Measuring the Compressibility of Cellulose Nanofiber-Stabilized Microdroplets Using Acoustophoresis

Droplets with a liquid perfluoropentane core and a cellulose nanofiber shell have the potential to be used as drug carriers in ultrasound-mediated drug delivery. However, it is necessary to understand their mechanical properties to develop ultrasound imaging sequences that enable in vivo imaging of the vaporization process to ensure optimized drug delivery. In this work, the compressibility of droplets stabilized with cellulose nanofibers was estimated using acoustophoresis at three different acoustic pressures. Polyamide particles of known size and material properties were used for calibration. The droplet compressibility was then used to estimate the cellulose nanofiber bulk modulus and compare it to experimentally determined values. The results showed that the acoustic contrast factor for these droplets was negative, as the droplets relocated to pressure antinodes during ultrasonic actuation. The droplet compressibility was 6.6–6.8 ×10−10 Pa−1, which is higher than for water (4.4×10−10 Pa−1) but lower than for pure perfluoropentane (2.7×10−9 Pa−1). The compressibility was constant across different droplet diameters, which was consistent with the idea that the shell thickness depends on the droplet size, rather than being constant.

Optimization of Local Contrast Factor with Adaptive Brightness Improvement: Impact on Mammogram Image Analysis

Mammography has been known worldwide as the most common imaging modalities utilized for early detection of breast cancer. The mammographic images produced are in greyscale, however they often produced low contrast images, contain artefacts and noise, as well as non-uniform illumination. These limitations can be overcame in the pre-processing stage with the image enhancement process. Therefore, in this research we developed an optimized enhancement framework where the local contrast factor is manipulated to preserve details of the image. This method aims to improve the overall image visibility without altering histogram of the original image, which will affect the segmentation and classification processes. We performed dark background removal in the image histogram at early stage to increase the efficiency of new mean histogram calculation. Then, the histogram is separated into two partitions to allow histogram clipping process to be conducted individually for underexposed and overexposed areas. Consequently, the local contrast factor optimization is conducted to preserve the image details. The results from our proposed method are compared with other methods by the measurement of peak signal-to-noise ratio, structural similarity index, average contrast, and average entropy difference. The results portrayed that our proposed method yield better quality over the others with highest peak signal-to-noise ratio of 32.676. In addition, in terms of qualitative analysis, our proposed method depicted better lesion segmentation with smoother shape of the lesion.

Edge Enhancement Method for Detection of Text From Handwritten Documents

Edge detection from handwritten text documents, particularly of Kannada language, is a challenging task. Kannada has a huge character set, amounting to 17,340 character combinations. Moreover, in handwritten Kannada, the character strokes are highly variable in size and shape due to varying handwriting styles. This chapter presents a solution for edge detection of Kannada handwritten documents. Sobel edge detection method, which efficiently enhances the image contrast and detects the character edges, is proposed. Experimentation of this edge detection approach yielded high F-measure and global contrast factor values.

The Preference for Joint Attributions to Contrast-factor Attributions in Causal Contrast Situations

A current issue about causal attribution is whether people take simple contrast-factor attributions or complex joint attributions in contrast situations. For example, a stone does not dissolve in water, and a piece of salt dissolves in water. That the piece of salt dissolves in water is due to which? (A. The influence of the piece of salt; B. The influence of the water; C. The joint influence of the piece of salt and the water). For such questions, we propose a mechanism-based sufficiency account. It argues that causal attributions are guided by mechanism-based explanatory sufficiency, and people prefer a causal attribution based on mechanism knowledge if it is sufficient for an effect than other available attributions. This account predicts the sufficient joint attribution (the C option), whereas the conventional covariation approach predicts the contrast-factor attribution (the A option). Two experiments investigated whether contrast situations affect causal attributions for compound causation with explicit mechanism information and simple causation without explicit mechanism information, respectively. Both experiments showed that contrast situations didn’t affect causal attributions. In both the presence and absence of contrast situations, the majority of participants preferred sufficient joint attributions to simple contrast-factor attributions regardless of whether explicit mechanism information was present. These findings favor the mechanism-based sufficiency account rather than the covariation approach and the complexity account. In contrast situations, the predominance of joint attributions implies that explanatory complexity affects causal attributions by the modulation of explanatory sufficiency, and people prefer mechanism-based joint attributions that provide sufficient explanations for effects. The present findings are beyond the existing approaches to causal attributions.

A Novel Contrast Enhancement Technique Based on Combination of Local and Global Statistical Data on Malaria Images

Malaria appears to be one of the main reasons for detrimental health issue at the global scale that is responsible for approximately half a million deaths every year. As the cases of malaria seem to escalate at an annual rate, it is vital to provide a rapid and accurate diagnosis through manual microscopic assessment in the attempt to control the spread of malaria. Nevertheless, varied staining steps and noise disruptions can cause inaccurate diagnosis due to wrong interpretation. Hence, to address such issues, this study investigated the performance upon removing background noise and the method of correcting illumination that has an impact upon segmentation for a computer-assisted diagnostic system. The findings display that the technique of based on Otsu threshold and statistic data used to enhance the contrast image as to determine cells infected by the malaria parasite, in comparison to other methods. In fact, this method was tested on 450 malaria images, which consisted of P. Vivax, P. Falciparum, and P. Knowlesi species at the stages of trophozoite, schizont, and gametocyte. As a result, the HSE approach yielded 1.31 for Global Contrast Factor (GCF), while 10.56 for Signal Noise Ratio (SNR).

Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud Model

The process of creating nonphotorealistic rendering images and animations can be enjoyable if a useful method is involved. We use an evolutionary algorithm to generate painterly styles of images. Given an input image as the reference target, a cloud model-based evolutionary algorithm that will rerender the target image with nonphotorealistic effects is evolved. The resulting animations have an interesting characteristic in which the target slowly emerges from a set of strokes. A number of experiments are performed, as well as visual comparisons, quantitative comparisons, and user studies. The average scores in normalized feature similarity of standard pixel-wise peak signal-to-noise ratio, mean structural similarity, feature similarity, and gradient similarity based metric are 0.486, 0.628, 0.579, and 0.640, respectively. The average scores in normalized aesthetic measures of Benford’s law, fractal dimension, global contrast factor, and Shannon’s entropy are 0.630, 0.397, 0.418, and 0.708, respectively. Compared with those of similar method, the average score of the proposed method, except peak signal-to-noise ratio, is higher by approximately 10%. The results suggest that the proposed method can generate appealing images and animations with different styles by choosing different strokes, and it would inspire graphic designers who may be interested in computer-based evolutionary art.

Percepción del estudiantado sobre la evaluación del aprendizaje en la educación superior

This research aimed to know university students’ perception about learning assessment carried out by their teachers, their level of objectivity and skill, among other aspects. The study was conducted in Medellin, Colombia, between January and July 2015. A final sample size of 400 university students from public and private institutions, randomly selected, was used. The data analysis was carried out by using multivariate analysis of variance (MANOVA) with orthogonal-type canonical contrast, factor analysis, and one-dimensional type frequency analysis. It was found that university students have a good perception about the assessment practices of their teachers. Likewise, highly significant differences between men and women in their perception of learning assessment were identified. Students consider that learning assessment practices have contributed to improve their learning and are in accordance with the learning objectives. Nevertheless, most students have felt that their teachers are not objective in evaluation and they often use questions that confuse students, and very theoretical questions without application to practice. A lack of non-traditional assessment practices, such as peer assessment, self-assessment as well as virtual platforms use for assessments, was found. These findings imply the need to improve teacher training on assessment skills to allow them to plan evaluation as a strategy to improve learning, involving students in an active way.

Evaluation of Potential Clinical Surrogate Markers of a Trauma Induced Alteration of Clotting Factor Activities

Objective.The aim of this study was to identify routinely available clinical surrogate markers for potential clotting factor alterations following multiple trauma.Methods.In 68 patients admitted directly from the scene of the accident, all soluble clotting factors were analyzed and clinical data was collected prospectively. Ten healthy subjects served as control group.Results.Patients showed reduced activities of clotting factors II, V, VII, and X and calcium levels (allP<0.0001to 0.01). Levels of hemoglobin and base deficit correlated moderately to highly with the activities of a number of clotting factors. Nonsurvivors and patients who needed preclinical intubation or hemostatic therapy showed significantly reduced factor activities at admission. In contrast, factor VIII activity was markedly elevated after injury in general (P<0.0001), but reduced in nonsurvivors (P<0.05).Conclusions.Multiple trauma causes an early reduction of the activities of nearly all soluble clotting factors in general. Initial hemoglobin and, with certain qualifications, base deficit levels demonstrated a potential value in detecting those underlying clotting factor deficiencies. Nevertheless, their role as triggers of a hemostatic therapy as well as the observed response of factor VIII to multiple trauma and also its potential prognostic value needs further evaluation.