Vietnam National University, Ho Chi Minh City

WO3 is a semiconductor with a suitable valence band maximum (VBM) for the oxidation of water or hydroxide ions to generate hydroxyl radicals, which can be used to degrade organic compounds nonselectively. However, its poor crystallinity, rapid recombination of photogenerated electrons and holes, and an unfavorable conduction band minimum (CBM) for the single-electron reduction of O-2 limit the practical application of this semiconductor. To ameliorate these drawbacks, Fe3+-doped WO3 nanomaterials were fabricated by a hydrothermal method and investigated using density functional theory (DFT) calculations to achieve a comprehensive understanding of how Fe3+ doping affects the properties of WO3. The crystallinity of WO3 was significantly improved, with phase transformation from monoclinic-WO3 to hexagonal-WO3 occurring in the presence of Fe3+. This transition is evidenced by the increase in the hexagonal phase fraction (phi(h)) from 32% in WO3 to 61% in 7% Fe:WO3. In addition, the presence of Fe3+ at optimal levels created the intermediate energy states and oxygen vacancies on the surface to enhance electron-hole separation, reduce recombination, and improve the tetracycline (TC) adsorption capacity. As a result, the 7% Fe:WO3 demonstrated a photodegradation efficiency of 31.6% (k = 0.002 min(-1)), a 1.6-fold enhancement over the WO3. Furthermore, h(+) and OH & centerdot; were the main oxidizing agents, and the presence of the Fe3+ ion allowed the photocatalyst to utilize O-2 for producing O-2(& centerdot;), thus overcoming the disadvantages of WO3. Moreover, Fe3+ doping introduces shallow trap states in both the bulk and at the surface, which effectively suppress photogenerated electron-hole recombination and consequently facilitate the OH & centerdot;/H2O redox process.

Oranges (Citrus sinensis) are produced at tens of millions of tons annually, yet juice manufacturing still discards over half of the fruit mass as low‑value residues. In this review, a zero‑waste valorization roadmap for the whole orange is outlined, integrating natural‑product chemistry with enabling technologies across food, cosmetics, environmental remediation, and energy materials. Evidence on orange‑juice constituents, including vitamin C, flavanones (e.g., hesperidin, naringin), organic acids, and carotenoids, is synthesized with emphasis on bioaccessibility, antioxidant and cardiometabolic actions, skin benefits, and processing strategies (e.g., ultrasonication, heat) that preserve bioactives. Orange‑peel essential oil, dominated by limonene, is examined with nanodelivery approaches (zein nanoparticles, nanoemulsions) that overcome volatility and solubility limitations, enabling antimicrobial food packaging and agricultural applications. Peel residues are upcycled into high‑surface‑area carbonaceous structures and magnetic/composite derivatives for water decontamination and high‑performance supercapacitor electrodes, where pore hierarchy, heteroatom doping, and metal‑oxide hybrids govern adsorption and electrochemical behavior. Collectively, composition, process, property, and application relationships highlight the technical feasibility and sustainability potential of whole‑orange circular utilization across sectors.

Although stress and mental health challenges during crises have been widely documented, limited attention has been given to how strong family bonds may also transmit or amplify stress among family members. This dynamic, often reflected in the idea that the suffering of one member affects the entire group, remains particularly understudied in culturally family-oriented contexts such as Vietnam. This study investigates stress patterns among 988 Vietnamese respondents and examines the factors associated with stress using the COVID-19 pandemic as a case study of crisis impact. We employ the Perceived Stress Scale (PSS) and integrate Conservation of Resources Theory, the Social Determinants Framework, and the Family Systems-Illness Model in our analysis. The key finding highlights how strong family bonds in Vietnamese culture intensify stress levels when family members become infected with the virus, particularly due to, e.g., caregiving responsibilities and the emotional burden of being physically separated from ill family members. Policymakers, when designing interventions to address mental health challenges, should not only focus on individuals directly experiencing illness but also consider the well-being of other family members. The findings should be interpreted with caution, given the cross-sectional design and the context-specific nature of the study.

The increasing complexity and miniaturization of electronic devices have intensified the demand for high-quality printed circuit boards, particularly assembled boards (PCBAs), where early defect detection is essential to prevent severe degradation in device reliability and performance. In this paper, we propose a deep learning-based multi-modal fusion approach with three-mode optical illumination for automated PCBA defect detection. The proposed approach integrates a three-mode optical acquisition system with a purpose-built multi-modal deep learning model to enable robust and efficient defect recognition. In the first stage, we design a custom three-mode optical system integrating coaxial, polarized coaxial and dark-field illumination to enhance shape, edge and surface irregularity cues, thereby generating high-contrast and geometrically stable input images. In the second stage, we develop a multi-modal deep learning framework that performs mid-level feature fusion across three specialized inputs using two complementary strategies: cross-attention-based fusion (IMCAF) and gated Mixture-of-Experts fusion (IMGF). A realistic multi-modal dataset is constructed from defective PCBAs collected in manufacturing environments, comprising 1,774 images and a total of 10,475 annotated defect instances (bounding boxes) across eight defect categories with high morphological similarity and small-scale variations. Experimental results indicate that, under three-mode inputs, the proposed IMGF-based model achieves the highest detection accuracy, while the IMCAF-based model yields slightly lower accuracy with marginally improved inference efficiency. Across backbone comparisons, ConvNeXtV2-T exhibits the most favorable accuracy–efficiency trade-off compared with ResNeSt and Swin Transformer. Relative to single-mode, dual-mode and early-fusion approaches (IECAF), the proposed method delivers substantial performance gains (from approximately 60–70

The nearside-farside (NF) decomposition method developed originally by Fuller for elastic scattering of a nonidentical nucleus-nucleus system was generalized to study the nuclear rainbow pattern in a symmetric or core-symmetric dinuclear system. It has been shown that the projectile-target identity of an identical system implies a symmetric interchange of the nearside and farside components of elastic scattering amplitude around θ _c.m.=90^∘ . A similar interchange appears also in a nonidentical core-symmetric system due to elastic transfer of cluster or nucleon between two identical cores. The analysis of the ^12C+^12C , ^16O+^12C , and ^13C+^12C systems shows how the generalized NF decomposition method reveals the nuclear rainbow pattern in these systems, which can be helpful in probing the real optical potential and nuclear clustering.