Theoretical and experimental studies of a novel cone-jet sensor

Modeling of a novel cone-jet sensor using two-dimensional (2-D) finite element analysis was investigated for dimensional measurement. Theoretical and experimental studies demonstrated that a cone-jet sensor supplied with air can be used to accurately measure displacement, and its work range of 1.5 to 4.2 mm is some ten times greater than a simple back-pressure sensor. It is anticipated that this type of sensor will find wide applications in manufacturing industry due to its wider working range, high precision, and other features

Potentials to differentiate milk composition by different feeding strategies

To investigate the effect of the dietary intake of the cow on milk composition, bulk-tank milk was collected on 5 occasions from conventional (n = 15) and organic (n = 10) farms in Denmark and on 4 occasions from low-input nonorganic farms in the United Kingdom, along with management and production parameters. Production of milk based on feeding a high intake of cereals, pasture, and grass silage resulted in milk with a high concentration of α-linolenic acid (9.4 ± 0.2 mg/ kg of fatty acids), polyunsaturated fatty acids (3.66 ± 0.07 mg/kg of fatty acids), and natural stereoisomer of α-tocopherol (RRR-α-tocopherol, 18.6 ± 0.5 mg/kg of milk fat). A milk production system using a high proportion of maize silage, by-products, and commercial concentrate mix was associated with milk with high concentrations of linoleic acid (LA; 19.7 ± 0.4 g/kg of fatty acids), monounsaturated fatty acids (27.5 ± 0.3 mg/kg of fatty acids), and a high ratio between LA and α-linolenic acid (4.7 ± 0.2). Comparing these 2 production systems with a very extensive nonorganic milk production system relying on pasture as almost the sole feed (95 ± 4% dry matter intake), it was found that the concentrations of conjugated LA (cis-9,trans-11; 17.5 ± 0.7 g/kg of fatty acids), trans-11-vaccenic acid (37 ± 2 g/kg of fatty acids), and monounsaturated fatty acids (30.4 ± 0.6 g/kg of fatty acids) were higher in the extensively produced milk together with the concentration of antioxidants; total α-tocopherol (32.0 ± 0.8 mg/kg of milk fat), RRR-α-tocopherol (30.2 ± 0.8 mg/kg of milk fat), and β-carotene (9.3 ± 0.5 mg/kg of milk fat) compared with the organic and conventional milk. Moreover, the concentration of LA (9.2 ± 0.7 g/kg of fatty acids) in milk from the extensive milk production system was found to approach the recommended unity ratio between n-6 and n-3, although extensive milk production also resulted in a lower daily milk yield

Optimization of sensor locations for measurement of flue gas flow in industrial ducts and stacks using neural networks

This paper presents a novel application of neural network modeling in the optimization of sensor locations for the measurement of flue gas flow in industrial ducts and stacks. The proposed neural network model has been validated with an experiment based upon a case-study power plant. The results have shown that the optimized sensor location can be easily determined with this model. The industry can directly benefit from the improvement of measurement accuracy of the flue gas flow in the optimized sensor location and the reduction of manual measurement operation with Pitot tube

Investigation of potential of differential absorption Lidar techniques for remote sensing of atmospheric pollutants

The NASA multipurpose differential absorption lidar (DIAL) system uses two high conversion efficiency dye lasers which are optically pumped by two frequency-doubled Nd:YAG lasers mounted rigidly on a supporting structure that also contains the transmitter, receiver, and data system. The DIAL system hardware design and data acquisition system are described. Timing diagrams, logic diagrams, and schematics, and the theory of operation of the control electronics are presented. Success in obtaining remote measurements of ozone profiles with an airborne systems is reported and results are analyzed

The social geography of childcare: 'making up' the middle class child

Childcare is a condensate of disparate social forces and social processes. It is gendered and classed. It is subject to an excess of policy and political discourse. It is increasingly a focus for commercial exploitation. This is a paper reporting on work in progress in an ESRC funded research project (R000239232) on the choice and provision of pre-school childcare by middle class (service class) families in two contrasting London locations. Drawing on recent work in class analysis the paper examines the relationships between childcare choice, middle class fractions and locality. It suggests that on the evidence of the findings to date, there is some evidence of systematic differences between fractions in terms of values, perspectives and preferences for childcare, but a more powerful case for intra-class similarities, particularly when it comes to putting preferences into practice in the 'making up of a middle class child' through care and education

Quantitative spectroscopy of extreme helium stars - Model atmospheres and a non-LTE abundance analysis of BD+10∘^\circ2179?

Extreme helium stars (EHe stars) are hydrogen-deficient supergiants of spectral type A and B. They are believed to result from mergers in double degenerate systems. In this paper we present a detailed quantitative non-LTE spectral analysis for BD+10$^\circ$2179, a prototype of this rare class of stars, using UVES and FEROS spectra covering the range from $\sim$3100 to 10 000 {\AA}. Atmosphere model computations were improved in two ways. First, since the UV metal line blanketing has a strong impact on the temperature-density stratification, we used the Atlas12 code. Additionally, We tested Atlas12 against the benchmark code Sterne3, and found only small differences in the temperature and density stratifications, and good agreement with the spectral energy distributions. Second, 12 chemical species were treated in non-LTE. Pronounced non-LTE effects occur in individual spectral lines but, for the majority, the effects are moderate to small. The spectroscopic parameters give $T_\mathrm{eff}$ = 17 300$\pm$300 K and $\log g$ = 2.80$\pm$0.10, and an evolutionary mass of 0.55$\pm$0.05 $M_\odot$. The star is thus slightly hotter, more compact and less massive than found in previous studies. The kinematic properties imply a thick-disk membership, which is consistent with the metallicity $[$Fe/H$]\approx-1$ and $\alpha$-enhancement. The refined light-element abundances are consistent with the white dwarf merger scenario. We further discuss the observed helium spectrum in an appendix, detecting dipole-allowed transitions from about 150 multiplets plus the most comprehensive set of known/predicted isolated forbidden components to date. Moreover, a so far unreported series of pronounced forbidden He I components is detected in the optical-UV.Comment: Accepted for publication in MNRAS, 26 pages, 19 Figure

Effect of production system and geographic location on milk quality parameters

A main reason for the rapid increase in organic food consumption is the perception that organic foods have a superior nutritional composition and/or convey health benefits. However, there is currently limited scientific knowledge about the effect of production systems on food composition. The study reported here compared fatty acid profiles and levels of fat soluble antioxidants in milk from organic and conventional production systems in 5 geographic regions in Europe (Wales, England, Denmark, Sweden and Italy). Levels of nutritionally desirable mono- and poly-unsaturated fatty acids (vaccenic acid, CLA, α-linolenic acid) and/or a range of fat soluble antioxidants were found to be significantly higher in organic milk

Time-varying Learning and Content Analytics via Sparse Factor Analysis

We propose SPARFA-Trace, a new machine learning-based framework for time-varying learning and content analytics for education applications. We develop a novel message passing-based, blind, approximate Kalman filter for sparse factor analysis (SPARFA), that jointly (i) traces learner concept knowledge over time, (ii) analyzes learner concept knowledge state transitions (induced by interacting with learning resources, such as textbook sections, lecture videos, etc, or the forgetting effect), and (iii) estimates the content organization and intrinsic difficulty of the assessment questions. These quantities are estimated solely from binary-valued (correct/incorrect) graded learner response data and a summary of the specific actions each learner performs (e.g., answering a question or studying a learning resource) at each time instance. Experimental results on two online course datasets demonstrate that SPARFA-Trace is capable of tracing each learner's concept knowledge evolution over time, as well as analyzing the quality and content organization of learning resources, the question-concept associations, and the question intrinsic difficulties. Moreover, we show that SPARFA-Trace achieves comparable or better performance in predicting unobserved learner responses than existing collaborative filtering and knowledge tracing approaches for personalized education