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In recent years, human activity recognition (HAR) technologies in e-health have triggered broad interest. In literature, mainstream works focus on the body's spatial information (i.e. postures) which lacks the interpretation of key bioinformatics associated with movements, limiting the use in applications requiring comprehensively evaluating motion tasks' correctness. To address the issue, in this article, a Wearables-based Multi-column Neural Network (WMNN) for HAR based on multi-sensor fusion and deep learning is presented. Here, the Tai Chi Eight Methods were utilized as an example as in which both postures and muscle activity strengths are significant. The research work was validated by recruiting 14 subjects in total, and we experimentally show 96.9% and 92.5% accuracy for training and testing, for a total of 144 postures and corresponding muscle activities. The method is then provided with a human-machine interface (HMI), which returns users with motion suggestions (i.e. postures and muscle strength). The report demonstrates that the proposed HAR technique can enhance users' self-training efficiency, potentially promoting the development of the HAR area.

Fueled by the recent proliferation of energy-efficient and energy-autonomous or self-powered nanotechnology-based wearable smart systems, human motion intention prediction (MIP) plays a critical role in a wide range of applications, such as rehabili- tation and assistive robotics, to enable more natural, biologically inspired, and seamless integrated motion assistance task execution, including for elders and physically impaired patients. With the increasing complexity of human-machine interactions and the need for personalized assistance, there is a growing demand for real-time and accurate MIP sys- tems. This review aims to provide a comprehensive understanding of the interdisciplinary field of MIP, under the logic of its physiological foundations, by discussing state-of-the- art sensing technologies, including brain-computer interfaces (BCI), electromyography (EMG), and motion sensors, alongside the relevant data processing techniques and decod- ing algorithms. We emphasize the importance of fostering collaboration among scholars from different domains to capture the intricate dependencies between the set of stimuli and responses of the central nervous system and the activation of the complex set of muscles and joints that produce human motion. By offering insights into the recent advancements and future prospects of the field, this review seeks to stimulate further research and innova- tion in the rapidly evolving area of human motion intention prediction, for a future where technologies understand and respond to complex human intentions patterns, anticipating their needs.

Ferroptosis is characterized by excessive accumulation of iron and lipid peroxides, which are involved in ischemia, reperfusion-induced organ injury, and stroke. Propofol, an anesthetic agent, has neuroprotective effects due to its potent antioxidant, anti-ischemic, and anti-inflammatory properties. However, the relationship between propofol and ferroptosis is still unclear. In the current study, we elucidated the role of ferroptosis in the neuroprotective effect of propofol in mouse brains subjected to cerebral ischemia reperfusion injury (CIRI). Ferroptosis was confirmed by Western blotting assays, transmission electron microscopy, and glutathione assays. Propofol regulated Nrf2/Gpx4 signaling, enhanced antioxidant potential, inhibited the accumulation of lipid peroxides in CIRI-affected neurons, and significantly reversed CIRI-induced ferroptosis. Additionally, Gpx4 inhibitor RSL3 and Nrf2 inhibitor ML385 attenuated the effects of propofol on antioxidant capacity, lipid peroxidation, and ferroptosis in CIRI-affected neurons. Our data support a protective role of propofol against ferroptosis as a cause of cell death in mice with CIRI. Propofol protected against CIRI-induced ferroptosis partly by regulating the Nrf2/Gpx4 signaling pathway. These findings may contribute to the development of future therapies targeting ferroptosis induced by CIRI.

Image-text matching using the image caption method has made a great progress. However, there are many named entities in news text, and existing approaches are unable to directly generate named entities in the news image caption. It leads to a semantic gap between text and news image caption. Moreover, the existing methods lack the analysis of indirect relations between named entities. Therefore those approaches easily leads to relations error when generating news image caption. To generate the news image caption with named entities by analyzing the indirect relations between named entities. We propose a novel model. In details, we propose the TopNews dataset with related news, which aims to construct the relations between named entities as widely as possible. Then we develop the news knowledge graph by extracting named entities from TopNews dataset. Furthermore, we propose News Knowledge Driven Graph Neural Network (NKD-GNN). We utilize NKD-GNN to analyzing the whole relations of entities in news knowledge graph. In this way, we generate the news image caption with named entities. The results of extensive experiments based on TopNews dataset and common dataset demonstrate that our approach is effective in detecting the consistency of news images and text.

Single-nucleotide polymorphisms (SNPs) of microRNA (miRNA) (miRSNP) are SNPs located on miRNA genes or miRNA target sites, which have been supposed to be involved in the development of central nervous system diseases by interfering with miRNA-mediated regulatory functions. However, the association of miRSNP with post-stroke depression (PSD) has not been well-investigated. In this study, we collected 54 PSD risk genes via manual literature-mining and integrated PSD-related risk pathways based on multiple public databases. Furthermore, we systematically screened candidate functional miRSNPs for PSD and integrated a miRSNP-based PSD-associated pathway network, which included 99 miRNAs that target 12 PSD risk pathways. We also reviewed the association between three risk pathways and PSD pathogenetic mechanism thoroughly. Combining literature mining and network analysis, our results proposed an underlying mechanism of “miRSNP → miRNA → risk gene → pathway” axis effects on PSD pathogenesis, especially for rs28457673 (miR-15/16/195/424/497 family) → IGF1R → hsa04010 (MAPK signaling pathway). Our studies revealed a functional role in genetic modifier at the system level in the pathogenesis of PSD, which might provide further information for the miRSNP studies in PSD.

Litter size has a great impact on the profit of swine producers. Uterine development is an important determinant of reproduction efficiency and could hence affect litter size. Chinese Erhualian pig is one of the most prolific breeds in the world, even though large phenotypic variation in litter size was observed within Erhualian sows. To dissect the genetic basis of the phenotypic variation, we herein conducted genome-wide association studies for total number born and number born alive (NBA) of Erhualian sows. In total, one significant single nucleotide polymorphism (SNP) (P

The reductive transformation of furfural (FAL) into furfuryl alcohol (FOL) is an attractive route for the use of renewable bio-sources but it suffers from the heavy use of H 2 . We describe here a highly efficient reduction protocol for converting aqueous FAL to FOL. A single phase rutile TiO 2 support with a gold catalyst (Au/TiO 2 -R) that used CO/H 2 O as the hydrogen source catalyze this reduction efficiently under mild conditions. By eliminating the consumption of fossil fuel-derived H 2 , our process has the benefit afforded by using CO as a convenient and cost competitive reducing reagent.

Summary The Chinese Erhualian pig has the highest record for litter size in the world. However, the genetic mechanism of its high prolificacy remains poorly understood. In our study, large phenotypic variations in litter size were found among Erhualian sows. Significant differences in total number born (TNB) and corpora lutea numbers were observed between sows with high and low estimated breeding values (EBVs) for TNB. To identify single nucleotide polymorphisms (SNPs) associated with TNB, a selective genomic scan was conducted on 18 sows representing the top 10% and 18 sows representing the bottom 10% of EBVs of 177 sows using Illumina Porcine SNP60 genotype data. Genome-wide fixation coefficient (FST) values were calculated for each SNP between the high- and low-EBV groups. A total of 154 SNPs were significantly differentiated loci between the two groups. Of the top 10 highest FST SNPs, rs81399474, rs81400131 and rs81405013 on SSC8 and rs81434499 and rs81434489 on SSC 12 corresponded to previously reported QTL for litter size. The other five SNPs, rs81367039 on SSC2, rs80891106 on SSC7, rs81477883 on SSC12 and rs80938898 and rs80971725 on SSC14, appeared to be novel QTL for TNB. Significant associations between rs81399474 on SSC8 and TNB were confirmed in 313 Erhualian sows. Forty genes were identified around the top 10 highest FST SNPs, of which UCHL1, adjacent to rs81399474, and RPS6KB1 and CLTC, adjacent to rs81434499, have been reported to affect the ovulation rate in pig. The findings can advance understanding of the genetic variations in litter size of pigs.

Given the vital importance of furfural (FFA) upgrading towards a sustainable bio-based economy, an eco-friendly aqueous route to produce a sole valuable product from FFA is highly desirable. We herein describe an efficient approach to quantitatively convert FFA into cyclopentanone (CPO) in neat water, employing H2 as the clean reductant and supported gold nanoparticles as a simple yet versatile catalyst. The use of anatase TiO2 featuring only mild Lewis acidic sites as the underlying support is essential, not only for preventing undesirable side reactions, but also for attaining high CPO selectivity. The feasibility of using biogenic CPO and CO2 as benign carbon sources to synthesize the industrially important feedstock dimethyl adipate is also demonstrated.

Finger recovery is much harder than other parts on the upper limbs, because finger recovery movement has several key problems need to overcome, including high precision of movement, high control resolution requirements, variable data with different person, as well as the fuzzy signal during the movement. In order to overcome the difficulties, a new scheme of finger recovery is presented in the paper based on symmetric rehabilitation. In the paralyzed hand side, a mechanical exoskeleton hand is designed and simulated to provide skeletal traction, while in the regular hand side, the curve magnitude of every joint during movement is detected. Then the hand motion is analyzed and recognized using Multi-class SVM. Many candidates were chosen to perform the experiment, and the data produced by the candidates were divided the training parts and recognition parts. Experiments shows that the Multi-class SVM is effective and practical for classification and recognition, and could be helpful in the finger recovery process.

In order to optimize the performance of a steam ejector used in a MED-TVC desalination system, an auxiliary entrainment inlet is added at the ejector’s low pressure region. The steam ejector is simulated by using the CFD method to investigate the position, width and pressure of the auxiliary entrainment inlet. Detailed analyses and discussions are presented based on the ejector inlet and outlet mass flow rates, internal pressure contours and velocity vector fields. The results indicate that when the pressure at the auxiliary entrainment inlet exceeds a certain value, the internal backflow can be effectively avoided. Besides, there exists an optimal position and width of the auxiliary entrainment inlet. Compared with the conventional ejector, the entrainment ratio is slightly increased by 2.7%, but the ejector outlet mass flow rate can be increased about 15.5% for the auxiliary entrainment inlet with the optimal position and width. Therefore, for a MED-TVC desalination system, applying a steam ejector with auxiliary entrainment inlet can effectively increase the efficiency of the system and increase the production of fresh water.

The impact sensitivity is a very important property for indicating the safety, reliability and stability of high-energy-density materials (HEDM). A quantitative structure-property relationship (QSPR) study was used for prediction of impact sensitivity of some nitro compounds. Employing the square of nitro group charge (QNO22) and OB100as the parameters, a good QSPR model was built for predicting H50of two sorts of nitro compounds. The predictive ability of the model was assessed by leave-one-out cross-validation method. The cross-validation results shows that the model is significant and stable, and its predicted accuracy is within 0.21 m. This quantitative model may be a useful tool for the design of HEDM.

The gut microbiota plays an important role in nutrient digestibility in animals. To examine changes in the pig gut microbiota across growth stages and its effects on nutrient digestion, the gut microbiota population in pigs at 28 days (before weaning) and 60, 90 and 150 days of age was assessed by 16S rDNA gene sequencing. The apparent digestibility of crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein (CP) and ether extract (EE) was also assessed in these pigs. A total of 19,875 operational taxonomic units (OTUs) were identified from all samples. Both bacterial abundance and diversity increased with age. A total of 22 phyla and 249 genera were identified from all fecal samples; Firmicutes and Bacteroidetes were the most dominant phyla in all samples. With increasing age, the proportion of TM7 and Tenericutes increased, whereas the proportion of Lentisphaerae and Synergistetes decreased. The abundance of 36 genera varied with age and the apparent digestibility of CF increased with age. Three phyla, Proteobacteria, Tenericutes and TM7 and 11 genera, including Anaeroplasma, Campylobacter and Clostridium, were correlated with apparent CF digestibility.