Bridging the Granularity Gap for Acoustic Modeling

While Transformer has become the de-facto standard for speech, modeling upon the fine-grained frame-level features remains an open challenge of capturing long-distance dependencies and distributing the attention weights. We propose \textit{Progressive Down-Sampling} (PDS) which gradually compresses the acoustic features into coarser-grained units containing more complete semantic information, like text-level representation. In addition, we develop a representation fusion method to alleviate information loss that occurs inevitably during high compression. In this way, we compress the acoustic features into 1/32 of the initial length while achieving better or comparable performances on the speech recognition task. And as a bonus, it yields inference speedups ranging from 1.20$\times$ to 1.47$\times$. By reducing the modeling burden, we also achieve competitive results when training on the more challenging speech translation task.Comment: ACL 2023 Finding

ROS Reduction Does Not Decrease the Anticancer Efficacy of X-Ray in Two Breast Cancer Cell Lines

Radiotherapy is effective on a large number of cancer types and is one of the most frequently administrated treatments for cancer patients. The anticancer efficacy of X-ray radiotherapy has been frequently correlated with reactive oxygen species (ROS) elevation, which is also a limiting factor for its toxicity on normal tissues. Here, we found that although 4-10 Gy X-rays could significantly reduce cell numbers in both MDA-MB-231 and MCF-7 breast cancer cells, the ROS level changes are less in MCF-7 cells than in MDA-MB-231 cells. Moreover, although both the ROS scavenger N-acetyl-L-cysteine (NAC) and 1 T static magnetic field (SMF) could reduce X-ray-induced ROS elevation, they did not prevent X-ray-induced cell number reduction or cell death increase, which is significantly different from cisplatin. These results demonstrate that although the anticancer efficacy of cisplatin on two breast cancer cell lines is dependent on ROS, the anticancer efficacy of X-ray is not. Moreover, by testing 19 different cell lines, we found that 1 T SMF could effectively reduce ROS levels in multiple cell lines by 10-20%, which encourages further studies to investigate whether SMF could be used as a potential “physical antioxidant” in the future

Magnetic Fields and Reactive Oxygen Species

Reactive oxygen species (ROS) ubiquitously exist in mammalian cells to participate in various cellular signaling pathways. The intracellular ROS levels are dependent on the dynamic balance between ROS generation and elimination. In this review, we summarize reported studies about the influences of magnetic fields (MFs) on ROS levels. Although in most cases, MFs increased ROS levels in human, mouse, rat cells, and tissues, there are also studies showing that ROS levels were decreased or not affected by MFs. Multiple factors could cause these discrepancies, including but not limited to MF type/intensity/frequency, exposure time and assay time-point, as well as different biological samples examined. It will be necessary to investigate the influences of different MFs on ROS in various biological samples systematically and mechanistically, which will be helpful for people to get a more complete understanding about MF-induced biological effects. In addition, reviewing the roles of MFs in ROS modulation may open up new scenarios of MF application, which could be further and more widely adopted into clinical applications, particularly in diseases that ROS have documented pathophysiological roles

The Sustainable Rural Industrial Development under Entrepreneurship and Deep Learning from Digital Empowerment

This paper aims to realize the planning of resource utilization and development of rural industries endowed by digitalization under entrepreneurship. First, the global classic practical experience of digitizing rural industries is studied, and the development model of existing rural industries is captured from the perspective of entrepreneurship. Second, the influencing factors of rural industrial development are extracted, the structure of resource development is analyzed, and a Neural Network (NN) model of industrial development aiming at expected per capita annual income is established. In addition, a Genetic Algorithm (GA) is introduced to learn the weights of influencing factors in the model. The structure of the NN is determined through extensive experiments. Finally, conclusions are drawn through the simulation and experiment of NN and GA. Tourism, infrastructure, and transportation planning have weights of 7.79, 5.6, and 6.4, respectively, and these three sectors should be vigorously developed. In the future, the weight values of these factors can be used for reference, and the development of various aspects can be refined. This paper clarifies the core of industrial development in rural revitalization based on the perspective of entrepreneurship. The problem of how to realize the optimal utilization of resources is solved scientifically and rationally through the mathematical model. The introduction of deep learning algorithm models provides data support for resource allocation and industrial planning in the process of digital empowerment of traditional rural industries, which is of great value and significance for exploring digital models for rural industry development

Novel pH-sensitive cationic lipids with linear ortho ester linkers for gene delivery

In an effort to develop pH-sensitive lipoplexes for efficient gene delivery, we report three novel cationic lipids containing a linear ortho ester linker that conjugates either the headgroup (Type I) or one hydrocarbon chain (Type II) with the rest of the lipid molecule. The cationic lipids carry either an iodide or a chloride counterion. Compared to our previously reported cyclic ortho ester linker, the linear ortho ester linker facilitated the construction of cationic liposomes and lipoplexes with different helper lipids. The chloride counterion not only facilitated the hydration of the lipid films during liposome construction, but also enhanced the hydrolysis of the ortho ester linker in the lipoplexes. After incubation at endosomal pH 5.5, the Type I lipoplexes aggregated and destabilized the endosome-mimicking model liposomes, but not the Type II lipoplexes. The helper lipids (DOPE or cholesterol) of the lipoplexes enhanced the pH-sensitivity of the Type I lipoplexes. In CV-1 cells (monkey kidney fibroblast), the Type I ortho ester-based lipoplexes, especially those with the chloride counterion, significantly improved the gene transfection efficiency, in some cases by more than 100 fold, compared to their pH-insensitive counterparts consisting of DOTAP. The gene transfection efficiency of the ortho ester-based lipoplexes was well correlated with their rate of aggregation and membrane destabilization in response to the endosomal pH 5.5