National Taiwan University of Science and Technology

Wu J.Y., Chen C., Wu C., Lin G.

Huang M., Luo Y., He J., Zhen L., Wu L., Zhang Y.

Science communication conducted through mobile devices and mobile applications is an efficient and widespread phenomenon that requires communicators and design practitioners to further develop suitable design elements and strategies for such platforms. The effective application of multimodal or multisensory design in interfaces provides users with rich experiences. However, there is a lack of guiding recommendations for user interface design in the citizen science community. This study investigated factors affecting users' perceptions and behavioral intentions toward multimodal scientific communication interface designs and identified the optimal combinations of such factors for such designs. Through a focus group, we defined three design dimensions of a science communication interface: visual, auditory, and haptic. An online experiment involving 916 participants was then conducted and integrated the technology acceptance model, expectation–confirmation model, and Taguchi method to examine the hierarchical combinations with the greatest influence in each dimension. The results indicated that interface design combinations primarily focusing on visual elements, with auditory and haptic as secondary elements, can serve as effective tools for science communication. Moreover, layout, color tones, vibration intensity, and sound volume significantly affected users' perceptions and behavioral intentions. As one of the few studies using the Taguchi method to explore the design of science communication interfaces, the present findings enrich the multimodal theory from the perspectives of design and communication, highlighting its value in science communication. This paper simultaneously provides insights into how to select and combine multimodal design elements in science communication interfaces, demonstrating the potential of such designs to affect a user perception, satisfaction, confirmation, and continued usage intention.

Lee C., Zhuo G.

Laysandra L., Bazliah D., Njotoprajitno A., Chen K., Chiu Y.

Hsiao H., Wang K.

Hussein M.A., Abbas A., Abdelnaby M.M., Huang S., Azeem M.A.

Hydrogen storage materials are critical for sustainable energy applications. Magnesium is a promising material for hydrogen storage due to its high volumetric and gravimetric hydrogen storage capacities. However, its application in fuel cells is hindered by slow hydrogen sorption kinetics. This study aims to investigate the hydrogen absorption of a commercial AM60 alloy catalyzed by Ti and multiwalled carbon nanotubes additives, as well as the microstructural changes induced by high‐energy ball milling (HEBM). The results show that the HEBM of the AM60 alloy reduces the particle size to 22 μm, introducing microvoids and porosity between the particles, which increase the total pore volume and hydrogen absorption capacity from 1.5 to 4 wt%. Catalyzing the AM60 alloy with a 5 wt% Ti increases absorption to 4.35 wt%. The AM60‐5 wt% MWCNT sample shows higher surface area of 34 m2 g−1, highest hydrogen absorption capacity of 6.2 wt%, and the fastest hydrogen absorption rate. The novelty of this study lies in demonstrating the synergistic effects of HEBM and MWCNT additives, thereby establishing a practical approach for optimizing magnesium‐based materials for hydrogen storage.

Chang C., Adi P., Mulyani R., Lin C., Listyaningrum R.S., Santoso S.P., Gavahian M., Hsieh C.

This research investigates potential mechanisms of novel magnetic field (MF) treatments in inhibiting cell-wall-degrading enzymes, aiming to reduce weight loss and preserve the post-harvest quality of tomatoes (Solanum lycopersicum L.) as a climacteric fruit. The optimization of the processing parameters, including MF intensity (1, 2, 3 mT), frequency (0, 50, 100 Hz), and duration (10, 20, 30 min), was accomplished by applying an orthogonal array design. In particular, the investigation delved into the underlying mechanisms by which MF impedes the activity of tissue-degrading enzymes, such as pectin esterase (PE), polygalacturonase (PG), and cellulase (Cx), during the storage period. The results showed that MF treatment delayed the increase in soluble solids by 1.5 times and reduced titratable acidity by 1.2 times. The optimal treatment conditions—2 mT, 50 Hz, and 10 min—achieved the most significant inhibition of weight loss (4.22%) and maintained tissue integrity for up to 21 days. Optimized MF significantly suppressed enzyme activity, with PE activity reduced by 1.5 times, PG by 2.8 times, and Cx by 2.5 times. Also, cross-sectional images and external appearance demonstrated that MF-treated tomatoes retained their internal tissue structure throughout the extended storage period. These findings suggest that MF treatments can effectively suppress the key enzymes responsible for tissue degradation, ultimately delaying weight loss and softening, preserving post-harvest quality, and contributing to sustainable food production and zero waste.

Cho C., Yeh Y., Veeramuthu L., Kuo C., Tung K., Chiang W.

AbstractControlling the redox ability is crucial for optimizing catalytic processes in clean energy, environmental protection, and CO2 reduction, as it directly influences the reaction efficiency and electron transfer rates, driving sustainable and effective outcomes. Here, we report the plasma‐electrified synthesis of composition‐controlled FeAu bimetallic nanoparticles, specifically engineered to enhance the redox catalytic performance through precise tuning of their chemical states. Utilizing atmospheric‐pressure microplasmas, FeAu nanoparticles were synthesized under ambient conditions without the need for reducing agents or organic solvents, thereby providing a green and sustainable approach. The catalytic activity of the FeAu nanoparticles was significantly influenced by the oxidation states of Au (Au0, Au+, and Au3+), which were carefully modulated by adjusting the precursor concentration. This precise tuning directly affects the oxidation‐reduction potential (ORP) of the nanoparticles, driving their superior degradation performance. The FeAu‐1.52 sample exhibited the highest normalized rate constant (k=46.3 s−1 g−1), attributed to an optimal Au+/Au0 ratio that facilitates efficient electron transfer and redox cycling during the catalytic reduction of 4‐NP to 4‐aminophenol (4‐AP). Beyond 4‐NP, the FeAu nanoparticles demonstrated robust catalytic degradation of multiple dye pollutants, including Congo Red, Rhodamine B, Methyl Blue, and Methylene Blue, showing their versatility and potential for industrial wastewater treatment. This study elucidates the critical role of chemical state tuning in determining redox performance and presents a promising nanotechnology platform for sustainable environmental remediation.

Chen Y., Jhong S., Lin H., Wu Y.

Lin C., Lin D., Chang M.

ABSTRACTA low‐cost, low‐profile, high‐performance antenna array based on a 4×4 series‐fed patch with elliptical slots is presented in this article for fifth‐generation millimeter‐wave communications (5G mmWave). The antenna array can be manufactured easily on a two‐layer printed circuit board because of its simple design and lack of complex structures. It is designed for the Ka‐band (n257 band) with an impedance bandwidth of 3.1 GHz, covering the range from 26.1 GHz to 29.2 GHz. There is a fractional bandwidth of about 11.2%, several times greater than the fractional bandwidth of a series‐fed antenna. Within the impedance bandwidth, the radiation gain exceeds 11 dBi, with a maximum gain of 18.25 dBi. The radiation efficiency reaches an impressive 94% and the aperture efficiency reaches 44.6%. The isolation between the four excitation ports is less than −30 dB. Additionally, the 70% impedance bandwidth features right‐hand elliptical polarization with a 3:1 axial ratio. It also has an excellent beam steering range (theta angle: ). The following section will provide a detailed description of the antenna array and an analysis of the resonance frequencies. Further, the array antenna is combined with the Butler matrix network to form a beamforming function. Finally, the measured results agree well with the simulation results. This low‐cost, low‐profile, high‐performance antenna array will promote the popularization of 5G mmWave communications, which will be widely used worldwide.

Bui T., Lee P., Liobe J., Barzdenas V., Udris D.

Yu I., Guo J., Lin W., Fang J.

Kitaw S.L., Ahmed Y.W., Candra A., Wu T., Anley B.E., Chen Y., Cheng Y., Chen K., Thammaniphit C., Hsu C.C., Wu Y.T., Khan M.H., Tsai H.

This study presents the synthesis and characterization of Ag/Au nanostar alloys. A 75:25 Ag/Au nanostar alloy achieved the highest SERS sensitivity for rhodamine 6G detection, emphasizing its potential for sensing applications.

Nachimuthu S., Xie G., Jiang J.

Despite significant progress in low-temperature methane (CH

Wang C., Firdi N.P., Chu T., Faiz M.F., Iqbal M.Z., Li Y., Yang B., Mallya M., Bashashati A., Li F., Wang H., Lu M., Xia Y., Chao T.

Ovarian cancer, predominantly epithelial ovarian cancer (EOC), is a global health concern due to its high mortality rate. Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian cancer, more than 70% of advanced patients are with recurrent cancer and disease. Bevacizumab is a humanized monoclonal antibody, which blocks VEGF signaling in cancer, inhibits angiogenesis and causes tumor shrinkage, and has been recently approved by the FDA as a monotherapy for advanced ovarian cancer in combination with chemotherapy. Unfortunately, Bevacizumab may also induce harmful adverse effects, such as hypertension, bleeding, arterial thromboembolism, poor wound healing and gastrointestinal perforation. Given the expensive cost and unwanted toxicities, there is an urgent need for predictive methods to identify who could benefit from bevacizumab. Of the 18 (approved) requests from 5 countries, 6 teams using 284 whole section WSIs for training to develop fully automated systems submitted their predictions on a test set of 180 tissue core images, with the corresponding ground truth labels kept private. This paper summarizes the 5 qualified methods successfully submitted to the international challenge of automated prediction of treatment effectiveness in ovarian cancer using the histopathologic images (ATEC23) held at the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) in 2023 and evaluates the methods in comparison with 5 state of the art deep learning approaches. This study further assesses the effectiveness of the presented prediction models as indicators for patient selection utilizing both Cox proportional hazards analysis and Kaplan-Meier survival analysis. A robust and cost-effective deep learning pipeline for digital histopathology tasks has become a necessity within the context of the medical community. This challenge highlights the limitations of current MIL methods, particularly within the context of prognosis-based classification tasks, and the importance of DCNNs like inception that has nonlinear convolutional modules at various resolutions to facilitate processing the data in multiple resolutions, which is a key feature required for pathology related prediction tasks. This further suggests the use of feature reuse at various scales to improve models for future research directions. In particular, this paper releases the labels of the testing set and provides applications for future research directions in precision oncology to predict ovarian cancer treatment effectiveness and facilitate patient selection via histopathological images.