104 research outputs found
Minimising microbubble size through oscillation frequency control
Microbubbles are bubbles below 1 mm in size and have been extensively deployed in industrial settings to improve gaseous exchange between gas and liquid phases. The high surface to volume ratio offered by microbubbles enables them to enhance transport phenomena and therefore can be used to reduce energy demands in many applications including, waste water aeration, froth flotation, oil emulsion separations and evaporation dynamics. Microbubbles can be produced by passing a gas stream through a micro-porous diffuser placed at the gas–liquid interface. Previous work has shown that oscillating this gas steam can reduce the bubble size and therefore increase energy savings. In this work we show that it is possible to further reduce microbubble size (and consequently maximise the number of bubbles) by varying the frequency of the oscillating gas supply. Three different microbubble generation systems have been investigated; an acoustic oscillation system and a mesh membrane, a fluidic oscillator coupled to a single orifice membrane and a fluidic oscillator coupled to a commercially available ceramic diffuser. In all three bubble generation methods there is an optimum oscillation frequency at which the bubble size is minimised and the number of microbubbles maximised. In some cases a reduction in bubble size of up to 73% was achieved compared with non-optimal operating frequencies. The frequency at which this optimum occurs is dependent on the bubble generation system; more specifically the geometry of the system, the type micro-porous diffuser and the gas flow rate. This work proves that by tuning industrial microbubble generators to their optimal oscillation frequency will result in a reduction of microbubble size and increase their number density. This will further improve gaseous exchange rates and therefore improve the efficiency of the industrial processes where they are being employed to produce bubbles, leading to a reduction in associated energy costs and an increase in the overall economic and energetic feasibility of these processes
Angiotensin-converting enzyme (ACE) inhibition in type 2, diabetic patients – interaction with ACE insertion/deletion polymorphism
Angiotensin-converting enzyme (ACE) insertion(I)/deletion (D) polymorphism may modify the effect of inhibition of the renin–angiotensin–aldosterone system (RAAS) on survival and cardiorenal outcomes in type 2, diabetes. A consecutive cohort of 2089 Chinese type 2 diabetic patients with mean (±standard deviation) age of 59.7±13.1 years were genotyped for this polymorphism by polymerase chain reaction method and were followed prospectively for a median period of 44.6 (interquartile range: 23.7, 57.5) months. Clinical outcomes, including all-cause mortality, cardiovascular and renal end points, were examined. The frequency for I allele was 67.1 and 32.9% for D allele, with observed genotype frequencies of 45.8, 42.6, and 11.6% for 3, DI and DD, respectively. ACE DD polymorphism was an independent predictor for renal end point with hazard ratio (HR) (95% confidence interval) of 1.72 (1.16, 2.56), but not for cardiovascular end point or mortality. After controlling for confounding factors, including ACE I/D genotype, the usage of RAAS inhibitors was associated with reduced risk of mortality (HR 0.34 (0.23, 0.50)) and renal end point (HR 0.55 (0.40, 0.75)). On subgroup analysis, the beneficial effects on survival (II vs DI vs DD: HR 0.29 (0.16, 0.51) vs 0.25 (0.14, 0.46) vs 1.33 (0.41, 4.31)) and renoprotection (II vs DI vs DD: 0.52 (0.30, 0.90) vs 0.43 (0.25, 0.72) vs 0.95 (0.43, 2.12)) were most evident in II and DI carriers. In conclusion, inhibition of RAAS was associated with reduced risk of mortality and occurrence of renal end point in Chinese type 2 diabetic patients. These benefits were most evident among II and DI carriers
Evaluating Food Policy Councils Using Structural Equation Modeling
At least 282 Food Policy Councils (FPCs) are currently working to improve access to healthy foods in their communities by connecting food system sectors, gathering community input, and advising food policy. Empirical research on FPCs is limited. This study empirically evaluates FPCs to better understand the relationships between Organizational Capacity, Social Capital, and Council Effectiveness by testing a FPC Framework adapted from Allen and colleagues (2012). Members of all FPCs in the U.S., Canada, and Native American Tribes and First Nations were invited to complete the Food Policy Council Self-Assessment Tool (FPC-SAT). Structural equation modeling was used to test the FPC Framework. Three hundred and fifty-four FPC members from 95 councils completed the FPC-SAT. After slight modification, a revised FPC Framework was a good fit with the data (χ2 = 40.085, df = 24, p-value =.021, comparative fit index = 0.988, Tucker Lewis index = 0.982, root mean squared error of approximation = 0.044, p-close =.650). A moderation analysis revealed that community context influences the relationship between Social Capital and Council Effectiveness within the FPC Framework. The FPC Framework can guide capacity building interventions and FPC evaluations. The empirically tested framework can help FPCs efficiently work toward achieving their missions and improving their local food system
A genome-wide association study identifies novel and functionally related susceptibility loci for Kawasaki Disease
Machine Learning in Automated Text Categorization
The automated categorization (or classification) of texts into predefined
categories has witnessed a booming interest in the last ten years, due to the
increased availability of documents in digital form and the ensuing need to
organize them. In the research community the dominant approach to this problem
is based on machine learning techniques: a general inductive process
automatically builds a classifier by learning, from a set of preclassified
documents, the characteristics of the categories. The advantages of this
approach over the knowledge engineering approach (consisting in the manual
definition of a classifier by domain experts) are a very good effectiveness,
considerable savings in terms of expert manpower, and straightforward
portability to different domains. This survey discusses the main approaches to
text categorization that fall within the machine learning paradigm. We will
discuss in detail issues pertaining to three different problems, namely
document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey
D* Production in Deep Inelastic Scattering at HERA
This paper presents measurements of D^{*\pm} production in deep inelastic
scattering from collisions between 27.5 GeV positrons and 820 GeV protons. The
data have been taken with the ZEUS detector at HERA. The decay channel
(+ c.c.) has been used in the study. The
cross section for inclusive D^{*\pm} production with
and is 5.3 \pms 1.0 \pms 0.8 nb in the kinematic region
{ GeV and }. Differential cross
sections as functions of p_T(D^{*\pm}), and are
compared with next-to-leading order QCD calculations based on the photon-gluon
fusion production mechanism. After an extrapolation of the cross section to the
full kinematic region in p_T(D^{*\pm}) and (D^{*\pm}), the charm
contribution to the proton structure function is
determined for Bjorken between 2 10 and 5 10.Comment: 17 pages including 4 figure
Observation of Scaling Violations in Scaled Momentum Distributions at HERA
Charged particle production has been measured in deep inelastic scattering
(DIS) events over a large range of and using the ZEUS detector. The
evolution of the scaled momentum, , with in the range 10 to 1280
, has been investigated in the current fragmentation region of the Breit
frame. The results show clear evidence, in a single experiment, for scaling
violations in scaled momenta as a function of .Comment: 21 pages including 4 figures, to be published in Physics Letters B.
Two references adde
Observation of Events with an Energetic Forward Neutron in Deep Inelastic Scattering at HERA
In deep inelastic neutral current scattering of positrons and protons at the center of mass energy of 300 GeV, we observe, with the ZEUS detector, events with a high energy neutron produced at very small scattering angles with respect to the proton direction. The events constitute a fixed fraction of the deep inelastic, neutral current event sample independent of Bjorken x and Q2 in the range 3 · 10-4 \u3c xBJ \u3c 6 · 10-3 and 10 \u3c Q2 \u3c 100 GeV2
Correction: “The 5th edition of The World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms” Leukemia. 2022 Jul;36(7):1720–1748
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