bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative assessment of differently randomized accelerated particle swarm optimization and squirrel search algorithms for selective harmonics elimination problem
Authors: Tariq Muhammad Ayyaz , Fakhar Muhammad Salman , Abbas Ghulam , Kashif Syed Abdul Rahman , Rehman Ateeq Ur , Ouahada Khmaies , Hamam Habib 
Published: June 2024

AbstractA random initialization of the search particles is a strong argument in favor of the deployment of nature-inspired metaheuristic algorithms when the knowledge of a good initial guess is lacked. This article analyses the impact of the type of randomization on the working of algorithms and the acquired solutions. In this study, five different types of randomizations are applied to the Accelerated Particle Swarm Optimization (APSO) and Squirrel Search Algorithm (SSA) during the initializations and proceedings of the search particles for selective harmonics elimination (SHE). The types of randomizations include exponential, normal, Rayleigh, uniform, and Weibull characteristics. The statistical analysis shows that the type of randomization does impact the working of optimization algorithms and the fittest value of the objective function.
Stability of asymmetric Schwarzschild–Rindler–de Sitter thin shell wormhole
Authors: Eid A. , Alkaoud A. , Khader M. M. , Bakry M. A. 
Published: June 2024

AbstractThe paper examines the dynamics of asymmetric thin shell wormholes that connect two distinct spacetimes using the cut and paste technique. The focus is on analyzing the linear stability of these wormholes by considering radial perturbations and utilizing the modified generalized Chaplygin gas equation of state. The specific case of an asymmetric wormhole connecting Schwarzschild–Rindler spacetime to Schwarzschild–Rindler–de Sitter space–time is analyzed using this formalism. Our investigation uncovers the existence of both stable and unstable regions, which are contingent upon the appropriate selection of various parameters within the metric spacetime and equation of state. Additionally, we determine that stability regions exist as a consequence of the square speed of sound. By increasing the value of the cosmological constant, the stability region is expanded. Furthermore, the stability regions are augmented by the influence of Rindler parameters, while the stability regions are also affected by adjustments in the equation of state parameters, leading to their enlargement.
Epidemiological trends, antifungal drug susceptibility and SQLE point mutations in etiologic species of human dermatophytosis in Al-Diwaneyah, Iraq
Authors: Mahmood Hussein R. , Shams-Ghahfarokhi Masoomeh , Salehi Zahra , Razzaghi-Abyaneh Mehdi 
Published: June 2024

AbstractDermatophytes show a wide geographic distribution and are the main causative agents of skin fungal infections in many regions of the world. Recently, their resistance to antifungal drugs has led to an obstacle to effective treatment. To address the lack of dermatophytosis data in Iraq, this study was designed to investigate the distribution and prevalence of dermatophytes in the human population and single point mutations in squalene epoxidase gene (SQLE) of terbinafine resistant isolates. The identification of 102 dermatophytes isolated from clinical human dermatophytosis was performed through morphological and microscopic characteristics followed by molecular analysis based on ITS and TEF-1α sequencing. Phylogeny was achieved through RAxML analysis. CLSI M38-A2 protocol was used to assess antifungal susceptibility of the isolates to four major antifungal drugs. Additionally, the presence of point mutations in SQLE gene, which are responsible for terbinafine resistance was investigated. Tinea corporis was the most prevalent clinical manifestation accounting for 37.24% of examined cases of dermatophytosis. Based on ITS, T. indotineae (50.98%), T. mentagrophytes (19.61%), and M. canis (29.41%) was identified as an etiologic species. T. indotineae and T. mentagrophytes strains were identified as T. interdigitale based on TEF-1α. Terbinafine showed the highest efficacy among the tested antifungal drugs. T. indotineae and T. mentagrophytes showed the highest resistance to antifungal drugs with MICs of 2–4 and 4 μg/mL, while M. canis was the most susceptible species. Three of T. indotineae isolates showed mutations in SQLE gene Phe397Leu substitution. A non-previously described point mutation, Phe311Leu was identified in T. indotineae and mutations Lys276Asn, Phe397Leu and Leu419Phe were diagnosed in T. mentagrophytes XVII. The results of mutation analysis showed that Phe397Leu was a destabilizing mutation; protein stability has decreased with variations in pH, and point mutations affected the interatomic interaction, resulting in bond disruption. These results could help to control the progression of disease effectively and make decisions regarding the selection of appropriate drugs for dermatophyte infections.
Unsupervised underwater shipwreck detection in side-scan sonar images based on domain-adaptive techniques
Authors: Wei Chengwei , Bai Yunfei , Liu Chang , Zhu Yuhe , Wang Caiju , Li Xiaomao 
Published: June 2024

AbstractUnderwater object detection based on side-scan sonar (SSS) suffers from a lack of finely annotated data. This study aims to avoid the laborious task of annotation by achieving unsupervised underwater object detection through domain-adaptive object detection (DAOD). In DAOD, there exists a conflict between feature transferability and discriminability, suppressing the detection performance. To address this challenge, a domain collaborative bridging detector (DCBD) including intra-domain consistency constraint (IDCC) and domain collaborative bridging (DCB), is proposed. On one hand, previous static domain labels in adversarial-based methods hinder the domain discriminator from discerning subtle intra-domain discrepancies, thus decreasing feature transferability. IDCC addresses this by introducing contrastive learning to refine intra-domain similarity. On the other hand, DAOD encourages the feature extractor to extract domain-invariant features, overlooking potential discriminative signals embedded within domain attributes. DCB addresses this by complementing domain-invariant features with domain-relevant information, thereby bolstering feature discriminability. The feasibility of DCBD is validated using unlabeled underwater shipwrecks as a case study. Experiments show that our method achieves accuracy comparable to fully supervised methods in unsupervised SSS detection (92.16% AP50 and 98.50% recall), and achieves 52.6% AP50 on the famous benchmark dataset Foggy Cityscapes, exceeding the original state-of-the-art by 4.5%.
Research on spatial carving method of glutenite reservoir based on opacity voxel imaging
Authors: Zhao Hu , Zhang Zhong-wei , Yang Hong-wei , Wei Guo-hua 
Published: June 2024

AbstractThe glutenite reservoir in an exploration area in eastern China is well-developed and holds significant exploration potential as an important oil and gas alternative layer. However, due to the influence of sedimentary characteristics, the glutenite reservoir exhibits strong lateral heterogeneity, significant vertical thickness variations, and low accuracy in reservoir space characterization, which affects the reasonable and effective deployment of development wells. Seismic data contains the three-dimensional spatial characteristics of geological bodies, but how to design a suitable transfer function to extract the nonlinear relationship between seismic data and reservoirs is crucial. At present, the transfer functions are concentrated in low-dimensional or high-dimensional fixed mathematical models, which cannot accurately describe the nonlinear relationship between seismic data and complex reservoirs, resulting in low spatial description accuracy of complex reservoirs. In this regard, this paper first utilizes a fusion method based on probability kernel to fuse seismic attributes such as wave impedance, effective bandwidth, and composite envelope difference. This provide a more intuitive reflection of the distribution characteristics of glutenite reservoirs. Moreover, a hybrid nonlinear transfer function is established to transform the fused attribute cube into an opaque attribute cube. Finally, the illumination model and ray casting method are used to perform voxel imaging of the glutenite reservoirs, brighten the detailed characteristics of reservoir space, and then form a set of methods for ' brightening reservoirs and darkening non-reservoirs ', which improves the spatial engraving accuracy of glutenite reservoirs.
Integrated PBPK-EO modeling of osimertinib to predict plasma concentrations and intracranial EGFR engagement in patients with brain metastases
Authors: Liang Feng , Zhang Yimei , Xue Qian , Zhang Xiaoling 
Published: June 2024

AbstractThe purpose of this study was to develop and validate a physiologically based pharmacokinetic (PBPK) model combined with an EGFR occupancy (EO) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and the intracranial time-course of EGFR (T790M and L858R mutants) engagement in patient populations. The PBPK model was also used to investigate the key factors affecting OSI pharmacokinetics (PK) and intracranial EGFR engagement, analyze resistance to the target mutation C797S, and determine optimal dosing regimens when used alone and in drug-drug interactions (DDIs). A population PBPK-EO model of OSI was developed using physicochemical, biochemical, binding kinetic, and physiological properties, and then validated using nine clinical PK studies, observed EO study, and two clinical DDI studies. The PBPK-EO model demonstrated good consistency with observed data, with most prediction-to-observation ratios falling within the range of 0.7 to 1.3 for plasma AUC, Cmax, Ctrough and intracranial free concentration. The simulated time-course of C797S occupancy by the PBPK model was much lower than T790M and L858R occupancy, providing an explanation for OSI on-target resistance to the C797S mutation. The PBPK model identified ABCB1 CLint,u, albumin level, and EGFR expression as key factors affecting plasma Ctrough and intracranial EO for OSI. Additionally, PBPK-EO simulations indicated that the optimal dosing regimen for OSI in patients with brain metastases is either 80 mg once daily (OD) or 160 mg OD, or 40 mg or 80 mg twice daily (BID). When used concomitantly with CYP enzyme perpetrators, the PBPK-EO model suggested appropriate dosing regimens of 80 mg OD with fluvoxamine (FLUV) itraconazole (ITR) or fluvoxamine (FLUC) for co-administration and an increase to 160 mg OD with rifampicin (RIF) or efavirenz (EFA). In conclusion, the PBPK-EO model has been shown to be capable of simulating the pharmacokinetic concentration–time profiles and the time-course of EGFR engagement for OSI, as well as determining the optimum dosing in various clinical situations.
Consistency in climate change impact reports among indigenous peoples and local communities depends on site contexts
Authors: Schunko Christoph , Álvarez-Fernández Santiago , Benyei Petra , Calvet-Mir Laura , Junqueira André B. , Li Xiaoyue , Porcuna-Ferrer Anna , Schlingmann Anna , Attoh Emmanuel M. N. A. N. , Carmona Rosario , Chengula Fasco , Fernández-Llamazares Álvaro , Singh Priyatma , Torrents-Ticó Miquel , Reyes-García Victoria 
Published: June 2024

AbstractIndigenous Peoples and local communities are heavily affected by climatic changes. Investigating local understandings of climate change impacts, and their patterned distribution, is essential to effectively support monitoring and adaptation strategies. In this study, we aimed to understand the consistency in climate change impact reports and factors influencing consistency at site and individual levels. We conducted cross-cultural research among iTaukei (Fiji), Dagomba (Ghana), fisherfolks (Tanzania), Tsimane’ (Bolivia), Bassari (Senegal), ribeirinhos (Brazil), Mapuche (Chile), Mongolian (China), Tibetan (China) and Daasanach (Kenya) communities using semi-structured interviews, focus groups, and surveys among 1860 individuals. We found that cross-culturally more than two-thirds of individual reports of climate change impacts match site-confirmed reports. Consistency in reports is higher for changes related to pastoralism than crop production and wild plant gathering. Individual’s experience with nature, Indigenous and local knowledge, and local family roots are not significantly associated with consistency across sites, but site-specific associations are prevalent. Despite high average consistency among sites, there is considerable variation caused by site-specific factors, including livelihood activities, socio-cultural settings, and environmental conditions. Site contexts and related consistency in climate change impact reports need to be taken into account for climate change monitoring and adaptation planning.
Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives
Authors: Thelen Adam , Huan Xun , Paulson Noah , Onori Simona , Hu Zhen , Hu Chao 
Published: June 2024

AbstractDiagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.
Multiferroics: different routes to magnetoelectric coupling
Authors: Mostovoy Maxim 
Published: June 2024

AbstractThe simultaneous presence of ferroelectricity and magnetism in multiferroics breaks both spatial inversion and time reversal symmetries at the macroscopic scale, which opens the door to many interesting phenomena and resembles the violation of these symmetries in particle physics. The symmetry breaking in multiferroics occurs spontaneously at phase transitions rather than at the level of fundamental interactions, and thus can be controlled. Moreover, each crystal is a universe in itself with a unique set of symmetries, coupling constants and ordered patterns, which presents plenty of opportunities to find and design materials with strong magnetoelectric coupling.
Mechanically reconfigurable metasurfaces: fabrications and applications
Authors: Zhao Yinghao , Liu Zhiguang , Li Chongrui , Jiao Wenlong , Jiang Senlin , Li Xiaowei , Duan Jiahua , Li Jiafang 
Published: June 2024

AbstractOptical metasurfaces that control the light wavefront play an important role in various applications, from imaging to spectroscopy. Over the past decade, metasurfaces-based dynamic optical manipulation has been broadly investigated on diverse reconfigurable mechanisms, providing a footing ground for light control in both spatial and temporal dimensions. Therein, mechanical reconfiguration, as one of the most direct methods, allows for the geometric alteration of constituent meta-atoms through external stimuli, thereby facilitating the evolution of metasurfaces from single function to multifunctional. This review focuses on introducing the primary mechanisms behind current mechanically reconfigurable metasurfaces, including mechanical, electrical, thermal, and optical modulations. Their emerging applications, such as dynamic focusing, image display, beam steering, polarization manipulator, thermal radiation, etc., are briefly highlighted. The main challenges and future development directions are also summarized within this dynamic and rapidly evolving research area, offering insights and future perspectives for advancements in the related fields.
Nano-optomechanical fiber-tip sensing
Authors: Hendriks Arthur L. , Picelli Luca , van Veldhoven René P. J. , Verhagen Ewold , Fiore Andrea 
Published: June 2024

AbstractNano-optomechanical sensors exploit light confinement at the nanoscale to enable very precise measurements of displacement, force, acceleration, and mass. Their application is hampered by the complex optical set-ups or packaging schemes required to couple light to and from the nano-optomechanical resonator. In this work, we present a fiber-coupled nano-optomechanical sensor that requires no coupling optics. This is achieved by directly placing a nano-optomechanical structure, a double membrane photonic crystal (DM-PhC), on the facet of a fiber, using a simple and scalable wafer-to-fiber transfer method. The device is probed in reflection and has a resonance at telecom wavelengths with a relatively broad spectral width of 3–10 nm, which is advantageous for a simple read-out and achieves a displacement imprecision of $$10\,{{\rm{fm}}}/{\sqrt{{\rm{Hz}}}}$$

10

fm
/

Hz

. Using resonant driving and a ringdown measurement, we can induce and monitor mechanical oscillations with an nm-scale amplitude via the fiber, which allows for tracking the mechanical resonant frequency and the mechanical linewidth with imprecisions of 79 and 12 Hz, respectively, at integration times of 4.5 s. We further demonstrate the application of this fiber-tip sensor to the measurement of pressure, using the effect of collisional damping on the mechanical linewidth, leading to the imprecision of $$9\times {10}^{-4}\,{\rm{mbar}}$$

9
×

10

−
4

mbar

with an integration time of 290 s. This combination of optomechanics and fiber-tip sensing may open the way to a new generation of fiber sensors with unprecedented functionality, ultrasmall footprint, and low-cost readout.
Voice interactive information metasurface system for simultaneous wireless information transmission and power transfer
Authors: Meng Zan Kui , Shi Yan , Wu Quan Wei , Wei Wen Yue , Hui Ru , Wang Shao Ze , Dai Shi Han , Ma Qian , Cui Tie Jun 
Published: June 2024

AbstractIntelligent voice interaction offers a flexible and powerful way to connect individuals with smart devices beyond our expectations. The real-time nature of voice communication enables smart devices to comprehend the user language, execute the corresponding instructions, and facilitate seamless communications, transforming our lives in unprecedented ways. Owing to self-adaptive and reprogrammable functionalities, information metasurface (IMS) opens up a new avenue for smart home and smart cities. To further enhance the intelligence of IMS, we propose an IMS system via intelligent voice interaction and information processing. The voice interaction enables the efficient remote control on the IMS in a flexible, convenient, touchless manner. Leveraging speech recognition, speech synthesis, target detection, and communication technologies, the IMS system achieves automatic beam manipulation capabilities for wireless information transmissions and wireless power transfers. The IMS system is designed to operate in two distinct modes: instruction mode, wherein the user instructs the operations, and autonomous mode, wherein the automatic detections govern the actions, in which seamless mode switching through the voice commands is supported. Users can flexibly achieve precise control over the functions of the intelligent metasurface system through voice interaction at a distance, without the need for close-range manual touch control, which greatly simplifies the operation difficulty and is particularly suitable for remote control and complex application scenarios. A series of experiments, including wireless video transmissions and wireless power transfers are conducted to demonstrate the flexibility and convenience of the IMS system. The incorporation of intelligent voice interaction technology with the IMS presents a novel paradigm for the applications of programmable and information metasurfaces.
Resonator embedded photonic crystal surface emitting lasers
Authors: Bian Zijun , Zhao Xingyu , Liu Jingzhao , Kim Daehyun , McKenzie Adam F. , Thoms Stephen , Reynolds Paul , Gerrard Neil D. , Kyaw Aye S. M. , Grant James , Rae Katherine , Orchard Jonathan R. , Hill Calum H. , Munro Connor W. , Ivanov Pavlo , Childs David T. D. , Taylor Richard J. E. , Hogg Richard A. 
Published: June 2024

AbstractThe finite size of 2D photonic crystals results in them being a lossy resonator, with the normally emitting modes of conventional photonic crystal surface emitting lasers (PCSELs) differing in photon lifetime via their different radiative rates, and the different in-plane losses of higher order spatial modes. As a consequence, the fundamental spatial mode (lowest in-plane loss) with lowest out-of-plane scattering is the primary lasing mode. For electrically driven PCSELs, as current is increased, incomplete gain clamping results in additional spatial (and spectral) modes leading to a reduction in beam quality. A number of approaches have been discussed to enhance the area (power) scalability of epitaxy regrown PCSELs through careful design of the photonic crystal atom1–3. None of these approaches tackle the inflexibility in being unable to independently modify the photon lifetime of the different modes at the Γ2 point. As a method to introduce design flexibility, resonator embedded photonic crystal surface emitting lasers (REPCSELs) are introduced. This device, combining comparatively low coupling strength photonic crystal structures along with perimeter mirrors, allow a Fabry–Pérot resonance effect to be realised that provides wavelength selective modification of the photon lifetime. We show that surface emission of different surface emitting modes may be selectively enhanced, effectively changing the character of the modes at the Γ2 point. This is a consequence of the selective modification of in-plane loss for particular modes, and is dependent upon the alignment of the photonic crystal (PhC) band-structure and distributed Bragg reflectors’ (DBRs) reflectance spectrum. These findings offer new avenues in surface emitting laser diode engineering. The use of DBRs to reduce the lateral size of a PCSEL opens the route to small, low threshold current (Ith), high output efficiency epitaxy regrown PCSELs for high-speed communication and power sensitive sensing applications.