A highly sensitive photoelectrochemical (PEC) biosensor without external bias was developed in this study. The biosensor was configured with a p-Cu2O and n-ZnO heterostructure. Hexamethylenetetramine ...(HMTA) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) was used to improve the crystal structure of Cu2O and ZnO and reduce the defects in the Cu2O/ZnO interface. This fabrication method provided the highly crystallized Cu2O/ZnO structure with excellent electrical property and photoresponse in visible light. The structure was applied to a biosensor for detecting two different cancerous levels of esophageal cells, namely, OE21 and OE21-1, with a high gain in photocurrent (5.8 and 6.2 times, respectively) and a low detection limit (3000 cells in 50 μL). We believe that such a p-n heterojunction PEC biosensor could advance biosensor development and provide a promising candidate for biomedical applications.
Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision ...medicine and drug discovery. In this study, we performed comparative studies between deep neural networks (DNN) and other ligand-based virtual screening (LBVS) methods to demonstrate that DNN and random forest (RF) were superior in hit prediction efficiency. By using DNN, several triple-negative breast cancer (TNBC) inhibitors were identified as potent hits from a screening of an in-house database of 165,000 compounds. In broadening the application of this method, we harnessed the predictive properties of trained model in the discovery of G protein-coupled receptor (GPCR) agonist, by which computational structure-based design of molecules could be greatly hindered by lack of structural information. Notably, a potent (~ 500 nM) mu-opioid receptor (MOR) agonist was identified as a hit from a small-size training set of 63 compounds. Our results show that DNN could be an efficient module in hit prediction and provide experimental evidence that machine learning could identify potent hits in silico from a limited training set.
This article presents a novel static random access memory computing-in-memory (SRAM-CIM) structure designed for high-precision multiply-and-accumulate (MAC) operations with high energy efficiency ...(EF), high readout accuracy, and short compute latency. The proposed device employs 1) a time-domain incremental-accumulation (TDIA) scheme to enable high-accumulation MAC operations while maintaining a large signal margin across MAC values (MACVs), 2) a dynamic differential-reference (D2REF) scheme based on software-hardware co-design to reduce read energy consumption, and 3) a low-dMACV-aware recursive time-to-digital converter (LMAR-TDC) for implementation with the D2REF scheme to further suppress readout energy consumption. A 28 nm 1 Mb SRAM-CIM macro fabricated using foundry-provided compact 6T-SRAM cells achieved EF of 39.31 TOPS/W and compute latency of 6.6 ns for 8b-MAC operations with 64 accumulations per cycle and near-full output precision (22b).
This study explores how the MNE's parent can effectively benefit from the subsidiary reverse technology transfer, and how the institutional distance may influence it. We found that the MNE's global ...R&D intensity led to positive subsidiary reverse technology transfer in a linear way, while the MNE's global R&D diversity in geographical scope imposed a curvilinear effect on the subsidiary reverse technology transfer. Specifically, the curvilinear relationship of the later was negatively moderated by institutional distance. This study makes contributions by enriching the knowledge on the antecedents and performance consequence of the subsidiary reverse technology transfer from the MNE parent's perspective.
This study investigates how host-country governance and investment environment may impact multinational corporations' (MNCs') selection of innovative partners, an underexplored topic in existing IB ...literature. Drawing on the transaction cost perspective and a behavioral theory of the firm, we analyzed data from 1980 nonservice-sector MNCs in Taiwan (2007-2012), totaling 4921 observations. Results show that MNCs' satisfaction with host-country governance and investment conditions influences their technology sourcing and innovative partner selection. Higher governance satisfaction leads MNCs to choose partners within their value chain, while high investment environment satisfaction prompts the selection of third-party consultants or research centers as partners. Moreover, underperforming MNCs are less likely to source technology from their parent firms, preferring external consultants or research centers during underperforming periods. This research provides novel insights into MNCs' local partner selection and practical implications.
Abstract Despite the recognized importance of subsidiary reverse knowledge transfer (RKT) for multinational enterprises' (MNEs') competitive advantages, little is understood about how host country ...policy uncertainty may affect it. This study, based on absorptive capacity and resource dependence theories and utilizing the global economic policy uncertainty (GEPU) index, examines 1565 firm‐year observations of Taiwanese MNE parent–subsidiary activities. Findings suggest that GEPU indirectly undermines subsidiary RKT benefit by reducing MNEs' global R&D intensity and geographical R&D diversity. Notably, this effect is mitigated when MNEs choose joint venture entry modes. This study enriches international business literature by elucidating the intricate relationships between the host country policy uncertainty, MNE strategies, and subsidiary RKT outcomes, thus contributing to a deeper scholarly understanding in the RKT domain.
Advanced artificial intelligence edge devices are expected to support floating-point (FP) multiply and accumulation operations while ensuring high energy efficiency and high inference accuracy. This ...work presents an FP compute-in-memory (CIM) macro that exploits the advantages of computing in the time, digital, and analog-voltage domain for high energy efficiency and accuracy. This work employs: 1) a hybrid-domain macrostructure to enable the computation of both the exponent and mantissa within the same CIM macro; 2) a time-domain computing scheme for energy-efficient exponent computation; 3) a product-exponent-based input-mantissa alignment scheme to enable the accumulation of the product mantissa in the same column; and 4) a place-value-dependent digital-analog-hybrid computing scheme to enable energy-efficient mantissa computations of sufficient accuracy. A 22-nm 832-kB FP-CIM macro fabricated using foundry-provided compact 6T-static random access memory (SRAM) cells achieved a high energy efficiency of 72.14 tera-floating-point operations per second (TFLOPS)/W while performing FP-multiply-and-accumulate (MAC) operations involving BF16-input, BF16-weight, FP32-output, and 128 accumulations.
Effect of high intensity ultrasound (HIUS) treatment on the rheological property and microstructure of tofu made from yellow and black soybeans was investigated. Raw soymilk was either heated at 95°C ...for 10min, or HIUS treated at 25 and 50°C for 5, 15, and 30min, and then was coagulated by adding Glucono-δ-lactone (GDL) to produce tofu. Results showed that HIUS denatured the soy protein and was confirmed by the changes in protein surface hydrophobicity. The HIUS-treated soymilk and the heat-treated soymilk expressed different gelation behaviors, which led to distinct rheological property and microstructure in the final products. The network of tofu prepared with HIUS-treated soymilk was constructed by thicker strands in a loose arrangement. The rheological property and microstructure of HIUS-treated tofu can be modified by changing the sonication time and temperature. The tofu made form soymilk with HIUS at 25°C for 15min gave the best rheological property.
Tofu is a widely accepted and commonly manufactured soy product in Asia. The worldwide tofu consumption is increasing due to its unique texture and health benefits. However, the thermal process of soymilk during tofu making is time and energy consuming. HIUS is a more efficient and environment-friendly technology that can be commercially applied as an energy and labor saving alternative to the conventional thermal treatment. The rheological property and microstructure are two important parameters for the gel texture evaluation. This research paper presents a comparative study between soymilk treated by heating and by HIUS using yellow soybean and black soybean to produce tofu with unique rheological property. Finding in this research gave the primary knowledge for further application of HIUS on tofu processing.
•Ultrasonic-treated tofu had the rheological property different from the heat-treated tofu.•The rheological property of tofu were affected by the sonication time and temperature.•Ultrasonics is a time-effective method for tofu making as compared to current technology.
Abstract
Our goal is to establish a remote-plasma-based aerosol-assisted atmospheric-pressure plasma deposition (RAAPD) system for depositing protein–plasma-polymerized-ethylene coatings. The method ...of RAAPD is using plasma to polymerize ethylene and add protein aerosol at downstream region to coat protein–plasma-polymerized-ethylene on substrate. We investigated effects of different mixing, mesh, deposition distance, gas flow, voltage, and frequency. Results showed that downstream-mixing method reduced heat effects on protein. The optimal coating was achieved when using mesh, at a close deposition distance, with high flow rate of protein aerosol, and under high voltage. Compared with current methods, impacts of RAAPD include reducing effects of plasma generated heat, reactive species, and UV on protein, and deposition will not be limited by electrode area and substrate material.
Egg is a regularly consumed food item. Currently, chlorinated water washing is the most common practice used to disinfect eggs, but this process has a negative environmental impact. A new physical ...technique, plasma-activated water (PAW), has been demonstrated to possess effective antibacterial activities without long-term chemical residue. In this study, air PAW was used to inactivate Salmonella enterica serovar Enteritidis on shell eggs. Different combinations of activation parameters, including water sources (reverse osmotic (RO) water, tap water), power (40 W, 50 W, 60 W) and activation time (10 min, 20 min, 30 min), were evaluated. The oxidation–reduction potential (ORP) and pH values of each combination were measured, and their antibacterial activity was tested in a bacterial suspension. Higher antibacterial activities, higher ORP values, and lower pH values were obtained with higher power, longer activation time, and lower water hardness. The antibacterial activities of PAW decreased rapidly by increasing the storage time both at room and refrigeration temperatures. Afterwards, RO water was pre-activated for 20 min at 60 W, and then the eggs inoculated with S. enteritidis were placed into PAW for 30 s, 60 s, 90 s, or 120 s with a plasma on-site treatment in the water. More than a 4 log reduction was obtained with 60-s and 120-s treatments. The results showed that the freshness indexes of the eggs treated with PAW were similar to those of the untreated controls and better than those of the eggs treated with commercial processes. In addition, observation under a scanning electron microscope also showed less surface damage of the cuticle on the PAW-treated eggs than on the commercially treated eggs. The results of this study indicate that PAW could be an effective antibacterial agent with less damage to the freshness of shell eggs than commercial methods.
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