Mn-containing AlPO-11 and SAPO-11 catalysts for simultaneous isomerization and dehydrogenation of n-butane

MnAPO-11 and MnAPSO-11 were synthesized hydrothermally, and supported Mn-AlPO-11 and Mn-SAPO-11 were also prepared for comparison. Characterization results showed that there were differences in acidity and reducibility caused by the different incorporation methods of manganese. The manganese species in the samples also weakened the metallic properties of the palladium particles when the latter was added into the catalysts. Catalytic testing results for dehydroisomerization of n-butane indicated that incorporation of manganese increased the selectivity toward isomerization products. The highest isobutene selectivity (34.86%) could be obtained over a Pd/MnAPO-11 catalyst. When a combined catalyst system containing Pd/SAPO-11 and MnAPSO-11 was used in a single bed of two layers, the isobutene selectivity could be greatly improved, as compared to the single catalyst alone.

Analysis of amphetamines in urine with liquid-liquid extraction by capillary electrophoresis with simultaneous electrochemical and electrochemiluminescence detection

Amphetamines including methamphetamine, 3,4-methylenedioxyamphetamine and 3,4-methylenedioxymethamphetamine were separated and detected by CE using simultaneous electrochemical (EC) and electrochemiluminescence (ECL) detection (CE-EC/ ECL). Factors that influenced the separation and detection performance, such as the detection potential, the pH value and concentration of the running buffer, the separation voltage and the pH of the detection buffer, were investigated.

A novel technique for NACE coupled with simultaneous electrochemiluminescence and electrochemical detection for fast analysis of tertiary amines

A simultaneous electrochemiluminescence (ECL) and electrochemical (EC) detection scheme for NACE was presented for fast analysis of tertiary amines. Both ECL and EC signals were generated at the same Pt electrode. Triethylamine (TEA), tripropylamine (TPrA), chlorpromazine, promethazine, and dioxopromethazine (DPZ) were selected to validate NACE-ECL/EC dual detection strategy. The linear ranges for TEA and TPrA were 0.01-500 and 0.01-10 mu M with the detection limits of 8.0 and 5.0 nM (S/N=3), respectively. The RSDs (n = 6) of the migration time and the ECL intensity for 1 mu M TEA and 0.5 mu M TPrA were 0.1 and 2.8%, and 0.2 and 1.8% with theoretical plate numbers of 180 000 and 700 000 per meter, respectively. These two analytes could be separated within 92 s and the Pt electrode did not need reactivation during the experiments.

Shape and Phase-Controlled Synthesis of KMgF3 Colloidal Nanocrystals via Microwave Irradiation

In this paper, we present a facile one-step route to controlled synthesis of colloidal KMgF3 nanocrystals via the thermolysis of metal trifluoroacetate precursors in combined solvents (OA/OM) using microwave irradiation. X-ray diffraction (XRD), transmission electron microscopy (TEM), thermogravimetric and differential thermal analysis (TG-DTA), Fourier transform infrared (FT-IR) spectra, and photoluminescence (PL) spectra were employed to characterize the samples. Only through the variation of the OA/OM ratio, can the phase and shape of nanocrystals be readily controlled, resulting in the formation of well-defined near-spherical nanoparticles, and nanoplates of cubic-phased KMgF3, as well as nanorods of tetragonal-phased MgF2, and a possible mechanism has been proposed to elucidate this effect. Furthermore, all these samples in this system can be well dispersed in nonpolar solvents such as cyclohexane to form stable and clear colloidal solutions, due to the successful coating of organic surfactants (OA/OM) on the nanocrystal surface.

Vectorizing Face Images by Interpreting Shape and Texture Computations

The correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. This representation has two components: (1) shape, or (x, y) feature locations, and (2) texture, defined as the image grey levels mapped onto the standard reference image. This paper explores an automatic technique for "vectorizing" face images. Our face vectorizer alternates back and forth between computation steps for shape and texture, and a key idea is to structure the two computations so that each one uses the output of the other. A hierarchical coarse-to-fine implementation is discussed, and applications are presented to the problems of facial feature detection and registration of two arbitrary faces.

Simultaneous Localization and Recognition of Dynamic Hand Gestures

A framework for the simultaneous localization and recognition of dynamic hand gestures is proposed. At the core of this framework is a dynamic space-time warping (DSTW) algorithm, that aligns a pair of query and model gestures in both space and time. For every frame of the query sequence, feature detectors generate multiple hand region candidates. Dynamic programming is then used to compute both a global matching cost, which is used to recognize the query gesture, and a warping path, which aligns the query and model sequences in time, and also finds the best hand candidate region in every query frame. The proposed framework includes translation invariant recognition of gestures, a desirable property for many HCI systems. The performance of the approach is evaluated on a dataset of hand signed digits gestured by people wearing short sleeve shirts, in front of a background containing other non-hand skin-colored objects. The algorithm simultaneously localizes the gesturing hand and recognizes the hand-signed digit. Although DSTW is illustrated in a gesture recognition setting, the proposed algorithm is a general method for matching time series, that allows for multiple candidate feature vectors to be extracted at each time step.

On the Interaction between Data Aggregation and Topology Control in Wireless Sensor Networks

Wireless sensor networks are characterized by limited energy resources. To conserve energy, application-specific aggregation (fusion) of data reports from multiple sensors can be beneficial in reducing the amount of data flowing over the network. Furthermore, controlling the topology by scheduling the activity of nodes between active and sleep modes has often been used to uniformly distribute the energy consumption among all nodes by de-synchronizing their activities. We present an integrated analytical model to study the joint performance of in-network aggregation and topology control. We define performance metrics that capture the tradeoffs among delay, energy, and fidelity of the aggregation. Our results indicate that to achieve high fidelity levels under medium to high event reporting load, shorter and fatter aggregation/routing trees (toward the sink) offer the best delay-energy tradeoff as long as topology control is well coordinated with routing.

Modeling the evolution of regulatory elements by simultaneous detection and alignment with phylogenetic pair HMMs.

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.