We conduct DNA high-resolution melting (HRM) analysis using optofluidic lasers based on a Fabry-Pérot microcavity. Compared to the fluorescence-based HRM, the laser-based HRM has advantages of higher emission intensity for better signal-to-noise ratio and sharper transition for better temperature resolution. In addition, the melting temperature can be lowered by optimizing the laser conditions such as external pump and cavity Q-factor. In this work, we first theoretically analyze the laser-based HRM. Then experiments are performed on three long DNA sequences as model systems, one being 99 bases and the other two being 130 bases long but with different GC contents. We show that the laser-based HRM is able to distinguish the target and the single-base mismatched DNA as long as 130 bases and with nearly 50% GC content. The dependence of laser threshold on the temperature for each DNA sample is first experimentally investigated and by optimizing the external pump, the melting temperature is reduced by more than 10 °C, compared to the fluorescence-based HRM for long DNA sequences up to 130 bases. Finally, we demonstrate an alternative method of using the laser-based HRM for rapid DNA screening that does not exist for the fluorescence-based HRM, in which laser excitation is scanned at a fixed temperature to distinguish the target and the base-mismatched DNA sequences. It is shown that the 130-bases-long DNA with nearly 50% GC content can have as much as 20% difference in the laser threshold and 40% difference in the laser output slope between the target and the single-base mismatched sequences, despite only 0.5 °C difference in their melting temperature, indicating that the laser-excitation-scanning method can also be suitable for long DNA sequences with higher GC content.

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Field-controlled microrobots have attracted extensive research in the biological and medical fields due to the prominent characteristics including high flexibility, small size, strong controllability, remote manipulation, and minimal damage to living organisms. However, the fabrication of these field-controlled microrobots with complex and high-precision 2- or 3-dimensional structures remains challenging. The photopolymerization technology is often chosen to fabricate field-controlled microrobots due to its fast-printing velocity, high accuracy, and high surface quality. This review categorizes the photopolymerization technologies utilized in the fabrication of field-controlled microrobots into stereolithography, digital light processing, and 2-photon polymerization. Furthermore, the photopolymerized microrobots actuated by different field forces and their functions are introduced. Finally, we conclude the future development and potential applications of photopolymerization for the fabrication of field-controlled microrobots.

Feature Selection (FS) is considered as an important preprocessing step in data mining and is used to remove redundant or unrelated features from high-dimensional data. Most optimization algorithms for FS problems are not balanced in search. A hybrid algorithm called nonlinear binary grasshopper whale optimization algorithm (NL-BGWOA) is proposed to solve the problem in this paper. In the proposed method, a new position updating strategy combining the position changes of whales and grasshoppers population is expressed, which optimizes the diversity of searching in the target domain. Ten distinct high-dimensional UCI datasets, the multi-modal Parkinson's speech datasets, and the COVID-19 symptom dataset are used to validate the proposed method. It has been demonstrated that the proposed NL-BGWOA performs well across most of high-dimensional datasets, which shows a high accuracy rate of up to 0.9895. Furthermore, the experimental results on the medical datasets also demonstrate the advantages of the proposed method in actual FS problem, including accuracy, size of feature subsets, and fitness with best values of 0.913, 5.7, and 0.0873, respectively. The results reveal that the proposed NL-BGWOA has comprehensive superiority in solving the FS problem of high-dimensional data.

With the rapid development of new media, the world has been concerned about the significant influence of media communication on the image and status of women, which has led to an increasing number of studies on media and gender. In addition, using new media to promote gender equality has become a new focus. However, due to the enormous amount of information in the new media era, the way of people received information has been greatly influenced. Meanwhile, the way people receive media information has changed from passive and limited choices to active and diverse options. As new media has convenient and efficient communication characteristics, it also brings opportunities and challenges to disseminating gender equality awareness and developing gender equality education. Therefore, this paper uses Lasswell's 5W communication theory as a theoretical framework to analyze the current new media coverage of gender equality in China from five aspects: communicator, message, media, receiver, and communication effect in the communication process, with reviewing existing literature. In addition, the paper focuses on the problems and positive and negative impacts of news reporting. This paper also proposes that the influence of media on gender role attitudes should be viewed dialectically. Finally, after reviewing previous research and the implication of the reports on Chinese new media, this paper proposes recommendations for journalists to promote gender equality, which should be helpful for future researchers and journalists.