Moisture conditioning of wood using a continuous microwave dryer

Lower moisture content in wood, preferably 5–6%, is desirable for many chemical modification reactions. Economically, it is not feasible to dry timber to such low moisture content by conventional drying without drying degrades. Microwave heating was evaluated and found to be effective in reducing the moisture content of radiata pine from 13% to 6% in a microwave cycle of two minutes. The energy consumption is about 55 kWh/m³. Moisture distribution profiles demonstrate very uniform drying across the sample thickness. The findings suggest that microwave heating can potentially be applied to condition wood in a very short period of time.     

Spectral characteristics of a binary dye-mixture laser

We have investigated laser action in a binary mixture of dyes, Rh-6G and DCM, resulting in tunable laser emission over an extended frequency region. The two dyes absorb the same pump radiation but fluoresce over frequency ranges that are shifted with respect to each other, thereby resulting in extended tunability. Following a time-dependent analysis of a rate-equation model that describe the operation of such a laser, theoretical estimates for optimum dye concentrations and the corresponding extension of the laser tuning range have been obtained.     

On the choice of spatial and categorical scale in remote sensing land cover classification

Our interest in this paper is on the choice of spatial and categorical scale, and their interaction, in creating classifications of land cover from remotely sensed measurements. We note that in discussing categorical scale, the concept of spatial scale naturally arises, and in discussing spatial scale, the issue of aggregation of measurements must be considered. Therefore, and working towards an ultimate goal of producing multiscale, multigranular characterizations of land cover, we address here successively and in a cumulative fashion the topics of (1) aggregation of measurements across multiple scales, (2) adaptive choice of spatial scale, and (3) adaptive choice of categorical scale jointly with spatial scale. We show that the use of statistical finite mixture models with groups of original pixel-scale measurements, at successive spatial scales, offers improved pixel-wise classification accuracy as compared to the commonly used technique of label aggregation. We then show how a statistical model selection strategy may be used with the finite mixture models to provide a data-adaptive choice of spatial scale, varying by location (i.e., multiscale), from which classifications at least as accurate as those of any single spatial scale may be achieved. Finally, we extend this paradigm to allow for jointly adaptive selection of spatial and categorical scale. Our emphasis throughout is on the empirical quantification of the role of the various elements above, and a comparison of their performance with standard methods, using various artificial landscapes. The methods proposed in this paper should be useful for a variety of scale-related land cover classification tasks.     

Estimation of the magnitude and spatial distribution of combustible materials in urban areas. A case study of the San Jose area,California

This paper describes a methodology for estimating the magnitude and spatial distribution of urban fuel loadings using San Jose, California, as a case study. The study was undertaken to provide basic inputs into the modeling of large urban fires ignited by nuclear explosions, which has important implications for studies of the global climatic effects of nuclear war, or the so-called ‘nuclear winter’ phenomenon. The methodology is based on the measurement of the numbers and sizes of different building occupancy types from aerial photographs for approximately 6000 1000-ft (304.8-m) grid cells covering the study area. These measurements were combined with literature-derived average fuel loadings for each building type to yield the total fuel loading per cell. The total fuel loading thus calculated is approximately 4558.56 × 10⁶ kg, yielding an average of 8.4 kg m⁻² (1.7 lb ft⁻²) for the built-up area of the city and 9.4 kg m⁻² (1.9 lb ft⁻²) if unoccupied cells (i.e. cells containing no fuel) within the built-up area are excluded. These figures are lower than previously published average values, due to the low-density character of San Jose and the exclusion of certain components of total fuel loading by the methodology.     

Role of the stimulated-emission rate in the photostability of solid-state dye lasers

The lasing and photostability characteristics of Rhodamine 6G and Pyrromethene 567 dyes dispersed in polymeric host materials have been investigated as a function of the intensities of incident pump and signal beams in a longitudinally pumped dye laser in an oscillator-amplifier configuration. A substantial reduction in the rate of photodegradation was observed under lasing conditions and with increasing signal intensity in a dye amplifier, establishing that the service lives of these materials improve with an increase in the rate of stimulated emission. We observed approximately 62% amplifier efficiency at 2 Hz operation and 10% reduction in amplifier efficiency at 10 Hz operation after exposure of 72,000 pulses by use of a Pyrromethene disk.     

Gender difference in color preference across cultures: An archetypal pattern modulated by a female cultural stereotype

A gender difference in color preference among British participants has been repeatedly reported, in which both males and females show a preference for blue‐green colors, while females express an additional preference for pink‐purple colors. To investigate the robustness of gender difference in color preference in a different culture, we tested 81 young adult Indians from a school of design and compared them to 80 young British students in Psychology. The 35‐item International Personality Item Pool (IPIP) and Bem Sex Role Inventory (BSRI) questionnaires were also administered to explore possible links between personality traits, gender schemata, and color preferences. Results confirmed a gender difference in both cultures; participants collectively expressed a preference for cool over warm colors, while in addition females showed a preference for pink colors, with a warm bias for Indian females and a cool bias for British females. While these results extend gender difference to Indian culture and support the universality of an underlying pattern they also reveal a culture‐specific contribution essentially observed in females. In British participants, color preference was correlated exclusively with BSRI scores in females and overwhelmingly with IPIP scores in males; this gender‐specific pattern of correlation was not replicated in the Indian sample. Results point to an archetypal pattern of gender difference in color preference with a remarkable cross‐cultural similarity in men and a subtle but significant cultural difference in women whose origin is yet to be explained.     

A data constrained approach for brain tumour detection using fused deep features and SVM

Multimedia Tools and Applications - The identification of MR images of the brain with tumours is one of the most critical tasks of any brain tumour (BT) detection system. Interestingly, because of...     

Identification of wheat tiller based on AlexNet-feature fusion

Wheat genotype identification is possible with proper recognition of its tiller. It is again challenging to recognize the wheat tiller in complex imaging conditions such as blurred image due to motion and dense appearance due to overlap of heads. The identification of wheat tiller helps to recognize the wheat genotypic and provides knowledge about the variability of growth stages, the orientation of the head, and the presence of awn. This research considered the Global Wheat Head Detection (GWHD) dataset with seven traits of wheat. The multi-feature fusion technique is adapted in AlexNet to enhance the performance of the classifier. The fc6 feature and fc7 feature of AlexNet are concatenated and fed to Linear-SVM to classify the seven traits of wheat and achieved 94.14% of accuracy.

     

Evaluation of an Accurate Mass Approach for the Simultaneous Detection of Drug and Metabolite Distributions via Whole-Body Mass Spectrometric Imaging

In drug discovery and development, in vitro absorption and metabolism assays along with in vivo pharmacokinetic (PK), pharmacodynamic (PD), and toxicokinetic (TK) studies are used to evaluate a potential drug candidate. More recently, imaging mass spectrometry approaches have been successfully reported to aid in the preclinical assessment of drug candidates, resulting in the rapid and noteworthy acceptance of the technique in pharmaceutical research. Traditionally, drug distribution studies via mass spectrometric imaging (MSI) are performed as targeted MS/MS analyses, where the analytes of interest, drug and/or metabolite, are known before the imaging experiment is performed. The study presented here describes a whole-body mass spectrometric imaging (WB-MSI) approach using a hybrid MALDI-LTQ-Orbitrap-MS to detect the distribution of reserpine at 2 h post a 20 mg/kg oral dose. This study effectively demonstrates the utility of obtaining accurate mass measurements across a wide mass range combined with postprocessing tools to efficiently identify drug and metabolite distributions without the need for any a priori knowledge.