bluuebunny/crossref_metadata_2025 huggingface dataset:
Personalism and purges: Are personalist dictators more likely to engage in elite purges?
Authors: Ishiyama John , Breuning Marijke , Kim Taekbin
Published: June 2024

Objective

In this article, we empirically examine the relationship between personalism and employing purging or cooptation as regime elite management techniques. Much of the literature suggests that there is a close relationship between personalism and the use of violence to maintain power, and thus suggests a connection between personalism and violent purges.

Methods

Using data from 109 autocracies from 1946 to 2008, we employ a seemingly unrelated negative binomial regression estimation

Results

We find that personalist regimes are not more likely to engage in purges when compared to other regimes. Further, the results suggest that personalist regimes are not more likely to rely on purges as an elite management strategy. In fact, our analysis suggests that personalism as a regime attribute (rather than as an institutional type) is associated with less (not more) use of purges and that personalism tends to be more associated with the use of cooptation than purges.

Conclusion

We offer an explanation for these findings and suggest that future research should focus on the characteristics of the autocrat as a political agent when explaining the propensity to engage in different elite management techniques.
Detection of the HLA‐A*11:127N allele in a Taiwanese individual
Authors: Yang Kuo‐Liang , Lin Py‐Yu
Published: June 2024

A nucleotide mutation in codon 171 of HLA‐A*11:01:01:01 results in a novel allele HLA‐A*11:127N.
Characterisation of novel MICB alleles by next generation sequencing: MICB*055 and MICB*005:15
Authors: Shivarov Velizar , Ivanova Milena
Published: June 2024

Two novel MICB alleles with coding polymorphisms in exon 3 were detected by next generation sequencing.
Characterisation of the novel MICA*112:02 allele by next generation sequencing
Authors: Ivanova Milena , Shivarov Velizar
Published: June 2024

The novel MICA*112:02 allele was detected by next generation sequencing.
Parallel Interactions Between Linguistic and Contextual Factors in Bilinguals
Authors: Mishra Ramesh K. , Prasad Seema
Published: June 2024

The necessity for introducing interactionist and parallelism approaches in different branches of cognitive science emerged as a reaction to classical sequential stage‐based models. Functional psychological models that emphasized and explained how different components interact, dynamically producing cognitive and perceptual states, influenced multiple disciplines. Chiefly among them were experimental psycholinguistics and the many applied areas that dealt with humans’ ability to process different types of information in different contexts. Understanding how bilinguals represent and process verbal and visual input, how their neural and psychological states facilitate such interactions, and how linguistic and nonlinguistic processing overlap, has now emerged as an important area of multidisciplinary research. In this article, we will review available evidence from different language‐speaking groups of bilinguals in India with a focus on situational context. In the discussion, we will address models of language processing in bilinguals within a cognitive psychological approach with a focus on existent models of inhibitory control. The paper's stated goal will be to show that the parallel architecture framework can serve as a theoretical foundation for examining bilingual language processing and its interface with external factors such as social context.
On K‐stability of P3$\mathbb {P}^3$ blown up along a (2,3) complete intersection
Authors: Guerreiro Tiago Duarte , Giovenzana Luca , Viswanathan Nivedita
Published: June 2024

We prove K‐stability of every smooth member of the Fano 3‐fold family 2.15 of the Mori, Mukai and Iskovskikh classification.
DeltaFlex—An Additively Manufactured Delta Robot With Compliant Joints: Virtual Prototyping and Experimental Evaluation
Authors: Parmiggiani Alberto , Ottonello Emilio , Kargar Seyyed Masoud , Baggetta Mario , Hao Guangbo , Berselli Giovanni
Published: June 2024

The current study presents the development and validation of a compliant Delta robot with a monolithic structure, which has been fabricated using additive manufacturing (AM). The monolithic design and the use of AM accelerate the robot development cycle by enabling rapid prototyping and deployment while also facilitating experimentation with novel or different robot kinematics. The use of flexible joints for robots presents a challenge in achieving sufficient workspaces. However, parallel architectures are well suited for incorporating compliant joints, as they require lower ranges of motion for individual joints compared to serial architectures. Therefore, the Delta configuration has been chosen for this study. Multibody flexible dynamics (MfBD) simulations have been used as a means to guide design choices and simulate the structural behaviour of the robot. A design for additive manufacturing (DfAM) technique has been adopted to minimize the need for support structures and maximize mechanical strength. The quantitative evaluation of the Delta’s overall performance has been conducted in terms of stiffness and precision. The stiffness test aimed to gauge the robot’s ability to withstand applied loads, whereas the repeatability test assessed its precision and accuracy. This approach offers a promising path for robot design with significant potential for future advancements and practical applications while highlighting the trade-offs that designers should consider when adopting this methodology.
Risk-Based Design Optimization via Scenario Generation and Genetic Programming Under Hybrid Uncertainties
Authors: Li Wei , Zhou Xiaowei , Huang Haihong , Garg Akhil , Gao Liang
Published: June 2024

The design of complex systems often requires the incorporation of uncertainty optimization strategies to mitigate system failures resulting from multiple uncertainties during actual operation. Risk-based design optimization, as an alternative methodology that accounts for the balance between design cost and performance, has garnered significant attention and recognition. This paper presents a risk design optimization method for tackling hybrid uncertainties via scenario generation and genetic programming. The hybrid uncertainties are quantified through the scenario generation method to obtain risk assessment indicators. The genetic programming method is used to simulate the real output of the objective or constraints. To drive the optimization process, the sample-based discrete gradient expression is constructed, and the optimal scheme aligning the risk requirements is obtained. Three calculation examples of varying computing complexity are presented to verify the efficacy and usability of the suggested approach.
Axisymmetric Vibration of Inviscid Compressible Fluid-Filled Soft Dielectric Elastomer Actuator Tube
Authors: Almamo Ahmad , Su Yipin , Chen Weiqiu , Wang Huiming
Published: June 2024

Driven by the versatility and adaptability of next-generation soft robotic devices, investigating the vibrational behavior under fluid-electromechanical coupling represented by a soft dielectric elastomer actuator (DEA) tube filled with fluid evokes much attention. Here, we investigate the axisymmetric vibration of an inviscid compressible fluid-filled thin DEA tube by using the Gent model to define the behavior of the tube under multi-fields. We consider the effect of the fluid by exploiting the relation of the radial fluid pressure at the fluid–solid interface. Following the general incremental theory of nonlinear electro-elasticity, we formulate the incremental governing and constitutive equations needed for vibration analysis and solve them numerically using the state-space method (SSM). The results demonstrate the influence of the applied voltage, overcritical circumferential stretch, higher frequency modes, and phase velocity modes on the early development of axisymmetric instability and dielectric breakdown. The existence of the fluid contributes to more reduction in the frequency and phase velocity compared to the fluid-free case due to the added mass effect. Moreover, the results show the role of fluid in the partial self-healing of the soft DEA. A parametric study on specific variables deduces that increasing the thickness of the soft DEA tube reduces the frequency effectively, whereas applying higher voltages causes a thinning in the thickness, leading to the need for thicker tubes.
Understanding Electric Current Effects on Tribological Behaviors of Instantaneous Current-Carrying Pair With Recurrence Plot
Authors: Zhao Huan , Wang Wei , Xu Xiaojun , Zhong Hua , Wei Daogao , Liu Xiaojun
Published: June 2024

Armature–rail instantaneous current-carrying friction in electromagnetic launchers refers to a sliding electric-mechanical impact friction and transition-induced arc erosion on a millisecond time scale. To reveal the electric current (50–300 A) effects on friction behavior and wear mechanism, the instantaneous current-carrying friction tests were performed with Al 1060 and Brass H62. Given the short nonlinear friction-induced signals, the friction behavior, including the time-domain information and system state, was comprehensively analyzed via frictional sound pressure (FSP), recurrence plot (RP), and recurrence quantification analysis (RQA). The wear topography was observed and characterized by the multifractal spectrum. Recurrence analyses demonstrate that as the current increases, the nonstationarity of the system state weakens, and the complexity and unpredictability enhance. Higher currents reduce the FSP amplitude, i.e., enhance the interfacial lubrication effect, but intensify electrical wear and surface roughness. This signifies a wear mechanism transition from abrasive wear and slight adhesive wear to arc ablation, fatigue wear, and severe adhesive wear. The widening spectrum width implies that the irregularity and fluctuation of the topography are enhanced with the current. RP patterns and RQA quantifiers correlate with the wear damage state. The results provide a reference for antiwear design and online degradation tracking of the rail.
Review on the Interaction Mechanism of Nitrogen/Sulfur Pollutants During Fuel Combustion
Authors: Shi Shaoxu , Wang Jinquan , Xu Xudong , Ma Honghe
Published: June 2024

The formation and control of pollutants emitted from fuel combustion have always been a focal point in combustion chemistry. Key pollutants primarily include nitrogen oxides (NOx) and sulfur oxides (SOx), making it crucial to elucidate the formation processes of nitrogen and sulfur components during combustion for pollutant control. Due to the highly coupled evolution processes of both components, independent reaction mechanisms struggle to describe this process; thus, considering the interactions between them is significant for the evolution of nitrogen and sulfur components. This article investigates the promotional or inhibitory effects between nitrogen and sulfur components in fuel combustion experiments, with the magnitude of this interactive effect varying between 2% and 250%, contingent upon the equivalence ratio and the N/S ratio impacts. Additionally, from a microkinetic perspective, two mechanisms underlying N/S interactions are identified: direct and indirect interactions. Direct interaction involves the formation of NS radicals, primarily through direct reactions of nitrogen species (NOx/HCN/NHi, where i ranges from 0 to 3) with sulfur constituents (SOx/H2S). Conversely, indirect interaction alters the radical pool via the intervention of NO or SO2, subsequently influencing each other's reaction pathways. It is noted that the current reaction system is incomplete, lacking key reactions, while the kinetic parameters of some reactions are still contentious. Advanced theoretical calculations are needed to refine the N/S interaction reaction model, to provide more accurate predictions for nitrogen and sulfur pollutant levels.
Unassigning bacterial species for microbiome studies
Authors: Tanes Ceylan , Tu Vincent , Daniel Scott , Bittinger Kyle
Published: June 2024

The method of 16S rRNA marker gene sequencing has fueled microbiome research and continues to be relevant. A perceived weakness of the method is that taxonomic assignments are not possible to make at the rank of species. We show that by working to
rule out
bacterial or archaeal species membership, we can provide an answer that is more accurate and useful. The Unassigner software operates on 16S rRNA marker gene data and computes a rule-out probability for species membership using a beta-binomial distribution. We demonstrate that our approach is accurate based on full-genome comparisons. Our method is consistent with existing approaches and dramatically improves on them based on the percentage of reads it can associate with a species in a sample. The software is available at
https://github.com/PennChopMicrobiomeProgram/unassigner
.

IMPORTANCE

While existing methods do not provide reliable species-level assignments for 16S rRNA marker gene data, the Unassigner software solves this problem by ruling out species membership, allowing researchers to reason at the species level.
Neurocognitive and psychiatric outcomes associated with postacute COVID-19 infection without severe medical complication: a meta-analysis
Authors: Knapp Sarah A B , Austin David S , Aita Stephen L , Caron Joshua E , Owen Tyler , Borgogna Nicholas C , Del Bene Victor A , Roth Robert M , Milberg William P , Hill Benjamin D
Published: June 2024

Background

Cognitive symptoms are often reported by those with a history of COVID-19 infection. No comprehensive meta-analysis of neurocognitive outcomes related to COVID-19 exists despite the influx of studies after the COVID-19 pandemic. This study meta-analysed observational research comparing cross-sectional neurocognitive outcomes in adults with COVID-19 (without severe medical/psychiatric comorbidity) to healthy controls (HCs) or norm-referenced data.

Methods

Data were extracted from 54 studies published between January 2020 and June 2023. Hedges’ g was used to index effect sizes, which were pooled using random-effects modelling. Moderating variables were investigated using meta-regression and subgroup analyses.

Results

Omnibus meta-analysis of 696 effect sizes extracted across 54 studies (COVID-19 n=6676, HC/norm-reference n=12 986; average time since infection=~6 months) yielded a small but significant effect indicating patients with COVID-19 performed slightly worse than HCs on cognitive measures (g=−0.36; 95% CI=−0.45 to –0.28), with high heterogeneity (Q=242.30, p<0.001, τ=0.26). Significant within-domain effects was yielded by cognitive screener (g=−0.55; 95% CI=−0.75 to –0.36), processing speed (g=−0.44; 95% CI=−0.57 to –0.32), global cognition (g=−0.40; 95% CI=−0.71 to –0.09), simple/complex attention (g=−0.38; 95% CI=−0.46 to –0.29), learning/memory (g=−0.34; 95% CI=−0.46 to –0.22), language (g=−0.34; 95% CI=−0.45 to –0.24) and executive function (g=−0.32; 95% CI=−0.43 to –0.21); but not motor (g=−0.40; 95% CI=−0.89 to 0.10), visuospatial/construction (g=−0.09; 95% CI=−0.23 to 0.05) and orientation (g=−0.02; 95% CI=−0.17 to 0.14). COVID-19 samples with elevated depression, anxiety, fatigue and disease severity yielded larger effects.

Conclusion

Mild cognitive deficits are associated with COVID-19 infection, especially as detected by cognitive screeners and processing speed tasks. We failed to observe clinically meaningful cognitive impairments (as measured by standard neuropsychological instruments) in people with COVID-19 without severe medical or psychiatric comorbidities.
Improvements of the shape and strength of the diaphragm after endoscopic lung volume reduction
Authors: Taton Olivier , Gevenois Pierre Alain , Van Muylem Alain , Bondue Benjamin , Van Laethem Sébastien , Leduc Dimitri
Published: June 2024

Rationale

Endoscopic lung volume reduction improves lung function, quality of life and exercise capacity in severe emphysema patients. However, its effect on the diaphragm function is not well understood. We hypothesised that endoscopic lung volume reduction increases its strength by modifying its shape.

Objectives

To investigate changes in both diaphragm shape and strength induced by the insertion of endobronchial valves.

Methods

In 19 patients, both the diaphragm shape and strength were investigated respectively by 3D Slicer software applied on CT scans acquired at functional residual capacity and by transdiaphragmatic pressure measurements by bilateral magnetic stimulation of the phrenic nerves before and 3 months after unilateral valves insertion.

Measurements and main results

After lung volume reduction (median (IQR), 434 mL (−597 to −156], p<0.0001), diaphragm strength increased (transdiaphragmatic pressure: 3 cmH2O (2.3 to 4.2), p<0.0001). On the treated side, this increase was associated with an increase in the coronal (16 mm (13 to 24), p<0.0001) and sagittal (26 mm (21 to 30), p<0.0001) lengths as well as in the area of the zone of apposition (62 cm2(3 to 100), p<0.0001) with a decrease in the coronal (8 mm (−12 to −4), p<0.0001) and sagittal (9 mm (−18 to −2), p=0.0029) radii of curvature.

Conclusions

Endoscopic lung volume reduction modifies the diaphragm shape by increasing its length and its zone of apposition and by decreasing its radius of curvature on the treated side, resulting in an increase in its strength.

Trial registration number

NCT05799352.
A structural and metabolic framework for classifying pre-clinical tuberculosis infection phenotypes using 18F-FDG PET-CT: a prospective cohort analysis followingM. tuberculosisexposure
Authors: Kim Jee Whang , Vadera Sonam , Sharifpour Meedya , Bajaj Amrita , Kamil Anver , Haldar Pranabashis
Published: June 2024

Tuberculosis (TB) control efforts are limited by ineffective characterisation of tuberculosis infection (TBI) —a heterogeneous spectrum of pre-clinical infection states, invisible to tools of routine clinical screening, that are associated with variable risk of progression to TB disease. In this prospective study, we use positron emission tomography-CT (PET-CT) as a high-resolution imaging modality to characterise and classify structural and metabolic features observed in 16 asymptomatic household TB contacts with normal chest radiographs. We identify four feature patterns that associate with distinct clinical and microbiological outcomes, supporting potential utility of PET-CT for objective classification of TBI phenotypes.
Ways of identifying lichen and plant species by the Nenets reindeer herders in Yamal
Authors: Laptander Roza , Stammler Florian , Forbes Bruce C. , Stark Sari
Published: June 2024

Yamal Nenets herders have historically developed a rich knowledge of lichens and vascular plants, which feature in the diet of their migratory reindeer herds in the tundra zone of northwest Siberia. In the Nenets language there are native names for certain species of lichens and other reindeer forage plants, including graminoids, herbs, shrubs, berries, and mushrooms. During participant fieldwork together with nomadic tundra Nenets herders, we documented names and definitions of reindeer food on herding territories during their long migration routes from the northern forest-tundra transition zone to the northern coastal tundra. Like many other Indigenous peoples of Siberia, Nenets have noticed that the Arctic is changing and some of its recent dynamics are seriously affecting their livelihood. The degradation of some lichen composition and cover on tundra pastures has also contributed to a decrease of herders’ linguistic palette for describing these losses in a concrete manner. Since the Nenets language is on the list of endangered languages of the world, this has an especially negative impact on the language skills and traditional knowledge of the younger generations of Nenets people, who may not know what these lichens look like and why they are important for the Nenets reindeer herding culture.
THE IMPACT OF THE USE OF DIGITAL FINANCIAL SERVICES ON HOUSEHOLD VICTIMIZATION BY CYBER-TELECOM FRAUD
Authors: LI YUAN , WANG SIYUAN
Published: June 2024

While digital finance has made financial services more accessible, it has also increased the risk of personal information leakage, which may make households more vulnerable to cyber-telecom fraud. Using data from the 2015 China Household Finance Survey (CHFS), this paper investigates the impact of the use of digital financial services on household victimization by cyber-telecom fraud. This paper finds that the use of digital financial services significantly heightens the risk of households falling victim to cyber-telecom fraud, as evidenced by an increased likelihood of encountering such fraud, experiencing financial losses and suffering greater monetary losses as a result. The sub-dimensional analyses show that using digital payments increases the risk of households falling victim to cyber-telecom fraud, and engaging in digital wealth management increases the likelihood of households experiencing cyber-telecom fraud losses and the amount of money lost. Further interactive analysis shows that financial literacy moderates the situation. Specifically, as households’ level of financial literacy increases, the likelihood of encountering cyber-telecom fraud through digital finance, experiencing related losses and the amount of losses incurred decreases. After overcoming the endogeneity problem and performing robustness tests, the conclusions remain consistent.
EXPLORING THE RELATIONSHIP BETWEEN RESIDENTIAL LOCATION AND LONG-TERM SETTLEMENT INTENTIONS: A STUDY OF MIGRANT WORKERS IN URBAN CHINA
Authors: DING WEIWU , LIU CHU , WU YUTING , LI PEILIN , WU YUFENG , WANG SHENGJIN
Published: June 2024

This study delves into the link between the residential locations of migrant workers in China and their intentions to settle, set against the backdrop of the household registration system’s liberalization and the rise of a market economy. While migrant workers have significantly contributed to the societal development of China, research indicates their struggles with local community integration, leading many to eventually return to their hometowns. The influence of migrant workers’ residential choices on their migration patterns has been underexplored in Chinese scholarly discussions, a stark contrast to the attention it has received in Western academia. Employing segmented assimilation theory and spatial assimilation theory as theoretical frameworks, the study scrutinizes the relationship between migrant workers’ residential location and their long-term settlement intentions, utilizing questionnaire data collected in 2020. The empirical findings indicate that residential location is significantly related to their long-term settlement intentions, as migrant workers residing in urban centers exhibit a more pronounced intention to remain in their host cities compared to their suburban counterparts. Furthermore, the relationship is also shaped by the degree of their social integration. The study further emphasizes the importance of accounting for migration timing and homeownership status when examining this relationship, contributing to a deeper understanding of the factors that shape migration decisions in the context of China’s rapid urbanization.
Finite element approximation of unique continuation of functions with finite dimensional trace
Authors: Burman Erik , Oksanen Lauri
Published: June 2024

We consider a unique continuation problem where the Dirichlet trace of the solution is known to have finite dimension. We prove Lipschitz stability of the unique continuation problem and design a finite element method that exploits the finite dimensionality to enhance stability. Optimal a priori and a posteriori error estimates are shown for the method. The extension to problems where the trace is not in a finite dimensional space, but can be approximated to high accuracy using finite dimensional functions is discussed. Finally, the theory is illustrated in some numerical examples.
Local-length-scale calculation in T-splines meshes for complex geometries
Authors: Mikawa Shohei , Takizawa Kenji , Otoguro Yuto , Terahara Takuya , Tezduyar Tayfun E.
Published: June 2024

Variational multiscale methods and their precursors, stabilized methods, which are sometimes supplemented with discontinuity-capturing (DC) methods, have been playing their core-method role in flow computations increasingly with isogeometric discretization. The stabilization and DC parameters embedded in most of these methods play a significant role. The parameters almost always involve some local-length-scale expressions, most of the time in specific directions, such as the direction of the flow or solution gradient. The direction-dependent expressions introduced earlier target B-splines meshes for complex geometries. The key stages of deriving these expressions are mapping the direction vector from the physical element to the parent element in the parametric space, accounting for the discretization spacing along each of the parametric coordinates, and mapping what has been obtained back to the physical element. Here, we extend the local-length-scale calculation method to meshes built from T-splines. T-splines meshes are a superset of B-splines meshes. They provide smooth basis functions in complex geometry and effective refinement without subdividing where we do not need higher resolution. In this article, we focus on the product form T-splines basis functions. They are represented individually in product form, from multiplication of [Formula: see text] 1D basis functions, where [Formula: see text] is the number of parametric dimensions. Each 1D basis function comes from the set of functions associated with one of the parametric directions and the set of functions is defined considering the T-splines nature of the mesh. The product-form basis functions satisfy the partition of unity without using rational functions. For these T-splines, based on the method introduced for B-splines, the local length scales are calculated with Bézier-extraction row operators, which are element-level constants. Using T-splines involves element splitting also for increased integration accuracy. Our local-length-scale expressions are invariant with respect to element splitting performed for integration accuracy but account for the element splitting that is for enhancing the function space.
Non-diffeomorphic minimal genus relative trisections of the same 4-manifold
Authors: Takahashi Natsuya
Published: June 2024

We show the existence of a [Formula: see text]-manifold with boundary that admits two non-diffeomorphic minimal genus relative trisections of the same [Formula: see text]-type. To prove this, we introduce a simple operation that produces a trisection diagram of a closed [Formula: see text]-manifold from a relative trisection diagram.
Evaluation of the optical, photoluminescence, and thermal characteristics of Barium thiourea chloride (BTCL), a metal–organic crystal for photonic applications
Authors: Albert Helen Merina , Shibu Smitha , Gupta Abha , Ganganagunta Srinivas , Neelima Patnaik D. , Rajagopalan N. R. , Manoj Kumar Nellore
Published: June 2024

The development of crystal fabrication and characterization approaches makes it possible to study novel materials with enhanced linear and nonlinear optical properties. The solution growth method was adopted in the present investigation to create Barium thiourea chloride (BTCL), a metal–organic single crystal. Structural, optical, and thermal characteristics of the BTCL crystals were evaluated by XRD analysis, Fourier transform infrared spectroscopy, UV–Vis spectrometry, photoluminescence, SHG, and thermal analyses. The XRD method was applied to investigate the structural characteristics of the BTCL, which is related to the monoclinic structure. The FT-IR spectral investigation was conducted to observe the vibrational modes in BTCL. The optical measurements showed the transmittance in the near-UV and visible spectrums. Optical characteristics include bandgap, refractive index, extinction coefficient, optical, and electrical conductivities, and dielectric constants were obtained. The PL curve showed two notable emission peaks at 482.5[Formula: see text]nm and 491[Formula: see text]nm. The ability to generate second harmonics was investigated using the Kurtz and Perry method, and the SHG was more than 1.79 times the KDP sample. The thermal behavior of the BTCL was evaluated by TGA/DTA measurements. The Coats–Redfern relation was used to estimate the activation energy of the thermal system and the value was determined to be 9.48[Formula: see text]KJ/mol. The findings indicate that the BTCL crystals possess excellent optical transparency, higher SHG potency, and good thermal stability, which are suitable for use in photonic structures.
Bi-free probability theory and reflection positivity
Authors: Speicher Roland
Published: June 2024

We point out that bi-free product constructions respect reflection positivity.
Hand Gesture Recognition System Based on Indian Sign Language Using SVM and CNN
Authors: Gupta Anuj Kumar , Singh Shaminder
Published: June 2024

Hand gestures (HGs) have been extensively acknowledged as a communication standard for the deaf and dumb school system in the Indian sign language (ISL). We suggested an automated Indian sign language recognition (ISLR) method for English in this study. Initially, the hand region is segmented using the Grasshopper optimization algorithm (GOA) based on the skin color model method. The segmentation’s efficacy is further assessed using three techniques: GOA-based skin color detection algorithm (SCDA), particle swarm optimization-based SCDA (PSO-SCDA), and artificial bee colony-based SCDA (ABC-SCDA). Finally, a database for the retrieved motions representing distinct English alphabets is created. For gesture recognition, the system is trained, and a template-based matching approach is used. The classification technique employs the support vector machine (SVM) and the convolution neural network (CNN). Our suggested recognition method achieved the highest accuracy of 97.85% with GOA-SCDA, compared to 89.29% and 93.96% with PSO-SCDA and ABC-SCDA, respectively. Furthermore, CNN outperformed SVM in classification, with a high accuracy of 99.2% and precision of 81.8%.
Viscosity solutions to the inhomogeneous reaction–diffusion equation involving the infinity Laplacian
Authors: Lin Tao , Liu Fang
Published: June 2024

In this paper, we study the inhomogeneous reaction–diffusion equation involving the infinity Laplacian: [Formula: see text] where the continuous function [Formula: see text] satisfies [Formula: see text] a positive function [Formula: see text] [Formula: see text] [Formula: see text] and [Formula: see text]. Such a model permits existence of solutions with dead core zones, i.e. a priori unknown regions where non-negative solutions vanish identically. For [Formula: see text] and the non-positive inhomogeneous term [Formula: see text] we establish the existence, uniqueness and stability of the viscosity solution of the corresponding continuous Dirichlet problem. Under additional structure conditions on [Formula: see text] and [Formula: see text] we obtain the optimal [Formula: see text] regularity across the free boundary [Formula: see text] Moreover, we establish the porosity of the free boundary and Liouville type theorem for entire solutions. Finally, we prove that the dead core vanishes in the limit case [Formula: see text]
The continuous-time magnetic quantum walk and its probability invariance on a class of graphs
Authors: Cao Jiaqi , Wang Caishi , Zhao Jijun , Yang Zheng
Published: June 2024

Let [Formula: see text] be a nonnegative integer and [Formula: see text] the power set of the set [Formula: see text]. Then there is an adjacency relation in [Formula: see text] such that [Formula: see text] together with the relation forms a regular graph. In this paper, we propose a model of continuous-time magnetic quantum walk (MQW) on the graph [Formula: see text], and investigate its properties from a viewpoint of probability and quantum information. We first introduce a magnetic Laplacian [Formula: see text] on the graph [Formula: see text] and examine its spectrum. And then, with [Formula: see text] as the Hamiltonian, we construct our model of continuous-time MQW on the graph [Formula: see text]. We find that the model has probability distributions that are completely independent of the magnetic potential at all times. And we show that it has perfect state transfer at time [Formula: see text] when the magnetic potential satisfies some mild conditions. Some other interesting results are also obtained.
Computational Study and Application of the Hamilton and Crosser Model for Ternary Hybrid Nanofluid Flow Past a Riga Wedge with Heterogeneous Catalytic Reaction
Authors: Al-Turef Gadah Abdulrahman , Obalalu A. M. , Saleh Waafa , Shah S. H. A. M. , Darvesh Adil , Khan Umair , Ishak Anuar , Adegbite Peter , Ojewola O. B. , Hussain Syed Modassir
Published: June 2024

The research of heat and mass transfer enhancement is influenced by several physical effects such as thermal conductivity, heterogeneous catalytic reaction, heat source/sink, thermal radiation and suction/injection, and is a significant area of study, particularly in the field of applied materials science, nanotechnology and mechanical engineering. The main objective of this research is to analyze and explore the heat and mass transfer of a novel ternary hybrid nanofluids binary nanofluid flow while considering the influences of the control parameters mentioned earlier. The model is developed for Hamilton and Crosser to analyze the radiation mechanism in a fluid system subjected to a Riga wedge. Due to the upgraded thermal transportation, the novel ternary hybrid nanofluids (THNs) show great potential in addressing these difficulties because of their significant properties, which include enhanced thermal conductivity, convective thermal transport and the ability to improve autocatalysis reactions. The governing model equations and boundary conditions are nondimensionalized by introducing suitable similarity transformations. Thereafter, the computational Chebyshev collocation spectral technique implemented in the MATHEMATICA 11.3 environment is used to calculate the numerical solution. The THNs demonstrate an efficiency rate of about 2.79%, with a minimum efficiency rate of 3.27%. It has been revealed that heat generation and solar radiation parameters are significant physical features for enhancing heat transfer processes.
Simulation and modeling in cloud computing-based smart grid power big data analysis technology
Authors: Padmanaban K. , Baby Kalpana Y. , Geetha M. , Balan K. , Mani V. , Sivaraju S. S.
Published: June 2024

Cloud computing’s simulation and modeling capabilities are crucial for big data analysis in smart grid power; they are the key to finding practical insights, making the grid resilient, and improving energy management. Due to issues with data scalability and real-time analytics, advanced methods are required to extract useful information from the massive, ever-changing datasets produced by smart grids. This research proposed a Dynamic Resource Cloud-based Processing Analytics (DRC-PA), which integrates cloud-based processing and analytics with dynamic resource allocation algorithms. Computational resources must be able to adjust the changing grid circumstances, and DRC-PA ensures that big data analysis can scale as well. The DRC-PA method has several potential uses, including power grid optimization, anomaly detection, demand response, and predictive maintenance. Hence the proposed technique enables smart grids to proactively adjust to changing conditions, boosting resilience and sustainability in the energy ecosystem. A thorough simulation analysis is carried out using realistic circumstances within smart grids to confirm the usefulness of the DRC-PA approach. The methodology is described in the intangible, showing how DRC-PA is more efficient than traditional methods because it is more accurate, scalable, and responsive in real-time. In addition to resolving existing issues, the suggested method changes the face of contemporary energy systems by paving the way for innovations in grid optimization, decision assistance, and energy management.
Curriculum Reinforcement Learning for Autonomous Planning in Unprotected Left Turn Scenarios
Authors: Zhu Yuzhen , Xu Shuyuan , Chen Xuemei , Zhao Yanan , Dong Xianyuan
Published: June 2024

In complex urban scenarios like intersections without dedicated left-turn signals, the construction of planning systems that maximize efficiency while guarantee safety has been a significant challenge. In this paper, we propose a reinforcement learning approach based on curriculum learning using real world dataset, and we develop a partial end-to-end planning and control model capable of adapting to variable temporal and spatial dimensional state inputs, applying it to autonomous driving task. Our model is compared with mainstream reinforcement learning algorithms to validate that our proposed algorithm can effectively solve complex spatio-temporal planning problems. This significantly enhances the efficiency of passing while maintaining a certain level of safety.
Bibliometrics researches on the application of artificial intelligence-aided diagnosis system in CT medical diagnosis
Authors: Lei Yuxin , Zhang Weiguo , Zhang Zhu , Li Meiran
Published: June 2024

Artificial Intelligence (AI) technology could provide new impetus for the development of medical image, and this also could be seen as the new developing chance for both AI and medical image. In this study, we are mainly focused on the Computed Tomography (CT) diagnostic technology in medical imaging. The analysis of AI-assisted CT diagnostic research aims to provide the overall status of this field. Therefore, the analysis of bibliometrics was applied. Bibliometrics is generated by the open literature index by national or international platforms, which can demonstrate the research features of AI-assisted CT diagnostic. Those obtained results indicate that the development of AI-assisted CT imaging medical research slowed down in the past 2 years. This change is affected by the appearance of some uncertainties. However, the total number of published literatures from all countries basically accelerated in the past decade. Take the year of 2022 as example; in this year, China and the United States were the world’s first and second largest contributors of relevant research literature. Researchers in these two countries have done plenty of works to the development of AI-assisted CT diagnostic. But in terms of literature influence, China still has a certain gap from the United States. Because of this, the number of high citation literature published from China is lower than those published from the United States. To some extent, this work presents the research progress of this field, so it is essential to review and apply experiences from those discussed countries.
An Entropic Analysis of Efficiency in the West Texas Intermediate Crude Oil Futures Market
Authors: Yuhn Ky-Hyang , Sagul Ryan
Published: June 2024

For the last 50 years or so, the efficient market hypothesis (EMH) has been the central pillar of economic thought and the building block of portfolio theory. However, the validity of the EMH still remains controversial, and the methods of testing for market efficiency have been criticised. This study utilises entropy analysis combined with generalised autoregressive conditional heteroscedasticity (GARCH) regressions to provide extensive empirical evidence on informational efficiency. This study develops an innovative method for studying market efficiency by investigating the complexity of information saturated in the market. To this end, we have used daily West Texas Intermediate (WTI) crude oil futures contracts from June 1983 to February 2016, giving a total data set of 282,427 observations. The results of the Jensen–Shannon informational criteria indicate that the informational efficiency measure has never reached the maximum value of 1 which indicates weak-form efficiency. Our study has further found that the informational efficiency measure tends to decrease consistently during recessionary periods and to increase in subsequent periods. We have also found that the entropy measure tends to increase over time, supporting the adaptive market hypothesis over the EMH.
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers
Authors: Zhao Xiaoyan , Deng Yang , Yang Min , Wang Lingzhi , Zhang Rui , Cheng Hong , Lam Wai , Shen Ying , Xu Ruifeng
Published: June 2024

Relation extraction (RE) involves identifying the relations between entities from underlying content. RE serves as the foundation for many natural language processing (NLP) and information retrieval applications, such as knowledge graph completion and question answering. In recent years, deep neural networks have dominated the field of RE and made noticeable progress. Subsequently, the large pre-trained language models (PLMs) have taken the state-of-the-art RE to a new level. This survey provides a comprehensive review of existing deep learning techniques for RE. First, we introduce RE resources, including datasets and evaluation metrics. Second, we propose a new taxonomy to categorize existing works from three perspectives, i.e., text representation, context encoding, and triplet prediction. Third, we discuss several important challenges faced by RE and summarize potential techniques to tackle these challenges. Finally, we outline some promising future directions and prospects in this field. This survey is expected to facilitate researchers’ collaborative efforts to address the challenges of real-world RE systems.
Solid-State Microfabricated Potentiometric Sensors for Selective Assessment of Diclofenac Sodium Utilizing Pentafluorophenyl Diazonium Modified Carbon Nanotubes Transducer Layer
Authors: Sami Iman , Monir Hany H. , Mahmoud Amr M. , El-Saharty Yasser S. , Rostom Yasmin
Published: June 2024

In the pharmaceutical field, analytical chemistry is evolving and one area that is experiencing enthusiasm is the design and implementation of solid contact ion-selective electrodes. We have developed two potentiometric sensors for the selective assay of a widely used drug diclofenac sodium. Diclofenac sodium was targeted in one of its most recommended dosage forms (Arthrotec® tablets) in the presence of misoprostol. A cost-effective copper printed circuit board as a substrate has been coated with a PVC sensing membrane to fabricate sensor I. Hydrophobic carbon nanotubes (CNTs) have been modified through in situ reduction of pentafluorophenyl diazonium using sodium borohydride. An interlayer of the modified CNTs was inserted as a transducer layer between the Cu substrate and the ion-sensing membrane in sensor II to enhance its electrochemical performance and stability. The microfabricated electrodes demonstrated encouraging outcomes upon the direct assay of diclofenac sodium in combination with misoprostol and other additives without sample preparation steps. The responses presented a linear Nernstian pattern in the range of 1.0 × 10−4 to 1.0 × 10−2 mol l−1 with a slope of −58.2 and −58.4 mV/decade for sensors I and II, consequently. Finally, the sustainability of the developed technique was assured using advanced green metrics.
Modeling Electrode Shape Changes in Electrodeposition and Electrochemical Dissolution
Authors: Colli A. N. , Dominguez-Benetton X. , Fransaer J.
Published: June 2024

In the fields of metal production, surface finishing, and electronic device manufacturing, achieving precise control over electrochemical processes is crucial for product quality, efficiency, and cost-effectiveness. This paper introduces an open-source modeling tool based on a dynamic mesh technique built on the finite volume method using the C

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toolbox OpenFOAM. This tool has been validated against both newly proposed analytical solutions and existing numerical and experimental results in various conditions and kinetic controls. The analytical solution predicts the electrode surface position, current, or cell voltage difference for confined electrodes. It considers primary and secondary current distributions with linear kinetics under different electric control modes. Notably, the validation highlights the congruence of the new method with prior studies and underscores its potential to offer enhanced predictive capabilities. Furthermore, this work extends beyond traditional modeling approaches by incorporating pulse reverse plating, which has been successfully modeled using the dynamic mesh method. Additionally, a modified Wagner number

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is proposed to predict in advance the optimal conditions for achieving a more uniform deposit. This innovative approach contributes to the advancement of theoretical understanding and will improve practical applications in electrochemical deposition and dissolution processes.
Simulation‐Based Education as a Solution to Challenges Encountered with Clinical Teaching in Nursing and Midwifery Education in Malawi: A Qualitative Study
Authors: Mwalabu Gertrude , Msosa Annie , Tjoflåt Ingrid , Urstad Kristin Hjorthaug , Bø Bodil , Furskog-Risa Eva Christina , Mapulanga Patrick , Msiska Masauko
Published: June 2024

Nursing and midwifery education in Malawi entails theoretical learning and clinical practice, essential for developing competent professionals. However, challenges such as staff shortages and limited resources hinder effective clinical teaching. Simulation‐based education (SBE) offers a promising solution. This study aims to explore how SBE can enhance clinical teaching in Malawian nursing and midwifery education. Data were collected through in‐depth interviews with lecturers, clinical instructors, and focus group discussion (FGD) with the final‐year students. Thematic analysis revealed several key findings: SBE serves as a valuable gap‐filler in clinical education, addressing complex needs while offering diverse learning opportunities. It also provides a platform for enhanced supervision and assessment strategies. The results indicate that SBE enables students to master various clinical skills without direct patient contact, reducing congestion at clinical sites while ensuring credit acquisition. Moreover, it proves effective as both a supervision and assessment tool for evaluating students’ clinical performance. In conclusion, the study advocates for the integration of SBE into Malawian nursing and midwifery education to alleviate the challenges associated with traditional clinical teaching. By leveraging SBE, institutions can mitigate overcrowding at clinical sites and provide students with diverse learning experiences. However, successful implementation requires adequate infrastructure, resources, and skilled lecturers. Ultimately, SBE holds the potential to significantly enhance the quality and outcomes of nursing and midwifery education in Malawi.