bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailoring second harmonic emission by ZnO nanostructures: Enhancement of directionality
Authors: Petronijevic Emilija , Sibilia Concita 
Published: February 2024

Tailoring nonlinear optical properties at the nanoscale is a hot topic in nowadays nanophotonics, promising for applications spanning from sensing to ultrafast optical communications. Here we present a numerical approach of designing a simple semiconductor nanostructure able to tailor second harmonic emission in the near- and far-field. We start from linear simulations of ZnO nanospheres, which reveal multipolar nature of the scattering. Next, we show how the same nanospheres, with radii in 30–130 nm range, excited at 800 nm, manipulate the directivity of the emitted second harmonic. We observe that the nanospheres which exhibit Kerker condition at 400 nm, emit the second harmonic field in the forward direction. We further investigate how the asymmetry (ellipsoid geometry) tailors the second harmonic directivity. We finally introduce geometry with low chiro-optical response, and observe that the second harmonic far-field depends on the handedness of the light exciting the nanostructure at 800 nm.
Navigating uncertainty: public diplomacy vs. AI
Authors: Di Martino Luigi , Ford Heather 
Published: February 2024

AbstractSome have heralded generative AI models as an opportunity to inform diplomacy and support diplomats’ communication campaigns. Others have argued that generative AI is inherently untrustworthy because it simply manages probabilities and doesn’t consider the truth value of statements. In this article, we examine how AI applications are built to smooth over uncertainty by providing a single answer among multiple possible answers and by presenting information in a tone and form that demands authority. We contrast this with the practices of public diplomacy professionals who must grapple with both epistemic and aleatory uncertainty head on to effectively manage complexities through negotiation. We argue that the rise of generative AI and its “operationalization of truth” invites us to reflect on the possible shortcoming of AI’s application to public diplomacy practices and to recognize how prominent uncertainty is in public diplomacy practices.
Human extreme heat protective behaviours: the effects of physical risks, psychological perception, and public measures
Authors: Li Jiayan , Sun Ranhao , Li Jialei , Ma Yongfu , Zhang Meng , Chen Liding 
Published: February 2024

AbstractIndividual actions can mitigate the consequences of extreme heat. Therefore, understanding the mechanism of protective behaviours against extreme heat is critical. Although extreme heat protective behaviours have been widely mentioned, the roles of psychological risk perception and public restraint are poorly understood. In this study, we developed a physical-measure-psychosocial model (PMP) to reveal the intrinsic motivation for protective behaviours during extreme heat based on a nationwide survey in China (n = 1791). The results showed that (1) high levels of physical risk perception promote outdoor, indoor, and traffic protective behaviours. Psychological risk perception is positively associated with outdoor and indoor protective behaviours but is not significantly associated with traffic protective behaviour. (2) There are differences in the main paths from heat exposure to outdoor, indoor, and traffic protective behaviours. The indirect effect controlled by physical risk is the main path from exposure to outdoor and traffic protective behaviours, while the direct effect of heat exposure is the strongest pathway for indoor protective behaviour. (3) Enhanced facility conditions are linked to reduced physical risk and psychological risk perception. Subsidies have a significant effect on traffic protective behaviour, and warnings significantly affect outdoor protective behaviour. The direct effect of warning systems on outdoor protective behaviour is greater than the indirect effect mediated by psychological risk perception. (4) Multigroup analysis based on structural equation models revealed a certain degree of robustness among the different gender, age, education level, and income level groups. This study enables us to understand the underlying mechanisms of extreme heat behaviours and support policy-makers in effective mitigation practices.
Salient sociophonetic features, stereotypes, and attitudes toward Jazani Arabic
Authors: Ruthan Mohammed Q. 
Published: February 2024

AbstractFar more attention has been paid to attitudes toward Standard Arabic than colloquial varieties, especially Jazani Arabic. This study aimed to identify Saudis’ stereotypes, beliefs, and attitudes toward Jazani, as well as salient sociophonetic features that might have an impact on those attitudes. An additional goal was to determine whether Saudi speakers of other dialects could identify Jazani. The study asked the following questions. Can speakers of different Saudi dialects identify Jazani speakers from sociophonetic input alone? What are Saudi speakers’ attitudes toward Jazani Arabic? What are the salient sociophonetic features of Jazani Arabic? A total of 183 Saudi Arabic speakers participated in an online attitudinal survey. Qualitative and quantitative analyses were conducted on the collected data. Findings showed that respondents could identify the speakers as Jazanis based solely on sociophonetic characteristics. Non-emphatic /r/ and word-initial consonant clusters were pointed out as salient features of Jazani Arabic. In addition, participants’ responses included general impressions, cultural associations, and social status. Overall, speakers of other Saudi dialects had more positive attitudes than Najdi speakers, who held more negative attitudes toward Jazani speakers. The results reflected the social stratification in Saudi Arabia and confirmed beliefs, stereotypical views, and misrepresentations of Jazani speakers’ social status.
Implications of media reports of crime for public trust and social support: a conceptual analysis of individuals’ psychological wellbeing
Authors: Şahinoğlu Belkıs , Saygılı Neriman , Muhtaroğulları Ayşe , Sinal Aysin 
Published: February 2024

AbstractCrime reporting influences the public regardless of its source (traditional or social media outlets). In this regard, the current research focuses on crime reports in Northern Cyprus, a small society, where individual psychological and social aspects can be influenced by media content. Specifically the effects of media on public trust, presumption of innocence, psychological wellbeing and social support are addressed through a qualitative approach. In this study, a mixed methodology of content and discourse analysis determined the negative coverage of crime through the existence of unethical principles among 507 articles from different media outlets. Furthermore, a thematic network approach was used to analyse semi-structured interviews, in which 38 individuals provided in-depth data about their personal experiences and emotions regarding media publication. Results showed how the influence of media coverage of crime can extend to affect the psychological well-being and social relationships of those individuals involved, particularly concerning anxiety, public trust, and social support. These effects can be further amplified due to the increased stress and anxiety felt among the public during the COVID-19 pandemic, ongoing at the time of the interviews. This research can provide a better understanding of media and its influence on trust and support during uncertain times. Hence, both scholars and practitioners can benefit from the current findings.
Euramet RMO supplementary comparison low pressure air flow between 25m3/h and 400 m3/h
Authors: Wendel Thomas , Busuladžić Dr Ibrahim , Windenberger Christophe , Mickan Dr Bodo , Huu Dr Marc de 
Published: February 2024

Main text
The purpose of this Supplementary Comparison (SC) for "Low Pressure Air Flow" measurement is to support the Calibration and Measurement Capabilities (CMC) of the participating National Metrology Institutes and Designated Institutes according to CIPM MRA-G-13. The outcome of this comparison should lead to 'a clear and unequivocal' comparison of measurement results between participants.
The comparison was performed over the span of one year which started in March 2021 with the determination of the volume flow rate error of the test artifact by VSL. The test artifact was shipped to each participant where they also determined the volume flow rate error in turn. At the completion by all participants, the artifact was shipped back to VSL for a final calibration to show the stability of the artifact.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
A ferromagnetic skyrmion-based spin-torque nano-oscillator with modified edge magnetization
Authors: Luo Danyu , Yu Guoliang , Li Yan , Qiu Yang , Wang Jiawei , Zhu Mingmin , Zhou Haomiao 
Published: February 2024

Abstract
Magnetic skyrmion-based spin-torque nano-oscillators (STNOs) have attracted significant interest because of their potential applications as microwave signal emitters and integrability in the existing CMOS process flow. However, the stable circular motion of the skyrmion in the nanodisk is affected by the Magnus force, which can destroy and annihilate the skyrmion at the nanodisk edge, thereby limiting the application of the maximum oscillation frequency. To overcome this problem, we investigated the influence of a modified magnetized structure at the edge of the nanodisk on the oscillation dynamics of skyrmions, in which the modified magnetized profile is acquired by local modification of the magnetic material parameters, and these skyrmions can move along the tilting magnetization formatted wall. It was found that the upper threshold for steady skyrmion oscillations can be improved by approximately two times compared to the standard structure without modified edge magnetization profiles. Based on the effective field analysis, we confirmed that the spatial distribution of the tilting moment at the edge layer changed the effective field distribution and caused a non-monotonic change in the upper threshold current with the modified region width. Our results may provide an optional route for designing future skyrmion-based STNOs with better performance in the communication and computing areas.
Pressure-driven dome-shaped superconductivity in topological insulator GeBi2Te4
Authors: Liu Chenchen , Gao Yiping , Tian Can , Jiang Chuang , Zhu Chengcheng , Wu Xinyue , Huang Xiaoli , Cui Tian 
Published: February 2024

Abstract
The discovery of new superconductors based on topological insulators always captures special attention due to their unique structural and electronic properties. High pressure is an effective way to regulate the lattice as well as electronic states in the topological insulators, thus altering their electronic properties. Herein, we report the structural and electrical transport properties of the topological insulator GeBi2Te4 by using high-pressure techniques. The synchrotron x-ray diffraction revealed that GeBi2Te4 underwent two structural phase transitions from R-3m (phase I) to C2/m (phase II) and then into Im-3m (phase III). Superconductivity was observed at 6.6 GPa to be associated with the first structural phase transition. The superconducting transition temperature Tc
reached a maximum value of 8.4 K, accompanied by the RH
sign changing from negative to positive at 14.6 GPa, then gradually decreased with increasing pressure in phase III, showing a dome-shaped phase diagram. The present results provide a platform for understanding the interplay between the crystal structure and superconductivity by the regulation of pressure in the topological insulator materials.
Seepage prediction model of the earth-rock dam based on TCN considering rainfall lag effect
Authors: Qu Manli 
Published: February 2024

Abstract
Renewable energy has the highest conversion efficiency, is the most flexible in regulating peak power in the grid, and has the potential to significantly reduce emissions. Hydropower is one of the main ways to optimize power energy structure by building earth-rock dams that block water and generate electricity. Seepage is a physical quantity that characterizes the safety of earth-rock dams. Studying the intelligent prediction model of earth-rock dams is an effective means of understanding the evolution of seepage behavior, and it is also crucial for the safe operation and energy efficiency of earth-rock dams. To create a rainfall factor expression reflecting the hysteresis effect of rain, actual monitoring data of different piezoelectric tubes on the upstream and downstream sides of the soil core wall of an earth-rock dam is considered. Based on the key influencing factors of the seepage behavior of earth-rock dams, the novel temporal convolutional network (TCN) algorithm in deep learning is introduced into the seepage behavior prediction of earth-rock dams, constructing the intelligent prediction model of seepage of earth-rock dams based on TCN. The engineering example shows that the seepage prediction model of the earth-rock dam based on TCN has better prediction performance than the seepage prediction model of the earth-rock dam based on support vector regression (SVR), extreme learning machine, and long-short term memory. The determination coefficient is more significant than 0.9, and the relative error of prediction is less than 1‰. The model’s prediction accuracy is high, and the stability of the prediction performance is good. The model’s prediction performance also improves after considering the rainfall lag effect.
Enhanced control over size, areal density, and shape of substrate-supported Au and Ag nanoparticles by solid-state dewetting and alloying
Authors: Yadav Mahesh J , Aravindan S , Rao P V 
Published: February 2024

Abstract
The ability to manipulate the dimensions, areal density, and form of substrate-supported Au and Ag nanoparticles (NPs) is highly desirable for utilizing their plasmonic properties in biosensing, photovoltaics, and nanophotonic applications. The transformation of thin films into the substrate-supported nanostructures by solid-state dewetting (SSD), provides an avenue to manipulate the dimensional aspects of nanostructures simply and cost-effectively on a large scale. However, spontaneous agglomeration of the film produces randomly distributed and non-uniform nanostructures that must be controlled. Here, we have systematically studied the effect of annealing temperature, between 200 °C and 750 °C, on the dewetting morphology evolution of Au, Ag, and Au–Ag bilayer ultrathin films sputter deposited on the c-plane (0001) sapphire substrates. Regardless of the film thickness, Ag films dewet faster than Au films and produce spherical NPs, compared to faceted Au NPs, with broader size distribution. Whereas, by the SSD of Au–Ag bilayer ultrathin films, highly spherical and monodisperse AuAg bimetallic NPs can be fabricated. Furthermore, we have shown the possibility of fabricating the AuAg bimetallic NPs of varying compositions by adjusting the thickness of individual layers, thus enabling us to smoothly tune the spectral location of plasmonic resonance within the visible range.
Machine learning approach for proton range verification using real-time prompt gamma imaging with Compton cameras: addressing the total deposited energy information gap
Authors: Kazemi Kozani Majid 
Published: February 2024

Abstract

Objective. Compton camera imaging shows promise as a range verification technique in proton therapy. This work aims to assess the performance of a machine learning model in Compton camera imaging for proton beam range verification improvement. Approach. The presented approach was used to recognize Compton events and estimate more accurately the prompt gamma (PG) energy in the Compton camera to reconstruct the PGs emission profile during proton therapy. This work reports the results obtained from the Geant4 simulation for a proton beam impinging on a polymethyl methacrylate (PMMA) target. To validate the versatility of such an approach, the produced PG emissions interact with a scintillating fiber-based Compton camera. Main results. A trained multilayer perceptron (MLP) neural network shows that it was possible to achieve a notable three-fold increase in the signal-to-total ratio. Furthermore, after event selection by the trained MLP, the loss of full-energy PGs was compensated by means of fitting an MLP energy regression model to the available data from true Compton (signal) events, predicting more precisely the total deposited energy for Compton events with incomplete energy deposition. Significance. A considerable improvement in the Compton camera’s performance was demonstrated in determining the distal falloff and identifying a few millimeters of target displacements. This approach has shown great potential for enhancing online proton range monitoring with Compton cameras in future clinical applications.
Polarization properties of E-FISH signals and optimization of simultaneous measurement of electric field vectors
Authors: Zheng Xinlei , Zhao Zheng , Zheng Haotian , Huang Zongze , Sun Zihan , Li Jiangtao 
Published: February 2024

Abstract
Electric field measurements based on the electric field induced second harmonic (E-FISH) method have been employed in a wide range of studies. Most studies typically measure two components of the electric field separately. Although there have been proposals for the simultaneous measurement of electric field vectors, the imbalance of the two corresponding E-FISH signals has limited its application. Furthermore, the relationship between the polarization of the E-FISH signal and the direction of external electric field remains unclear. In this paper, the general expressions for the polarization and power of both components of E-FISH signals are derived, assuming arbitrary probe beam polarization and external electric field direction. The theoretical results indicate that the polarization of E-FISH signals varies along the interaction length. The final signal’s polarization is elliptically polarized for arbitrary electric field distribution and is correlated with the polarization of the probe beam, which deviates from what is commonly assumed to be consistent with the external electric field. If the polarization of the probe beam is not parallel to the axes, the power of each signal component is determined by both components of the external electric field, which lays the foundation for the simultaneous measurement of electric field vectors. This theoretical prediction is subsequently validated by experimental results. Finally, the power maps suggest that the optimal polarization angle of the probe beam is 45° or 135° to achieve a balanced signal power when measuring an unknown electric field vector. Both components of the electric field can be simultaneously obtained according to the theoretical relationship.
Chen inequality for general warped product submanifold of Riemannian warped products
I×fSm(c)
Authors: Mofarreh Fatemah , Ali Akram 
Published: February 2024

Abstract
In the present paper, we investigate the geometry and topology of warped product submanifolds in Riemannian warped product

I

×

f

S

m

(
c
)

and obtain the first Chen inequality that involves extrinsic invariants like the mean curvature and the length of the warping functions. This inequality also involves intrinsic invariants (δ-invariant and sectional curvature). In addition, an integral bound is provided for the Bochner operator formula of compact warped product submanifolds in terms of the gradient Ricci curvature. Our main object is to apply geometrically to number structures and obtained applications of Dirichlet eigenvalues problems. Some new results on mean curvature vanishing are presented, and a partial solution can be found to the well-known problem given by S S Chern. The family of Riemannian warped products generalized to Robertson-Walker space-times
Artificial intelligence-based position control: reinforcement learning approach in spring mass damper systems
Authors: Demircioğlu Ufuk , Bakır Halit 
Published: February 2024

Abstract
This work examines the use of deep Reinforcement Learning (RL) in mass-spring system position control, providing a fresh viewpoint that goes beyond conventional control techniques. Mass-spring systems are widely used in many sectors and are basic models in control theory. The novel aspect of this approach is the thorough examination of the impact of several optimizer algorithms on the RL methodology, which reveals the optimal control tactics. The research applies a Deep Deterministic Policy Gradient (DDPG) algorithm for continuous action spaces, where the actor and critic networks are important components in assessing the agent’s performance. The RL agent is trained to follow a reference trajectory using the Simulink environment for system modeling. The study provides insights into the agent’s learning approach and performance optimization by evaluating the training process using force-time graphs, reward graphs, and Episode Manager charts. Furthermore, the effect of different combinations of optimizers on the control performance of the agent is examined. The outcomes highlight the importance of optimizer selection in the learning process by revealing significant variations in training times. As a result, a better understanding of the relationship between various optimizers and control performance is provided by this study’s novel application of reinforcement learning in mass-spring system control. The results raise the possibility of more potent methods for controlling complex systems and add to the expanding field of study at the interface of control theory and deep learning.
Scattering by harmonically trapped 2D quantum gas near and around the critical regime
Authors: Das Samir 
Published: February 2024

Abstract
In this article, we analytically explore the quantum phenomena of scattering by harmonically trapped 2D quantum gases. We show the temperature’s dependence on the differential scattering cross-section (DSC) near and around the critical transition regime for both particle and light scattering cases separately. For the particle scattering case, we consider scatterers with quantized bound motion in a harmonic trap. Our findings on the structure factor for light scattering give phase transition phenomena for 2D bosonic atoms and the thermal behavior of the system. This result has practical significance for recent experimental setups such as in situ image analysis and bosonic simulations. Finally, we show the temperature-dependent refractive index for a 2D harmonically trapped bosonic medium. This parameter is important in neutron scattering experiments.
Design and performance analysis of tri-layered strained Si/Si1–x
Ge
x
/Si heterostructure DG feedback FET
Authors: Das Subir , Kumari Tripty , Katta Sai Shirov , Singh Jawar , Tiwari Pramod Kumar 
Published: February 2024

Abstract
This work presents the design and performance analysis of a tri-layered strained Si/Si1−x
Ge
x
/Si heterostructure double gate feedback field-effect transistor (DG FBFET). The proposed DG FBFET is designed by introducing biaxial strain in the device by sandwiching a Si1−x
Ge
x
layer between two thin Si layers to provide high ON current as well as ultra-steep switching characteristics. The device offers a significantly high ON current (3.4 x 10−3 A/μm), high I

ON
/I

OFF
ratio (∼1010), a large memory window of 1.06 V, and an extremely low subthreshold swing (∼0.3 μ V/decade), which can be very useful for memory and neuromorphic applications. Furthermore, the ON/OFF switching of the device has been accomplished at a lower threshold voltage (0.287 V), allowing it to be utilized in low-power electronics. Synopsys TCAD tool has been used to create the device structure and analyze the electrical performances of the device.