Sampling and analysis of nanoparticles with cold fibre SPME device

A new approach is described to capture nano‐size aerosols on internally‐cooled micro tubing of the solid‐phase microextraction (SPME) device followed by convenient introduction of the collected analytes into analytical instrument. Particles were generated using an aerosol formation by homogeneous nucleation of an organic vapor, and subsequent growth to nano‐size particles by coagulation of decanedioic acid, bis[2‐ethylhexyl] ester (DEHS). The approach was validated by using carbon dioxide‐cooled micro tubing to collect the nanosize DEHS particles followed by analyses on GC‐flame ionization detector (FID). Particle size ranged from 150 to 590 nm. Temperature difference between the SPME device and DEHS particles mixture created a temperature gradient and resulted in thermophoretic effect that was determining the extraction rate. SPME device was cooled to as low as –75°C, while the DEHS remained close to room temperature. Several aspects of nanoparticle sampling were tested to demonstrate the principle of the sampling approach. These included the effects of thermal gradient, sample flow rate, sampling time, CO₂ delivery mode (constant coolant delivery vs. constant temperature), and particle size. Results were normalized to measure particulate concentrations using direct sampling with PTFE filters. Nanoparticle extractions of DEHS mass were proportional to sampling time. Normalized mass of DEHS extracted increased with increase in temperature gradient and with increase of the cross flow velocity. Preliminary results indicate that the variation of heat transfer boundary layer caused by the variation in the cross flow velocity produce self‐compensating effect at constant coolant delivery, indicating that this approach could be used for field determinations including the time‐weighted average sampling of nanoparticles. Thus, it may be possible to develop simple device based on this concept for field applications.     

Quality and timeliness in medical laboratory testing

In terms of testing, modern laboratory medicine can be divided into centralized testing in central laboratories and point-of-care testing (POCT). Centralized laboratory medicine offers high-quality results, as guaranteed by the use of quality management programs and the excellence of the staff. POCT is performed by clinical staff, and so such testing has moved back closer to the patient. POCT has the advantage of shortening the turnaround time, which potentially benefits the patient. However, the clinical laboratory testing expertise of clinical staff is limited. Consequently, when deciding which components of laboratory testing must be conducted in central laboratories and which components as POCT (in relation to quality and timeliness), it will be medical necessity, medical utility, technological capabilities and costs that will have to be ascertained. Provided adequate quality can be guaranteed, POCT is preferable, considering its timeliness, when testing vital parameters. It is also preferred when the central laboratory cannot guarantee the delivery of results of short turn-around-time (STAT) markers within 60 or (even better) 30 min. POCT should not replace centralized medical laboratory testing in general, but it should be used in cases where positive effects on patient care have been clearly demonstrated.     

Numerical differentiation inspired by a formula of R.P. Boas

First, we briefly discuss three classes of numerical differentiation formulae, namely finite difference methods, the method of contour integration, and sampling methods. Then we turn to an interpolation formula of R.P. Boas for the first derivative of an entire function of exponential type bounded on the real line. This formula may be classified as a sampling method. We improve it in two ways by incorporating a Gaussian multiplier for speeding up convergence and by extending it to higher derivatives. For derivatives of order s, we arrive at a differentiation formula with N^′ nodes that applies to all entire functions of exponential type without any additional restriction on their growth on the real line. It has an error bound that converges to zero like e^-αN/N^m as N→∞, where α>0 and N^′=2N, m=3/2 for odd s while N^′=2N+1, m=5/2 for even s. Comparable known formulae have stronger hypotheses and, for the same α, they have m=1/2 only. We also deduce a direct (error-free) generalization of Boas’ formula (Corollary 5). Furthermore, we give a modification of the main result for functions analytic in a domain and consider an extension to non-analytic functions as well. Finally, we illustrate the power of the method by examples.     

Paley-Wiener Approximations and Multiscale Approximations in Sobolev and Besov Spaces on Manifolds

An approximation theory by bandlimited functions (≡ Paley-Wiener functions) on Riemannian manifolds of bounded geometry is developed. Based on this theory multiscale approximations to smooth functions in Sobolev and Besov spaces on manifolds are obtained. The results have immediate applications to the filtering, denoising and approximation and compression of functions on manifolds. There exists applications to problems arising in data dimension reduction, image processing, computer graphics, visualization and learning theory.      

Discovering New Classes of <Emphasis Type="Italic">Brugia malayi</Emphasis> Asparaginyl-tRNA Synthetase Inhibitors and Relating Specificity to Conformational Change

SLIDE software, which models the flexibility of protein and ligand side chains while docking, was used to screen several large databases to identify inhibitors of Brugia malayi asparaginyl-tRNA synthetase (AsnRS), a target for anti-parasitic drug design. Seven classes of compounds identified by SLIDE were confirmed as micromolar inhibitors of the enzyme. Analogs of one of these classes of inhibitors, the long side-chain variolins, cannot bind to the adenosyl pocket of the closed conformation of AsnRS due to steric clashes, though the short side-chain variolins identified by SLIDE␣apparently bind isosterically with adenosine. We hypothesized that an open conformation of the motif 2 loop also permits the long side-chain variolins to bind in the adenosine pocket and that their selectivity for Brugia relative to human AsnRS can be explained by differences in the sequence and conformation of this loop. Loop flexibility sampling using Rigidity Optimized Conformational Kinetics (ROCK) confirms this possibility, while scoring of the relative affinities of the different ligands by SLIDE correlates well with the compounds’ ranks in inhibition assays. Combining ROCK and SLIDE provides a promising approach for exploiting conformational flexibility in structure-based screening and design of species selective inhibitors.     

Approximation error of the Whittaker cardinal series in terms of an averaged modulus of smoothness covering discontinuous signals

The Whittaker-Shannon-Kotel'nikov sampling theorem enables one to reconstruct signals f bandlimited to [−πW,πW] from its sampled values f(k/W), k∈Z, in terms of

     

石家庄地区某场地不同取样方法获取土样的对比分析

采取原状土样是工程勘察中的重要环节,不同的取样方法对土样质量的影响不同。一般认为竖井中采取的大块土样,是"真正"的原状样,钻孔中使用取土器采取的原状样存在不同程度的扰动。在钻孔中采用不同的取样方法,土样受到的扰动程度也不一样。笔者通过对钻孔两种方法获取的土样与竖井土样试验数据的对比发现,钻孔取样对土样有明显的扰动和压密作用,造成了土的干密度增大、孔隙比减小、渗透系数降低、压缩模量增大。同时发现,钻孔快速冲入取样质量略好于上部击入取样质量。为保证工程安全,对常规钻孔取样试验成果的使用应当慎重,对重要工程宜采用探坑、竖井取样,或采用双筒薄壁取土技术。     

Speeding up COMPASS for high-dimensional discrete optimization via simulation

The convergent optimization via most promising area stochastic search (COMPASS) algorithm is a locally convergent random search algorithm for solving discrete optimization via simulation problems. COMPASS has drawn a significant amount of attention since its introduction. While the asymptotic convergence of COMPASS does not depend on the problem dimension, the finite-time performance of the algorithm often deteriorates as the dimension increases. In this paper, we investigate the reasons for this deterioration and propose a simple change to the solution-sampling scheme that significantly speeds up COMPASS for high-dimensional problems without affecting its convergence guarantee.     

Random sampling of bandlimited signals on graphs

We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, i.e., independent of the graph structure, and its performance depends on a parameter called the graph coherence. On the contrary, the second strategy is adaptive but yields optimal results. Indeed, no more than $O(k\log ?(k))$ measurements are sufficient to ensure an accurate and stable recovery of all k-bandlimited signals. This second strategy is based on a careful choice of the sampling distribution, which can be estimated quickly. Then, we propose a computationally efficient decoder to reconstruct k-bandlimited signals from their samples. We prove that it yields accurate reconstructions and that it is also stable to noise. Finally, we conduct several experiments to test these techniques.     

Bayesian Sampling Plans for Exponential Distribution Based on Type I Censoring Data

We study variable sampling plans for the exponential distribution based on type I censoring data. Using a suitable loss function, a Bayesian variable sampling plan (n _B , t _B , _B ) is derived. For certain prior distributions and loss functions, the numerical values of the Bayesian sampling plans and the associated minimum Bayes risks are tabulated. In terms of Bayes risks, comparisons between the proposed Bayesian sampling plans (n _B , t _B , _B ) and the Bayesian variable sampling plans (n ₀, t ₀, ^L _{T 0}) of Lam (1994, Ann. Statist., 22, 696–711) have been made. The numerical results indicate that under the same conditions, the proposed Bayesian sampling plan is superior to that of Lam in the sense that the Bayes risk of (n _B , t _B , _B ) is less than that of (n ₀, t ₀, ^L _{T 0}).