important crop species.

Knowledge Base on Species Life Traits: A Spanish/French Plinian Core implementation use case

The French “Traits” working group was created in 2021 to support the development of the national knowledge base on species life traits managed by the PatriNat department*1, to identify and implement a suitable standard for managing and sharing species life traits (including interactions) at the national, then international, level. Its core members are part of several PatriNat teams (Species Knowledge, Dissemination & Mediation, Coordination of Information Systems), as well as other French research units*2 working on the topic of traits and ontologies. The Plinian Core (Plinian Core Task Group 2021) was first discussed in 2004 and its development began in 2005–2006 when the first version was deployed as a collaboration between InBIO*3 (Costa Rica) and GBIF Spain*4. It reuses and extends the Darwin Core vocabulary (Wieczorek et al. 2012, Darwin Core Maintenance Interest Group 2014) to describe different aspects of biological species information, that is, all kinds of properties or traits related to taxa, including biological and non-biological species traits. The Plinian Core was discussed with Dr Pando (convener of the TDWG Plinian Core Task Group*5) during one of the Traits working group meetings, and was found to be relevant to the French species life traits database (currently in development). The Traits working group future works will be following the example of the Plinian Core-based EIDOS database*6 (Spanish Ministry for the Ecological Transition), which allows for detailed species pages with distinct information sections (e.g., interactions, taxonomy, legal status, conservation). This collaboration resulted in a Capacity Enhancement Support Programme project submission (GBIF 2023) between French and Spanish partners, allowing for the consolidation of both the infrastructure and the sharing process of species life traits for taxa found on all French territories, as well as European Union territories. Additionally, this is an opportunity to provide information to GBIF (Global Biodiversity Information Facility) through a new update of the TAXREF (Gargominy 2022) national checklist, one of the core constituents of the GBIF Backbone Taxonomy (GBIF 2022). Species life traits and interactions will be added thanks to the new Plinian Core extension implemented on the GBIF Integrated Publishing Toolkit (IPT),*7 and an Atlas of Living Australia’s architecture BIE (Biodiversity Information Explorer) module*8 developed by Costa Rica in the context of a Capacity Enhancement Support Programme (CESP) project carried out with SIBBR*9 (GBIF Brasil).

A Comparative Study of RCC Pre-Cast and Composite Structure Using Delta Beams

Composite structures are gaining greater recognition these days in production regions. Composite beams like concrete filled metal tube are components with precise performance because of the confinement impact of metal with concrete and layout versatility. The composite shape has extra advantage over RCC body structure. The study about the behaviour and the characteristics of a composite over RCC is the high need. In India, concrete is a very famous material of production, particularly in the case of high-raised building, medium-raised and low-raised buildings. where in structural steel is typically used, the composite production isn't that popular, but it's miles possible that composite creation can be extra useful in the case of medium and high-raised buildings. steel concrete composite creation may be constructed in region of RCC systems to get maximum benefit of steel and concrete, to produce green and low-budget systems. it's miles the selection of the contractor or owner which kind of properties they require within the area and in line with those properties, the sort of material can be selected. This paper is in particular based totally at the assessment of the RCC frame structure with the Composite beam structure by using the delta beam. It is largely focused on the structural behaviour and results are tabulated within the form of comparison.

How did life become cellular?

How did life become cellular?

Adaptive and propagated mesh filtering

In this paper, we present an adaptive and propagated mesh filtering algorithm, which utilizes the common two-stage mesh denoising architecture. In the first stage, face normals are filtered by calculating cumulative differences of two kinds of properties along the geodesic paths connecting centroids of face neighbors. Compared with the well-known bilateral strategy and its variants, our strategy respects the spatial structure of mesh itself through using intrinsic metrics. Furthermore, the parameters in the weight strategy of our algorithm can be fully determined adaptively, which avoids the dilemma that previous methods use trial and error to get satisfactory denoised results. In the second stage, mean curvature flow theorem is used to update the vertex positions, namely, the direction of vertex update is adjusted to a linear combination between the direction of differential coordinates and the descending direction given by least squares, which improves the quality of meshes. Extensive experiments demonstrate the effectiveness of our method in preserving latent geometric features compared with the state-of-the-art approaches. • Face normals are filtered by calculating cumulative differences of two kinds of properties along the geodesic paths connecting centroids of face neighbors and the parameters in the weight strategy of our algorithm can be fully determined adaptively. • Compared with the well-known bilateral strategy and its variants, our strategy respects the spatial structure of mesh itself through using intrinsic metrics. • In addition, we use mean curvature flow theorem to update vertex positions, which improves the quality of mesh.

Phthalic anhydride (PA): a valuable substrate in organic transformations.

This review has been centralized on applications of phthalic anhydride (PA) as a valuable and significant heterocyclic substrate in two- and multicomponent organic reactions. The article has been subdivided into the following parts: (i) PA introduction by focusing on its characterization, synthesizing procedure, and multiple-aspect applications. In addition, the previous review articles based on PA have also been indicated; (ii) the applications of PA as a substrate have been subdivided into parts with a glance on the reaction components numbers; (iii) the applications of PA in esterification reactions; and (iv) some examples of PA in multistep synthesis. The review covers the corresponding literature up to the end of 2022. According to the abovementioned classifications, PA is a potent substrate to design a wide range of heterocyclic compounds that possess various kinds of properties and applications in chemistry, industry, and pharmaceuticals.

Vode kao predmet koncesije u pravu Republike Srpske

The author's interest in water usage under the concession model envisaged in the domestic legislation of Republika Srpska was sparked by the Decision of the Constitutional Court of Bosnia and Herzegovina in Case No. U-16/20. The analysis of this decision has paved the way for broader reflection, leading to further research which resulted in the creation of this article. Methodologically, the paper is rooted in the normative analysis of the Concessions Act and the Real Rights Act, the latter being the primary legislative act when discussing real property institutions in Republika Srpska. While the initial segment of this article addresses the specific legal regulation of certain kinds of properties and delineates the concepts of water, water assets, and water entities as subjects of property rights, the main focus is on pertinent issues related to water as the subject matter of concession. The scope of concession can encompass a vast array of economic activities. In the context of water, it typically pertains to the utilization of public water assets (e.g., water for technological processes in economic activities, water and waterfronts for hydro reservoirs, swimming pools, ponds, waterfronts for conducting certain economic tasks, and extraction of materials from waterways). Furthermore, the energy potential of water can be tapped when the objective of concession is the construction and operation of energy plants, which stand as one of the paramount economic facets of water utilization. The concluding section delves into the Constitutional Court's practices regarding the concession institution, as well as the notion of "state property" as an increasingly emphasized topic in domestic jurisprudence.

Visibility graph for time series prediction and image classification: a review.

The analysis of time series and images is significant across different fields due to their widespread applications. In the past few decades, many approaches have been developed, including data-driven artificial intelligence methods, mechanism-driven physical methods, and hybrid mechanism and data-driven models. Complex networks have been used to model numerous complex systems due to its characteristics, including time series prediction and image classification. In order to map time series and images into complex networks, many visibility graph algorithms have been developed, such as horizontal visibility graph, limited penetrable visibility graph, multiplex visibility graph, and image visibility graph. The family of visibility graph algorithms will construct different types of complex networks, including (un-) weighted, (un-) directed, and (single-) multi-layered networks, thereby focusing on different kinds of properties. Different types of visibility graph algorithms will be reviewed in this paper. Through exploring the topological structure and information in the network based on statistical physics, the property of time series and images can be discovered. In order to forecast (multivariate) time series, several variations of local random walk algorithms and different information fusion approaches are applied to measure the similarity between nodes in the network. Different forecasting frameworks are also proposed to consider the information in the time series based on the similarity. In order to classify the image, several machine learning models (such as support vector machine and linear discriminant) are used to classify images based on global features, local features, and multiplex features. Through various simulations on a variety of datasets, researchers have found that the visibility graph algorithm outperformed existing algorithms, both in time series prediction and image classification. Clearly, complex networks are closely connected with time series and images by visibility graph algorithms, rendering complex networks to be an important tool for understanding the characteristics of time series and images. Finally, we conclude in the last section with future outlooks for the visibility graph.

Plinian Core: The long and winding road

Plinian Core (PliC) is a set of vocabulary terms that can be used to describe different aspects of biological species information. Under "biological species information" all kinds of properties or traits related to taxa—biological and non-biological—are included. Thus, for instance, terms pertaining to descriptions, legal aspects, conservation, management, demographics, nomenclature, or related resources are incorporated. Plinian Core started as a collaborative project between Instituto Nacional de Biodiversidad (INBio, Costa Rica) and the Global Biodiversity Information Facility Spain (GBIF Spain) in 2005. In successive years, the National Commission for Knowledge and Use of Biodiversity (CONABIO, Mexico), the National Network of Open Biodiversity Data (SiB Colombia)/the Humboldt Institute (Colombia), the University of Granada (Spain) and the University of São Paulo (USP, Brazil) were also involved. In 2012. PliC aligned with the Biodiversity Information Standards (TDWG) and an umbrella Interest Group was created (Species Information IG, Pando 2017b) with developments carried out by its corresponding TDWG Task Group (Plinian Core Task Group 2020b). PliC design requirements include: ease of use, being self-contained, able to support data integration from multiple databases, and ability to handle different levels of granularity. Since its early stages, PliC was formalized as an XML Schema. Its terms can be grouped in its current version as follows: Metadata Base elements Record metadata Nomenclature and classification Taxonomic description Natural history Invasive species Habitat and distribution Demography and threats Uses, management and conservation Miscellaneous: associated party, measurement or fact, references and ancillary data Metadata Base elements Record metadata Nomenclature and classification Taxonomic description Natural history Invasive species Habitat and distribution Demography and threats Uses, management and conservation Miscellaneous: associated party, measurement or fact, references and ancillary data During its years of existence, PliC has been implemented in several real-life contexts (e.g., Spanish Ministry for the Ecological Transition and the Demographic Challenge 2020, CRBIO 2020, SIB Colombia 2020), and a set of extensions for using PliC in GBIF Integrated Publishing Toolkit (IPT) was developed (Plinian Core Task Group 2020a). PliC has been featured in some TDWG conferences, either to explore and explain how it relates to other TDWG standards (Pando 2018), how PliC handles specific information aspects (Pando 2017a), or how it may be used in biodiversity portals (Vargas et al. 2018, Vargas et al. 2019). Recent work has focused on how to represent terms and codify structure as an XML Schema (XSD) under the current TDWG Documentation Standard (SDS, Vocabulary Maintenance Specification Task Group 2017). Challenges identified in the process comprise: how to handle terms used in different contexts, how to preserve the semantic context of terms reflected in the XSD hierarchy in the SDS flat layout, and how to refer to terms and definitions defined in other data specifications. These are the areas to focus our contribution.

Fatty Acids/Tetraphenylethylene Conjugates: Hybrid AIEgens for the Preparation of Peptide-Based Supramolecular Gels.

Aggregation-induced emissive materials are gaining particular attention in the last decades due to their wide application in different fields, from optical devices to biomedicine. In this work, compounds having these kinds of properties, composed of tetraphenylethylene scaffold combined with fatty acids of different lengths, were synthesized and characterized. These molecules were found able to self-assemble into different supramolecular emissive structures depending on the chemical composition and water content. Furthermore, they were used as N-terminus capping agents in the development of peptide-based materials. The functionalization of a 5-mer laminin-derived peptide led to the obtainment of luminescent fibrillary materials that were not cytotoxic and were able to form supramolecular gels in aqueous environment.

Numerical simulation of hydraulic fracture height using cohesive zone method

Hydraulic fracturing is a popular method used in the petroleum industry to increase the well performance by improving the permeability of the reservoir. However, while there has been extensive research on the development of the length of the fracture, the fractured height has been frequently assumed to be equal to the reservoir thickness. The objective of this paper is to study the influence of formation rock characteristics and the impact of underground stress state on the development of the fracture height. To achieve this objective, a finite element model was built using a cohesive zone method to predict the development of fracture height in time and space. Different scenarios were then effectuated by varying the values of the primary formation variables which are the Young’s modulus, the porosity, the Poisson ratio, the fracture energy, and the maximum horizontal stress of the reservoir and of the beddings. This research therefore covered principally uncontrolled factors which are the formation properties and stress state underground, which contribute mostly to the erroneous prediction in fracture height. The findings revealed that the fracture height was strongly influenced by the properties of the formation and of the adjacent layers. However, the influence levels are not the same for different kinds of properties. This study showed that the most influential mechanical property of the rock on the fracture height is the Young’s modulus. Regarding the porosity, its effect on the fracture height is extremely small. However, it is worth noting that the porosity is still an important parameter in hydraulic fracturing because it can be used to estimate others parameters and to model the development of fracture geometry which are width, length, and height. Practical suggestions for real-life hydraulic fracturing jobs can be deduced from this study, in order to control the fracture height as accurately as possible, and to decrease financial cost by concentrating mostly on the high influential factors instead of doing all kinds of tests for other less influential mechanical properties of the rock.

Co-branding hotel owners and operators to increase willingness to pay

ABSTRACT Although hotel brands are well established in the industry, customers have not been educated about the different kinds of properties, nor has hotel structure been utilised as a functional marketing tool. Drawing on previous studies, the purpose of this study is to evaluate consumer branding preferences and willingness to pay because of co-branding and informed ownership, operational, or franchise branding. This two-part study looks at consumer awareness and consumer preferences in the first part through semi-structured interviews, and in the second part, an experimental survey. Results reveal that most travellers do not understand the difference between a corporate-owned and -managed hotel and a franchised hotel. Co-branding efforts for management and ownership companies were not significant in both value perceptions and willingness to pay. However, co-branding efforts by ownership companies with parent companies increased their guests’ willingness to pay.

An Effective Resource Matching Scheme Based on a Novel Unified Descriptive Model for Modern Manufacturing Industry Systems

In order to effectively solve the problem of heterogeneous design/manufacturing/service resources and isolation in the whole lifecycle and realize unified description of design/manufacturing/service resources and resource sharing across subjects and stages, this paper proposes a hierarchical and modularized ontology-based resource-unified descriptive model, according to the characteristics of design/manufacturing/service resources. We analyze all kinds of properties of the resources, design a specific descriptive model of ontology, function, and service, ensure the consistency and independence of resource descriptions, and use the OWL (Web Ontology Language) ontology descriptive language and Protégé tools to verify. Then, based on the unified descriptive model, a resource matching method based on multi-level tags is proposed, which matches the task request with the resources in the resource library, selects the resources that meet the task request, and guarantees the resource sharing across subjects and stages. The resource matching work first performs task description and decomposition, and uses information entropy and rough set theory to sort the importance of subtasks, then uses the semantic similarity algorithm to complete multi-level tags’ matching. Finally, two examples are used to prove the feasibility and effectiveness of the experiment.

Nominalist dispositional essentialism

Dispositional Essentialism, as commonly conceived, consists in the claims that at least some of the fundamental properties essentially confer certain causal-nomological roles on their bearers, and that these properties give rise to the natural modalities. As such, the view is generally taken to be committed to a realist conception of properties as either universals or tropes, and to be thus incompatible with nominalism as understood in the strict sense. Pace this common assumption of the ontological import of Dispositional Essentialism, the aim of this paper is to explore a nominalist version of the view, Austere Nominalist Dispositional Essentialism. The core features of the proposed account are that it eschews all kinds of properties (be they universals, tropes, or sets of particulars), takes certain predicative truths as fundamental, and employs the so-called generic notion of essence. As I will argue, the account is significantly closer to the core idea behind Dispositional Essentialism than the only nominalist account in the vicinity of Dispositional Essentialism that has been offered so far—Ann Whittle’s (2009) Causal Nominalism—and is immune to crucial problems that affect this view.

Dependently-typed data plane programming

Programming languages like P4 enable specifying the behavior of network data planes in software. However, with increasingly powerful and complex applications running in the network, the risk of faults also increases. Hence, there is growing recognition of the need for methods and tools to statically verify the correctness of P4 code, especially as the language lacks basic safety guarantees. Type systems are a lightweight and compositional way to establish program properties, but there is a significant gap between the kinds of properties that can be proved using simple type systems (e.g., SafeP4) and those that can be obtained using full-blown verification tools (e.g., p4v). In this paper, we close this gap by developing Π4, a dependently-typed version of P4 based on decidable refinements. We motivate the design of Π4, prove the soundness of its type system, develop an SMT-based implementation, and present case studies that illustrate its applicability to a variety of data plane programs.

Single-valued hyperlogarithms, correlation functions and closed string amplitudes

We give new proofs of a global and a local property of the integrals which compute closed string theory amplitudes at genus zero. Both kinds of properties are related to the newborn theory of single-valued periods, and our proofs provide an intuitive understanding of this relation. The global property, known in physics as the KLT formula, is a factorisation of the closed string integrals into products of pairs of open string integrals. We deduce it by identifying closed string integrals with special values of single-valued correlation functions in two dimensional conformal field theory, and by obtaining their conformal block decomposition. The local property is of number theoretical nature. We write the asymptotic expansion coefficients as multiple integrals over the complex plane of special functions known as single-valued hyperlogarithms. We develop a theory of integration of single-valued hyperlogarithms, and we use it to demonstrate that the asymptotic expansion coefficients belong to the ring of single-valued multiple zeta values.

Deep generative models for peptide design.

Computers can already be programmed for superhuman pattern recognition of images and text. For machines to discover novel molecules, they must first be trained to sort through the many characteristics of molecules and determine which properties should be retained, suppressed, or enhanced to optimize functions of interest. Machines need to be able to understand, read, write, and eventually create new molecules. Today, this creative process relies on deep generative models, which have gained popularity since powerful deep neural networks were introduced to generative model frameworks. In recent years, they have demonstrated excellent ability to model complex distribution of real-word data (e.g., images, audio, text, molecules, and biological sequences). Deep generative models can generate data beyond those provided in training samples, thus yielding an efficient and rapid tool for exploring the massive search space of high-dimensional data such as DNA/protein sequences and facilitating the design of biomolecules with desired functions. Here, we review the emerging field of deep generative models applied to peptide science. In particular, we discuss several popular deep generative model frameworks as well as their applications to generate peptides with various kinds of properties (e.g., antimicrobial, anticancer, cell penetration, etc). We conclude our review with a discussion of current limitations and future perspectives in this emerging field.

PENETAPAN KADAR FLAVONOID FRAKSI ETIL ASETAT DAUN KARET KEBO (Ficus elastica) DENGAN METODE SPEKTROFOTOMETRI UV-VIS

Rubber plant ( Ficus elastica ) is a plant that has been widely used as traditional medicine. The leaves of this plant are used as medicine for coughing up blood, laxative urine, relieving pain and improving blood circulation. Various kinds of properties and benefits of the rubber plant ( Ficus elastica ) cannot be separated from the compounds contained in it such as saponins, polyphenols, and flavonoids. The aims of this research is to determine the flavonoid total content in the ethyl acetate fraction of the rubber leaves ( Ficus elastica ). Simplicia was extracted by maceration method, using 96% ethanol solvent for 3x24 hours and partitioned with a mixture of 96% ethanol - aquadest (2:3) and ethyl acetate as a solvent. Determination of flavonoid content using UV-Vis spectrophotometry method , with a maximum wavelength of 438 nm, using quercetin as a comparison. The results of this research obtained that the total flavonoid content in the ethyl acetate fraction of rubber leaves ( Ficus elastica ) was an average of 74,345 mgQE/g fraction