Indoor Human Fall Detection Algorithm Based on Wireless Sensing

As the main health threat to the elderly living alone and performing indoor activities, falls have attracted great attention from institutions and society. Currently, fall detection systems are mainly based on wear sensors, environmental sensors, and computer vision, which need to be worn or require complex equipment construction. However, they have limitations and will interfere with the daily life of the elderly. On the basis of the indoor propagation theory of wireless signals, this paper proposes a conceptual verification module using Wi-Fi signals to identify human fall behavior. The module can detect falls without invading privacy and affecting human comfort and has the advantages of noninvasive, robustness, universality, and low price. The module combines digital signal processing technology and machine learning technology. This paper analyzes and processes the channel state information (CSI) data of wireless signals, and the local outlier factor algorithm is used to find the abnormal CSI sequence. The support vector machine and extreme gradient boosting algorithms are used for classification, recognition, and comparative research. Experimental results show that the average accuracy of fall detection based on wireless sensing is more than 90%. This work has important social significance in ensuring the safety of the elderly.Temple University. College of Science and TechnologyComputer and Information Science

A New Classification Method of Infrasound Events Using Hilbert-Huang Transform and Support Vector Machine

Infrasound is a type of low frequency signal that occurs in nature and results from man-made events, typically ranging in frequency from 0.01 Hz to 20 Hz. In this paper, a classification method based on Hilbert-Huang transform (HHT) and support vector machine (SVM) is proposed to discriminate between three different natural events. The frequency spectrum characteristics of infrasound signals produced by different events, such as volcanoes, are unique, which lays the foundation for infrasound signal classification. First, the HHT method was used to extract the feature vectors of several kinds of infrasound events from the Hilbert marginal spectrum. Then, the feature vectors were classified by the SVM method. Finally, the present of classification and identification accuracy are given. The simulation results show that the recognition rate is above 97.7%, and that approach is effective for classifying event types for small samples

Structural analysis of type 3 resistant starch from Canna edulis during in vitro simulated digestion and its post-digested residue impact on human gut microbiota

IntroductionResistant starch (RS) has garnered attention for its health benefits, including modulating the gut microbiota and promoting the production of short-chain fatty acids (SCFAs).MethodsThis study investigates structural changes of type 3 resistant starch from Canna edulis (CE) during in vitro simulated digestion and explores its health-relevant properties using healthy individuals’ fecal microbiota.ResultsCE, prepared with a RS content of 59.38%, underwent a comprehensive analysis employing X-ray diffraction (XRD), fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). During simulated digestion, XRD analysis demonstrated a significant rise in CE’s relative crystallinity from 38.92 to 49.34%. SEM illustrated the transition of CE from a smooth to a rough surface, a notable morphological shift. Post-digestion, CE was introduced into microbial fermentation. Notably, propionic acid and valeric acid levels significantly increased compared to the control group. Furthere more, beneficial Bifidobacterium proliferated while pathogenic Escherichia-Shigella was suppressed. When comparing CE to the well-known functional food fructo-oligosaccharide (FOS), CE showed a specific ability to support the growth of Bifidobacterium and stimulate the production of short-chain fatty acids (SCFAs) without causing lactic acid accumulation.DiscussionCE demonstrates potential as a functional health food, with implications for gut health enhancement and SCFAs production

Eriodictyol protects skin cells from UVA irradiation-induced photodamage by inhibition of the MAPK signaling pathway

Solar UVA irradiation-generated reactive oxygen species (ROS) induces the expression of matrix metalloproteinase 1 (MMP-1), leading to photoaging, however the molecular mechanism remains unclear. In the present study, we found that eriodictyol remarkably reduces UVA-mediated ROS generation and protects the skin cells from oxidative damage and the ensuing cell death. Moreover eriodictyol pretreatment significantly down-regulates the UVA-induced MMP-1 expression, and lowers the inflammatory responses within the skin cells. Pretreatment with eriodictyol upregulates the expression of tissue inhibitory metalloproteinase 1 (TIMP-1) and collagen-I (COL-1) at the transcriptional level in a dose-dependent manner. UVA-induced phosphorylation levels of c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK) and p38 leading to increased MMP-1 expression are significantly reduced in eriodictyol-treated skin cells. In addition, eriodictyol pretreatment significantly suppresses inflammatory cytokines and inhibits the activation of MAPK signaling cascades in skin cells. Taken together, our results demonstrate that eriodictyol has both potent anti-inflammatory and anti-photoaging effects.</p

Application of recombinant severe fever with thrombocytopenia syndrome virus nucleocapsid protein for the detection of SFTSV-specific human IgG and IgM antibodies by indirect ELISA

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging disease that was first reported in China in 2011. It is caused by SFTS virus (SFTSV) which is a member of the Phlebovirus genus in the Bunyaviridae family. SFTSV has been classified as a BSL3 pathogen. There is a need to develop safe and affordable serodiagnostic methods for proper clinical management of infected patients. Methods: The full length nucleocapsid (N) gene of SFTSV Yamaguchi strain was amplified by RT-PCR and cloned to an expression vector pQE30. The recombinant (r) SFTSV-N protein was expressed by using Escherichia coli (E. coli) expression system and purified under native conditions. rSFTSV-N protein based indirect IgG and IgM enzyme linked immunosorbent assay (ELISA) systems were established to detect specific human IgG and IgM antibodies, respectively. One hundred fifteen serum samples from clinically suspected-SFTS patients were used to evaluate the newly established systems and the results were compared with the total antibody detecting sandwich ELISA system. Results: The native form of recombinant (r) SFTSV-N protein was expressed and purified. Application of the rSFTSV-N protein based indirect IgG ELISA to the 115 serum samples showed results that perfectly matched those of the total antibody sandwich ELISA with a sensitivity and specificity of 100 %. The rSFTSV-N protein based indirect IgM ELISA missed 8 positive samples that were detected by the total antibody sandwich ELISA. The sensitivity and specificity of rSFTSV-N-IgM capture ELISA were 90.59 and 100 %, respectively. Conclusions: The rSFTSV-N protein is highly immunoreactive and a good target for use as an assay antigen in laboratory diagnosis. Its preparation is simpler in comparison with that used for the total antibody sandwich system. Our rSFTSV-N protein-based IgG and IgM ELISA systems have the advantage of distinguishing two types of antibodies and require small volume of serum sample only. They are safe to use for diagnosis of SFTS virus infection and especially fit in large-scale epidemiological investigations

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes

The association of serum vascular endothelial growth factor levels and psoriasis vulgaris: a protocol for systematic review and Meta-analysis

Psoriasis affects about 2% of the population worldwide. Although the exact etiology and pathogenesis of psoriasis are not completely clear, the idea that the immune system is involved in the pathogenesis of psoriasis has been widely accepted. Through genome-wide analysis, psoriasis-related genes are mainly immune-related genes. The disorder of innate immunity and acquired skin immune response are the main reasons for the development and maintenance of psoriasis inflammation. Vascular endothelial growth factor (VEGF) plays an important role in the pathogenesis of psoriasis by promoting angiogenesis. The purpose of this study is to evaluate the relationship between serum vascular endothelial growth factor and psoriasis vulgaris