Validity of the “Streitberger” Needle in a Chinese Population with Acupuncture: A Randomized, Single-Blinded, and Crossover Pilot Study

We studied the validity of a “Streitberger” needle as a valid approach in a Chinese population with experience of acupuncture. Volunteers were recruited from students of the School of Acupuncture and Moxibustion, Guangzhou University of Chinese Medicine. Sixty students receiving education in acupuncture theory and experience in practical acupuncture were tested in study determining whether needling with the placebo needle felt any different from conventional acupuncture. Outcomes included measures of penetration sensation, VAS ratings, and Deqi sensation questionnaire. As a result, needle penetration, VAS ratings for either needle and Deqi sensation were not significantly different between two kinds of needles. Our findings show that the use of “Streitberger” needle is credible in a Chinese population with acupuncture experience

Ex-Ante PLM Misfit Analysis Methodology: A Cognitive Fit Approach

Commercial off-the-shelf (COTS) Product Lifecycle Management (PLM) systems have been introduced by companies to facilitate their new product development process to shorten the product time to market, reduce the product development cost, and meet the dynamic demands of customers. However, PLM implementation is not an easy job and some of the attempted projects failed. A common problem encountered in adopting PLM packages has been the issue of misfits, i.e., the gaps between the specifications offered by a PLM package and those required by the adopting organization, which easily causes the project to fail. Current approaches for the ex-ante analysis of PLM misfits are extremely limited. This paper develops a methodology grounded in the extended cognitive fit theory for the misfit analysis. This approach can assist in identifying and representing consistent set of information for functions and workflow processes across business requirements and the PLM package. Particularly, Petri nets that are of graphical representations and easy to understand are employed to model the function-embedded workflow process. A case study is presented to examine the feasibility of this approach. We conclude that with our methodology, PLM analysts or adopting organizations can systematically identify potential misfits and the degree of misfit between the business requirements and PLM packages in an ex-ante analysis to mitigate the risks in PLM implementations

Risk of cardiovascular disease in Chinese patients with rheumatoid arthritis: a cross sectional study based on hospital medical records in 10 years

Objective: Though the risk of cardiovascular disease (CVD) in rheumatoid arthritis (RA) has been established in Western population, little is known about the risk in Chinese people with RA. Our objective was to estimate the risk of CVD in Chinese people with RA using hospital medical records data. Methods The inpatients medical record database 2005‐2015 of Sichuan provincial people’s hospital was examined. All individuals with a primary diagnosis of RA were included as cases, and those of osteoarthritis (OA) were included as controls, which consisted of the unmatched dataset. Then, RA cases and OA controls were matched by sex and age at 1:1 ratio, forming the matched dataset. The morbidity of CVD (including ischemia heart disease (IHD), congestive heart failure (CHF), et al), stroke and arthrosclerosis were extracted from the database, so as the demographic data and comorbidities related to CVD. Multiple logistic regression analysis was used to estimate the risk of CVD in RA adjusted for demographics and comorbidities using the unmatched dataset. Sensitivity analysis was conducted 1) considering interaction terms between RA and comorbidities, and 2) using multivariable conditional logistic regression for the matched dataset. Results: The unmatched data set comprised of 1824RA cases and 1995 OA controls and the matched dataset comprised of 1022 pairs of sex and age matched RA and OA patients. RA exhibited increased odds of prevalent CVD compared with OA, and the adjusted ORs (95%CIs) for CVD, stroke, IHD, CHF, and atherosclerosis were1.86(1.42‐2.43), 1.11(0.71‐1.74), 1.47(0.97‐2.24), 2.09(1.03‐4.22), and 2.49 (1.97‐3.13), respectively, and was 2.26 (1.29‐3.96) for IHD further adjusted for interaction term. The matched dataset analysis found similar results. Conclusions: Chinese people with RA were approximated 2 times more 1 likely to have CVD, IHD, CHF and atherosclerosis compared with those with OA. The findings justified the need of further longitudinal study to establish the causal‐relationship between RA and CVD and to estimate the precise risk in this population

Novel Salicylic Acid Analogs Induce a Potent Defense Response in Arabidopsis

The master regulator of salicylic acid (SA)-mediated plant defense, NPR1 (NONEXPRESSER OF PR GENES 1) and its paralogs NPR3 and NPR4, act as SA receptors. After the perception of a pathogen, plant cells produce SA in the chloroplast. In the presence of SA, NPR1 protein is reduced from oligomers to monomers, and translocated into the nucleus. There, NPR1 binds to TGA, TCP, and WRKY transcription factors to induce expression of plant defense genes. A list of compounds structurally similar to SA was generated using ChemMine Tools and its Clustering Toolbox. Several of these analogs can induce SA-mediated defense and inhibit growth of Pseudomonas syringae in Arabidopsis. These analogs, when sprayed on Arabidopsis, can induce the accumulation of the master regulator of plant defense NPR1. In a yeast two-hybrid system, these analogs can strengthen the interactions among NPR proteins. We demonstrated that these analogs can induce the expression of the defense marker gene PR1. Furthermore, we hypothesized that these SA analogs could be potent tools against the citrus greening pathogen Candidatus liberibacter spp. In fact, our results suggest that the SA analogs we tested using Arabidopsis may also be effective for inducing a defense response in citrus. Several SA analogs consistently strengthened the interactions between citrus NPR1 and NPR3 proteins in a yeast two-hybrid system. In future assays, we plan to test whether these analogs avoid degradation by SA hydroxylases from plant pathogens. In future assays, we plan to test whether these analogs avoid degradation by SA hydroxylases from plant pathogens

A Multichannel MAC Protocol for IoT-enabled Cognitive Radio Ad Hoc Networks

Cognitive radios have the ability to dynamically sense and access the wireless spectrum, and this ability is a key factor in successfully building Internet-of-Things (IoT)-enabled mobile ad hoc networks. This paper proposes a contention-free token-based multichannel MAC protocol for IoT-enabled Cognitive Radio Ad Hoc Networks (CRAHNs). In this, secondary users of CRAHNs detect activity on the wireless spectrum and then access idle channels licensed by primary users. CRAHNs are divided into clusters, and the channel to use for transmission is determined dynamically from the probability of finding idle primary-user channels. The token-based MAC window size is adaptive, with adjustment according to actual traffic, which reduces both end-to-end MAC contention delay and energy consumption. High throughput and spatial reuse of channels can also be achieved using a dynamic control channel and dynamic schemes for contention windows. We performed extensive simulations to verify that the proposed method can achieve better performance in mobile CRAHNs than other MAC schemes can

News-based soft information as a corporate competitive advantage

This study establishes a decision-making conceptual architecture that evaluates decision making units (DMUs) from numerous aspects. The architecture combines financial indicators together with a variety of data envelopment analysis (DEA) specifications to encapsulate more information to give a complete picture of a corporate’s operation. To make outcomes more accessible to non-specialists, multidimensional scaling (MDS) was performed to visualize the data. Most previous studies on forecasting model construction have relied heavily on hard information, with quite a few works taking into consideration soft information, which contains much denser and more diverse messages than hard information. To overcome this challenge, we consider two different types of soft information: supply chain influential indicator (SCI) and sentimental indicator (STI). SCI is computed by joint utilization of text mining (TM) and social network analysis (SNA), with TM identifying the corporate’s SC relationships from news articles and SNA to determining their impact on the network. STI is extracted from an accounting narrative so as to comprehensively illustrate the relationships between pervious and future performances. The analyzed outcomes are then fed into an artificial intelligence (AI)-based technique to construct the forecasting model. The introduced model, examined by real cases, is a promising alternative for performance forecasting. First published online 21 November 201