A Novel Energy-Efficient Approach for Human Activity Recognition

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper

The association between dietary inflammatory index and cognitive function in adults with/without chronic kidney disease

Background and aimsCognitive impairment (CI) is a prevalent condition in patients with chronic kidney disease (CKD), who face an elevated risk of developing cognitive decline. The fundamental mechanism underlying CI is linked to chronic inflammation, which can be gauged by the Dietary Inflammatory Index (DII). The DII is categorized into anti-inflammatory diets with lower scores and pro-inflammatory diets with higher scores. Specifically, pro-inflammatory diets may contribute to chronic inflammation. However, the correlation between the inflammatory potential of diet and cognitive function in patients with CKD has not been explored. This study aims to investigate the connection between the inflammatory potential of diet and cognitive function in individuals with or without chronic kidney disease.MethodsData from the 2011–2012 and 2013–2014 National Health and Nutrition Examination Survey (NHANES) were utilized. Participants under the age of 60 or lacking DII, CI, CKD, and other essential data were excluded. DII was computed based on a 24-h dietary recall interview for each participant. Cognitive performance was evaluated using three cognitive tests: the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) test, the Animal Fluency Test (AFT), and the Digital Symbol Substitution Test (DSST). Logistic regression analysis and subgroup analysis were conducted to assess the independent relationship between DII score and CI in the CKD and non-CKD populations.ResultsThe study included a total of 2069 subjects, with CI prevalence ranging from 21.4 to 23.5%. Multiple regression models showed that after adjusting for all covariates of the three cognitive function tests, higher DII scores were significantly associated with increased risk of CI (CERAD OR = 1.18, 95% CI: 1.1 ~ 1.26, AFT OR = 1.15, 95% CI: 1.08 ~ 1.23, DSST OR = 1.19, 95% CI: 1.11 ~ 1.28). Subgroup analysis indicated that the effect of DII score on CI remained consistent in all subgroups (p > 0.05).ConclusionHigher DII scores were associated with an increased risk of cognitive impairment in people with or without CKD, suggesting that consuming a pro-inflammatory diet may contribute to the impairment of the cognitive function

Identification and characterization of miRNA169 family members in banana (Musa acuminata L.) that respond to fusarium oxysporum f. sp. cubense infection in banana cultivars

MicroRNAs (miRNAs) play an important role in plant resistance to pathogen infections. However, little is known about the role of miRNAs in banana Fusarium wilt, which is the most economically devastating disease in banana production. In the present study, we identified and characterized a total of 18 miR169 family members in banana (Musa acuminata L.) based on small RNA sequencing. The banana miR169 family clustered into two groups based on miRNA evolutionary analysis. Multiple sequence alignment indicated a high degree of sequence conservation in miRNA169 family members across 28 plant species. Computational target prediction algorithms were used to identify 25 targets of miR169 family members in banana. These targets were enriched in various metabolic pathways that include the following molecules: glycine, serine, threonine, pentose, glycerolipids, nucleotide sugars, starch, and sucrose. Through miRNA transcriptomic analysis, we found that ma-miR169a and ma-miR169b displayed high expression levels, whereas the other 16 ma-miR169 members exhibited low expression in the HG and Baxi banana cultivars. Further experiments indicate that there were negative relationships between ma-miR169a, ma-miR169b and their targets basing on their expression levels to Foc4 (Fusarium oxysporum f. sp. cubense tropical race 4) infection in resistant cultivars. But they were low expressed in susceptive cultivars. These results suggested that the expression levels of ma-miR169a and ma-miR169b were consistent with the resistance degree of the banana cultivars to Foc4. The analysis presented here constitutes a starting point to understand ma-miR169-mediated Fusarium wilt resistance at the transcriptional level in banana and predicts possible candidate targets for the genetic improvement of banana resistance to Foc4

Electronic structure and ferromagnetic properties of Zn vacancies in ZnO screw dislocations: First-principles calculations

First principle calculation, based on density functional theory, is applied to study the configuration and electronic structure of ZnO screw dislocations along [0001] and [112¯0]. O-O bonds can be found in the core of dislocations along [0001], which induces an occupied energy level in forbidden band. The dislocations along [0001] also facilitate the formation and accumulation of Zn vacancies, due to the stress relief in dislocations. Moreover, the dislocations are periodic and continuous, and can mediate the ferromagnetic coupling between Zn vacancies. The antibonding state of O-O bonds around Zn vacancies is responsible for the ferromagnetic state, which is a kind of d0 ferromagnetism. The result also gives us a new view to think the origin of d0 ferromagnetism in ZnO

A TDMA based media access control protocol for wireless ad hoc networks

Conference Name:2012 5th International Conference on Machine Vision: Algorithms, Pattern Recognition and Basic Technologies, ICMV 2012. Conference Address: Wuhan, China. Time:October 20, 2012 - October 21, 2012.Science and Engineering InstituteThis paper presents a novel Time Division Multiplex Access (TDMA) based Media Access Control (MAC) protocol of wireless Ad Hoc network. To achieve collision free transmission, time slots in a MAC frame are cataloged into three types, that is access slot, control slot and traffic slot. Nodes in the network access to the network in the access slot, and an exclusive control is allocated subsequently. Data packets are transmission by dynamic schedule the traffic slots. Throughput and transmission delay are also analyzed by simulation experiment. The proposed protocol is capable of providing collision free transmission and achieves high throughput. ? 2013 SPIE

O(3P)+HBr(DBr)反应的含时量子散射计算

基于LEPS势能面，用三维含时量子波包法对O（^3p）＋HBr（DBr）反应进行了准确的动力学计算．计算的结果表明，振动激发对这个反应是有效的，而转动激发在某一能量范围内具有方位效应．计算得到了该反应的速率常数和反应截面，速率常数kO＋HBr的计算值同实验值符合得很好．通过对相应结果的对比，可以发现这个反应具有比较明显的同位素效应

O(3P)+HBr(DBr)反应的含时量子散射计算

基于LEPS势能面，用三维含时量子波包法对O（^3p）＋HBr（DBr）反应进行了准确的动力学计算．计算的结果表明，振动激发对这个反应是有效的，而转动激发在某一能量范围内具有方位效应．计算得到了该反应的速率常数和反应截面，速率常数kO＋HBr的计算值同实验值符合得很好．通过对相应结果的对比，可以发现这个反应具有比较明显的同位素效应

An Indoor Navigation Algorithm Using Multi-Dimensional Euclidean Distance and an Adaptive Particle Filter

The inertial navigation system has high short-term positioning accuracy but features cumulative error. Although no cumulative error occurs in WiFi fingerprint localization, mismatching is common. A popular technique thus involves integrating an inertial navigation system with WiFi fingerprint matching. The particle filter uses dead reckoning as the state transfer equation and the difference between inertial navigation and WiFi fingerprint matching as the observation equation. Floor map information is introduced to detect whether particles cross the wall; if so, the weight is set to zero. For particles that do not cross the wall, considering the distance between current and historical particles, an adaptive particle filter is proposed. The adaptive factor increases the weight of highly trusted particles and reduces the weight of less trusted particles. This paper also proposes a multidimensional Euclidean distance algorithm to reduce WiFi fingerprint mismatching. Experimental results indicate that the proposed algorithm achieves high positioning accuracy