Monopolar Acoustic Pulses in Histotripsy and Other Applications

Monopolar acoustic pulses decouple the compressional (positive) and rarefactional (negative) half-cycles within acoustic bursts and could be crucial for many applications. In this work, a frequency compounding transducer was designed and built to generate pseudo-monopolar peak positive pulses and peak negative pulses. The transducer consisted of 113 individual piezoelectric elements with 7 various resonant frequencies. Focal waveforms of both peak positive pulses and peak negative pulses were measured. Different pulsing sequences were then designed and applied for studying several aspects of histotripsy. First off, the use of pseudo-monopolar pulses with variable, controllable delays could achieve a new technique called “enhanced shock scattering histotripsy”. The shock scattering process in normal shock scattering histotripsy might not be optimal because it involves a complex interaction between positive and negative phases within an acoustic pulse to initiate a robust cavitation bubble cloud. With enhanced shock scattering histotripsy, we aimed to generate cavitation bubble clouds by shock scattering with mostly peak positive pulses. Observations of bubble clouds generated by this technique were achieved by using high-speed photography. For example, 16 successive bubble clouds were generated by 16 peak positive pulses following an initial peak negative pulse. The feasibility of the technique was tested by generating a precise lesion in a red-blood-cell phantom. Additional efforts were made to investigate the cavitation thresholds at pressure-release interfaces by applying pseudo-monopolar peak positive pulses with various pressure levels. Different interface models were explored. Threshold curves showed that the thresholds at interfaces were less than 20 MPa negative, which was lower than the intrinsic threshold in free water. They also varied with spatial locations for certain materials. Another potential application of high amplitude monopolar pulses is ultrasonic neural stimulation. Preliminary work was done where we hypothesized the generation of de-modulated low frequency currents from simultaneous ultrasound and high frequency, oscillating magnetic fields. Varying the two frequencies by a few kHz could produce a de-modulated, difference-frequency current similar to that generated by Transcranial Magnetic Stimulation. The pressure field generated by a 500 kHz ultrasound transducer and the resultant current density magnitude distribution in the presence of a magnetic field were simulated. Experimentally, with same conditions, currents of 0.34 μA/cm^2 at 4 kHz and 0.39 μA/cm^2 at 3 kHz were detected, which matched the simulation results.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149796/1/yigeli_1.pd

Contrastive Learning enhanced Author-Style Headline Generation

Headline generation is a task of generating an appropriate headline for a given article, which can be further used for machine-aided writing or enhancing the click-through ratio. Current works only use the article itself in the generation, but have not taken the writing style of headlines into consideration. In this paper, we propose a novel Seq2Seq model called CLH3G (Contrastive Learning enhanced Historical Headlines based Headline Generation) which can use the historical headlines of the articles that the author wrote in the past to improve the headline generation of current articles. By taking historical headlines into account, we can integrate the stylistic features of the author into our model, and generate a headline not only appropriate for the article, but also consistent with the author's style. In order to efficiently learn the stylistic features of the author, we further introduce a contrastive learning based auxiliary task for the encoder of our model. Besides, we propose two methods to use the learned stylistic features to guide both the pointer and the decoder during the generation. Experimental results show that historical headlines of the same user can improve the headline generation significantly, and both the contrastive learning module and the two style features fusion methods can further boost the performance.Comment: Accepted at EMNLP 202

The impact of virtual tour on tourism: the role of virtual tourism in COVID-19 and the impact on on-site tourism

Purpose- The aim of this thesis is to investigate the relationship between virtual tourism experiences, virtual tourism revisit intentions and field tourism as influenced by the COVID-19. To aid in optimizing virtual tourism technology, understanding the present elements impacting traveler adoption of virtual tourism experience technology is essential. In addition, to investigate the extrinsic and intrinsic factors influencing the acceptance of virtual tourism technology by users. Finally, exploring the impact of virtual tourism technology under the epidemic on users' attitudes towards switching to field tourism is helpful to provide some insights into the recovery of a depressed tourism industry. Design and Methodology- This paper adds risk perception to the dual model of technology acceptance and the theory of planned behaviour and applies the new model to the study of behaviour and attitudes towards virtual travel. Considering the current regulations on social distance and transportation constraints, this study will distribute questionnaires using high-traffic social media platforms to acquire a rapid sample that fits the requirements. 330 people participated anonymously in this survey, of which a total of 309 valid data were obtained. The data obtained were processed and analysed using SPSS software. Findings- For this investigation, a total of 309 valid data were collected. The results of the study show that perceived risk, subjective norms, perceived usefulness and perceived enjoyment combine to influence users' acceptance of virtual tourism technology. Surprisingly, virtual consumers are less concerned with the ease of use and more concerned with the usefulness and enjoyment of the technology. Furthermore, the integrated virtual tourism experience effects not only the virtual tourist's intention to return to virtual tourism, but also the virtual tourist's attitude toward exploring the destination. Research limitation- The validity of the data in this study is limited by the study design and sample size. Because the underage and older age groups' virtual travel experiences were not thoroughly evaluated, and no study on specific virtual travel locations was undertaken, the results produced may be somewhat biased. In this regard, it is advised that future studies continue to investigate the aspects that impact the virtual tourist experience for different age groups, as well as that virtual tourism behavior be examined for different risk categories. Finally, due to the specific context of COVID-19, the current study is somewhat time-sensitive and the current findings may not be applicable to post-epidemic virtual tourism research, so it is strongly recommended that future researchers continue to explore the transformation of the relationship between virtual tourism and field tourism in terms of intrinsic factors. Originality- This paper contributes to existing research in the field of virtual tourism. In the context of the COVID-19 reality, this study extends TAM and TPB, and theoretically verifies that perceived usefulness, perceived enjoyment, subjective norms, and risk perception all have significant effects on the acceptance of virtual tourism technology. This broadens the scope of application of TPB and TAM to a certain extent and enriches the study of virtual tourists' behaviour. Given the rapid advancement of digital technology and the existing virus, research into the variables influencing the acceptability of virtual tourism technology and its role in field tourism is a worthwhile and long-term study that can be undertaken to enhance tourist growth. This study's conclusions will be useful to both present academics and relevant practitioners in the field of tourism

Theory of fractional hybrid differential equations

AbstractIn this paper, we develop the theory of fractional hybrid differential equations involving Riemann–Liouville differential operators of order 0<q<1. An existence theorem for fractional hybrid differential equations is proved under mixed Lipschitz and Carathéodory conditions. Some fundamental fractional differential inequalities are also established which are utilized to prove the existence of extremal solutions. Necessary tools are considered and the comparison principle is proved which will be useful for further study of qualitative behavior of solutions

Reconstructive Neuron Pruning for Backdoor Defense

Deep neural networks (DNNs) have been found to be vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications. While existing defense methods have demonstrated promising results, it is still not clear how to effectively remove backdoor-associated neurons in backdoored DNNs. In this paper, we propose a novel defense called \emph{Reconstructive Neuron Pruning} (RNP) to expose and prune backdoor neurons via an unlearning and then recovering process. Specifically, RNP first unlearns the neurons by maximizing the model's error on a small subset of clean samples and then recovers the neurons by minimizing the model's error on the same data. In RNP, unlearning is operated at the neuron level while recovering is operated at the filter level, forming an asymmetric reconstructive learning procedure. We show that such an asymmetric process on only a few clean samples can effectively expose and prune the backdoor neurons implanted by a wide range of attacks, achieving a new state-of-the-art defense performance. Moreover, the unlearned model at the intermediate step of our RNP can be directly used to improve other backdoor defense tasks including backdoor removal, trigger recovery, backdoor label detection, and backdoor sample detection. Code is available at \url{https://github.com/bboylyg/RNP}.Comment: Accepted by ICML2

Self-supervised Heterogeneous Graph Variational Autoencoders

Heterogeneous Information Networks (HINs), which consist of various types of nodes and edges, have recently demonstrated excellent performance in graph mining. However, most existing heterogeneous graph neural networks (HGNNs) ignore the problems of missing attributes, inaccurate attributes and scarce labels for nodes, which limits their expressiveness. In this paper, we propose a generative self-supervised model SHAVA to address these issues simultaneously. Specifically, SHAVA first initializes all the nodes in the graph with a low-dimensional representation matrix. After that, based on the variational graph autoencoder framework, SHAVA learns both node-level and attribute-level embeddings in the encoder, which can provide fine-grained semantic information to construct node attributes. In the decoder, SHAVA reconstructs both links and attributes. Instead of directly reconstructing raw features for attributed nodes, SHAVA generates the initial low-dimensional representation matrix for all the nodes, based on which raw features of attributed nodes are further reconstructed to leverage accurate attributes. In this way, SHAVA can not only complete informative features for non-attributed nodes, but rectify inaccurate ones for attributed nodes. Finally, we conduct extensive experiments to show the superiority of SHAVA in tackling HINs with missing and inaccurate attributes

Transcriptome and digital gene expression analysis reveal immune responses of mantle and visceral mass pearl culturing in Hyriopsis cumingii

Biomineralization is a widespread phenomenon in marine mollusks and is responsible for the production of shells and pearls. However, the regulatory mechanisms governing the adaptive immune responses in the mollusk mantle and visceral mass during mineralization remain unclear. In this work, we examined the mantle and visceral mass immune responses of Hyriopsis cumingii during pearl culture using high-throughput sequencing techniques. A mantle transcriptome database was established using transcriptome sequencing technology and reference to the major databases. Digital gene expression profiling was used to identify the differentially expressed genes of mantle and visceral mass at different insertion periods. Moreover, quantitative real-time PCR was used to verify the expression of five immune-related genes. Transcriptome sequencing results showed 257,457 unigenes were identified. Digital gene expression profiles showed 1389, 3572, 1888, and 2613 differentially expressed genes (DEGs) in the mantle and visceral mass at 5, 20, 50, and 90 d after insertion, respectively, with the highest number at 20 d and the lowest at 5 d after insertion (q &lt; 0.05). A cluster analysis of the DEGs showed similar clustering and expression features in the mantle to the control group, and at 5, 50 and 90 d, after mantle insertion. The DEGs in the visceral mass showed similar clustering and expression features to the control group and at 5, 20 and 50 d after insertion. We also screened 22 immune-related DEGs in the mantle and visceral mass during the same pearl culture period, including serine/threonine-protein kinase NLK, C-type lectin, and galectin. The greatest number of DEGs was found 90 d after insertion. Compared with the mantle, more immune-related DEGs were down-regulated than up-regulated in the visceral mass during pearl culture, indicating that the immune regulatory mechanisms in the visceral mass and the mantle differ during pearl culture, and that the visceral mass is liable to higher infection and mortality rates. Quantitative real-time PCR results showed that the expression of five immune-related genes was consistent with DGE results. Our findings will further knowledge of the immune systems that are present in the mantle and visceral mass during pearl culture

Proteogenomic insights suggest druggable pathways in endometrial carcinoma

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC

A case study of repetitive transcranial magnetic stimulation for cryptococcal meningitis combined with cognitive impairment

Cryptococcal meningitis (CM) is a central nervous system disease caused by a novel Cryptococcus infection that leads to subacute or chronic inflammatory changes in the nervous system. In this study, we present the case of a woman aged 72 years with CM and severe cognitive impairment and disabilities. The cognitive assessment indicated that, although her cognitive function was impaired, especially executive function, it largely improved after receiving anti-infectious and repetitive transcranial magnetic stimulation, which can alter the membrane potential of the cortical nerve cells by triggering long-term potentiation and depression, modulating and releasing hormones, reducing the level of neuroinflammatory and peripheral blood cytokines, promoting nerve regeneration and synaptic remodeling, and changing the activity of the neural circuitry of the dorsolateral prefrontal cortex. We argue that this case provides a novel method of treatment for patients with CM in conjunction with cognitive impairments