Incremental Semi-supervised Federated Learning for Health Inference via Mobile Sensing

Mobile sensing appears as a promising solution for health inference problem (e.g., influenza-like symptom recognition) by leveraging diverse smart sensors to capture fine-grained information about human behaviors and ambient contexts. Centralized training of machine learning models can place mobile users' sensitive information under privacy risks due to data breach and misexploitation. Federated Learning (FL) enables mobile devices to collaboratively learn global models without the exposure of local private data. However, there are challenges of on-device FL deployment using mobile sensing: 1) long-term and continuously collected mobile sensing data may exhibit domain shifts as sensing objects (e.g. humans) have varying behaviors as a result of internal and/or external stimulus; 2) model retraining using all available data may increase computation and memory burden; and 3) the sparsity of annotated crowd-sourced data causes supervised FL to lack robustness. In this work, we propose FedMobile, an incremental semi-supervised federated learning algorithm, to train models semi-supervisedly and incrementally in a decentralized online fashion. We evaluate FedMobile using a real-world mobile sensing dataset for influenza-like symptom recognition. Our empirical results show that FedMobile-trained models achieve the best results in comparison to the selected baseline methods

Big-Data Based Analysis for Communication Effect of Science-Technology Public Accounts On Social Media

Public accounts on social media have become important channels for information dissemination. Well-designed public social media accounts are vital to better communicate science and technology (S-T) achievements. This article defines the S-T communication concept and proposes the analyzing dimensions. In order to measure the communication effect, this research collected 7,246 articles from S-T public accounts on WeChat. We analysis these massive data incorporating neural network (NN) and multivariate linear regression (MLR) model. The evaluation indicator system of communication effect includes three levels indicators. The research found the following factors affecting the S-T communication effect in different degrees: the number of active fans on Science Technology Public Accounts on Social Media (STPA-SM), locations where the articles are published, the authentication status of STPA-SM, and so on. Finally, the article proposes some strategic suggestions for improving the communication effects of S-T achievements through STPA-SM

Structural Health Monitoring for Composite Materials

Computer networking & communication

Effects of photoperiod on body mass, thermogenesis and body composition in Eothenomys miletus during cold exposure

Many small mammals respond to seasonal changes in photoperiod by altering body mass and adiposity. These animals may provide valuable models for understanding the regulation of energy balance. In present study, we examined the effect on body mass, rest metabolic rate, food intake and body composition in cold-acclimated (5 °C) in Eothenomys miletus by transferring them from a short (SD, 8h :16h L: D) to long day photoperiod (LD, 16h: 8h L:D). During the first 4 weeks of exposure to SD, E. miletus decreased body mass. After the next 4 weeks of exposure to LD, which the average difference between body masses of LD and SD voles was 4.76 g. This 14.74% increase in body mass reflected significant increases in absolute amounts of body components, including wet carcass mass, dry carcass mass and body fat mass. After correcting body composition and organ morphology data for the differences in body mass, only livers, kidney, and small intestine were enlarged due to photoperiod treatment during cold exposure. E. miletus increased RMR and energy intake exposure to LD, but maintained a stable level to SD after 28 days. Serum leptin levels were positively correlated with body mass, body fat mass, RMR as well as energy intake. All of the results indicated that E. miletus may provide an attractive novel animal model for investigation of the regulation of body mass and energy balance at organism levels. Leptin is potentially involved in the photoperiod induced body mass regulation and thermogenesis in E. miletus during cold exposure

The lithospheric S-wave velocity structure beneath the NE Tibetan Plateau and its surrounding craton basins

It is essential to investigate the spatial distribution of the lithosphere and asthenosphere in detail, to further obtain the understanding of the effect of plate collision and the process of orogenic movement. From the joint inversion of receiver functions and surface waves, the three-dimensional S-wave velocity structure results down to 200 km depth in the study area were obtained at 1,843 seismic stations. Analysis was performed on the sedimentary thickness, crustal thickness, lower crustal wave velocity, and lithospheric thickness. According to the crustal thickness, we evaluated the distribution of low-velocity zones in the lower crust. The results show that there are low-velocity bodies in the lower crust in the Qinling tectonic belt, but they are not connected, indicating that they may not be able to be used as a channel for material extrusion from the NE Tibetan Plateau at the crustal scale. According to the section results and the depth distribution of the lithosphere-astenosphere boundary, a relatively thick lithosphere exists below the Sichuan Basin and Ordos Basin, and the lithosphere in the east of the study area is relatively thin with a thickness of about 60–80 km, indicating that the lithosphere in the east of the study area has been severely destructed and restructured. The delamination has been observed in the lithosphere under the Songpan-Ganzi Block, showing characteristics of vertical movement of asthenosphere materials. There is a relatively thick low-velocity zone at the top of the mantle lithosphere of the NE plateau; however, it does not exist under the relatively stable Sichuan Basin and the Ordos Block. Compared with the Sichuan Basin and the Ordos Basin at both sides, the Qinling tectonic belt has a low-velocity zone at the depth of 100–160 km, which may be asthenosphere material. In combination with the polarization direction characteristics of the SKS wave, it is clearly observed that asthenospheric material movement exists in an approximate east-west direction beneath the Qinling tectonic belt. Therefore, the asthenosphere beneath the Qinling tectonic belt may serve as an important channel for material extrusion in the NE Tibetan Plateau

Offline Contextual Multi-armed Bandits for Mobile Health Interventions: A Case Study on Emotion Regulation

Delivering treatment recommendations via pervasive electronic devices such as mobile phones has the potential to be a viable and scalable treatment medium for long-term health behavior management. But active experimentation of treatment options can be time-consuming, expensive and altogether unethical in some cases. There is a growing interest in methodological approaches that allow an experimenter to learn and evaluate the usefulness of a new treatment strategy before deployment. We present the first development of a treatment recommender system for emotion regulation using real-world historical mobile digital data from n = 114 high socially anxious participants to test the usefulness of new emotion regulation strategies. We explore a number of offline contextual bandits estimators for learning and propose a general framework for learning algorithms. Our experimentation shows that the proposed doubly robust offline learning algorithms performed significantly better than baseline approaches, suggesting that this type of recommender algorithm could improve emotion regulation. Given that emotion regulation is impaired across many mental illnesses and such a recommender algorithm could be scaled up easily, this approach holds potential to increase access to treatment for many people. We also share some insights that allow us to translate contextual bandit models to this complex real-world data, including which contextual features appear to be most important for predicting emotion regulation strategy effectiveness.Comment: Accepted at RecSys 202

Auxin response factor 6A regulates photosynthesis, sugar accumulation, and fruit development in tomato.

Auxin response factors (ARFs) are involved in auxin-mediated transcriptional regulation in plants. In this study, we performed functional characterization of SlARF6A in tomato. SlARF6A is located in the nucleus and exhibits transcriptional activator activity. Overexpression of SlARF6A increased chlorophyll contents in the fruits and leaves of tomato plants, whereas downregulation of SlARF6A decreased chlorophyll contents compared with those of wild-type (WT) plants. Analysis of chloroplasts using transmission electron microscopy indicated increased sizes of chloroplasts in SlARF6A-overexpressing plants and decreased numbers of chloroplasts in SlARF6A-downregulated plants. Overexpression of SlARF6A increased the photosynthesis rate and accumulation of starch and soluble sugars, whereas knockdown of SlARF6A resulted in opposite phenotypes in tomato leaves and fruits. RNA-sequence analysis showed that regulation of SlARF6A expression altered the expression of genes involved in chlorophyll metabolism, photosynthesis and sugar metabolism. SlARF6A directly bound to the promoters of SlGLK1, CAB, and RbcS genes and positively regulated the expression of these genes. Overexpression of SlARF6A also inhibited fruit ripening and ethylene production, whereas downregulation of SlARF6A increased fruit ripening and ethylene production. SlARF6A directly bound to the SAMS1 promoter and negatively regulated SAMS1 expression. Taken together, these results expand our understanding of ARFs with regard to photosynthesis, sugar accumulation and fruit development and provide a potential target for genetic engineering to improve fruit nutrition in horticulture crops

Efficient inhibition of HIV-1 replication by an artificial polycistronic miRNA construct

10.1186/1743-422X-9-118Virology Journal9

A framework combining window width-level adjustment and Gaussian filter-based multi-resolution for automatic whole heart segmentation

Heart diseases are prevalent among the general population. These diseases can be diagnosed in their early stages through a quantitative evaluation of cardiac functions. In a typical procedure, heart segmentation is initially performed. Quantitative information is then obtained from a 3D reconstructed image of the heart. However, manual segmentation is time-consuming and prone to inter- and intra-observer variations. As such, automatic methods must be developed to assess cardiac functions quantitatively. In this study, an automatic algorithm for whole heart segmentation was established through window width-level adjustment and Gaussian filter-based multi-resolution methods. The proposed algorithm preprocesses the image by adjusting the window width and the centre to acquire cardiac images with clear anatomical structures. The cardiac image is then decomposed into several resolution layers by using a Gaussian filter to eliminate discontinuity associated with traditional pyramid down-sampling and decomposition. A registration-based segmentation algorithm is applied to the cardiac image. The proposed segmentation algorithm was validated with a clinical dataset of 14 cardiac dual-source computed tomography images. Results show that the proposed methods improve the registration accuracy of the epicardium and the endocardium. The volume of the manual segmentation standard is not significantly different from that of the proposed segmentation and the accuracy of the method reaches almost 1 mm in most areas. Thus, the proposed method can be used to perform a high-precision segmentation of the whole heart

The impact of Chinese COVID-19 pandemic on the incidence of peripheral facial nerve paralysis after optimizing policies

ObjectiveTo evaluate the impact of the COVID-19 pandemic on the occurrence of Peripheral Facial Nerve Paralysis (PFNP) in Chinese patients, identify contributing factors, and explore the relationship between COVID-19 and PFNP.MethodsWe conducted a retrospective study covering the years 2020 to 2023, categorizing patients into three groups based on their visit dates: Group 1 (December 8, 2020 to February 28, 2021), Group 2 (December 8, 2021 to February 28, 2022), and Group 3 (December 8, 2022 to February 28, 2023). We collected and compared data on disease onset and patient characteristics among these groups.ResultsIn Group 3, following the widespread COVID-19 outbreak, there was a significant increase of 22.4 and 12.1% in PFNP cases compared to the same periods in the preceding 2 years (p < 0.001). Group 3 patients were more likely to be aged between 30 and 60 years, experience onset within 7 days, present with Hunter syndrome, and have a higher H-B score of VI compared to the previous 2 years (p < 0.017). Logistic regression analysis revealed a strong association between the COVID-19 pandemic and the incidence of Hunter syndrome in PFNP (OR = 3.30, 95% CI 1.81–6.03, p < 0.001).ConclusionThe incidence of PFNP increased in China after the COVID-19 pandemic, particularly in patients with Hunter syndrome, indicating that COVID-19 infection can trigger and worsen PFNP