A Theoretical Study of Deflection of AFM Bimaterial Cantilevers Versus Irradiated Position

The bimaterial cantilevers of atomic force microscopes have been widely used in chemical and bio-sensing. Due to the difference in the thermal expansion coefficients of the two layers, the cantilever is deflected and its deflections is dependent on the heat absorption from the ambient environment or the objects adsorbed on the cantilever surface. In this study, we theoretically examine the deflection of this cantilever considering different irradiated configurations of a laser beam and thicknesses of the coating layer. We show that the temperature difference between the end and the clamped position is maximized for an irradiation at the cantilever end and this difference reduces with increasing coating thickness. Especially, the maximal deflection is seen for an irradiation in the middle of the cantilever, around 0.6 of the cantilever length from the clamped position. The obtained results could help determining an irradiated configuration of laser and the coating thickness to optimize the sensitivity of the cantilevers in thermally sensing devices

Optical Phonon Modes and Electron-optical Phonon Interaction in Core-shell Semiconductor Quantum Wires

Within the framework of the macroscopic dielectric continuum model the longitudinal optical (LO) phonon modes are derived for a cylindrical semiconductor quantum wire made of semiconductor 1 (well material) embedded in another finite semiconductor 2 (barrier material).  The phonon states of modes are given by solving the generalized Born-Huang equation. It is shown that there may exist four types of longitudinal optical phonon modes according to the concrete materials forming the wire. The dispersion equations for phonon frequencies with wave-vector components parallel to the wire are obtained. After having quantized the phonon field we derive the Fröhlich Hamiltonian describing the electron--LO-phonon interaction. The influence of the thickness of the barrier layer as well as the thin metallic shell on the phonon frequencies and their interaction with electrons is studied

FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding

Although Domain Adaptation in Semantic Scene Segmentation has shown impressive improvement in recent years, the fairness concerns in the domain adaptation have yet to be well defined and addressed. In addition, fairness is one of the most critical aspects when deploying the segmentation models into human-related real-world applications, e.g., autonomous driving, as any unfair predictions could influence human safety. In this paper, we propose a novel Fairness Domain Adaptation (FREDOM) approach to semantic scene segmentation. In particular, from the proposed formulated fairness objective, a new adaptation framework will be introduced based on the fair treatment of class distributions. Moreover, to generally model the context of structural dependency, a new conditional structural constraint is introduced to impose the consistency of predicted segmentation. Thanks to the proposed Conditional Structure Network, the self-attention mechanism has sufficiently modeled the structural information of segmentation. Through the ablation studies, the proposed method has shown the performance improvement of the segmentation models and promoted fairness in the model predictions. The experimental results on the two standard benchmarks, i.e., SYNTHIA $\to$ Cityscapes and GTA5 $\to$ Cityscapes, have shown that our method achieved State-of-the-Art (SOTA) performance.Comment: Accepted to CVPR'2

Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition

In this work, we investigate the problem of face reconstruction given a facial feature representation extracted from a blackbox face recognition engine. Indeed, it is a very challenging problem in practice due to the limitations of abstracted information from the engine. We, therefore, introduce a new method named Attention-based Bijective Generative Adversarial Networks in a Distillation framework (DAB-GAN) to synthesize the faces of a subject given his/her extracted face recognition features. Given any unconstrained unseen facial features of a subject, the DAB-GAN can reconstruct his/her facial images in high definition. The DAB-GAN method includes a novel attention-based generative structure with the newly defined Bijective Metrics Learning approach. The framework starts by introducing a bijective metric so that the distance measurement and metric learning process can be directly adopted in the image domain for an image reconstruction task. The information from the blackbox face recognition engine will be optimally exploited using the global distillation process. Then an attention-based generator is presented for a highly robust generator to synthesize realistic faces with ID preservation. We have evaluated our method on the challenging face recognition databases, i.e., CelebA, LFW, CFP-FP, CP-LFW, AgeDB, CA-LFW, and consistently achieved state-of-the-art results. The advancement of DAB-GAN is also proven in both image realism and ID preservation properties.Comment: arXiv admin note: substantial text overlap with arXiv:2003.0695

Economic policy uncertainty and corporate social responsibility: evidence from emerging countries

This study examines the impact of economic policy uncertainty on corporate social responsibility (CSR) performance using a panel dataset spanning from 2004 to 2021 across six emerging countries within Southeast Asia. We find a negative association between country-level economic policy uncertainty and firms’ CSR performance, particularly in terms of environmental and social indicators. Our findings remain robust across various robustness analyses and after addressing endogeneity concerns. Further, our study sheds light on how country-level policy uncertainty influences firms’ sustainability investments across different sectors. Specifically, firms in the Consumer Discretionary, Basic Materials and Real Estate sectors experience adverse effects from increased economic uncertainty, whereas those in the Health Care sector demonstrate a positive correlation. The study suggests that policymakers and firm managers should address economic policy uncertainty to enhance CSR performance and sustainability investments across industries