bluuebunny/crossref_metadata_2025_split huggingface dataset:
American zebra optimization algorithm for global optimization problems
Authors: Mohapatra Sarada , Mohapatra Prabhujit 
Published: March 2023

AbstractA novel bio-inspired meta-heuristic algorithm, namely the American zebra optimization algorithm (AZOA), which mimics the social behaviour of American zebras in the wild, is proposed in this study. American zebras are distinguished from other mammals by their distinct and fascinating social character and leadership exercise, which navies the baby zebras to leave the herd before maturity and join a separate herd with no family ties. This departure of the baby zebra encourages diversification by preventing intra-family mating. Moreover, the convergence is assured by the leadership exercise in American zebras, which directs the speed and direction of the group. This social lifestyle behaviour of American zebras is indigenous in nature and is the main inspiration for proposing the AZOA meta-heuristic algorithm. To examine the efficiency of the AZOA algorithm, the CEC-2005, CEC-2017, and CEC-2019 benchmark functions are considered, and compared with the several state-of-the-art meta-heuristic algorithms. The experimental outcomes and statistical analysis reveal that AZOA is capable of attaining the optimal solutions for maximum benchmark functions while maintaining a good balance between exploration and exploitation. Furthermore, numerous real-world engineering problems have been employed to demonstrate the robustness of AZOA. Finally, it is anticipated that the AZOA will accomplish domineeringly for forthcoming advanced CEC benchmark functions and other complex engineering problems.
Deep multilevel wet etching of fused silica glass microstructures in BOE solution
Authors: Konstantinova T. G. , Andronic M. M. , Baklykov D. A. , Stukalova V. E. , Ezenkova D. A. , Zikiy E. V. , Bashinova M. V. , Solovev A. A. , Lotkov E. S. , Ryzhikov I. A. , Rodionov I. A. 
Published: March 2023

AbstractFused silica glass is a material of choice for micromechanical, microfluidic, and optical devices due to its chemical resistance, optical, electrical, and mechanical performance. Wet etching is the key method for fabricating of such microdevices. Protective mask integrity is a big challenge due extremely aggressive properties of etching solution. Here, we propose multilevel microstructures fabrication route based on fused silica deep etching through a stepped mask. First, we provide an analysis of a fused silica dissolution mechanism in buffered oxide etching (BOE) solution and calculate the main fluoride fractions like$${HF}_{2}^{-}$$HF2-,$${F}^{-}$$F-,$${(HF)}_{2}$$(HF)2as a function of pH and NH4F:HF ratio. Then, we experimentally investigate the influence of BOE composition (1:1–14:1) on the mask resistance, etch rate and profile isotropy during deep etching through a metal/photoresist mask. Finally, we demonstrate a high-quality multilevel over-200 μm etching process with the rate up to 3 μm/min, which could be of a great interest for advanced microdevices with flexure suspensions, inertial masses, microchannels, and through-wafer holes.
Evaluation of artificial intelligence model for crowding categorization and extraction diagnosis using intraoral photographs
Authors: Ryu Jiho , Kim Ye-Hyun , Kim Tae-Woo , Jung Seok-Ki 
Published: March 2023

AbstractDetermining the severity of dental crowding and the necessity of tooth extraction for orthodontic treatment planning are time-consuming processes and there are no firm criteria. Thus, automated assistance would be useful to clinicians. This study aimed to construct and evaluate artificial intelligence (AI) systems to assist with such treatment planning. A total of 3,136 orthodontic occlusal photographs with annotations by two orthodontists were obtained. Four convolutional neural network (CNN) models, namely ResNet50, ResNet101, VGG16, and VGG19, were adopted for the AI process. Using the intraoral photographs as input, the crowding group and the necessity of tooth extraction were obtained. Arch length discrepancy analysis with AI-detected landmarks was used for crowding categorization. Various statistical and visual analyses were conducted to evaluate the performance. The maxillary and mandibular VGG19 models showed minimum mean errors of 0.84 mm and 1.06 mm for teeth landmark detection, respectively. Analysis of Cohen’s weighted kappa coefficient indicated that crowding categorization performance was best in VGG19 (0.73), decreasing in the order of VGG16, ResNet101, and ResNet50. For tooth extraction, the maxillary VGG19 model showed the highest accuracy (0.922) and AUC (0.961). By utilizing deep learning with orthodontic photographs, dental crowding categorization and diagnosis of orthodontic extraction were successfully determined. This suggests that AI can assist clinicians in the diagnosis and decision making of treatment plans.
Output‐feedback stochastic model predictive control of chance‐constrained nonlinear systems
Authors: Zhang Jingyu , Ohtsuka Toshiyuki 
Published: March 2023

AbstractThis study covers the output‐feedback model predictive control (MPC) of nonlinear systems subjected to stochastic disturbances and state chance constraints. The stochastic optimal control problem is solved in a stochastic dynamic programming fashion, and the output‐feedback control is performed with the extended Kalman filter. The information state is summarized as a dynamic Gaussian belief model. Thus, the stochastic Bellman equation is transformed into a deterministic equation using this model. The resulting constrained Bellman equation is solved using the proposed constrained, approximate dynamic programming algorithm. The algorithm is proved to have a Q‐superlinear local convergence rate. Numerical experiments show that the proposed algorithm can attain good control performance and reasonable chance‐constraint satisfaction and is computationally efficient owing to its dynamic programming structure.
Compact diplexer with high isolation based on mixed‐mode triangular substrate integrated waveguide cavities
Authors: Deng Senshen , Xu Feng , Zheng Zichao 
Published: March 2023

AbstractA novel compact diplexer based on mixed‐mode isosceles right triangular (IRT) substrate integrated waveguide (SIW) cavities is presented. A dual‐mode IRT SIW junction cavity is direct‐coupled with two single‐mode IRT SIW cavities for lower and upper channels, respectively. The diplexer has two third‐order filtering channels, centred at 16 and 18.3 GHz with 400 and 422 MHz bandwidths. The in‐band measured return and insertion losses are 19 dB/1.3 dB in the lower band and 17 dB/1.36 dB in the upper band. Due to the orthogonality of TE102 and TE201 modes in dual‐mode IRT SIW cavity, high isolation (>45 dB) between two channels is obtained. Besides, the proposed diplexer based on the triangular SIW cavity also has advantages of low cost and easy integration with other planar circuits.
Quantum privacy‐preserving service for secure lane change in vehicular networks
Authors: Rahmani Zeinab , Barbosa Luis S. , Pinto Armando N. 
Published: March 2023

AbstractSecure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks. However, classical SMC implementations suffer from efficiency and security challenges. To address this problem, two quantum communication technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution were utilised. These technologies supply symmetric and oblivious keys respectively, allowing fast and secure inter‐vehicular communications. These quantum technologies are integrated with the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to form a Quantum Secure Multiparty Computation (QSMC) platform. A lane change service is implemented in which vehicles broadcast private information about their intention to exit the highway. The proposed QSMC approach provides unconditional security even against quantum computer attacks. Moreover, the communication cost of the quantum approach for the lane change use case has decreased by 97% when compared to the classical implementation. However, the computation cost has increased by 42%. For open space scenarios, the reduction in communication cost is especially important, because it conserves bandwidth in the free‐space radio channel, outweighing the increase in computation cost.
Whole system radar modelling: Simulation and validation
Authors: Kannanthara Jithin , Griffiths Darren , Jahangir Mohammed , Jones Jonathan M. , Baker Chris J. , Antoniou Michail , Bell Colin J. , White Henry , Bongs Kai , Singh Yeshpal 
Published: March 2023

AbstractThe ever‐expanding horizon of radar applications demands solutions with high‐end radar functionalities and technologies and is often limited by the available radar equipment, cost and time. A practical method to tackle the situation is to rely on the modelling and simulation of radar systems based on the user requirements. The comprehensive system‐level modelling of a pulsed Doppler radar in MATLAB/Simulink consisting of all the fundamental blocks in the transmit chain, the environment, the receive chain, and the data processing chain is presented in this article. The first half of the article discusses the high‐fidelity simulation of each building block in the radar model. In the second half of the article, the range‐Doppler plot generated from the high‐fidelity radar model is compared and validated using the range‐Doppler plot from a real radar trial. The radar phase noise plays a crucial role in the detection of slowly moving, low radar cross‐section targets in the presence of strong clutter. The article also briefly discusses the effects of radar oscillator phase noise in the range‐Doppler plot. The validated, fully flexible radar model has the advantage of supporting the addition of further building blocks and optimising the parameters based on user requirements.
The chemical ecology of coumarins and phenazines affects iron acquisition by pseudomonads
Authors: McRose Darcy L. , Li Jinyang , Newman Dianne K. 
Published: March 2023

Secondary metabolites are important facilitators of plant–microbe interactions in the rhizosphere, contributing to communication, competition, and nutrient acquisition. However, at first glance, the rhizosphere seems full of metabolites with overlapping functions, and we have a limited understanding of basic principles governing metabolite use. Increasing access to the essential nutrient iron is one important, but seemingly redundant role performed by both plant and microbial Redox-Active Metabolites (RAMs). We used coumarins, RAMs made by the model plant
Arabidopsis thaliana
, and phenazines, RAMs made by soil-dwelling pseudomonads, to ask whether plant and microbial RAMs might each have distinct functions under different environmental conditions. We show that variations in oxygen and pH lead to predictable differences in the capacity of coumarins vs phenazines to increase the growth of iron-limited pseudomonads and that these effects depend on whether pseudomonads are grown on glucose, succinate, or pyruvate: carbon sources commonly found in root exudates. Our results are explained by the chemical reactivities of these metabolites and the redox state of phenazines as altered by microbial metabolism. This work shows that variations in the chemical microenvironment can profoundly affect secondary metabolite function and suggests plants may tune the utility of microbial secondary metabolites by altering the carbon released in root exudates. Together, these findings suggest that RAM diversity may be less overwhelming when viewed through a chemical ecological lens: Distinct molecules can be expected to be more or less important to certain ecosystem functions, such as iron acquisition, depending on the local chemical microenvironments in which they reside.
Returning to a new normal
Authors: Heinzmann Sybille , Hilbe Robert , Bleichenbacher Lukas , Ehrsam Kristina 
Published: March 2023

AbstractThis article presents a comparative case study analysis of two mobility students who, during the first wave of the COVID-19 pandemic, had to terminate their stay abroad early and return home after seven and eleven weeks, respectively. The study aims to shed light on the impact of the outbreak of the pandemic on students’ social contacts and their re-adaptation back home, drawing on interview and questionnaire data. The interview data were analyzed using qualitative content analysis and suggest that, while the outbreak of the COVID-19 pandemic was a stressful experience for both students, which impacted the social contacts they entertained and their re-adaptation at home, the two students’ experiences also differed in many ways. We argue that these differences may be attributable to the social contacts the students maintained prior to the outbreak of the pandemic, the goals associated with the stay abroad, and the students’ coping strategies.
Understanding, collecting, and presenting data in New Englishes research
Authors: Neuhausen Miriam 
Published: March 2023

Abstract
Against the background of my fieldwork in an isolated Old Order Mennonite community averse to secular norms and values, I suggest ethnographic fieldwork is key to understanding, collecting, and presenting New Englishes data. Before entering the field, researchers must begin to question principles that work in Western urban societies but may play out differently in lesser-studied communities. An understanding of the sociolinguistic realities in the community under investigation paves the way for the discovery of new social variables, access to speakers, and the accomplishment of meaningful research. I illustrate these benefits mainly in reference to the Labovian sociolinguistic interview. Finally, the paper argues that researchers need to ensure that their representation of the community is in line with the community’s interests.
Complicating the field
Authors: Heyd Theresa 
Published: March 2023

Abstract
In this contribution, I explore the growing role of digital communication for the study of World Englishes and specifically the potential of digital ethnography as a methodological framework. I outline basic principles and traditions of digital ethnography and point out continuities between the importance of traditional, on-the-ground fieldwork for World Englishes, and consequences of more complex and fuzzy notions of the digital field. I give a closer examination of applications of digital ethnography by pointing to three case studies in different global settings. Finally, the chapter concludes with a discussion of the research ethics gap in digital ethnography and initial suggestions for ethical grounding of digital ethnography approaches in World Englishes.
Controllable coexistence of threshold and non-volatile crosspoint memory for highly linear synaptic device applications
Authors: Pal Parthasarathi , Singh Amit , Wang Yeong-Her 
Published: March 2023

Abstract
A highly reliable and versatile resistive memory device that demonstrates threshold and non-volatile memory (NVM) switching behaviour depending on the compliance current (CC) modulation was utilised by doping a semiconducting (Si) material into a high-k (HfO
x
) film with highly linear synaptic behaviour. The device shifted towards volatile switching at a CC less than 1 µA and exhibited NVM behaviour at a CC limit above 10 µA. A 3-bit/cell data storage capability on RESET voltage modulation was implemented for high-density memory application. The device exhibited excellent programming linearity of potentiation/depression responses up to 10 000 pulses compatible with fast pulse (100 ns) with good I
ON/I
OFF ratio (>103), stable data retention capability (105 s) at 85 °C and high WRITE endurance (∼107 cycles) with a pulse width of 200 ns. The neuromorphic applications were successfully emulated through neural network simulations using the experimentally calibrated data of the Si-doped HfO
x
resistive cross-point devices. Simulation results revealed a low nonlinearity of 0.03 with 98.08% pattern recognition accuracy. The estimated results revealed the potential of the device as a low-power selector and high-density NVM storage in large-scale crossbar array in future neuromorphic computing applications.
Evidence of multi-band superconductivity in non-centrosymmetric full Heusler alloy LuPd2Sn
Authors: Yadav Kavita , Mukherjee K 
Published: March 2023

Abstract
In this work, evidence of multi-band superconductivity and presence of mixed parity states in full Heusler alloy LuPd2Sn is investigated using the x-ray diffraction, temperature and field dependent resistivity, temperature dependent magnetization, and heat capacity measurements. Our studies reveal that LuPd2Sn is a type II superconductor and undergoes superconducting transition below 2.5 K. Above 2.5 K, the temperature and field dependence of resistivity indicate to the presence of multiple bands and inter-band phonon assisted scattering. The upper critical field, H
C2 (T) exhibits linear behaviour and deviates from Werthamer, Helfand and Hohenberg model over the measured temperature range. Additionally, the Kadowaki–Woods ratio plot supports the unconventional superconductivity in this alloy. Moreover, a significant deviation from the s-wave behaviour is noted, which is studied using phases fluctuation analysis. It indicates the presence of spin triplet along with spin singlet component arising due to antisymmetric spin orbit coupling.
Correlation between charge density wave phase transition and hydrogen adsorption in 1T-TaS2 thin film devices
Authors: Ishiguro Yasushi , Suzuki Rintaro , Yangzhou Zhao , Kodama Naoko , Takai Kazuyuki 
Published: March 2023

Abstract
Thin films of tantalum disulfide in the 1T-polytype structural phase (1T-TaS2), a type of metallic two-dimensional (2D) transition metal dichalcogenides (TMDs), are reactive to H2. Interestingly, in the incommensurate charge-density wave (ICCDW) phase with a metallic state, the electrical resistance of the 1T-TaS2 thin film decreases when H2 is adsorbed on it and returns to its initial value upon desorption. In contrast, the electrical resistance of the film in the nearly commensurate CDW (NCCDW) phase, which has a subtle band overlap or a small bandgap, does not change upon H2 adsorption/desorption. This difference in H2 reactivity is a result of differences in the electronic structure of the two 1T-TaS2 phases, namely, the ICCDW and NCCDW phases. Compared to other semiconductor 2D-TMDs such as MoS2 and WS2, the metallic TaS2 has been theoretically proven to capture gas molecules more easily because Ta has a stronger positive charge than Mo or W. Our experimental results provide evidence of this. Notably, this study is the first example of H2 sensing using 1T-TaS2 thin films and demonstrates the possibility of controlling the reactivity of the sensors to the gas by changing the electronic structure via CDW phase transitions.
Non-Abelian hierarchies of compatible maps, associated integrable difference systems and Yang-Baxter maps
Authors: Kassotakis Pavlos 
Published: March 2023

Abstract
We present two non-equivalent families of hierarchies of non-Abelian compatible maps and we provide their Lax pair formulation. These maps are associated with families of hierarchies of non-Abelian Yang-Baxter maps, which we provide explicitly. In addition, these hierarchies correspond to integrable difference systems with variables defined on edges of an elementary cell of the

Z

2

graph, that in turn lead to hierarchies of difference systems with variables defined on vertices of the same cell. In that respect we obtain the non-Abelian lattice-modified Gel’fand-Dikii hierarchy, together with the explicit form of a non-Abelian hierarchy that we refer to as the lattice-NQC (or lattice-

(
Q
3

)
0

) Gel’fand-Dikii hierarchy.
Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy
Authors: Szmul Adam , Taylor Sabrina , Lim Pei , Cantwell Jessica , Moreira Isabel , Zhang Ying , D’Souza Derek , Moinuddin Syed , Gaze Mark N. , Gains Jennifer , Veiga Catarina 
Published: March 2023

Abstract

Objective. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve the quality of on-board cone beam CT (CBCT) images for dose calculation using deep learning. Approach. We propose a novel framework for CBCT-to-CT synthesis using cycle-consistent Generative Adversarial Networks (cycleGANs). The framework was tailored for paediatric abdominal patients, a challenging application due to the inter-fractional variability in bowel filling and small patient numbers. We introduced to the networks the concept of global residuals only learning and modified the cycleGAN loss function to explicitly promote structural consistency between source and synthetic images. Finally, to compensate for the anatomical variability and address the difficulties in collecting large datasets in the paediatric population, we applied a smart 2D slice selection based on the common field-of-view (abdomen) to our imaging dataset. This acted as a weakly paired data approach that allowed us to take advantage of scans from patients treated for a variety of malignancies (thoracic-abdominal-pelvic) for training purposes. We first optimised the proposed framework and benchmarked its performance on a development dataset. Later, a comprehensive quantitative evaluation was performed on an unseen dataset, which included calculating global image similarity metrics, segmentation-based measures and proton therapy-specific metrics. Main results. We found improved performance for our proposed method, compared to a baseline cycleGAN implementation, on image-similarity metrics such as Mean Absolute Error calculated for a matched virtual CT (55.0 ± 16.6 HU proposed versus 58.9 ± 16.8 HU baseline). There was also a higher level of structural agreement for gastrointestinal gas between source and synthetic images measured using the dice similarity coefficient (0.872 ± 0.053 proposed versus 0.846 ± 0.052 baseline). Differences found in water-equivalent thickness metrics were also smaller for our method (3.3 ± 2.4% proposed versus 3.7 ± 2.8% baseline). Significance. Our findings indicate that our innovations to the cycleGAN framework improved the quality and structure consistency of the synthetic CTs generated.