Authenticity green coffee bean species and geographical origin using near-infrared spectroscopy combined with chemometrics

To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.     

Effect of Supports and Promoters on the Performance of Ni-Based Catalysts in Ethanol Steam Reforming

Ethanol steam reforming (ESR) is one of the potential processes to convert ethanol into valuable products. Hydrogen produced from ESR is considered as green energy for the future and can be an excellent alternative to fossil fuels with the aim of mitigating the greenhouse gas effect. The ESR process has been well studied, using transition metals as catalysts coupled with both acidic and basic oxides as supports. Among various reported transition metals, Ni is an inexpensive material with activity comparable to that of noble metals, showing promising ethanol conversion and hydrogen yields. Additionally, different promoters and supports were utilized to enhance the hydrogen yield and the catalyst stability. This review summarizes and discusses the influences of the supports and promoters of Ni-based catalysts on the ESR process.     

Towards a Dual-Tip STM Application in Mesoscopic Electron Transport

A new design for a dual-tip scanning tunneling microscope (STM) is presented. The design is a variation on the mechanically controllable break-junction with two electron beam-induced deposition nano-tips. The new design enables one to scan surfaces simultaneously with two probes having a nano-gap separation. By collecting the lateral current flowing between the tips, the transconductance map can then be compared with the STM images for local characterizations of the electron transport. Since the lateral beam carries the property of the density of states of the surface at momentum space, the dispersion of the electronic structure should give an orientation and position dependence of the local transconductance current. In addition, the reduced terminal separation, on the order of the characteristic mesoscopic length scales, is likely to be sensitive to a variety of typically observed interactions and interference effects.     

Aspects of oligonucleotide and peptide sequencing with MALDI and electrospray mass spectrometry

Biopolymer sequencing with mass spectrometry has become increasingly important and accessible with the development of matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI). Here we examine the use of sequential digestion for the rapid identification of proteolytic fragments, in turn highlighting the general utility of enzymatic MALDI ladder sequencing and ESI tandem mass spectrometry. Analyses were performed on oligonucleotides ranging in size from 2 to 50 residues, on peptides ranging in size from 7 to 44 residues and on viral coat proteins. MALDI ladder sequencing using exonuclease digestion generated a uniform distribution of ions and provided complete sequence information on the oligonucleotides 2-30 nucleic acid residues long. Only partial sequence information was obtained on the longer oligonucleotides. C-terminal peptide ladder sequencing typically provided information from 4 to 7 amino acids into the peptide. Sequential digestion, or endoprotease followed by exoprotease exposure, was also successfully applied to a trypsin digest of viral proteins. Analysis of ladder sequenced peptides by LCMS generated less information than in the MALDI-MS analysis and ESI-MS2 normally provided partial sequence information on both the small oligonucleotides and peptides. In general, MALDI ladder sequencing offered information on a broader mass range of biopolymers than ESI-MS2 and was relatively straightforward to interpret, especially for oligonucleotides.     

Wireless transmission of HD video using H.264 compression over UWB channel

With the technological advancement, entertainment has become revolutionized and the high-definition (HD) video has become an integral feature of our modern amusement system. The demand for wireless transmission of HD video is rapidly rising for its ubiquitous nature, easy installation and relocation. Such wireless transmissions of HD video streams require very high bandwidth. The ultra-wideband (UWB) offers a large bandwidth, and short-range high-speed data transmission at low cost and low power consumption. In this paper, we present the feasibility study to transmit HD video wirelessly using H.264/AVC compression over the UWB communication channel. Simulations are carried out by controlling key H.264/AVC encoder parameters such as, in-loop deblocking filter, group of pictures, and quantization parameter. Based on the analysis, an optimum setting of these parameters is proposed for different bandwidth requirements, as well as acceptable video quality. The bandwidth achieved is restricted between 1.5 and 20?Mbps with a minimum reconstruction quality of 34?dB. The HD bit stream is then transmitted over the UWB communication channel and the demonstration shows that the overall encoder performance is satisfactory with the transmission bit-error-rate (BER) in the range of 10^?5?C10^?8.     

A Stream X-Machine Tool for Modelling and Generating Test Cases for Chronic Diseases Based on State-Counting Approach

Programming and Computer Software - In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents)...     

Mood sensing from social media texts and its applications

We present a large-scale mood analysis in social media texts. We organise the paper in three parts: (1) addressing the problem of feature selection and classification of mood in blogosphere, (2) we extract global mood patterns at different level of aggregation from a large-scale data set of approximately 18 millions documents (3) and finally, we extract mood trajectory for an egocentric user and study how it can be used to detect subtle emotion signals in a user-centric manner, supporting discovery of hyper-groups of communities based on sentiment information. For mood classification, two feature sets proposed in psychology are used, showing that these features are efficient, do not require a training phase and yield classification results comparable to state of the art, supervised feature selection schemes; on mood patterns, empirical results for mood organisation in the blogosphere are provided, analogous to the structure of human emotion proposed independently in the psychology literature; and on community structure discovery, sentiment-based approach can yield useful insights into community formation.