Design of the Control System of 2-DOF Parallel Manipulator Based on CoDeSys

The 2-DOF parallel manipulator takes a parallelogram construction which can make its workbench always remain stable. Now it is widely used in various industrial sites. In consideration of the construction features and the control demands of 2-DOF parallel manipulator, this paper mainly introduces the motion control scheme and man-machine interface design of the manipulator. Based on the motion control programming platform of CoDeSys, the motion control and simulation debugging of the 2-DOF parallel manipulator are realized

Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective

As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas. In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM). Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signs examined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes of disease occurrence and development. Patient classification is to divide patients into several classes based on different criteria. In this paper, from the machine learning perspective, a survey on patient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification. With the consideration of different diagnostic data analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively. For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction. According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification

The relationship between phosphine, methane, and ozone over paddy field in Guangzhou, China

Greenhouse effect has been attracting more and more attention in the world. Carbon dioxide (CO2) and methane (CH4) are the most important greenhouse gases. Phosphine (PH3) may have a potential greenhouse effect because it can react with hydroxyl radicals (·OH) in competition with other reducing gases. The aim of this study is to discover the relationship among PH3, ozone (O3) and CH4 in paddy fields and estimate the potential greenhouse effect of PH3 by field experiment. The results reveal that there was a significant negative correlation between O3 and PH3 (r = −0.494, p = 0.001, n = 42) during the whole period of rice growth. Similarly, CH4 was also negatively correlated with PH3, but not significant (r = −0.283, p = 0.069, n = 42). However, it was found that PH3 and CH4 corresponded to the reciprocal model. These results show that there was a certain competition relationship between PH3 and CH4. It was widely speculated that PH3 and CH4 were similar in the photochemical elimination process. ·OH could react with PH3, resulting in PH bond break. Then PH3 was oxidized to phosphate and other oxidation substances. Through Pearson correlation analysis and multiple stepwise linear regression analysis, light intensity was the principal factor affecting PH3 levels over the paddy field. The regression equation was [PH3] = -0.0003*[L] +20.025 (R2 = 0.243; F = 5.177; P < 0.01). These discoveries in this study have great reference values for the future investigation of greenhouse effect. Keywords: Phosphine, Methane, Ozone, Greenhouse effect, Paddy fields, Meteorological facto

Advances in patient classification for traditional chinese medicine: a machine learning perspective,”

As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas. In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM). Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signs examined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes of disease occurrence and development. Patient classification is to divide patients into several classes based on different criteria. In this paper, from the machine learning perspective, a survey on patient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification. With the consideration of different diagnostic data analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively. For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction. According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification

A GHz Silicon-Based Width Extensional Mode MEMS Resonator with <i>Q</i> over 10,000

This work presents a silicon-based capacitively transduced width extensional mode (WEM) MEMS rectangular plate resonator with quality factor (Q) of over 10,000 at a frequency of greater than 1 GHz. The Q value, determined by various loss mechanisms, was analyzed and quantified via numerical calculation and simulation. The energy loss of high order WEMs is dominated by anchor loss and phonon-phonon interaction dissipation (PPID). High-order resonators possess high effective stiffness, resulting in large motional impedance. To suppress anchor loss and reduce motional impedance, a novel combined tether was designed and comprehensively optimized. The resonators were batch fabricated based on a reliable and simple silicon-on-insulator (SOI)-based fabrication process. The combined tether experimentally contributes to low anchor loss and motional impedance. Especially in the 4th WEM, the resonator with a resonance frequency of 1.1 GHz and a Q of 10,920 was demonstrated, corresponding to the promising f × Q product of 1.2 × 1013. By using combined tether, the motional impedance decreases by 33% and 20% in 3rd and 4th modes, respectively. The WEM resonator proposed in this work has potential application for high-frequency wireless communication systems

Developing Qualitative Plasmid DNA Reference Materials to Detect Mechanisms of Quinolone and Fluoroquinolone Resistance in Foodborne Pathogens

The aim of this study was to develop homogeneous and stable plasmid DNA reference materials for detecting the mechanisms of resistance to quinolones and fluoroquinolones in foodborne pathogens. The DNA fragments of 11 target genes associated with quinolone and fluoroquinolone resistance were artificially synthesized, inserted into plasmid vectors, and transferred into recipient cells. PCR and sequencing of DNA were performed to assess the genetic stability of the target DNA in recombinant Escherichia coli DH5&alpha; cells during subculturing for 15 generations. The limit of detection (LOD) of the target DNA was determined using PCR and real-time qualitative PCR (qPCR). The homogeneity and storage stability of plasmid DNA reference materials were evaluated in terms of plasmid DNA quantity, PCR-measured gene expression, and qPCR threshold cycle. All 11 target DNAs were successfully synthesized and inserted into vectors to obtain recombinant plasmids. No nucleotide mutations were identified in the target DNA being stably inherited and detectable in the corresponding plasmids during subculturing of recombinant strains. When the target DNA was assessed using PCR and qPCR, the LOD was &le;1.77 &times; 105 and 3.26 &times; 104 copies/&mu;L, respectively. Further, when the reference materials were stored at 37 &deg;C for 13 days, 4 &deg;C for 90 days, and &minus;20 &deg;C for 300 days, each target DNA was detectable by PCR, and no mutations were found. Although the threshold cycle values of qPCR varied with storage time, they were above the LOD, and no significant differences were found in the quantity of each plasmid DNA at different timepoints. Further, the homogeneity and stability of the materials were highly consistent with the requirements of standard reference materials. To summarize, considering that our plasmid DNA reference materials conformed to standard requirements, they can be used to detect the mechanisms of quinolone and fluoroquinolone resistance in foodborne pathogens