Local Strain Research Articles

Comparative Analysis of the Response Accuracies of Large Language Models in the Korean National Dental Hygienist Examination Across Korean and English Questions.

Large language models such as Gemini, GPT-3.5, and GPT-4 have demonstrated significant potential in the medical field. Their performance in medical licensing examinations globally has highlighted their capabilities in understanding and processing specialized medical knowledge. This study aimed to evaluate and compare the performance of Gemini, GPT-3.5, and GPT-4 in the Korean National Dental Hygienist Examination. The accuracy of answering the examination questions in both Korean and English was assessed. This study used a dataset comprising questions from the Korean National Dental Hygienist Examination over 5 years (2019-2023). A two-way analysis of variance (ANOVA) test was employed to investigate the impacts of model type and language on the accuracy of the responses. Questions were input into each model under standardized conditions, and responses were classified as correct or incorrect based on predefined criteria. GPT-4 consistently outperformed the other models, achieving the highest accuracy rates across both language versions annually. In particular, it showed superior performance in English, suggesting advancements in its training algorithms for language processing. However, all models demonstrated variable accuracies in subjects with localized characteristics, such as health and medical law. These findings indicate that GPT-4 holds significant promise for application in medical education and standardized testing, especially in English. However, the variability in performance across different subjects and languages underscores the need for ongoing improvements and the inclusion of more diverse and localized training datasets to enhance the models' effectiveness in multilingual and multicultural contexts.

Evaluation of U-Notch and V-Notch Geometries on the Mechanical Behavior of PVDF: The DIC Technique and FEA Approach.

The notch effect of semicrystalline PVDF was investigated using U- and V-notch geometries with different depths, and tensile tests were performed at 23 °C using the DIC technique and FEA. Both unnotched and notched dumbbell-shaped specimens were subjected to tensile loading with the DIC technique to obtain mechanical curves and strain maps. The experimental data were compared to a numerical model, analyzing both global mechanical curves and local strain maps around the notch region to assess the accuracy of the simulations. The results demonstrated that the geometry and depth of the notch influence the mechanical behavior of PVDF, presenting a decrease in load and displacement compared to unnotched specimens. This aspect was corroborated by strain maps, which showed the increase in the local strain around the notch tip. For FEA, the global analysis indicated a good correlation with experimental results, and the local analysis demonstrated a reasonable agreement in strain map results within 0.5 mm of the notch neighborhood. Overall, the DIC technique and FEA provided a reliable evaluation of notch behavior on the PVDF used as pressure sheaths with reasonable precision.

Abnormal Response of Indirect Excitons to Non‐Uniform Elastic Strain in MoS2 Flakes

AbstractRegulating the electronic structures and carrier dynamics in 2D materials via elastic strain is a fascinating avenue for tailoring their optoelectronic properties at atomic scale. Here, the abnormal response of indirect excitons to non‐uniform elastic strain in MoS2 flakes is reported. The non‐uniform elastic strain in the MoS2 flakes is introduced by transferring them to pre‐prepared convex cross structures on a SiO2/Si substrate, where the topography and strain distribution are determined by atomic force microscopy and Raman spectroscopy, respectively. It is observed that the emission energy of the indirect excitons shows an unexpected blue‐shift followed by a red‐shift with increasing the local tensile strain, which is in sharp contrast to the linear red‐shift of the direct excitons. Density functional theory calculations reveal that the abnormal energy shift of the indirect excitons in the MoS2 flakes arises from the strain‐induced competition between two indirect bandgap transitions and the spatial exciton funnel effect in the non‐uniform strain field. This work provides new insights into the elastic strain effect on the indirect excitons in 2D semiconductors, which possesses potential applications in flexible optoelectronic devices.

Data Quality-Aware Client Selection in Heterogeneous Federated Learning

Federated Learning (FL) enables decentralized data utilization while maintaining edge user privacy, but it faces challenges due to statistical heterogeneity. Existing approaches address client drift and data heterogeneity issues. However, real-world settings often involve low-quality data with noisy features, such as covariate drift or adversarial samples, which are usually ignored. Noisy samples significantly impact the global model’s accuracy and convergence rate. Assessing data quality and selectively aggregating updates from high-quality clients is crucial, but dynamically perceiving data quality without additional computations or data exchanges is challenging. In this paper, we introduce the FedDQA (Federated learning via Data Quality-Aware) (FedDQA) framework. We discover increased data noise leads to slower loss reduction during local model training. We propose a loss sharpness-based Data-Quality-Awareness (DQA) metric to differentiate between high-quality and low-quality data. Based on the DQA, we design a client selection algorithm that strategically selects participant clients to reduce the negative impact of noisy clients. Experiment results indicate that FedDQA significantly outperforms the baselines. Notably, it achieves up to a 4% increase in global model accuracy and demonstrates faster convergence rates.

Analysis of shear bands in bulk metallic glasses based on elastoplastic phase transformation theory

Abstract Shear bands in amorphous alloys have been widely observed in uniaxial tension and compression experiments, reflecting strain localization, with plastic deformation occurring within the shear bands. In many instances, failures of bulk metallic glasses (BMGs) occur along the dominant shear bands. In this study, phase transformation theory is applied to investigate the mechanical properties of shear bands, focusing on the analysis of the two-phase deformations. The shear bands and the regions outside them are treated as two distinct phases in equilibrium. The deformation gradient tensor across the interface between these phases is discontinuous. By applying the jump conditions, governing equations are derived. As a case study, the shear bands and surrounding regions of plastic BMGs under uniaxial compression are analyzed, enabling the calculation of the stress associated with phase transformation and the inclination angle of the shear bands. The results obtained from this theoretical model align well with existing experimental and simulation data.

Strongly Enhanced Electronic Bandstructure Renormalization by Light in Nanoscale Strained Regions of Monolayer MoS2/Au(111) Heterostructures.

Understanding and controlling the photoexcited quasiparticle (QP) dynamics in monolayer (ML) transition metal dichalcogenides (TMDs) lays the foundation for exploring the strongly interacting, nonequilibrium two-dimensional (2D) QP and polaritonic states in these quantum materials and for harnessing the properties emerging from these states for optoelectronic applications. In this study, scanning tunneling microscopy/spectroscopy (STM/scanning tunneling spectroscopy) with light illumination at the tunneling junction is performed to investigate the QP dynamics in ML MoS2 on an Au(111) substrate with nanoscale corrugations. The corrugations on the surface of the substrate induce nanoscale local strain in the overlaying ML MoS2 single crystal, which result in energetically favorable spatial regions where photoexcited QPs, including excitons, trions, and electron-hole plasmas, accumulate. These strained regions exhibit pronounced electronic bandstructure renormalization as a function of the photoexcitation wavelength and intensity as well as the strain gradient, implying strong interplay among nanoscale structures, strain, and photoexcited QPs. In conjunction with the experimental work, we construct a theoretical framework that integrates nonuniform nanoscale strain into the electronic bandstructure of a ML MoS2 lattice using a tight-binding approach combined with first-principle calculations. This methodology enables better understanding of the experimental observation of photoexcited QP localization in the nanoscale strain-modulated electronic bandstructure landscape. Our findings illustrate the feasibility of utilizing nanoscale architectures and optical excitations to manipulate the local electronic bandstructure of ML TMDs and to enhance the many-body interactions of excitons, which is promising for the development of nanoscale energy-adjustable optoelectronic and photonic technologies, including quantum emitters and solid-state quantum simulators for interacting exciton polaritons based on engineered periodic nanoscale trapping potentials.

Effect mechanism of softening zone constraint on tensile failure of high-strength steel laser-welded joints

Softening of the heat-affected zone degrades the mechanical properties of high-strength steel-welded joints. This work revealed the key mechanism to suppress the adverse effects of the soft zone on joint performance by analyzing the constraint between different zones. The base metal (BM) can compete with the soft zone for plastic deformation when the soft zone is strongly constrained by the hard zone, which helps to disperse local strain and prevent premature necking. The constraint mode of the soft zone tends to evolve asymmetrically from bilateral to unilateral during the deformation. Reducing the width of the soft zone helps to achieve unilateral constraint, thus shifting the fracture location from the soft zone to the BM.

Evaluation of Rz2 Gene Expression in Sugar Beet Hybrids Infected with Beet Necrotic Yellow Vein Virus.

Sugar beet hybrids are essential in modern agriculture due to their superior yields, disease resistance, and adaptability. This study investigates the role of the Rz2 gene in conferring resistance to beet necrotic yellow vein virus (BNYVV) in 14 sugar beet hybrids cultivated in Kazakhstan, including local and European varieties. The Rz2 gene, encoding a CC-NB-LRR protein, is a known resistance factor against BNYVV. Using RT-qPCR, we assessed Rz2 expression and detected BNYVV in bait plants inoculated with virus-infested soil. Our findings identified two highly resistant varieties: the Kazakh cultivar 'Abulhair' and the French line 22b5006. Additionally, the Kazakh cultivar 'Pamyati Abugalieva' and the French hybrid 'Bunker' exhibited increased resistance, suggesting involvement of other resistance loci. Notably, the Danish hybrid 'Alando', despite resistance to rhizomania, did not effectively resist BNYVV, highlighting possible evasion of its genetic factors by local virus strains. Our results emphasize the importance of Rz2 in resistance breeding programs and advocate for further research on additional resistance genes and the genetic variability of BNYVV in Kazakhstan. This work pioneers the molecular evaluation of BNYVV resistance in sugar beet in Kazakhstan, contributing to sustainable disease management and improved sugar beet production.

Off-fault deformation feedback and strain localization precursor during laboratory earthquakes

Recent large-scale seismological observations have shown that off-fault strain localization and foreshock migration could serve as an early warning of an impending earthquake. However, this process is still largely unknown. In this study, state-of-the-art friction experiments were conducted in a oil-confined biaxial shear apparatus to investigate the link between stick-slip nucleation and off-fault deformation. Our findings indicate that there is a direct link between stick-slip nucleation and off-fault deformation, provided that the fault is conditionally unstable (a − b < 0). Inelastic off-fault deformation may trigger unstable slip by decreasing the stiffness of the surrounding rock volume, which favors earthquake nucleation. Additionally, the study presents laboratory observation of precursory strain localization around a fault during stick-slip cycles. These findings suggest that volumetric deformation processes could be a main factor in the nucleation of large ruptures and strain localization could be a reliable harbinger of large earthquakes.

Reducing inhomogeneous broadening of spin and optical transitions of nitrogen-vacancy centers in high-pressure, high-temperature diamond

With their optical addressability of individual spins and long coherence time, nitrogen-vacancy (NV) centers in diamond are often called “atom-like solid spin-defects”. As observed with trapped atomic ions, quantum interference mediated by indistinguishable photons was demonstrated between remote NV centers. In high sensitivity DC magnetometry at room temperature, NV ensembles are potentially rivaling with alkali-atom vapor cells. However, local strain induces center-to-center variation of both optical and spin transitions of NV centers. Therefore, advanced engineering of diamond growth toward crystalline perfection is demanded. Here, we report on the synthesis of high-quality HPHT (high-pressure, high-temperature) crystals, demonstrating a small inhomogeneous broadening of the spin transitions, of T2* = 1.28 μs, approaching the limit for crystals with natural 13C abundance, that we determine as T2* = 1.48 μs. The contribution from strain and local charges to the inhomogeneous broadening is lowered to ~17 kHz full width at half maximum for NV ensemble within a > 10 mm3 volume. Looking at optical transitions in low nitrogen crystals, we examine the variation of zero-phonon-line optical transition frequencies at low temperatures, showing a strain contribution below 2 GHz for a large fraction of single NV centers.

Towards value-sensitive and poisoning-proof model aggregation for federated learning on heterogeneous data

Federated Learning (FL) enables collaborative model training without sharing data, but traditional static averaging of local updates leads to poor performance on heterogeneous data. The following remedies, either by scheduling data distribution or mitigating local discrepancies, predominately fail to handle fine-grained heterogeneity (e.g., local imbalanced labels). To commence, we reveal that static averaging leads to the global model suffering from the mean fallacy. That is, the averaging process favors the local model with large parameters numerically rather than knowledge. To tackle this, we introduce FedVSA, a simple-yet-effective model aggregation framework sensitive to heterogeneous local data merits. Specifically, we invent a new global loss function for FL by prioritizing the valuable local updates, facilitating efficient convergence. We deduce a softmax-based aggregation rule and prove its convergence property via rigorous theoretical analysis. Additionally, we expose poisoning threats of model replacement that utilize the mean fallacy for attacks. To mitigate this threat, we propose a two-step mechanism involving auditing historic local training statistics and analyzing the Shapley Value. Through extensive experiments, we show that FedVSA achieves faster convergence (~1.52×) and higher accuracy (~1.6%) compared to the baselines. It also effectively mitigates poisoning attacks by agilely recovering and returning to normal aggregation.

Usefulness of Native T1 in Cardiac Magnetic Resonance Imaging and Echocardiographic Strain Parameters for Detecting Early Cardiac Involvement in Fabry Cardiomyopathy.

Non-invasive diagnosis of disease stage in Fabry cardiomyopathy with multimodality imaging is pivotal when deciding on the appropriate time to initiate enzyme replacement therapy. However, this approach has not been well established. We enrolled 14 patients with Fabry disease. All patients were evaluated using echocardiography and contrast cardiac magnetic resonance (CMR), and were divided into either an early-stage group without left ventricular hypertrophy (LVH; wall thickness >12 mm) or late gadolinium enhancement (LGE; n=7; median age 37 years; 4 female), or an advanced-stage group with LVH and/or LGE (n=7; median age 66 years; 7 female). Strain data from echocardiography and T1 mapping on CMR were compared between the groups. In the advanced-stage group, all strain data were impaired. In the early-stage group, localized longitudinal strain in the basal posterolateral segment was already reduced but both localized and global circumferential strain remained preserved. On CMR analysis, global and localized native T1 shortening were observed in the early-stage group, but were pseudo-normalized in the advanced-stage group. In logistic regression analysis, localized circumferential strain had significant diagnostic value for differentiating between early- and advanced stage (P=0.037) and significantly improved the predictive power of the model containing localized native T1 in CMR. A combination of localized native T1 in CMR and echocardiographic strain parameters could be useful for staging Fabry cardiomyopathy.

Oxygen vacancy order–disorder transition process during topotactic filament formation in a perovskite oxide tracked by Raman microscopy and transmission electron microscopy

Vacancy-ordered perovskite oxides are attracting attention due to their diverse functions such as resistive switching, electrocatalytic activity, oxygen diffusivity, and ferroelectricity. It is important to clarify the chemical lattice strains arising from compositional changes and the associated vacancy order–disorder phase transitions at the atomic scale. Here, we elucidate the intermediate process of a topotactic phase transition in Ca-doped bismuth ferrite films consisting of alternating stacks of oxygen perovskite layers and a brownmillerite-type oxygen vacancy layer. We use Raman spectroscopy and transmission electron microscopy to closely examine the evolution of local strains exerted on the constituent sub-layers by electrochemical oxidation. A negative Raman chemical shift is observed during oxidation, which is linearly correlated with the local negative chemical expansivity of the oxygen layer. It seemingly contradicts with the general trend that oxides undergo lattice contraction upon oxidation. Oxygen vacancies initially confined in the vacancy layers can be understood to diffuse into the oxygen layers during melting of the ordered structure. The finding deepens our understanding of the electro-chemo-mechanical coupling of vacancy-ordered oxides.

Microstructure and residual stress gradient evolution mechanism of electronic copper strip for lead frame

The miniaturization of integrated circuits has led to a shift in lead frame fabrication methods from physical stamping to chemical etching. However, this process is highly sensitive to residual stress. We investigated the gradient distribution of residual stress, microstructure, and macroscopic texture in electronic copper foils using a layer-by-layer peeling method, and proposed a novel strategy for evaluating residual stress levels. Our findings reveal that the rolling-induced residual stress exhibits a gradient distribution along the thickness direction. Specifically, from the surface to the central layer, the stress transitions gradually from tensile to compressive, with the stress type primarily influenced by metal flow during rolling. Additionally, we observed gradient variations in the S and Cube texture. Tensile stress favors the formation of Cube-texture, while compressive stress promotes S-texture development. Notably, Cube-texture can lead to strain localization during rolling, directly impacting the local residual stress levels and distribution. Furthermore, quantitative analysis of dislocation density using peak profile methods revealed a consistent trend between {111} plane dislocation density and lateral residual stress. Further investigation highlighted that dislocations and precipitates associated with {111} planes in face-centered cubic metals significantly influence residual stress, with their combined effects determining the overall stress magnitude in relation to texture, dislocations, and precipitates.

A Federated Transfer Fault Diagnosis Method for Cross-Domain and Incomplete Data

In fact, multiple clients often use similar devices and collect fault data separately, so joint multi-client collaborative fault diagnosis modeling can solve the problem of data scarcity, but this poses great challenges to data privacy protection. In this paper, we propose a federated transfer fault diagnosis method based on federated learning for cross-domain incomplete data. The proposed method only exchanges the parameters of the local training model, which achieves the privacy protection of the client’s local data. We construct a multi-client collaborative learning framework to address the problem of weak generalization ability caused by the lack of terms in single client training samples. We also propose a targeted semi-supervised fine-tuning strategy based on relative distance to reduce the probability of negative fine-tuning of out-of-distribution samples and improve the accuracy of diagnostic models. The results of cross-condition and cross-equipment experiments demonstrate that the proposed method has obvious advantages over the existing fault diagnosis methods.

On the nature of nano twin-induced shear band formation in a dispersion strengthened copper alloy under micro-mechanical loading

A key challenge in metallic alloys with high ductility is understanding how microstructural inhomogeneities influence shear localization, leading to localized plastic deformation and material failure. In this study, we explore the phenomenon of shear localization in coarse-grained copper, a material traditionally regarded as having low susceptibility to such behavior. Contrary to conventional understanding, our findings reveal that microstructural inhomogeneities play a pivotal role in inducing extensive strain localization during low strain rate micro-mechanical loading. The presence of fine precipitate particles leads to strain localization at small strains and low strain rates by activating shear localization driven by void formation mechanisms. Furthermore, nanoscale precipitates act as sites for dislocation pile-up within deformed structures of shear bands, leading to the formation of nano twins within these bands. Consequently, precipitate particles serve a dual role: contributing to strain localization and potential cracking, while also enhancing the alloy’s strength and ductility through nano-twinning mechanisms. This investigation offers a novel perspective on the interplay between material microstructure and deformation behavior, challenging existing paradigms in materials science.

Gated InAs quantum dots embedded in surface acoustic wave cavities for low-noise optomechanics

Self-assembled InAs quantum dots (QDs) are promising optomechanical elements due to their excellent photonic properties and sensitivity to local strain fields. Microwave-frequency modulation of photons scattered from these efficient quantum emitters has been recently demonstrated using surface acoustic wave (SAW) cavities. However, for optimal performance, a gate structure is required to deterministically control the charge state and reduce the charge noise of the QDs. Here, we integrate gated QDs and SAW cavities using molecular beam epitaxy and nanofabrication. We demonstrate that with careful design of the substrate layer structure, integration of the two systems can be accomplished while retaining the optimal performance of each subsystem. These results mark a critical step toward efficient and low-noise optomechanical systems that truly leverage the excellent properties of semiconductor QDs.

Edge-assisted U-shaped split federated learning with privacy-preserving for Internet of Things

In the realm of the Internet of Things (IoT), deploying deep learning models to process data generated or collected by IoT devices is a critical challenge. However, direct data transmission can cause network congestion and inefficient execution, given that IoT devices typically lack computation and communication capabilities. Centralized data processing in data centers is also no longer feasible due to concerns over data privacy and security. To address these challenges, we present an innovative Edge-assisted U-Shaped Split Federated Learning (EUSFL) framework, which harnesses the high-performance capabilities of edge servers to assist IoT devices in model training and optimization process. In this framework, we leverage Federated Learning (FL) to enable data holders to collaboratively train models without sharing their data, thereby enhancing data privacy protection by transmitting only model parameters. Additionally, inspired by Split Learning (SL), we split the neural network into three parts using U-shaped splitting for local training on IoT devices. By exploiting the greater computation capability of edge servers, our framework effectively reduces overall training time and allows IoT devices with varying capabilities to perform training tasks efficiently. Furthermore, we proposed a novel noise mechanism called LabelDP to ensure that data features and labels can securely resist reconstruction attacks, eliminating the risk of privacy leakage. Our theoretical analysis and experimental results demonstrate that EUSFL can be integrated with various aggregation algorithms, maintaining good performance across different computing capabilities of IoT devices, and significantly reducing training time and local computation overhead.

Local Strain Effects on Lattice Defect Dynamics and Interstitial Dislocation Loop Formation in Irradiated Tungsten-Molybdenum Alloys: A Molecular Dynamics Study.

In this study, molecular dynamics (MD) simulations were used to investigate how alloying tungsten (W) with molybdenum (Mo) and local strain affect the primary defect formation and interstitial dislocation loops (IDLs) in W-Mo alloys. While the number of Frenkel pairs (FPs) in the W-Mo alloy is similar to pure W, it is half that of pure Mo. The W-20% Mo alloy, chosen for further analysis, showed minimal FP variance after collision cascades induced by primary knock-on atoms (PKAs) at 10 to 80 keV. The research examined hydrostatic strains from -1.4% to 1.6%, finding that higher strains correlated with increased FP counts and cluster formation, including IDLs. The following two types of IDLs were identified: majority ½ <111> loops as well as <100> IDLs that formed within the initial picoseconds of the simulations under higher tensile strain (1.6%) and larger PKA energies (80 keV). The strain effects also correlated with changes in threshold displacement energy (TDE), with higher FP formation under tensile strain. This study highlights the impact of strain and alloying on radiation damage, particularly in low-temperature, high-energy environments.

Prevalence of the Potato virus Y strain composition impacting Michigan seed potato production

Potato virus Y (PVY) is a complex of multiple strains that cause a variety of foliar and tuber symptoms. Several current strains have potential to result in variety-dependent yield and quality losses. Understanding the local PVY strain population and variety responses are critical for detection and management. From 2019-2023, PVY strain composition was monitored across seven Michigan seed potato-producing counties growing prevalent chip, russet, and tablestock market classes. Using multiplex reverse-transcriptase polymerase chain reaction methods, PVY strains were identified from potato tuber or leaf samples collected through the certification program (N = 78 positive lots). PVYN-Wi remained most prevalent in Michigan, however, tuber necrotic strains PVYNTN and PVYE also continued to be detected. These, as well as some PVYN-Wi isolates, are known to cause necrotic symptoms in tubers, causing yield and quality reductions for susceptible potato cultivars. As in other U.S. potato-growing regions, PVYN-Wi and PVYNTN were most prevalent in Michigan seed potato lots. Of note, mild to severe tuber necrosis was observed in diagnostic samples positive with local PVYN-Wi strains. Parental strain PVYO appeared to re-emerge in 2023 and should be considered in certification and management. Mild or asymptomatic reactions may still lead to yield or quality losses and may pose a risk to more susceptible cultivars. Due to the diversity of strains and varieties prevalent in the Great Lakes region, continued uniform certification is recommended. Information gathered from this and future survey efforts will be valuable for growers, inspectors, and future breeding and selection efforts.