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A well known quotient of the real Stiefel manifold is the projective Stiefel manifold. We introduce a new family of quotients of the real Stiefel manifold by cyclic group of order 2 whose action is induced by simultaneous pairwise flipping of the coordinates. We obtain a description for their tangent bundles, compute their mod 2 cohomology and compute the Stiefel Whitney classes of these manifolds. We use these to provide applications to their stable span, parallelizability and equivariant maps, and some associated results in topological combinatorics. [ABSTRACT FROM AUTHOR]

In a comparative correlative construction, such as The less you read, the stupider you are, the two clauses must both be finite, like a root clause; but neither can stand alone, like a subordinate clause. The construction shares significant formal properties with one type of coordinate construction, such as You drink another can of beer and I'm leaving. The paper argues that a comparative correlative construction and such a coordinate construction have the same syntactic structure. In this structure, a functional element that is directly merged with a conjunct or a modifier occurs. Moreover, the construction-specific formatives, such as the clause-initial the or the Mandarin predicate-initial yue 'more', is analyzed as the result of the spanning of this functional element with another functional element in the clause. Furthermore, the pairing of the formatives in the construction comes from the Double Marking of this functional element. [ABSTRACT FROM AUTHOR]

Testosterone is one of the important hormones involved in various physiological activities including muscle growth, bone density, and libido. In this regard, delivery through niosomes may have potential advantages concerning its bioavailability and stability. Niosomes are vesicles based on non-ionic surfactants, an effective drug delivery system because of the encapsulation of different active pharmaceutical ingredients such as, hydrophilic, hydrophobics, and amphiphilic. In this work, differential scanning calorimetry (DSC), Fourier-transform infrared (FTIR) spectroscopy, and high-resolution transmission electron microscopy (HRTEM) were employed for the characterization of interactions and testosterone encapsulation in the fabricated niosome formulations. The main purpose of the work is to explain the absence of testosterone peaks in DSC spectra after the formulation of niosomes. Niosomes were prepared by dissolving 1% testosterone powder and different amounts of span60 powder, tween60 semisolid, and cholesterol powder via a modified solvent evaporation method. Besides the various plausible explanations associated with the testosterone peak changes, the few most important ones are solid-state transitions, interaction of the components via hydrogen bonding and van der Waals forces, encapsulation of testosterone, and dilution effect. These solid-state transitions might be polymorphic or transformation to the amorphous state from crystalline, which was also substantiated by the HRTEM images showing the crystalline structure at the center surrounded by an amorphous area. The FTIR data confirmed the testosterone encapsulation within the niosomes based on a chemical structure and functional groups. This analysis highlights the potential of designing stable niosome formulations for testosterone using different ingredients, facilitating its application in nanotechnology using different analysis techniques. [ABSTRACT FROM AUTHOR]

Vacuum gas atomization is the most commonly used technique to produce powders for additive manufacturing (AM). It is widely recognized that powder particle size distribution and micro-morphology can severely degrade the stability of powders in additive manufacturing and cannot be completely avoided. This particular study used a self-developed facility to produce aluminum powders that were sorted into various particle sizes via vacuum atomization. The study delved into the impact of melt superheat, positions of the delivery tube, and pressure on the physical properties of the powders. The findings indicated that pressure had the most pronounced effect on the satellite sphere. When the pressure was set at 3 MPa, the proportion of non-adherent powder reached 71.5%, with a span of 1.99. In contrast, the study revealed the influence of delivery tube position on the outcome was considerably negligible. [ABSTRACT FROM AUTHOR]

For a graph G (V , E) and ℓ ∈ ℕ , an ℓ distance coloring is a coloring f : V → { 1 , 2 , ... , t } of V with t colors such that ∀ u , v ∈ V , u ≠ v , f (u) ≠ f (v) when d (u , v) ≤ ℓ. Here d (u , v) is the distance between u and v and is equal to the minimum number of edges that connect u and v in G. The span of ℓ distance coloring of G , χ ℓ (G) , is the minimum t among all ℓ distance coloring of G. A class of channel assignment problem in cellular network can be formulated as a distance graph coloring problem in regular grid graphs. The cellular network is often modelled as an infinite hexagonal grid H , and hence determining χ ℓ (H) has relevance from practical point of view. Jacko and Jendrol [Discussiones Mathematicae Graph Theory, 2005] determined the exact value of χ ℓ (H) for any odd ℓ and for even ℓ ≥ 8 , it is conjectured that χ ℓ (H) = 3 8 (ℓ + 4 3) 2 where [ x ] is an integer, x ∈ ℝ and x − 1 2 < [ x ] ≤ x + 1 2 . For ℓ = 8 , the conjecture has been proved by Ghosh and Koley [ 2 2 nd Italian Conference on Theoretical Computer Science, 2021]. In this paper, we prove the conjecture for any even ℓ ≥ 1 0. [ABSTRACT FROM AUTHOR]

Direct ink writing (DIW) technology supersedes traditional mold‐based forming methods, significantly enhancing the fabrication of personalized and customized products with complex structures. This technology particularly excels in achieving precise control over the porosity of porous constructs. This study employs inorganic Al2O3 as raw material, sodium hexametaphosphate as dispersing agent, and inorganic SiO2 micropowder as binding medium to fabricate lattice porous structures. One challenge encountered is the viscoelastic behavior of the extruded filament. When spanning the unsupported segments of the lower layer, the upper extruded filaments are susceptible to deflection or collapse, adversely affecting the porosity and dimensional fidelity of the final specimens. Experimental results revealed that a larger span and smaller modulus will cause the extruded filament to be more prone to deformation at the midpoint. The introduction of 2 wt% polyethylene glycol as a plasticizer mitigates this issue, ensuring nondeflection of the extruded filaments at a span of 6 mm. The deflection model for the extruded filament about span and modulus identifies the minimum modulus necessary to prevent or minimize deflection under given spans, which closely approximates our experimental findings, offering a valuable framework for guiding the production of high‐precision, porosity‐controlled porous structures. [ABSTRACT FROM AUTHOR]

Implementation of sustainability principles in civil engineering has increased the substantive range of bridge engineering. The consideration of additional criteria, in particular ecological and social ones, requires the design process to be supported by appropriate tools. It refers especially to large bridge elements which affect their load-bearing capacity, e.g. girders or decks. The aim of this paper is to develop an original MCDA (Multi-Criteria Decision Analysis) method as a potential tool to support a decision-making process in the selection of material and design alternatives for bridge main girders. Therefore, an advanced hybrid algorithm was created consisting of the following methods: EA FAHP+FDEMATEL+ZUM (Extent Analysis Fuzzy Analytic Hierarchy Process + Fuzzy Decision-Making Trial and Evaluation Laboratory + Zero Unitarization Method), applied at the structure design stage. The pre-dimensioned alternatives selected for analysis were then subjected to an evaluation process based on a complex set of criteria arranged in a hierarchical control structure (HCS). The algorithm has been applied based on the example of a medium span slab-and-girder bridge, assuming 6 alternative concepts of girders, different in material and dimensions. The hybrid method was compared with the EA FAHP method. Analysis results obtained based on judgments from 3 teams of Decision Makers (DM) indicate effectiveness of the proposed algorithm and its practical aspect, which may contribute to improved quality and safety of bridge structures.

Sulfur‐polyacrylonitrile (SPAN) is a sulfur‐based active material for next‐generation lithium‐sulfur battery cathodes. Due to the covalent bonding between sulfur chains and the polymeric backbone, the shuttle effect degrading classical sulfur‐based cathodes can be suppressed while also achieving a high active material content in the cathode. In this paper, we investigate the processability of an industrially scalable SPAN active material with 38 wt.‐% of sulfur in a water‐based and scalable process route. The potential of the SPAN material for industrial adoption and the impact of the process route on the cell performance are discussed. We show that when processed correctly, the SPAN material delivers exceptional cycling stability and good C‐rate performance with ether‐based electrolytes. However, the performance of the SPAN cathode is influenced by the mixing characteristic. Using higher mixing intensities during the slurry preparation leads to deterioration of the electrochemical performance. This can be attributed to a decreasing carbon black percolation with increasing tip speed in combination with the kinetic limitation of sulfur cathodes during Li2S2 and Li2S oxidation. [ABSTRACT FROM AUTHOR]

Implementation of sustainability principles in civil engineering has increased the substantive range of bridge engineering. The consideration of additional criteria, in particular ecological and social ones, requires the design process to be supported by appropriate tools. It refers especially to large bridge elements which affect their load-bearing capacity, e.g. girders or decks. The aim of this paper is to develop an original MCDA (Multi-Criteria Decision Analysis) method as a potential tool to support a decision-making process in the selection of material and design alternatives for bridge main girders. Therefore, an advanced hybrid algorithm was created consisting of the following methods: EA FAHP+FDEMATEL+ZUM (Extent Analysis Fuzzy Analytic Hierarchy Process + Fuzzy Decision-Making Trial and Evaluation Laboratory + Zero Unitarization Method), applied at the structure design stage. The pre-dimensioned alternatives selected for analysis were then subjected to an evaluation process based on a complex set of criteria arranged in a hierarchical control structure (HCS). The algorithm has been applied based on the example of a medium span slab-and-girder bridge, assuming 6 alternative concepts of girders, different in material and dimensions. The hybrid method was compared with the EA FAHP method. Analysis results obtained based on judgments from 3 teams of Decision Makers (DM) indicate effectiveness of the proposed algorithm and its practical aspect, which may contribute to improved quality and safety of bridge structures. [ABSTRACT FROM AUTHOR]

Named entity recognition serves as an important foundation for many downstream tasks in the field of natural language processing. As an important international language, Chinese is unique in many aspects. Traditionally, models of Chinese named entity recognition tasks use sequence labeling mechanisms that require conditional random fields to capture label dependencies. However, this approach is prone to misclassification of labels. Aiming at this problem, a span-based named entity recognition model called RIB-NER is proposed. Firstly, the method provides character-level embedding through RoBERTa as a model embedding layer to obtain more contextual semantic and lexical information. Secondly, IDCNN is used to increase the position information between words with parallel convolution kernels, so that the connection between words is closer. At the same time, a BiLSTM network is integrated in the model to obtain context information. Finally, a Biaffine model is employed to score the start and end tokens in the sentence, and these tokens are used to explore spans. The proposed algorithm is tested on MSRA and Weibo corpora, the results show that it can accurately identify entity boundaries, achieving F1 scores of 95.11% and 73.94% respectively. Compared with traditional deep learning approaches, it demonstrates better recognition performance. [ABSTRACT FROM AUTHOR]

Solar greenhouses have been widely used in the vast western and northern regions of China, due mainly to the convenient construction and installation, low economic cost, and outstanding environmental adaptability. The slender steel can be the load-bearing components of the section-steel arched solar greenhouse to resist external loads, such as wind and snow. There are the prominent instability and disaster that caused by insufficient stiffness of solar greenhouse under extreme weather conditions, such as snowstorms. In this study, the nonlinear stability analysis was conducted on the commonly-used sectionsteel arched solar greenhouse in Hebei using elastic-plastic mechanics and nonlinear finite element (FE). A refined FE model was established for the section-steel arched solar greenhouse. The greenhouse arch roof and the vertical sections on both sides were simulated using the Beam188 element in the element library of the universal FE analysis program ANSYS. The linear elements were used to fit the circular arc segments. Diagonal tension bars, vertical brace struts, and longitudinal tie bars were all simulated using Link10 element. The bottom of the vertical sections on both sides of the arch was assumed to be consolidated with the foundation. The steel was made of Q235, with an elastic modulus of 206 GPa, a Poisson's ratio of 0.3, and a density of 7 850 kg/m³. Geometric and material nonlinearity was considered to simulate the constitutive relationship of steel using an ideal elastic-plastic model, followed by von Mises yield criterion and bilinear kinematic hardening model BKIN. The stability performance and parameter analysis of solar greenhouse structure were carried out under snow loads. The stability capacity of solar greenhouse was determined under different parameters, such as steel-section type (flat elliptical, hollow rectangular and hat-shaped cross-section), greenhouse span (8, 10, and 12 m), and snow load distribution pattern (non-uniform distribution thickness and asymmetric distribution area). There was the quantitative influence of snow load distribution on the stability capacity of solar greenhouses. The load factor-displacement curves were combined with the deformation, stress, axial, and bending moment at different points of loading time. The static instability of solar greenhouses was explored from two aspects: intuitive phenomena and intrinsic essence. The conclusions were obtained as follows: The stability capacity of the steel component with a flat elliptical section in the solar greenhouse was increased by 21.0% and 44.2%, respectively, compared with the box and hat-shaped section. There was no out of plane instability in the same cross-sectional area and flange width of the steel component. The stability capacity of solar greenhouse was rapidly reduced with the increase of span. The stability capacity of solar greenhouse under non-uniform distribution of snow loads was reduced by the maximum of 63.8%, compared with the uniform. The maximum stability capacity of a solar greenhouse increased by 9.0% and 66.8% with only tension bars and brace struts, respectively. The findings can provide the technical guidance and theoretical reference for the anti-snow loads, stability and disaster prevention in the section-steel arch solar greenhouses. [ABSTRACT FROM AUTHOR]

Architecture is a complex web of semiotics – signs, signals and signifiers. The creation of these codes, and their dynamic manipulation and interaction over time, is the lifeblood of experimental architecture practice SPAN's Doghouse project. Co‐founder Sandra Manninger explains how the project's articulation, robotic inhabitants and fluctuating symbolic meanings and languages create a complex multi‐readable architectural structure and text. [ABSTRACT FROM AUTHOR]

Span-based joint extraction simultaneously conducts named entity recognition (NER) and relation extraction (RE) in a text span form. However, since previous span-based models rely on span-level classifications, they cannot benefit from token-level label information, which has been proven advantageous for the task. In this paper, we propose a sequence tagging augmented span-based network (STSN), a span-based joint model that can make use of token-level label information. In STSN, we construct a core neural architecture by deep stacking multiple attention layers, each of which consists of three basic attention units. On the one hand, the core architecture enables our model to learn token-level label information via the sequence tagging mechanism and then uses the information in the span-based joint extraction; on the other hand, it establishes a bi-directional information interaction between NER and RE. Experimental results on three benchmark datasets show that STSN consistently outperforms the strongest baselines in terms of F1, creating new state-of-the-art results. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Nanchang University (Engineering & Technology) is the property of Nanchang University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the promising and current trends in the design of wide span sprinkling machines is the principle of resource saving. Trends for improving the design and technological parameters of sprinkling equipment based on the principles of resource conservation are considered, and a concept for the development of sprinkling equipment based on operating conditions is formed. The research carried out made it possible to improve the truss structures of the KASKAD model range of sprinkling machines. The reduction in material consumption is based on optimizing the parameters of spans and truss structures, for which coefficients of metal consumption of the truss and the weight of angles were proposed. Improvement of the truss structure made it possible to increase the span length by 22.1–33.8% with a slight increase in mass by 5.8–15.1%. [ABSTRACT FROM AUTHOR]

DC microgrids are seen as smart solutions to interface DC loads and distributed energy resources (DERs). However, in DC microgrids, the placement of sources and loads as well as the size of cable impact the system’s span, regulation of voltage, and losses. This paper proposes novel algorithms to determine the maximum span and optimal size of cable for the improved performance of a droop-controlled DC microgrid. The proposed algorithms utilize an improved power flow analysis (IPFA) method based on Newton-Raphson technique to determine the maximum span and the optimal size of cable, enhancing the voltage regulation and reducing the cost. Additionally, the impacts of power rating, droop constants, and size of cable on the DC microgrid’s maximum span are investigated and reported. Owing to the intricate nature of the problem concerning the ideal size of cable for the droop-controlled DC microgrid, a heuristic optimization approach is employed. Further to enhance the rate of convergence and computational performance, an improved particle swarm optimization (IPSO) is also proposed. The constraint of keeping the bus voltage variations below the allowable voltage regulation limits is applied to the objective function of the optimization problem. In the case of a droop-controlled, DC microgrid having a specified configuration, the suggested algorithm can determine the ideal size of cable, guaranteeing both the least cost and enhanced voltage regulation. Comprehensive numerical and modelling results have been presented for a droop-controlled DC microgrid with different loads and DERs to verify the effectiveness of the proposed methods. Furthermore, the analysis reveals that configuration III of the DC microgrid with an optimal cable size of 19 mm2 lowers the absolute voltage regulation to as low as 1.06 V. The results of the detailed analysis validate the enhanced performance of the proposed algorithms and are highly useful to both system designers and consumers of the DC microgrids, eventually paving the way for the widespread use of DC microgrids in the future.

Geographical positioning system based end computer control technology are utilized in the air modelling based dynamics models. Unmanned aircraft have the potential to significantly increase their coverage and flying precision. The observation area is effectively controlled if traditional continues pest control algorithms are used. Calculating the path phones take a long time. It is not ideal for aircraft control in real time, when Bezier curves are used to calculate the planning path point allow to minimize the calculation time in easiest way, but producing an expected target becomes difficult. When linear and circular interpolation devices which are frequently utilized in numerical, control system aid applied to the aircraft turning path control algorithm, the calculation time is reduced and the flight path becomes accurate as per objectives of this research discussed in section two. This paper combines flight course control and effects of flying speed an angle of attack on aircraft height to explain how the turning path control algorithm is implemented. The outcome results demonstrate that path control is accurate and the algorithm straight forward. Finally air photography and flight tests confirm the rationality of the design.

In the domain of news, recognizing named entities involves complex syntactic structures and long names, leading to the challenge of determine entity boundaries and the problem of early interruption of sequence labeling methods when predicting long entities. To address these issues, this paper proposes a new model, named SpaCE (Named Entity Recognition based on Span and Category Enhancement for Chinese News), to identify named entity from Chinese news. SpaCE is based on the pre-trained model of BERT and enhanced by span prediction and category description. In the process of encoding news text information, the model combines category description to enhance semantic knowledge, and adopts a span-based decoding method to solve the problem of long entity prediction interruption. In addition, the word boundary information is introduced by the method of precise labeling, and the entity matching strategy is optimized, which effectively reduces the non-entity matching situation caused by span decoding. Compared to the baseline models, SpaCE improves the performance on all three datasets. In addition, in the dataset with disordered texts, the SpaCE model still shows strong named entity recognition ability, indicating its good robustness.

Aspect sentiment triplet extraction (ASTE) is one of the subtasks of aspect-based sentiment analysis, which aims to identify all aspect terms, their corresponding opinion terms and sentiment polarities in sentences. Currently, pipeline or end-to-end models are adopted to accomplish the ASTE task. The former cannot solve the overlapping problem of aspect terms in triplets and ignores the dependency between opinion terms and sentiment polarities. The latter divides the ASTE task into two subtasks of aspect-opinion-extraction and sentiment-polarity-classification, which applies multi-task learning through a shared encoder. However, this setting does not distinguish the differences between the features of the two subtasks, leading to the feature confusion problem. SD-ASTE (span-level dual-encoder model for ASTE), a pipeline model with two modules, is proposed to address the above problems. The first module extracts aspect terms and opinion terms based on spans. The span feature representation incor-porates span head, tail and length information to focus on the boundary information of aspect terms and opinion terms. The second module judges the sentiment polarities expressed by aspect-opinion span pairs. The span-pair feature representation is based on levitated markers to focus on the dependency among triplet elements. The model utilizes two independent encoders to extract different features for each module. Comparative experimental results on multiple datasets show that the model is superior to the state-of-the-art pipeline and end-to-end models. Validity experiments show the effectiveness of the span feature representation, span-pair feature representation and the two independent encoders.

China is pushing ahead with the development of the electricity market based on renewable energies. Electricity futures and options are an important trading instrument in the electricity market, and margins in the electricity market are often used to measure the value at risk of derivatives such as options on electricity futures, which are usually calculated based on the SPAN system. However, traditional SPAN systems do not take into account the integrity of electricity (IoE) derivatives, which would affect the risk valuing and capital usage efficiency. This paper proposed an improved margin calculation method that considers the IoE and gave an example for explanation. Compared with the previous calculating method, the method can effectively control the sharp fluctuations in electricity prices when renewable energy sources are traded in the electricity market, and effectively control the default risk in the market.

This article discusses the concept of radio k-labellings of graphs and presents results on the radio k-chromatic number of path Pn for k = 2, 3, and 4. The authors provide lower bounds for the radio-chromatic number of a path and introduce definitions and lemmas related to path labeling and radio labeling. The text is highly technical and may require further study for a complete understanding. The paper acknowledges the financial support of the National Board for Higher Mathematics (NBHM) in India. [Extracted from the article]

In this paper, we demonstrate that the realm of near-vector spaces enables us to address nonlinear problems while also providing access to most of the tools that linear algebra offers. We establish fundamental results for near-vector spaces, which serve to extend classical linear algebra into the realm of near-linear algebra. Within this paper, we finalize the algebraic proof that for a given scalar group F, any nonempty F-subspace that remains stable under addition and scalar multiplication constitutes an F-subspace. We prove that any quotient of a near-vector space by an F-subspace is itself a near-vector space, along with presenting the First Isomorphism Theorem for near-vector spaces. In doing so, we obtain comprehensive descriptions of the span. By defining linear independence outside the quasi-kernel, we introduce a new concept of basis. We also establish that near-vector spaces are characterized based on the presence of a scalar basis. [ABSTRACT FROM AUTHOR]

The entity-relationship extraction model has a significant influence in relation extraction. The existing model cannot effectively identify the entity-relationship triples in overlapping relationships. It also has the problem of long-distance dependencies between entities. In this paper, an inter span learning for document-level relation extraction model is proposed. Firstly, the model converts input of the BERT pre-training model into word vectors. Secondly, it divides the word vectors to form span sequences by random initial span and uses convolutional neural networks to extract entity information in the span sequences. Dividing the word vector into span sequences can divide the entity pairs that may have overlapping relationships into the same span sequence, partially solving the overlapping relationship problem. Thirdly, the model uses inter span learning to obtain entity information in different span sequences. It fuses entity type features and uses Softmax regression to achieve entity recognition. Aiming at solving the problem of long-distance dependence between entities, inter span learning can fuse the information in different span sequences. Finally, it fuses text information and relationship type features, and uses Linear Layer to classify relationships. Experiments demonstrate that the model improves the F1-score of the DocRED dataset by 2.74% when compared to the baseline model. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract This study employs the finite element-based CSiBridge v.20.0.0 software to examine the response of a single-cell prestressed box-girder bridge subjected to Indian loading conditions. The analyses is carried out on a simply supported bridge considering the specifications of Indian Road Congress (IRC) 6:2017, IRC 18:2000 and IRC 21:2000. An existing model of prestressed skewed bridge is validated with the published one. A convergence study is conducted for determining the model’s mesh size. An extensive parametric study is carried out to gain a better understanding of the response of a skewed prestressed bridge. The parameters variables are: Skew angle (0°, 10°, 20°, 30°, 40°, 50°, and 60°); Span (35, 40, 45, 50, 55, and 60 m); and Span-depth ratio (10, 12, 14, 16 and 18). The results of this study are presented as ratios of Bending moment, Shear force, Torsional moment, and Vertical deflection. Finally, equations for estimation of these ratios for different span and span-depth ratio are also deduced from the statistical approach so that the results of skewed bridges may be evaluated directly. It is determined that the skewed bridge outperforms the straight bridge because of its higher span-depth ratio, which results in less bending moment development. Evidence suggests that the skewness may help to lessen the prestress load’s dominance. The findings of this study may be helpful to engineers and designers in the analysis and design of prestresssed skewed box-girder bridges.

This paper investigates the radio labeling of friendship networks ( F 3 , k ,     F 4 , k ,     F 5 , k , and   F 6 , k ). In contrast, a mathematical model is proposed for determining the upper bound of radio numbers for ( F 3 , k ,     F 4 , k ,     F 5 , k , and   F 6 , k ). A computational investigation is presented to demonstrate that our results are superior to those of the past. In conclusion, the empirical study demonstrates that the proposed results surpass the previous ones in terms of the upper bound of the radio number and the run-time. [ABSTRACT FROM AUTHOR]

Although entity and relation joint extraction can obtain relational triples efficiently and accurately, there are a number of problems; for instance, the information between entity relations could be transferred better, entity extraction based on span is inefficient, and it is difficult to identify nested entities. In this paper, a joint entity and relation extraction model based on an Enhanced Span and Gate Mechanism (ESGM) is proposed to solve the above problems. We design a new span device to solve the problem of entity nesting and inefficiency. We use the pointer network method to predict the beginning and end of the span, and combine them through the one-to-many matching principle. A binary classification model is then trained to predict whether the span of the combination is the subject. In the object prediction stage, a gating unit is added to fuse the subject information with the sentence information and strengthen the information transfer between the entity and the relationship. Finally, the relationship is used as the mapping function to predict the tail entity related to the head entity. Our experimental results prove the effectiveness of this model. The precision of the proposed model reached 93.8% on the NYT dataset, which was 0.4% higher than that of the comparison model. Moreover, when the same experiment was conducted in a nested entity scenario, the accuracy of the proposed model was 4.4% higher than that of the comparison model. [ABSTRACT FROM AUTHOR]

Over the last decade, millions of 4G and 5G-enabled mobile devices have become part of the Internet. Almost, all the applications have been shifted to smartphones. A person connects his smartphone to several other devices or remote servers for exchanging sensitive data. In this sense, security threats in terms of authentication, data confidentiality, and data integrity are increasing day by day for mobile devices. The asymmetric key cryptosystem is considered more secure, but it is heavyweight for smart devices on the basis of computation and communication costs. The symmetric key cryptosystem is considered lightweight for smart devices in terms of computation and communication overheads, but it is vulnerable to several attacks such as MITM attacks. Several symmetric key security systems have been proposed for smart devices but adopt complex mathematical procedures. Therefore, existing symmetric key security systems increase the computation and communication overheads. In this paper, we propose a lightweight and authentic symmetric key cryptosystem for resource-constrained mobile client–server environments. Our proposed cryptosystem consists of a lightweight symmetric session key exchange algorithm, mutual authentication service, and data confidentiality service, respectively. Moreover, we prove the robustness of our proposed cryptosystem with the help of informal and formal security analysis through the AVISPA tool. In addition, performance evaluation and comparisons with existing security systems show that our proposed cryptosystem is efficient, lightweight, secure, and most suitable for mobile computing. [ABSTRACT FROM AUTHOR]

The entity–relationship joint extraction model plays a significant role in entity relationship extraction. The existing entity–relationship joint extraction model cannot effectively identify entity–relationship triples in overlapping relationships. This paper proposes a new joint entity–relationship extraction model based on the span and a cascaded dual decoding. The model includes a Bidirectional Encoder Representations from Transformers (BERT) encoding layer, a relational decoding layer, and an entity decoding layer. The model first converts the text input into the BERT pretrained language model into word vectors. Then, it divides the word vectors based on the span to form a span sequence and decodes the relationship between the span sequence to obtain the relationship type in the span sequence. Finally, the entity decoding layer fuses the span sequences and the relationship type obtained by relation decoding and uses a bi-directional long short-term memory (Bi-LSTM) neural network to obtain the head entity and tail entity in the span sequence. Using the combination of span division and cascaded double decoding, the overlapping relations existing in the text can be effectively identified. Experiments show that compared with other baseline models, the F1 value of the model is effectively improved on the NYT dataset and WebNLG dataset. [ABSTRACT FROM AUTHOR]

During operation, cables of overhead power lines (OPLs) are exposed to the impact that differs in separate parts of the OPL span due to the different responses of cables near the clamps and far from them. This paper presents the results of a study of aluminum and steel wires cut from such separate parts of ACSR cables before and after exploitation. Structural, microstructural, and elastic–microplastic properties of wires and their changes during operation were studied through optical microscopy, energy-dispersive X-ray microanalysis, electron backscattering diffraction, X-ray diffraction, densitometry, and acoustic measurements. The characteristics of the properties of the wires along the span were found to change in a coordinated manner. Numerical estimates of the influence of the steel core on aging the ACSR cable were obtained. Changes in the properties of the wires, as well as oxidization and corrosion of their near-surface layers, were studied in detail. Quantitative values of the characteristics of properties, the most distant from those observed in the new wires, were revealed for samples of aluminum and steel wires cut from the cable at 1/4 span and near clamps. It is assumed that these cable parts should be the most crucial for cable durability. [ABSTRACT FROM AUTHOR]

Psycholinguistics is the study of how neuroanatomical processes influence language acquisition, language structure, and language use (Menn & Dronkers, 2017). According to the field of psycholinguistics, a concept is represented in the mind and is different from the word associated with those representations. Representational theory of mind seeks to explain concepts through symbols and models of cognitive processes (Williams, 1984). In order to be relevant from a psychological standpoint, representational theory of mind must utilize a computational model rather than focus on individual beliefs. Many different theories use a representational model to explore how individuals acquire and categorize concepts. The aim of this study is to develop a theoretical cognitive model—titled the Semantic-Phonological Association Network (SPAN)—of singular concept generation. While developing SPAN, an examination of the current literature and different theories of models relating to concept generation are used as the foundation for the research. For example, Pinker’s “Why We Curse” explores the relationship between the phonetics of swear words and the physical manifestations they represent (Pinker, 2007). It is necessary to represent the phonological and semantic networks as separate but intricately connected systems. SPAN seeks to symbolize the connection between the phonological and semantic system. The main goal is to establish auditory-semantic priming effects from the relationship between the mental systems and introduce a nuanced version about how one is able to generate singular concepts that contain semantic, phonological and lexical information.You can find our presentation link here: https://drive.google.com/file/u/2/d/1vRzU6wGm5Di0GQZclCa3VK34JWlOYmY0/view

The Euler-Bernoulli beam theory is used to establish the vibration differential equation of the rigid catenary, the cantilever support device is equivalent to the spring, and the pantograph is equivalent to the three mass block model. The double-pantograph-catenary (DPC) dynamic coupling model is established by using the penalty function, and utilize Newmark- $\beta $ solved the model, verifying the reliability of the model with the field test contact forces of the rigid catenary system (RCS) of Xi’an Metro in China, and illustrating the vibration characteristics and fluctuation propagation characteristics of the rigid catenary structure in combination with the fluctuation propagation theory of beam and the sag model of rigid catenary. Based on the model, the dynamic interaction mechanism between the pantograph and the rigid catenary is studied, including the influence of different spans, speeds on the dynamic contact force of the DPC, the flow field of the pantograph is analyzed with ANSYS, and the influence of train induced wind in the tunnel is studied in combination with the DPC model. The results show that when the train operates on RCS with a double pantograph, the contact force fluctuation of the trailing pantograph (TP) is more severe than that of the leading pantograph (LP); Among the three common spans of 6m, 8m, and 10m, when the speed is less than 80 km/h, the span of 8m or 10m should be selected, when the speed is 80–140 km/h, the span of 6m or 8m should be selected, when the speed is greater than 140 km/h, the span should be the minimum 6m; With the increase of the wind velocity and the angle of attack, the fluctuation of the pantograph-catenary contact force of the RCS increases, and compared to the LP, the contact force fluctuation of the TP is greater.

Due to advent of technology and internet, teaching too is now largely utilizing these modern devices and internet to impart education to the children. When it was mandatory to keep social distancing and hence avoid regular classes for medical students during the dreadful COVID pandemic, it was decided to teach the 1st year MBBS students online using the technology and the internet. This study aimed at determining if the students found this novel online teaching to be helpful or not. Methodology: A total of 100 1st year MBBS students in a tertiary medical college in central India were included in the study from September 2020 to February 2021 for 6 months. It was an observational study and an informed consent from the students was taken prior to the study. Classes were conducted as usual as per the institutional guidelines and feedback forms were collected after that. Results: Out of total 100 students, 65 were girls and 35 were boys. Average age of the class was 19.2  1.1 years. 85% had used mobile phones and internet for education before and 15% had never used it for education purpose. 75% had a concentration time of 30 minutes. About 50% students faced internet issues and faced moderate disturbance during the classes. 85% used mobile phones for the classes. 60% students opined that such online classes are effective for teaching anatomy while 40% told that it was not effective. Conclusion: The study concludes that currently online classes for the subject like anatomy are not as effective as regular classroom teaching. The factors could be low motivation, technology and internet problems, low attention span etc. [ABSTRACT FROM AUTHOR]

Deaf signers consistently show shorter memory spans than hearing nonsigners, but the scope and nature of this difference remain unclear. The present study tested whether Deaf signers are biased toward flexible use of visual aspects of linguistic items. Matched samples of adult Deaf signers (N = 33) and hearing nonsigners (N = 32) performed a letter-span task with visual serial presentation, to bias phonological processing, and a simultaneous presentation, to bias visuospatial processing. We also manipulated short-term memory by varying recall direction (forward, backward). Analyses revealed reduced spans for Deaf signers compared with hearing nonsigners, backward compared with forward recall, and sequential compared with simultaneous presentation. Item-level responses indicated that Deaf signers made more errors than hearing nonsigners across three error types. Deaf signers also showed reduced item position binding compared with hearing nonsigners, which indicates differences related to item order and sequencing in tasks with printed, linguistic stimuli. Deaf signers were the only group who demonstrated reduced omission errors when switching from sequential to simultaneous presentation, suggesting flexible processing mechanisms. No group differences were found for a secondary spatial span test, indicating the scope of group differences for ordered information was limited to verbal items. Overall, results are consistent with flexible use of different memory cues in Deaf signers. A core area for future research includes evaluating reduced activation of phonological representations of linguistic items in Deaf signers. These results amplify a novel M3 model approach for evaluating how errors contribute to short-term memory differences in Deaf signers. [ABSTRACT FROM AUTHOR]

This study employs the finite element-based CSiBridge v.20.0.0 software to examine the response of a single-cell prestressed box-girder bridge subjected to Indian loading conditions. The analyses is carried out on a simply supported bridge considering the specifications of Indian Road Congress (IRC) 6:2017, IRC 18:2000 and IRC 21:2000. An existing model of prestressed skewed bridge is validated with the published one. A convergence study is conducted for determining the model's mesh size. An extensive parametric study is carried out to gain a better understanding of the response of a skewed prestressed bridge. The parameters variables are: Skew angle (0°, 10°, 20°, 30°, 40°, 50°, and 60°); Span (35, 40, 45, 50, 55, and 60 m); and Span-depth ratio (10, 12, 14, 16 and 18). The results of this study are presented as ratios of Bending moment, Shear force, Torsional moment, and Vertical deflection. Finally, equations for estimation of these ratios for different span and span-depth ratio are also deduced from the statistical approach so that the results of skewed bridges may be evaluated directly. It is determined that the skewed bridge outperforms the straight bridge because of its higher span-depth ratio, which results in less bending moment development. Evidence suggests that the skewness may help to lessen the prestress load's dominance. The findings of this study may be helpful to engineers and designers in the analysis and design of prestresssed skewed box-girder bridges. [ABSTRACT FROM AUTHOR]