MiR-10a in Pancreatic Juice as a Biomarker for Invasive Intraductal Papillary Mucinous Neoplasm by miRNA Sequencing

New biomarkers are needed to further stratify the risk of malignancy in intraductal papillary mucinous neoplasm (IPMN). Although microRNAs (miRNAs) are expected to be stable biomarkers, they can vary owing to a lack of definite internal controls. To identify universal biomarkers for invasive IPMN, we performed miRNA sequencing using tumor-normal paired samples. A total of 19 resected tissues and 13 pancreatic juice samples from 32 IPMN patients were analyzed for miRNA expression by next-generation sequencing with a two-step normalization of miRNA sequence data. The miRNAs involved in IPMN associated with invasive carcinoma were identified from this tissue analysis and further verified with the pancreatic juice samples. From the tumor-normal paired tissue analysis of the expression levels of 2792 miRNAs, 20 upregulated and 17 downregulated miRNAs were identified. In IPMN associated with invasive carcinoma (INV), miR-10a-5p and miR-221-3p were upregulated and miR-148a-3p was downregulated when compared with noninvasive IPMN. When these findings were further validated with pancreatic juice samples, miR-10a-5p was found to be elevated in INV (p = 0.002). Therefore, three differentially expressed miRNAs were identified in tissues with INV, and the expression of miR-10a-5p was also elevated in pancreatic juice samples with INV. MiR-10a-5p is a promising additional biomarker for invasive IPMN.     

A survey on video content rating: taxonomy,challenges and open issues

Multimedia Tools and Applications - Rating a video based on its content is one of the most important solutions to classify videos for audience age groups. In this regard, Film content rating and TV...     

Segmentation and recognition of phonetic features in handwritten Pitman shorthand

There is a wish to be able to enter text into mobile computing devices at the speed of speech. Only handwritten shorthand schemes can achieve this data recording rate. A new, overall solution to the segmentation and recognition of phonetic features in Pitman shorthand is proposed in this paper. Approaches to the recognition of consonant outlines, vowel and diphthong symbols and shortforms, which are different components of Pitman shorthand, are presented. A new rule is introduced to solve the issue of smooth junctions in the consonant outlines which was normally the bottleneck for recognition. Experiments with a set of 1127 consonant outlines, 2039 vowels and diphthongs and 841 shortforms from three shorthand writers have demonstrated that the proposed solution is quite promising. The recognition accuracies for consonant outlines, vowels and diphthongs, and shortforms achieved 75.33%, 96.86% and 91.86%, respectively. From the evaluation of 461 outlines with smooth junction, the introduction of the new rule has a great positive effect on the performance of the solution. The recognition accuracy of smooth junction improves from 37.53% to 93.41% given a writing time increase of 14.42%.     

Software Agent with Reinforcement Learning Approach for Medical Image Segmentation

Many image segmentation solutions are problem-based. Medical images have very similar grey level and texture among the interested objects. Therefore, medical image segmentation requires improvements although there have been researches done since the last few decades. We design a self-learning framework to extract several objects of interest simultaneously from Computed Tomography (CT) images. Our segmentation method has a learning phase that is based on reinforcement learning (RL) system. Each RL agent works on a particular sub-image of an input image to find a suitable value for each object in it. The RL system is define by state, action and reward. We defined some actions for each state in the sub-image. A reward function computes reward for each action of the RL agent. Finally, the valuable information, from discovering all states of the interest objects, will be stored in a Q-matrix and the final result can be applied in segmentation of similar images. The experimental results for cranial CT images demonstrated segmentation accuracy above 95%.     

Mechanical properties of nanostructured Mg–5 wt%Al–x wt%AlN composite synthesized from Mg chips

In the present investigation, Mg chips are recycled to produce nanostructured Mg–5wt%Al reinforced with 1, 2 and 5 wt% nanosized AlN particulates by mechanical milling (MM). Each batch of composite mixture was milled for different milling durations to produce different degrees of grain refinement. The mechanical properties such as tensile strength, ductility and hardness with respect to the effect of grain refinement, in other words, milling duration were studied. It was found that grain size played an important role in controlling ductility of the composites.     

Adsorption Behavior of Halogenated Anesthetic and Water Vapor on Cr‐Based MOF (MIL‐101) Adsorbent. Part I. Equilibrium and Breakthrough Characterizations

A synthesized chromium‐based metal organic framework (Cr‐MOF) was used for the adsorption of halogenated anesthetics, i.e., sevoflurane (SF). Adsorption isotherm and breakthrough experiments involving SF (reference sorbate) and water vapor were measured at 298 K and atmospheric pressure on both Cr‐MOF and a commercially used reference adsorbent. The Cr‐MOF MIL‐101 showed a significantly higher SF adsorption capacity and much higher selectivity relative to water vapor compared to the reference adsorbent. Binary‐mixture breakthrough tests demonstrated a “roll‐up effect” for SF on the reference adsorbent while no such effect was observed on MIL‐101.     

Interface control for resolved CFD-DEM with capillary interactions

In this work, a resolved CFD–DEM coupling model for the simulation of gas-liquid-solid flows is developed: the interface capturing method based on the colour function is employed for fluids (i.e. a gas and liquid) whilst Discrete Element Method (DEM) is used for particles. The Volume Penalisation (VP) method is adopted to consider the hydrodynamic interactions between fluids and particles along with the Immersed Free Surface (IFS) method, which artificially extends the gas-liquid interface into the interior of the particle to account for the wettability. The unique point of the proposed model is that the thickness of the gas-liquid interface can be controlled by using both interface compression and diffuse interface techniques simultaneously. From the simulation results, it is presented that the accurate evaluation of the surface tension force as well as the capillary force can be achieved by appropriately controlling the interface thickness. Moreover, the major two methods in the literature to calculate the capillary force are compared in this work. The validity of the proposed model is presented for both static and dynamic cases. The behaviour of two colliding particles with a dynamic liquid bridge is then simulated to demonstrate the applicability of the proposed model to a complex three-phase system.     

Long wavelength GRIN-SCH MQW lasers incorporating graded GaAlInAs confinement layers

We report the growth and characterisation of the first GaAllnAs based GRIN-SCH MQW lasers operating at 1.3 and 1.6μm. In these devices, GaAllnAs barriers and either GalnAs or GaAllnAs wells have been used for the 1.6 and 1.3μm lasers, respectively, together with true continuously graded composition GaAlInAs regions for the confinement layers. The excellent structural quality of the active and confinement regions and control of wavelength uniformity has been confirmed. Buried ridge lasers fabricated from the GRIN-SCH MQW wafers lased at 1.3 and 1.6μm with CW threshold currents of 65 and 30 mA, respectively.