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Image-based automatic classification of vector mosquitoes has been investigated for decades for its practical applications such as early detection of potential mosquitoes-borne diseases. However, the classification accuracy of previous approaches has never been close to human experts’ and often images of mosquitoes with certain postures and body parts, such as flatbed wings, are required to achieve good classification performance. Deep convolutional neural networks (DCNNs) are state-of-the-art approach to extracting visual features and classifying objects, and, hence, there exists great interest in applying DCNNs for the classification of vector mosquitoes from easy-to-acquire images. In this study, we investigated the capability of state-of-the-art deep learning models in classifying mosquito species having high inter-species similarity and intra-species variations. Since no off-the-shelf dataset was available capturing the variability of typical field-captured mosquitoes, we constructed a dataset with about 3,600 images of 8 mosquito species with various postures and deformation conditions. To further address data scarcity problems, we investigated the feasibility of transferring general features learned from generic dataset to the mosquito classification. Our result demonstrated that more than 97% classification accuracy can be achieved by fine-tuning general features if proper data augmentation techniques are applied together. Further, we analyzed how this high classification accuracy can be achieved by visualizing discriminative regions used by deep learning models. Our results showed that deep learning models exploit morphological features similar to those used by human experts.

Over the past number of years, the power conversion efficiency of perovskite solar cells has remained at 25.5%, reflecting a respectable result for the general incorporation of organometallic trihalide perovskite solar cells. However, perovskite solar cells still suffer from long-term stability issues. Perovskite decomposes upon exposure to moisture, thermal, and UV-A light. Studies related to this context have remained ongoing. Recently, research was mainly conducted on the stability of perovskite against non-radiative recombination. This study improved a critical instability in perovskite solar cells arising from non-radiative recombination and UV-A light using a passivation layer. The passivation layer comprised a polyaniline (PANI) polymer as an interfacial modifier inserted between the active layer and the electron transport layer. Accordingly, the UV-A light did not reach the active layer and confined the Pb 2+ ions at PANI passivation layer. This study optimized the perovskite solar cells by controlling the concentration, thickness and drying conditions of the PANI passivation layer. As a result, the efficiency of the perovskite solar cell was achieved 15.1% and showed over 84% maintain in efficiency in the ambient air for one month using the 65 nm PANI passivation layer.

Bio-based production of many chemicals is not yet possible due to the unknown biosynthetic pathways. Here, we report a strategy combining retrobiosynthesis and precursor selection step to design biosynthetic pathways for multiple short-chain primary amines (SCPAs) that have a wide range of applications in chemical industries. Using direct precursors of 15 target SCPAs determined by the above strategy, Streptomyces viridifaciens vlmD encoding valine decarboxylase is examined as a proof-of-concept promiscuous enzyme both in vitro and in vivo for generating SCPAs from their precursors. Escherichia coli expressing the heterologous vlmD produces 10 SCPAs by feeding their direct precursors. Furthermore, metabolically engineered E. coli strains are developed to produce representative SCPAs from glucose, including the one producing 10.67 g L −1 of iso -butylamine by fed-batch culture. This study presents the strategy of systematically designing biosynthetic pathways for the production of a group of related chemicals as demonstrated by multiple SCPAs as examples. Short-chain primary amines (SCPAs) are industrially important compounds that are commonly produced under harsh synthetic conditions. Here, the authors report a combination of retrobiosynthesis and precursor selection step for design of biosynthetic pathways leading to production of SCPAs, using valine decarboxylase-expressing Escherichia coli strains.

Genome-scale metabolic network model (GEM) is a fundamental framework in systems metabolic engineering. GEM is built upon extensive experimental data and literature information on gene annotation and function, metabolites and enzymes so that it contains all known metabolic reactions within an organism. Constraint-based analysis of GEM enables the identification of phenotypic properties of an organism and hypothesis-driven engineering of cellular functions to achieve objectives. Along with the advances in omics, high-throughput technology and computational algorithms, the scope and applications of GEM have substantially expanded. In particular, various computational algorithms have been developed to predict beneficial gene deletion and amplification targets and used to guide the strain development process for the efficient production of industrially important chemicals. Furthermore, an Escherichia coli GEM was integrated with a pathway prediction algorithm and used to evaluate all possible routes for the production of a list of commodity chemicals in E. coli. Combined with the wealth of experimental data produced by high-throughput techniques, much effort has been exerted to add more biological contexts into GEM through the integration of omics data and regulatory network information for the mechanistic understanding and improved prediction capabilities. In this paper, we review the recent developments and applications of GEM focusing on the GEM-based computational algorithms available for microbial metabolic engineering.

Magnetic fields are widely utilized for remote control of magnetic objects, with various actuation systems developed for manipulating miniature robots in research and biomedical applications. When designing a manipulation system providing a uniform magnetic field, it is also important to consider both the accessibility of the workspace and the integration of imaging tools. This article presents an electromagnetic coil system that manipulates magnetic objects within a 3D space, enhancing the magnetic field in an upward orientation. The system includes eight metal‐core coils arranged hemispherically to ensure unimpeded access to the workspace and imaging tools, along with two air‐core coils. Easier control and repeatability of the magnetic field are achieved using two joysticks and sequential programming. The versatility of the system is demonstrated by using it to manipulate a magnetic guidewire and to guide micromagnets to various targets. Additionally, using this system, oscillating magnetic fields effectively control swarms of magnetic nanoparticles, enabling operations such as dispersion, assembly, and ribbon‐like shape formation. Furthermore, the manipulation of cell‐based microrobots (cell‐bots) showcases the system's capability to handle single and multiple cell‐bots, facilitating their collection while preserving cell viability. These experiments underscore the system's potential for fundamental biomedical research and various applications. An electromagnetic manipulation system enhances magnetic field strength in the Z‐direction for 3D control of microrobots and nanoparticles. Featuring eight metal‐core coils and two air‐core coils arranged hemispherically, it ensures unimpeded workspace access and integrates imaging tools. Quantitative experiments demonstrate its efficacy in guiding micromagnets, controlling nanoparticles, and manipulating cell‐based microrobots, underscoring its potential for biomedical research.

High-power transmitters for active SONAR (Sound Navigation and Ranging) individually drive acoustic transducers for a variety of applications. The acoustic transducer has largely varying equivalent impedance, and thus being damaged by an active power higher than the rated value. So, this paper proposes a new controller that satisfies such necessary requirements. The proposed controller is implemented using Second-Order Generalized Integrator-Frequency Locked Loop (SOGI-FLL), and thus controlling real-time peak value of output voltage, and active power for power limit control even under sudden load change. It is composed of the voltage control mode loop and active power limit control mode loop, and their mode change is smooth and easy. Through 7 experiments, it is verified that the proposed controller operates properly even in the worst load conditions such as load change, control area change, and frequency modulation.

Research on layered two-dimensional (2D) materials is at the forefront of material science. Because 2D materialshave variousplate shapes, there is a great deal of research on the layer-by-layer-type junction structure. In this study, we designed a composite catalyst with a dimension lower than two dimensions and with catalysts that canbe combined so that the band structures can be designed to suit various applications and cover for each other’s disadvantages. Among transition metal dichalcogenides, 1T-WS2 can be a promising catalytic material because of its unique electrical properties. Black phosphorus with properly controlled surface oxidation can act as a redox functional group. We synthesized black phosphorus that was properly surface oxidized by oxygen plasma treatment and made a catalyst for water quality improvement through composite with 1T-WS2. This photocatalytic activity was highly efficient such that the reaction rate constant k was 10.31 × 10−2 min−1. In addition, a high-concentration methylene blue solution (20 ppm) was rapidly decomposed after more than 10 cycles and showed photo stability. Designing and fabricating bandgap energy-matching nanocomposite photocatalysts could provide a fundamental direction in solving the future’s clean energy problem.

The high power transmitter of active sonar for underwater communication regularly switches between transmit and receive modes. The matching transformer in the high-power transmitter has significant power loss only during the transmit mode. The conventional design of the transformer, considering only the handling power of the transmit mode, may result in a bulky over-spec transformer. In a long operating period, the matching transformer has high stress due to a large temperature ripple at the hot spot of the winding conductor insulation, resulting in no guarantee of the transformer's lifespan. Hence, this paper proposes a new transformer design method considering the operating duty and lifespan of a high-power transmitter for active sonar. The proposed design method consists of initial design, verification, and redesign. It can guarantee the lifespan of a transformer at the design stage by utilizing the aging acceleration factor F AA and equivalent aging acceleration factor F EQA . The effectiveness of the proposed design method is verified by manufacturing a transformer and performing related simulations.

Targeted stem cell delivery utilizing a magnetic actuation system is an emerging technology in stem cell engineering that efficiently targets stem cells in specific areas in vitro. However, integrating precise magnetic control systems with selective neural differentiation has not yet been widely considered for building successful neural networks. Challenges arise in creating targeted functional neuronal networks, largely due to difficulties in simultaneously controlling the positions of stem cells and selectively stimulating their differentiation. These challenges often result in suboptimal differentiation rates and abnormalities in transplanted neural stem cells. In contrast, ultrasound stimulation has superior tissue penetration and focusing capability, and represents a promising noninvasive neural stimulation technique capable of modulating neural activity and promoting selective differentiation into neuronal stem cells. In this study, we introduce a method for targeted neural differentiation using localized ultrasonic stimulation with a piezoelectric micromachined ultrasound transducer (pMUT) array. Differentiation was assessed quantitatively by monitoring neurite outgrowth as the ultrasound intensity was increased. The neurite length of cells ultrasonically stimulated for 40 min was found to have increased, compared to the non-stimulated group (119.9 ± 34.3 μm vs. 63.2 ± 17.3 μm, respectively). Targeted differentiation was confirmed by measuring neurite lengths, where selective ultrasound stimulation induced differentiation in cells that were precisely delivered via an electromagnetic system. Magnetic cell-based robots reaching the area of localized ultrasound stimulation were confirmed to have enhanced differentiation. This research demonstrated the potential of the combination of precise stem cell delivery with selective neural differentiation to establish functional neural networks.

A parametric array (PA) loudspeaker is a highly directional audio source that might grant one's convenience if it is used with mobile devices. However, conventional PA loudspeakers is almost impossible to apply in mobile devices using a battery because of the large power consumption and large device size. In this study, a PA loudspeaker system (PALS) was fabricated and evaluated to show that those difficulties could be overcome to apply it to mobile devices. In order to construct a PALS for demonstration, a power amplifier and signal-processing unit should also be properly designed and built. The PA source transducer should also be designed and built for a mobile device application. These components were integrated into a single PALS. The PALS generated a 125-dB primary wave and 62 dB of a different frequency wave (DFW) through the PA at 0.45 m in a 3 m × 3 m × 2 m semi-anechoic chamber. We confirmed that the half-power bandwidth (HPBW) formed a 6° beam at 83 kHz of DFW and 90 kHz of the primary wave (PW), and the HPBW formed a 7.3° beam at 5 kHz of DFW and a 7.1° beam at 10 kHz of DFW, respectively. Lastly, the power required was 6.65 W without a matching circuit, and 3.25 W with such a circuit.