bluuebunny/crossref_metadata_2025 huggingface dataset:
The Evolution and Determinants of Ecosystem Services in Guizhou—A Typical Karst Mountainous Area in Southwest China
Authors: Jiao Lu , Yang Rui , Zhang Yinling , Yin Jian , Huang Jiayu
Published: July 2022

Due to rapid urbanization and economic development, the natural environment and ecological processes have been significantly affected by human activities. Especially in ecologically fragile karst areas, the ecosystems are more sensitive to external disturbances and have a hard time recovering, thus studies on the ecosystem services in these areas are significant. In view of this, we took Guizhou (a typical karst province) as the research area, evaluated the ecosystem service value (ESV) according to reclassified land uses and revised equivalent factors, and investigated the determinants of ecosystem services based on geographic detection. It was found that the total ESV showed a prominent increase trend, increasing from 152.55 billion CNY in 2000 to 285.50 billion CNY in 2020. The rise of grain prices due to growing social demands was the main factor in driving the increase of ESV. Spatially, the ESVs of central and western Guizhou were lower with cold spots appearing around human gathering areas, while that of southern and southeastern Guizhou were higher with hot spots that formed in continually distributed woodland. Moreover, the ESV per unit area and its change rate in karst regions were always lower than that in non-karst areas. Precipitation and temperature were the dominant nature factors while cultivation and population density were the main anthropogenic effects driving the evolution of ecosystem services. Therefore, positive human activities as well as rational and efficient land-use should be guided to promote the coordinated and high-quality development of ecology and the economy.
Bibliometric Analysis and Systematic Review of Indigenous Knowledge from a Comparative African Perspective: 1990–2020
Authors: Malapane Olgah Lerato , Musakwa Walter , Chanza Nelson , Radinger-Peer Verena
Published: July 2022

Globally, indigenous knowledge (IK) has been shown to be a critical factor in economic growth and sustainable development and is as important as scientific knowledge. However, when it comes to the African narrative, IK research still seems to fall short, even with the great recognition and interest it is attracting. IK has always been underprivileged and marginalized, treated as an unsubstantiated type of knowledge that cannot provide any scientific solutions. Consequently, the aim of this paper is to provide an insight into the importance of IK research from a comparative African perspective from 1990 to 2020. The paper used a combination of bibliometric analysis and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol to provide a comprehensive view of IK research. The VOSviewer software was used to provide a visualization of the bibliometric analysis through network maps. The findings suggest that while IK is a globally recognized concept, the African narrative is missing and not told by Africans. Most researched studies on IK in Africa are on ethnobotany, customs, traditions, agroforestry, and agriculture. Moreover, most of the IK research is from Southern Africa. There is a need for the integration of IK and scientific knowledge to develop well-informed approaches, methodologies, and frameworks that cater to indigenous communities and resilient ecological development. The research outcomes provide valuable insights for future research trends; they further highlight opportunities for building research partnerships for strengthening policy generation and implementation.
Spatial Relationship between Land Use Patterns and Ecosystem Services Value—Case Study of Nanjing
Authors: Lu Ming , Zhang Yan , Liang Fan , Wu Yuanxiang
Published: July 2022

The degree of land use reflects the progress of social and economic development; however, it also has a direct impact on land resources. Maximizing the ecosystem services of land resources in a limited space is a key issue in China’s rapid urbanization. Therefore, this study aims to analyze the spatial relationship between land use patterns and ecosystem services to enhance the benefits of urban ecology. First, we used the landscape pattern index to represent land use patterns and the equivalence factor method to quantify the ecosystem services value (ESV); second, spatial autocorrelation and spatial autoregression were used to explore the spatial relationship between the landscape pattern index and ESV. Our main conclusions were that (1) the landscape pattern index and ESV both showed obvious spatial aggregation, but that of ESV was more significant; (2) the largest patch index and contagion index had a greater degree of influence on ESV than other variables, with the largest patch index having a positive effect and the contagion index having a negative effect; (3) it was necessary to cultivate the landscape dominance of land patches in ecological spatial regulation and to form large-scale ecological agglomeration in key ecological source areas and nodes. The research results can ensure that land resources exert a higher level of ecological value by adjusting the spatial form of the landscape patch.
Evaluation of Urban Spatial Growth Performance from the Perspective of a Polycentric City: A Case Study of Hangzhou
Authors: Zhang Liang , Zhang Linlin , Liu Xue
Published: July 2022

Although polycentrism is widely promoted by city planners and policymakers as a potential solution for alleviating the sprawl of central urban areas, there is no sufficient empirical evidence to verify the validity of this claim. Our study aims to complement this experience by providing solid evidence on whether polycentric urban structures can mitigate the problem of urban sprawl. In this study, the corresponding evaluation factors are selected from four perspectives: socioeconomic, spatial form and organization, and ecological environment, to measure the performance of Hangzhou’s polycentric spatial development. The results show that the performance in Hangzhou has improved significantly, and the performance improvement is more prominent over the 2010–2020 period. Third, the changing characteristics of the spatial development performance of the city centers show a significant diversity. During the study period, the development of Jiangnan city started early, but the development performance of Xiasha city improved significantly, and the development of Linping city was relatively the weakest. Fourth, socioeconomic and urban spatial organization are the main factors causing the temporal stage and spatial variability of the performance in Hangzhou. It can be seen that market-driven endogenous factors are more conducive to improving spatial development performance than government-led exogenous factors.
Pen-and-Paper versus Computer-Mediated Writing Modality as a New Dimension of Task Complexity
Authors: Vasylets Olena , Marín Javier
Published: July 2022

In this paper we make a proposal that writing modality (pen-and-paper versus computer-based writing can be conceptualized as a cognitive task complexity factor. To lay ground for this theoretical proposal, we first review previous adaptations of cognitive task-based models to second language (L2) writing. We then compare pen-and-paper and computer-based writing modalities in terms of their general characteristics, outline the main tenets of multidisciplinary theoretical models which attribute learning and performance-related importance to writing modality, and review the available empirical evidence. From this we draw theoretical and empirical justification for our conceptualization of writing modality as a task complexity dimension. After outlining our conceptual view, we proceed with the review of the methods which could be used to independently assess cognitive load in paper and computer-written L2 tasks. In the conclusion, implications and suggestions for future research are provided.
CPU Performance Improvement Using Novel Thermally Conductive Carbon Nano Grease
Authors: Grablander Travis , Christensen Greg , Bailey Craig , Lou Ding , Hong Haiping , Younes Hammad
Published: July 2022

Electronics depend on their ability to shed operational heat to maintain operating temperature. Inferior grease can create preventable problems in electronics. This is typically achieved through a thermal grease or paste. If this grease fails to dissipate heat or maintain thermal contact, then the equipment will have faults. Greases with less-than-optimal performance create excessive wear, heat, and reduced life expectancy. This can cause equipment failures and malfunctions at the most inopportune moments. Thermal greases are applied to Central Processors (CPU) and Graphics Processors (GPU) in avionics LRUs, computers, Solar panels, HVAC systems, and other electronics. A high-performance novel nano grease will shed excess heat and increase device life expectancy. The fabricated nano greases show improvements of up to 80% in thermal conductivity measurements. CPU testing resulted in a 100% decrease in the standard deviation of temperature variation from commercial greases.
Concrete Made with Partially Substitutions of Copper Slag (CPS): State of the Art Review
Authors: Ahmad Jawad , Majdi Ali , Deifalla Ahmed Farouk , Isleem Haytham F. , Rahmawati Cut
Published: July 2022

Copper slag (CPS) is a large amount of waste material produced during the manufacture of copper. The disposal of this waste material becomes a problem for environmental concerns. Therefore, it is necessary to explore feasible alternate disposal options. They may also be utilized in concrete manufacturing to cut down on the usage of cement and natural aggregates. A lot of researchers focus on utilizing CPS in concrete, either as a cement replacement or as a filler material. This article aims to summarize the literature already carried out on CPS in conventional concrete to identify the influence of CPS on the fresh, hardened and durability performance of cement concrete. Results indicate that CPS improved the strength and durability performance of concrete but simultaneously decreased the slump value of concrete. Furthermore, an increase in the durability performance of concrete was also observed with CPS. However, the higher dose results declined in mechanical and durability aspects owing to a scarcity of flowability. Therefore, it is suggested to use the optimum dose of CPS. However, a different researcher recommends a different optimum dose ranging from 50 to 60% by weight of fine aggregate depending on the source of CPS. The review also recommends future researcher guidelines on CPS in concrete.
Use of Artificial Intelligence for Predicting Parameters of Sustainable Concrete and Raw Ingredient Effects and Interactions
Authors: Amin Muhammad Nasir , Ahmad Waqas , Khan Kaffayatullah , Ahmad Ayaz , Nazar Sohaib , Alabdullah Anas Abdulalim
Published: July 2022

Incorporating waste material, such as recycled coarse aggregate concrete (RCAC), into construction material can reduce environmental pollution. It is also well-known that the inferior properties of recycled aggregates (RAs), when incorporated into concrete, can impact its mechanical properties, and it is necessary to evaluate the optimal performance. Accordingly, artificial intelligence has been used recently to evaluate the performance of concrete compressive behaviour for different types of construction material. Therefore, supervised machine learning techniques, i.e., DT-XG Boost, DT-Gradient Boosting, SVM-Bagging, and SVM-Adaboost, are executed in the current study to predict RCAC’s compressive strength. Additionally, SHapley Additive exPlanations (SHAP) analysis shows the influence of input parameters on the compressive strength of RCAC and the interactions between them. The correlation coefficient (R2), root mean square error (RMSE), and mean absolute error (MAE) are used to assess the model’s performance. Subsequently, the k-fold cross-validation method is executed to validate the model’s performance. The R2 value of 0.98 from DT-Gradient Boosting supersedes those of the other methods, i.e., DT- XG Boost, SVM-Bagging, and SVM-Adaboost. The DT-Gradient Boosting model, with a higher R2 value and lower error (i.e., MAE, RMSE) values, had a better performance than the other ensemble techniques. The application of machine learning techniques for the prediction of concrete properties would consume fewer resources and take less time and effort for scholars in the respective engineering field. The forecasting of the proposed DT-Gradient Boosting models is in close agreement with the actual experimental results, as indicated by the assessment output showing the improved estimation of RCAC’s compressive strength.
Binary Promoter Improving the Moderate-Temperature Adhesion of Addition-Cured Liquid Silicone Rubber for Thermally Conductive Potting
Authors: Wu Jia-Kai , Zheng Kai-Wen , Wang Qiong-Yan , Nie Xin-Cheng , Wang Rui , Xu Jun-Ting
Published: July 2022

The strong adhesion of thermally conductive silicone encapsulants on highly integrated electronic devices can avoid external damages and lead to an improved long-term reliability, which is critical for their commercial application. However, due to their low surface energy and chemical reactivity, the self-adhesive ability of silicone encapsulants to substrates need to be explored further. Here, we developed epoxy and alkoxy groups-bifunctionalized tetramethylcyclotetrasiloxane (D4H-MSEP) and boron-modified polydimethylsiloxane (PDMS-B), which were synthesized and utilized as synergistic adhesion promoters to provide two-component addition-cured liquid silicone rubber (LSR) with a good self-adhesion ability for applications in electronic packaging at moderate temperatures. The chemical structures of D4H-MSEP and PDMS-B were characterized by Fourier transform infrared spectroscopy. The mass percentage of PDMS-B to D4H-MSEP, the adhesion promoters content and the curing temperature on the adhesion strength of LSR towards substrates were systematically investigated. In detail, the LSR with 2.0 wt% D4H-MSEP and 0.6 wt% PDMS-B exhibited a lap-shear strength of 1.12 MPa towards Al plates when curing at 80 °C, and the cohesive failure was also observed. The LSR presented a thermal conductivity of 1.59 W m−1 K−1 and good fluidity, which provided a sufficient heat dissipation ability and fluidity for potting applications with 85.7 wt% loading of spherical α-Al2O3. Importantly, 85 °C and 85% relative humidity durability testing demonstrated LSR with a good encapsulation capacity in long-term processes. This strategy endows LSR with a good self-adhesive ability at moderate temperatures, making it a promising material requiring long-term reliability in the encapsulation of temperature-sensitive electronic devices.
Unsupervised Tool Wear Monitoring in the Corner Milling of a Titanium Alloy Based on a Cutting Condition-Independent Method
Authors: Li Zhimeng , Zhong Wen , Shi Yonggang , Yu Ming , Zhao Jian , Wang Guofeng
Published: July 2022

Real-time tool condition monitoring (TCM) for corner milling often poses significant challenges. On one hand, corner milling requires configuring complex milling paths, leading to the failure of conventional feature extraction methods to characterize tool conditions. On the other hand, it is costly to obtain sufficient test data on corner milling for most of the current pattern recognition methods, which are based on the supervised method. In this work, we propose a time-frequency intrinsic feature extraction strategy of acoustic emission signal (AEs) to construct a cutting condition-independent method for tool wear monitoring. The proposed new feature-extraction strategy is used to obtain the tool wear conditions through the intrinsic information of the time-frequency image of AEs. In addition, an unsupervised tool condition recognition framework, including the unsupervised feature selection, the clustering based on adjacent grids searching (CAGS) and the density factor based on CAGS, is proposed to determine the relationship between tool wear values and AE features. To test the effectiveness of the monitoring system, the experiment is conducted through the corner milling of a titanium alloy workpiece. Five metrics, PUR, CSM, NMI, CluCE and ClaCE, are used to evaluate the effectiveness of the recognition results. Compared with the state-of-the-art supervised methods, our method provides commensurate monitoring effectiveness but requires much fewer test data to build the model, which greatly reduces the operating cost of the TCM system.
Neural Network Based Adaptive Event-Triggered Control for Quadrotor Unmanned Aircraft Robotics
Authors: Lu Pukun , Liu Meng , Zhang Xiuyu , Zhu Guoqiang , Li Zhi , Su Chun-Yi
Published: July 2022

With the aim of addressing the problem of the trajectory tracking control of quadrotor unmanned aircraft robots (UARs), in this study, we developed a neural network and event-triggering mechanism-based adaptive control scheme for a quadrotor UAR control system. The main technologies included this scheme are as follows. (1) Under the condition that only the quadrotor’s position information can be obtained, a modified high-gain state observer-based adaptive dynamic surface control (DSC) method was applied and the tracking control of quadrotor UARs was acquired. (2) An event-triggered mechanism for UARs was designed, in which the energy consumption was greatly reduced and the communication efficiency between the system and the control terminal was improved. (3) By selecting appropriate parameters, appropriate initial conditions for the adaptive laws, and establishing a high-gain state observer, a tracking performance of L∞ could be achieved. Finally, simulation results of the hardware-in-loop strategy are presented. The control method we propose here outperformed the traditional backstepping sliding mode control (BSMC) scheme.
Tackling Verification and Validation Techniques to Evaluate Cyber Situational Awareness Capabilities
Authors: Llopis Sanchez Salvador , Sandoval Rodriguez-Bermejo David , Daton Medenou Roumen , Pasqual de Riquelme Ramis , Torelli Francesco , Maestre Vidal Jorge
Published: July 2022

Since cyberspace was identified as a domain of operations, defence practitioners started a race with academy, researchers, and industry and military organizations working together towards defining related lines of capability development (e.g., DOTMLPFI) and exploring the needs and opportunities they entail. An essential cornerstone of adapting to the convergence of the cyber domain with conventional theaters of operation is the need for producing tools for easing to acquire cyber situational awareness (CSA), from which human operators shall be able to perceive, reason and project situations and events observed in cyberspace that may vertically/horizontally propagate from technological to tactical, operational and strategic planes. Benefiting from the higher maturity level of civilian capabilities for cybersecurity, the military sector has embraced the challenge of creating related beyond state-of-the-art CSA enablers that comprise the existing technological background while adopting concepts such as operations, missions or courses of action (CoAs), properly aligning them with military doctrine. Beyond ongoing development efforts, there is a wide methodological gap in the lack of suitable CSA verification and validation (V&V) frameworks, which are expected to analyze if related capabilities meet the requirements to operate in the military context; at the same time supporting the thorough development life-cycle of brand new cyber defence technologies. With the motivation of closing the identified gap, this research introduces a novel V&V framework able to guide the evaluation of CSA-related tools, which makes converge purely military aspects with dual-use state-of-the-art V&V approaches. Three core CSA evaluation concepts are discussed in-depth: software, operational and application tests. They range from the daily application of new capabilities to their ability to enable the acquisition of a joint operational picture understandable by human decision makers.
The Sharp Upper Estimate Conjecture for the Dimension δk(V) of New Derivation Lie Algebra
Authors: Hussain Naveed , Al-Kenani Ahmad N. , Arshad Muhammad , Asif Muhammad
Published: July 2022

Hussain, Yau, and Zuo introduced the Lie algebra Lk(V) from the derivation of the local algebra Mk(V):=On/(g+J1(g)+⋯+Jk(g)). To find the dimension of a newly defined algebra is an important task in order to study its properties. In this regard, we compute the dimension of Lie algebra L5(V) and justify the sharp upper estimate conjecture for fewnomial isolated singularities. We also verify the inequality conjecture: δ5(V)<δ4(V) for a general class of singularities. Our findings are novel and an addition to the study of Lie algebra.
Hydrodynamic Impacts of Short Laser Pulses on Plasmas
Authors: Fiore Gaetano , De Angelis Monica , Fedele Renato , Guerriero Gabriele , Jovanović Dušan
Published: July 2022

We determine conditions allowing for simplification of the description of the impact of a short and arbitrarily intense laser pulse onto a cold plasma at rest. If both the initial plasma density and pulse profile have plane symmetry, then suitable matched upper bounds on the maximum and the relative variations of the initial density, as well as on the intensity and duration of the pulse, ensure a strictly hydrodynamic evolution of the electron fluid without wave-breaking or vacuum-heating during its whole interaction with the pulse, while ions can be regarded as immobile. We use a recently developed fully relativistic plane model whereby the system of the Lorentz–Maxwell and continuity PDEs is reduced into a family of highly nonlinear but decoupled systems of non-autonomous Hamilton equations with one degree of freedom, the light-like coordinate ξ=ct−z instead of time t as an independent variable, and new a priori estimates (eased by use of a Liapunov function) of the solutions in terms of the input data (i.e., the initial density and pulse profile). If the laser spot radius R is finite and is not too small, the same conclusions hold for the part of the plasma close to the axis z→ of cylindrical symmetry. These results may help in drastically simplifying the study of extreme acceleration mechanisms of electrons.
Heterogeneous Network Embedding Based on Random Walks of Type and Inner Constraint
Authors: Chen Xiao , Hao Tong , Han Li , Leng Meng , Chen Jing , Guo Jingfeng
Published: July 2022

In heterogeneous networks, random walks based on meta-paths require prior knowledge and lack flexibility. On the other hand, random walks based on non-meta-paths only consider the number of node types, but not the influence of schema and topology between node types in real networks. To solve these problems, this paper proposes a novel model HNE-RWTIC (Heterogeneous Network Embedding Based on Random Walks of Type and Inner Constraint). Firstly, to realize flexible walks, we design a Type strategy, which is a node type selection strategy based on the co-occurrence probability of node types. Secondly, to achieve the uniformity of node sampling, we design an Inner strategy, which is a node selection strategy based on the adjacency relationship between nodes. The Type and Inner strategy can realize the random walks based on meta-paths, the flexibility of the walks, and can sample the node types and nodes uniformly in proportion. Thirdly, based on the above strategy, a transition probability model is constructed; then, we obtain the nodes’ embedding based on the random walks and Skip-Gram. Finally, in the classification and clustering tasks, we conducted a thorough empirical evaluation of our method on three real heterogeneous networks. Experimental results show that HNE-RWTIC outperforms state-of-the-art approaches. In the classification task, in DBLP, AMiner-Top, and Yelp, the values of Micro-F1 and Macro-F1 of HNE-RWTIC are the highest: 2.25% and 2.43%, 0.85% and 0.99%, 3.77% and 5.02% higher than those of five other algorithms, respectively. In the clustering task, in DBLP, AMiner-Top, and Yelp networks, the NMI value is increased by 19.12%, 6.91%, and 0.04% at most, respectively.
Almost Complex and Hypercomplex Norden Structures Induced by Natural Riemann Extensions
Authors: Bejan Cornelia-Livia , Nakova Galia
Published: July 2022

The Riemann extension, introduced by E. K. Patterson and A. G. Walker, is a semi-Riemannian metric with a neutral signature on the cotangent bundle T∗M of a smooth manifold M, induced by a symmetric linear connection ∇ on M. In this paper we deal with a natural Riemann extension g¯, which is a generalization (due to M. Sekizawa and O. Kowalski) of the Riemann extension. We construct an almost complex structure J¯ on the cotangent bundle T∗M of an almost complex manifold (M,J,∇) with a symmetric linear connection ∇ such that (T∗M,J¯,g¯) is an almost complex manifold, where the natural Riemann extension g¯ is a Norden metric. We obtain necessary and sufficient conditions for (T∗M,J¯,g¯) to belong to the main classes of the Ganchev–Borisov classification of the almost complex manifolds with Norden metric. We also examine the cases when the base manifold is an almost complex manifold with Norden metric or it is a complex manifold (M,J,∇′) endowed with an almost complex connection ∇′ (∇′J=0). We investigate the harmonicity with respect to g¯ of the almost complex structure J¯, according to the type of the base manifold. Moreover, we define an almost hypercomplex structure (J¯1,J¯2,J¯3) on the cotangent bundle T∗M4n of an almost hypercomplex manifold (M4n,J1,J2,J3,∇) with a symmetric linear connection ∇. The natural Riemann extension g¯ is a Hermitian metric with respect to J¯1 and a Norden metric with respect to J¯2 and J¯3.
Research on Location Selection Model of 5G Micro Base Station Based on Smart Street Lighting System
Authors: Liu Hanwei , Li Wenchao , Cai Huiling , Lin Qingcheng , Li Xuefeng , Xiao Hui
Published: July 2022

In order to promote the development and construction of smart cities, the massive equipment requirements of sensing terminals increased the pressure on urban site resource allocation. The light pole is suitable for carrying various urban functional equipment to form a smart street lighting system, which can provide rich site resources for the large-scale construction of urban functional facilities such as 5G micro base stations. However, the selection and combination of equipment mounted in the smart street lighting system only focus on the functional superposition at the physical level, without considering the relevance of each subsystem in practical application scenarios. Therefore, this study proposed a 5G micro base station location model based on a smart street lighting system. The correlation and cooperativity between 5G micro base stations and mounted devices were fully considered, and a universal system-level location selection index was developed to realize rational utilization of urban space site resources and intelligent linkage between subsystems. The results showed that the model is significantly effective for functional areas with different road network characteristics and provides practical, robust, effective, and accurate help for similar location selection problems.
Partial Learning Using Partially Explicit Discretization for Multicontinuum/Multiscale Problems with Limited Observation: Dual Continuum Heterogeneous Poroelastic Media Simulation
Authors: Tyrylgin Aleksei , Stepanov Sergei , Ammosov Dmitry , Grigorev Aleksandr , Vasilyeva Maria
Published: July 2022

In this paper, we consider the poroelasticity problem in heterogeneous media. The mathematical model is described by a coupled system of equations for displacement and pressure in the coupled dual continuum porous media. We propose a new method based on hybrid explicit–implicit (HEI) learning to solve the poroelasticity problem in dual continuum heterogeneous media. We use a finite element method with standard linear basis functions for spatial approximation. We apply the explicit–implicit time scheme, where the explicit scheme is used for the low-conductive continuum and the implicit scheme for the high-conductive. The fixed-strain splitting scheme is used to accelerate the computation and decouple the flow and mechanics problems. The main idea of the proposed method is partial learning of particular degrees of freedom of the high-conductive continuum’s pressure (implicit part of the flow). First, we train a deep neural network (DNN) to obtain values of the implicit part of the flow at some spatial points at some time moments. Then, we apply the Discrete Empirical Interpolation Method (DEIM) combined with Proper Orthogonal Decomposition (POD) to restore the complete implicit parts and perform linear interpolation over time. Consequently, we treat the high-conductive continuum’s pressure as a known function and use it to find the other continuum’s pressure and displacements. Numerical results for the two-dimensional model problem are presented. The results demonstrate that the proposed method provides fast and accurate predictions.
Iteration of Operators with Contractive Mutual Relations of Kannan Type
Authors: Mohapatra Ram N. , Navascués María A. , Sebastián María V. , Verma Saurabh
Published: July 2022

Inspired by the ideas of R. Kannan, we define the new concepts of mutual Kannan contractivity and mutual contractivity between two self-maps on a metric space that generalize the concepts of the Kannan map and contraction. We give some examples and deduce the properties of the operators satisfying this type of condition; in particular, we study the case where the space is normed, and the maps are linear. Then we generalize some theorems proposed by this author on the existence of a fixed point of one operator or a common fixed point for two operators. Our results first prove the existence of a common fixed point of a set of self-maps of any cardinal number (countable or uncountable) satisfying the conditions of Kannan type in metric spaces. The same is proved for a set of maps satisfying the mutual relations of classical contractivity. We prove in both cases the convergence of iterative schemes involving operators with mutual relations of contractivity, proposing sufficient conditions for the iteration of the operators on any element of the space to converge to the common fixed point when a different operator is taken in each step. The results obtained are applied to operators acting on real functions, coming from the fractal convolution with the null function.
On Some Properties of Signed Cayley Graph Sn
Authors: Sinha Deepa , Wardak Obaidullah , Dhama Ayushi
Published: July 2022

We define the signed Cayley graph on Cayley graph Xn denoted by Sn, and study several properties such as balancing, clusterability and sign-compatibility of the signed Cayley graph Sn. Apart from it we also study the characterization of the canonical consistency of Sn, for some n.
Probabilistic Interpretation of Number Operator Acting on Bernoulli Functionals
Authors: Zhang Jing , Zhang Lixia , Wang Caishi
Published: July 2022

Let N be the number operator in the space H of real-valued square-integrable Bernoulli functionals. In this paper, we further pursue properties of N from a probabilistic perspective. We first construct a nuclear space G, which is also a dense linear subspace of H, and then by taking its dual G*, we obtain a real Gel’fand triple G⊂H⊂G*. Using the well-known Minlos theorem, we prove that there exists a unique Gauss measure γN on G* such that its covariance operator coincides with N. We examine the properties of γN, and, among others, we show that γN can be represented as a convolution of a sequence of Borel probability measures on G*. Some other results are also obtained.
A Contribution to the Theory of Soft Sets via Generalized Relaxed Operations
Authors: Ali Basit , Saleem Naeem , Sundus Nozara , Khaleeq Sana , Saeed Muhammad , George Reny
Published: July 2022

Soft set theory has evolved to provide a set of valuable tools for dealing with ambiguity and uncertainty in a variety of data structures related to real-world challenges. A soft set is characterized via a multivalued function of a set of parameters with certain conditions. In this study, we relax some conditions on the set of parameters and generalize some basic concepts in soft set theory. Specifically, we introduce generalized finite relaxed soft equality and generalized finite relaxed soft unions and intersections. The new operations offer a great improvement in the theory of soft sets in the sense of proper generalization and applicability.
Designing a Custom CPU Architecture Based on Hardware RTOS and Dynamic Preemptive Scheduler
Authors: Zagan Ionel , Găitan Vasile Gheorghiță
Published: July 2022

The current trend in real-time operating systems involves executing many tasks using a limited hardware platform. Thus, a single processor system has to execute multiple tasks with different priorities in different real-time system (RTS) work modes. Hardware schedulers can greatly reduce event trigger latency and successfully remove most of the scheduling overhead, providing more computing cycles for applications. In this paper, we present a hardware-accelerated RTOS based on the replication of resources such as program counters, general purpose registers (GPRs) and pipeline registers. The implementation of this new concept, based on real-time event handling implemented in hardware, is intended to meet the current rigorous requirements imposed by critical real-time systems. The most important attribute of this FPGA implementation is the time required for task context switching, which is only one clock cycle or three clock cycles when working with the atomic instructions used in the case of inter-task synchronization and communication mechanisms. The main contribution of this article is its focus on mutexes and the speed of response associated with related events. Thus, fast switching between threads is also validated, considering the handling of events in the hardware using HW_nMPRA_RTOS (HW-RTOS). The proposed architecture implements inter-task synchronization and communication mechanisms with high performance, improving the overall response time when the mutex or message is expected to relate to a higher-priority task.
Enhanced Unconditionally Positive Finite Difference Method for Advection–Diffusion–Reaction Equations
Authors: Ndou Ndivhuwo , Dlamini Phumlani , Jacobs Byron Alexander
Published: July 2022

In this study, we develop the enhanced unconditionally positive finite difference method (EUPFD), and use it to solve linear and nonlinear advection–diffusion–reaction (ADR) equations. This method incorporates the proper orthogonal decomposition technique to the unconditionally positive finite difference method (UPFD) to reduce the degree of freedom of the ADR equations. We investigate the efficiency and effectiveness of the proposed method by checking the error, convergence rate, and computational time that the method takes to converge to the exact solution. Solutions obtained by the EUPFD were compared with the exact solutions for validation purposes. The agreement between the solutions means the proposed method effectively solved the ADR equations. The numerical results show that the proposed method greatly improves computational efficiency without a significant loss in accuracy for solving linear and nonlinear ADR equations.
Enhancing Model-Based Anticipatory Traffic Signal Control with Metamodeling and Adaptive Optimization
Authors: Huang Wei , Hu Yang , Zhang Xuanyu
Published: July 2022

Traffic signal control is one effective way to alleviate traffic congestion. Anticipatory traffic signal control determines signal settings from a network planning perspective, which takes into account the influence of travelers’ route choice response and triggers better equilibrium flow patterns for better network performance. For the route choice response, it is usually predicted by a response function known as traffic assignment model. However, the response behavior can never be precisely modeled, leading to a mismatch between the modeled and real traffic flow patterns. This model-reality mismatch generally contributes to suboptimal control performance and hence brings unexpected congestion in real-life traffic operations. This study aims to address the model-reality mismatch and proposes an effective anticipatory traffic control for real operations. A metamodel is introduced that serves as a surrogate of the unknown structural model bias. Then an iterative optimizing control scheme is applied to correct the model bias by learning from observations. By integrating the model-based control design with data-driven learning techniques, the metamodeling framework is able to enhance the control performance. Moreover, the analytical model bias formulation allows theoretical investigation of the model approximation error. To further improve the control performance, a joint traffic model parameter estimation is developed, hence achieving a better model calibration jointly with the model bias correction. The proposed control method is examined on a test network. Numerical examples confirm the effectiveness of the proposed method in improving control performance despite the model-reality mismatch. Comparison results show that the proposed method outperforms the traditional model-based control method and an improvement of 14.8% in total travel time is achieved in the example network.
Novel Drug and Gene Delivery System and Imaging Agent Based on Marine Diatom Biosilica Nanoparticles
Authors: Hussein Hanaa Ali , Nazir Muhammad Shahid , Azra Nizakat , Qamar Zeenat , Seeni Azman , Tengku Din Tengku Ahmad Damitri Al-Astani , Abdullah Mohd Azmuddin
Published: July 2022

Mesoporous silica nanoparticles (MSNs) have great potential for applications as a drug delivery system (DDS) due to their unique properties such as large pore size, high surface area, biocompatibility, biodegradability, and stable aqueous dispersion. The MSN-mediated DDS can carry chemotherapeutic agents, optical sensors, photothermal agents, short interfering RNA (siRNA), and gene therapeutic agents. The MSN-assisted imaging techniques are applicable in cancer diagnosis. However, their synthesis via a chemical route requires toxic chemicals and is challenging, time-consuming, and energy-intensive, making the process expensive and non-viable. Fortunately, nature has provided a viable alternative material in the form of biosilica from marine resources. In this review, the applications of biosilica nanoparticles synthesized from marine diatoms in the field of drug delivery, biosensing, imaging agents, and regenerative medicine, are highlighted. Insights into the use of biosilica in the field of DDSs are elaborated, with a focus on different strategies to improve the physico-chemical properties with regards to drug loading and release efficiency, targeted delivery, and site-specific binding capacity by surface functionalization. The limitations, as well as the future scope to develop them as potential drug delivery vehicles and imaging agents, in the overall therapeutic management, are discussed.
Heteronemin and Tetrac Induce Anti-Proliferation by Blocking EGFR-Mediated Signaling in Colorectal Cancer Cells
Authors: Unson Sukanya , Chang Tung-Cheng , Yang Yung-Ning , Wang Shwu-Huey , Huang Chi-Hung , Crawford Dana R. , Huang Haw-Ming , Li Zi-Lin , Lin Hung-Yun , Whang-Peng Jacqueline , Wang Kuan , Davis Paul J. , Li Wen-Shan
Published: July 2022

Overexpressed EGFR and mutant K-Ras play vital roles in therapeutic resistance in colorectal cancer patients. To search for an effective therapeutic protocol is an urgent task. A secondary metabolite in the sponge Hippospongia sp., Heteronemin, has been shown to induce anti-proliferation in several types of cancers. A thyroxine-deaminated analogue, tetrac, binds to integrin αvβ3 to induce anti-proliferation in different cancers. Heteronemin- and in combination with tetrac-induced antiproliferative effects were evaluated. Tetrac enhanced heteronemin-induced anti-proliferation in HT-29 cells (KRAS WT CRC) and HCT-116 cells (KRAS MT CRC). Heteronemin and tetrac arrested cell cycle in different phases. Combined treatment increased the cell accumulation in sub-G1 and S phases. The combined treatment also induced the inactivation of EGFR signaling and downregulated the phosphorylated ERK1/2 protein in both cell lines. Heteronemin and the combination showed the downregulation of the phosphorylated and total PI3K protein in HT-29 cells (KRAS WT CRC). Results by NanoString technology and RT-qPCR revealed that heteronemin and combined treatment suppressed the expression of EGFR and downstream genes in HCT-116 cells (KRAS MT CRC). Heteronemin or combined treatment downregulated genes associated with cancer progression and decreased cell motility. Heteronemin or the combined treatment suppressed PD-L1 expression in both cancer cell lines. However, only tetrac and the combined treatment inhibited PD-L1 protein accumulation in HT-29 cells (KRAS WT CRC) and HCT-116 cells (KRAS MT CRC), respectively. In summary, heteronemin induced anti-proliferation in colorectal cancer cells by blocking the EGFR-dependent signal transduction pathway. The combined treatment further enhanced the anti-proliferative effect via PD-L1 suppression. It can be an alternative strategy to suppress mutant KRAS resistance for anti-EGFR therapy.
Is Femoral Neck System a Valid Alternative for the Treatment of Displaced Femoral Neck Fractures in Adolescents? A Comparative Study of Femoral Neck System versus Cannulated Compression Screw
Authors: Lu Yunan , Canavese Federico , Nan Guoxin , Lin Ran , Huang Yuling , Pan Nuoqi , Chen Shunyou
Published: July 2022

Background and Objectives: The femoral neck system (FNS) is a new minimally invasive internal fixation system for femoral neck fractures (FNFs), but its use has not been reported in adolescents. The aim of this study was to compare the clinical and radiographic outcomes of displaced FNF in adolescents treated with FNS or a cannulated compression screw (CCS). Materials and Methods: A retrospective study of 58 consecutive patients with displaced FNF treated surgically was performed; overall, 28 patients underwent FNS and 30 CCS fixation. Sex, age at injury, type of fracture, associated lesions, duration of surgery, radiation exposure, and blood loss were collected from the hospital database. The clinical and radiographic results, as well as complications, were recorded and compared. Results: The patients were followed up for 16.4 ± 3.1 months on average after index surgery (range, 12 to 24). Consolidation time among patients treated with FNS was significantly lower than those managed by CCS (p = 0.000). The functional scores of patients treated with FNS were significantly higher than those managed by CCS (p = 0.030). Unplanned hardware removal in patients treated with FNS was significantly lower than in those managed by CCS (p = 0.024). Conclusions: FNS has a lower complication rate and better functional outcome than CCS. It may be a good alternative to treat femoral neck fractures in adolescents.
Assessment of Different Techniques for Adhesive Cementation of All-Ceramic Systems
Authors: Cuzic Cristiana , Pricop Marius Octavian , Jivanescu Anca , Ursoniu Sorin , Negru Radu Marcel , Romînu Mihai
Published: July 2022

Background and Objectives: Modern esthetic dentistry is based on all-ceramic restorations. Dentists still have reservations about using these restorations due to a lack of understanding of the cementation technique, which depends on the type of ceramic used. The aim of the study is to evaluate the approaches and practices of clinicians regarding the adhesive cementation of all-ceramic restorations. Materials and Methods: An online questionnaire regarding the use of all-ceramic restorations and their bonding methods was designed by distinguishing the cementation of oxide and silica-based ceramics. The survey included dentists practicing in Timiș County, Romania. The questionnaire and the evaluation of the answers were designed based on the techniques and evidence from the literature. Results: Considering the work experience, we obtained two groups: group 1—1 to 6 years and group 2—6 to 9+ years. The results revealed significant values when comparing the two groups in the surface protocol and decontamination (p = 0.005), type of cement used (p = 0.002), and isolation techniques (p = 0.002). Conclusions: The results show that many clinicians need additional training to improve their cementing technique and avoid the confusion caused by insufficient information about the interrelationship between the type of ceramic and the cementation procedure.
Evaluation of Remdesivir for Mildly to Moderately Ill Patients with COVID-19: A Single-Arm, Single-Center, Retrospective Study
Authors: Miyazaki Motoyasu , Yanagida Ryoko , Nakashima Akio , Matsuo Koichi , Moriwaki Norihiro , Uchiyama Masanobu , Yamada Yota , Hirata Hitomi , Kushima Hisako , Kinoshita Yoshiaki , Ishii Hiroshi , Imakyure Osamu
Published: July 2022

Background and Objectives: Remdesivir (RDV) is the first antiviral agent approved in Japan for the treatment of coronavirus disease 2019 (COVID-19). The aim of our study was to assess the efficacy and safety of RDV treatment in mildly to moderately ill patients with COVID-19. Materials and Methods: A single-center, retrospective study was performed in Fukuoka University Chikushi Hospital. Patients admitted to our hospital from June to October 2021 for RDV treatment against COVID-19 were enrolled. The primary end point was clinical status on days 10 and 14, using a 6-point ordinal scale ranging from death (category 6) to discharge (category 1). Adverse events were assessed and graded using the Japanese version of Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Results: In total, 47 COVID-19 patients receiving RDV treatment were assessed during the study period. Thirty-four (72.3%) out of 47 patients required oxygen therapy. Out of these 34 patients, 30 (88.2%) showed a 2-point clinical improvement on day 14 after RDV was initiated. Serum alanine aminotransferase levels were elevated in three patients (6.4%) (CTCAE Grade 3) and neutropenia was detected in one patient (2.1%) out of the 47 patients. Conclusions: RDV may be highly effective, with good safety profiles, in patients with COVID-19 requiring oxygen therapy.
Enzymatic Chicken Pulp Promotes Appetite, Digestive Enzyme Activity, and Growth in Litopenaeus vannamei
Authors: Hlordzi Vivian , Tan Beiping , Dong Xiaohui , Zhang Shuang , Zhu Lin , Zhang Ling , Hu Xiangna , Chi Shuyan
Published: July 2022

Enzymatic chicken pulp (ECP) is an animal protein source that has been proven to be of excellent nutritional content and good quality for the majority of aquatic organisms because of its quality protein, small peptides, palatability, vitamins, and minerals. An 8-week nutritional trial was conducted to assess the effects of an ECP-based diet on the growth performance, digestive enzyme activity, and gene mRNA expression of Pacific white shrimp (Litopenaeus vannamei). Fish soluble pulp (FSP) served as the control group while in the experimental groups, and ECPs with three protein contents were used to replace FSP in equal amounts, named ECP1, ECP2, and ECP3, respectively. No significant difference in weight gain rate, specific growth rate, survival rate, or feed conversion ratio was observed (p > 0.05) between the groups. Ash content in the Pacific shrimp’s whole body was significantly higher in the ECP1 and ECP3 groups compared to the other groups (p < 0.05). Intestinal amylase and protease activities were the highest in the ECP1 and ECP2 groups, respectively (p < 0.05). With respect to gene mRNA expression, neuropeptide Y, excitatory amino acid transporter, and fatty acid transport protein 4 were significantly high in the ECP1 group (p < 0.05). In conclusion, these three ECPs have their advantages to replace FSP in shrimp feed, but ECP1 is more effective if the effects of digestive enzyme activity, appetite, and expression of growth-related genes are considered.