Mathematical Modelling and Experimental Evaluation of Electrostatic Sensor Arrays for the Flow Measurement of Fine Particles in a Square-shaped Pipe

Abstract—Square-shaped pneumatic conveying pipes are used in some industrial processes such as fuel injection systems in coal-fired power plants and circulating fluidized beds. However, little research has been conducted to characterise the gas–solid two-phase flow in a square-shaped pneumatic conveying pipe. This paper presents mathematical modelling and experimental assessment of novel non-restrictive electrostatic sensor arrays for the measurement of pulverised fuel flow in a square-shaped pipe. The sensor arrays consist of twelve pairs of strip-shaped electrodes, which are uniformly embedded in the four flat pipe walls. An analytical mathematical model of the sensor arrays is established and the induced charge and currents of different electrodes due to a point charge are then derived based on the model. Experimental tests were conducted on a 54 mm square-shaped pipe section of a pneumatic conveyor test rig under a range of flow conditions. The fuel velocity profile over the whole cross-section of the pipe is measured. Mathematical modelling and experimental results demonstrate that the proposed non-restrictive electrostatic sensor arrays are capable of characterising the local pulverised fuel flow in a square-shaped pneumatic conveying pipe. Index Terms—electrostatic sensor, square-shaped pipe, mathematical modelling, velocity profile, pulverised fuel

Measurement of the Mass Flow Distribution of Pulverized Coal in Primary Air Pipes Using Electrostatic Sensing Techniques

On-line measurement of pulverized fuel (PF) distribution between primary air pipes on a coal-fired power plant is of great importance to achieve balanced fuel supply to the boiler for increased combustion efficiency and reduced pollutant emissions. An instrumentation system using multiple electrostatic sensing heads are developed and installed on 510 mm bore primary air pipes of a 600 MW coal-fired boiler for the measurement of mass flow distribution of PF. An array of electrostatic electrodes with different axial widths is housed in a sensing head. An electrode with a greater axial width and three narrower electrodes are used to derive the electrostatic signals for the determination of PF mass flow rate and velocity, respectively. The measured PF velocity is used for the calibration of coal mass flow rate. On-plant comparison trials of the developed system were conducted under typical operating conditions. Isokinetic sampling equipment is used to obtain reference data to evaluate the performance of the system. Experimental data demonstrate that the developed system is effective and reliable for the on-line continuous measurement of PF mass flow distribution between the primary air pipes of the same mill

NEW INTERPRETATION ON EMG CHARATERISTICS OF SPASTIC CEREBRAL PALSY DURING A REHABILITATIVE WALKING EXERCISE

The purpose of this study is to interpret the EMG characteristics of spastic cerebral palsy children during walking with power spectrum analysis. The EMG signal of 16 cerebral palsy patients (GP) and 18 age matched control (Normal) were collected during several walking trial. It was found that our CP participants ha:d significantly longer firing duration and higher median frequency within a gait cycle for al.l the muscle groups, these indicated of the EMG characteristics of in the spastic muscles. In addition, the CP produced significantly smaller root mean square value in tibialis anterior muscle than the normal; this indicated that the tibialis anterior muscle of GP was weakness or atrophy. Because of good objectivity and reproducibility, employing RMS and the MF could :be suggested to be the parameters for further gait studies

Development and Validation of 3-Year Atrial Fibrillation Prediction Models Using Electronic Health Record With or Without Standardized Electrocardiogram Diagnosis and a Performance Comparison Among Models.

Background Improved prediction of atrial fibrillation (AF) may allow for earlier interventions for stroke prevention, as well as mortality and morbidity from other AF-related complications. We developed a clinically feasible and accurate AF prediction model using electronic health records and computerized ECG interpretation. Methods and Results A total of 671 318 patients were screened from 3 tertiary hospitals. After careful exclusion of cases with missing values and a prior AF diagnosis, AF prediction models were developed from the derivation cohort of 25 584 patients without AF at baseline. In the internal/external validation cohort of 117 523 patients, the model using 6 clinical features and 5 ECG diagnoses showed the highest performance for 3-year new-onset AF prediction (C-statistic, 0.796 [95% CI, 0.785-0.806]). A more simplified model using age, sex, and 5 ECG diagnoses (atrioventricular block, fusion beats, marked sinus arrhythmia, supraventricular premature complex, and wide QRS complex) had comparable predictive power (C-statistic, 0.777 [95% CI, 0.766-0.788]). The simplified model showed a similar or better predictive performance than the previous models. In the subgroup analysis, the models performed relatively better in patients without risk factors. Specifically, the predictive power was lower in patients with heart failure or decreased renal function. Conclusions Although the 3-year AF prediction model using both clinical and ECG variables showed the highest performance, the simplified model using age, sex, and 5 ECG diagnoses also had a comparable prediction power with broad applicability for incident AF

Thermal stress induces glycolytic beige fat formation via a myogenic state.

Environmental cues profoundly affect cellular plasticity in multicellular organisms. For instance, exercise promotes a glycolytic-to-oxidative fibre-type switch in skeletal muscle, and cold acclimation induces beige adipocyte biogenesis in adipose tissue. However, the molecular mechanisms by which physiological or pathological cues evoke developmental plasticity remain incompletely understood. Here we report a type of beige adipocyte that has a critical role in chronic cold adaptation in the absence of β-adrenergic receptor signalling. This beige fat is distinct from conventional beige fat with respect to developmental origin and regulation, and displays enhanced glucose oxidation. We therefore refer to it as glycolytic beige fat. Mechanistically, we identify GA-binding protein α as a regulator of glycolytic beige adipocyte differentiation through a myogenic intermediate. Our study reveals a non-canonical adaptive mechanism by which thermal stress induces progenitor cell plasticity and recruits a distinct form of thermogenic cell that is required for energy homeostasis and survival

Controlled release from zein matrices: Interplay of drug hydrophobicity and pH

Purpose: In earlier studies, the corn protein zein is found to be suitable as a sustained release agent, yet the range of drugs for which zein has been studied remains small. Here, zein is used as a sole excipient for drugs differing in hydrophobicity and isoelectric point: indomethacin, paracetamol and ranitidine. Methods: Caplets were prepared by hot-melt extrusion (HME) and injection moulding (IM). Each of the three model drugs were tested on two drug loadings in various dissolution media. The physical state of the drug, microstructure and hydration behaviour were investigated to build up understanding for the release behaviour from zein based matrix for drug delivery. Results: Drug crystallinity of the caplets increases with drug hydrophobicity. For ranitidine and indomethacin, swelling rates, swelling capacity and release rates were pH dependent as a consequence of the presence of charged groups on the drug molecules. Both hydration rates and release rates could be approached by existing models. Conclusion: Both the drug state as pH dependant electrostatic interactions are hypothesised to influence release kinetics. Both factors can potentially be used factors influencing release kinetics release, thereby broadening the horizon for zein as a tuneable release agent

Self-rated health in middle-aged and elderly Chinese : distribution, determinants and associations with cardio-metabolic risk factors

Background: Self-rated health (SRH) has been demonstrated to be an accurate reflection of a person's health and a valid predictor of incident mortality and chronic morbidity. We aimed to evaluate the distribution and factors associated with SRH and its association with biomarkers of cardio-metabolic diseases among middle-aged and elderly Chinese. Methods: Survey of 1,458 men and 1,831 women aged 50 to 70 years, conducted in one urban and two rural areas of Beijing and Shanghai in 2005. SRH status was measured and categorized as good (very good and good) vs. not good (fair, poor and very poor). Determinants of SRH and associations with biomarkers of cardio-metabolic diseases were evaluated using logistic regression. Results: Thirty two percent of participants reported good SRH. Males and rural residents tended to report good SRH. After adjusting for potential confounders, residence, physical activity, employment status, sleep quality and presence of diabetes, cardiovascular disease, and depression were the main determinants of SRH. Those free from cardiovascular disease (OR 3.68; 95%CI 2.39; 5.66), rural residents (OR 1.89; 95% CI 1.47; 2.43), non-depressed participants (OR 2.50; 95% CI 1.67; 3.73) and those with good sleep quality (OR 2.95; 95% CI 2.22; 3.91) had almost twice or over the chance of reporting good SRH compared to their counterparts. There were significant associations -and trend- between SRH and levels of inflammatory markers, insulin levels and insulin resistance. Conclusion: Only one third of middle-aged and elderly Chinese assessed their health status as good or very good. Although further longitudinal studies are required to confirm our findings, interventions targeting social inequalities, lifestyle patterns might not only contribute to prevent chronic morbidity but as well to improve populations' perceived health

Statistical Optimization of Process Variables for Antibiotic Activity of Xenorhabdus bovienii

The production of secondary metabolites with antibiotic properties is a common characteristic to entomopathogenic bacteria Xenorhabdus spp. These metabolites not only have diverse chemical structures but also have a wide range of bioactivities of medicinal and agricultural interests. Culture variables are critical to the production of secondary metabolites of microorganisms. Manipulating culture process variables can promote secondary metabolite biosynthesis and thus facilitate the discovery of novel natural products. This work was conducted to evaluate the effects of five process variables (initial pH, medium volume, rotary speed, temperature, and inoculation volume) on the antibiotic production of Xenorhabdus bovienii YL002 using response surface methodology. A 25–1 factorial central composite design was chosen to determine the combined effects of the five variables, and to design a minimum number of experiments. The experimental and predicted antibiotic activity of X. bovienii YL002 was in close agreement. Statistical analysis of the results showed that initial pH, medium volume, rotary speed and temperature had a significant effect (P<0.05) on the antibiotic production of X. bovienii YL002 at their individual level; medium volume and rotary speed showed a significant effect at a combined level and was most significant at an individual level. The maximum antibiotic activity (287.5 U/mL) was achieved at the initial pH of 8.24, medium volume of 54 mL in 250 mL flask, rotary speed of 208 rpm, temperature of 32.0°C and inoculation volume of 13.8%. After optimization, the antibiotic activity was improved by 23.02% as compared with that of unoptimized conditions