Shape memory nanocomposite of poly(L-lactic acid)/graphene nanoplatelets triggered by infrared light and thermal heating

In this study, the effect of graphene nanoplatelets (GNPs) on the shape memory properties of poly(L-lactic acid) (PLLA) was studied. In addition to thermal activation, the possibility of infrared actuating of thermo-responsive shape memory PLLA/GNPs nanocomposite was investigated. The incorporated GNPs were expected to absorb infrared wave’s energy and activate shape memory PLLA/GNPs. Different techniques such as differential scanning calorimetry (DSC), wide-angle X-ray diffraction (WAXD), field emission gun scanning electron microscope (FEG-SEM) and dynamic mechanical thermal analysis (DMTA) were used to characterize samples. DSC and WAXD results indicated that GNPs augmented crystallinity due to nucleating effect of graphene particles. GNPs improved both thermal and infrared activating shape memory properties along with faster response. Pure shape memory PLLA was slightly responsive to infrared light and its infrared actuated shape recovery ratio was 86% which increased to more than 95% with loading of GNPs. Drastic improvement in the crystallinity was obtained in nanocomposites with lower GNPs contents (0.5 and 1 wt%) due to finer dispersion of graphene which resulted in more prominent mechanical and shape memory properties enhancement. Infrared activated shape memory PLLA/GNPs nanocomposites can be developed for wireless remote shape control of smart medical and bio-systems

Missing Surface Estimation Based on Modified Tikhonov Regularization: Application for Destructed Dental Tissue

Estimation of missing digital information is mostly addressed by 1- or 2-D signal processing methods; however, this problem can emerge in multi-dimensional data including 3-D images. Examples of 3-D images dealing with missing edge information are often found using dental micro-CT, where the natural contours of dental enamel and dentine are partially dissolved or lost by caries. In this paper, we present a novel sequential approach to estimate the missing surface of an object. First, an initial correct contour is determined interactively or automatically, for the starting slice. This contour information defines the local search area and provides the overall estimation pattern for the edge candidates in the next slice. The search for edge candidates in the next slice is performed in the perpendicular direction to the obtained initial edge in order to find and label the corrupted edge candidates. Subsequently, the location information of both initial and nominated edge candidates are transformed and segregated into two independent signals (X-coordinates and Y-coordinates) and the problem is changed into error concealment. In the next step, the missing samples of these signals are estimated using a modified Tikhonov regularization model with two new terms. One term contributes in the denoising of the corrupted signal by defining an estimation model for a group of mildly destructed samples, and the other term contributes in the estimation of the missing samples with the highest similarity to the samples of the obtained signals from the previous slice. Finally, the reconstructed signals are transformed inversely to edge pixel representation. The estimated edges in each slice are considered as initial edge information for the next slice, and this procedure is repeated slice by slice until the entire contour of the destructed surface is estimated. The visual results as well as quantitative results (using both contour-based and area-based metrics) for seven image data sets of tooth samples with considerable destruction of the dentin-enamel junction demonstrates that the proposed method can accurately interpolate the shape and the position of the missing surfaces in computed tomography images in both two and 3-D (e.g., 14.87 ± 3.87 $\mu \text{m}$ of mean distance (MD) error for the proposed method versus 7.33 ± 0.27 $\mu \text{m}$ of MD error between human experts and 1.25± ~ 0 % error rate (ER) of the proposed method versus 0.64± ~

Providing brood stocks of Caspian trout (Salmo trutta caspius) from Mazandaran Rivers and production of one hundred thousand fries

Caspian trout (Salmo trutta caspius) is one of valuable fishes of the Caspian sea for people living in the Northern coastal area of Iran. Since fish stock and natural resources protection is one the Iranian fisheries research objectives, the most activity on Caspian trout rehabilitation was focused on releasing thousands of smolts in the rivers discharge to Caspian Sea. Catch statistics of this species has declined over last decades thus this study on quality of provided brood stocks and producing fries with suitable quality can help rehabilitation and rearing of this valuable species. Several rivers were considered for providing brooders to keep genetic resources variety of sea stocks. In spawning season 25 (9 male, 16 female) and 30 (5 male, 25 female) brooders were collected from fishermen in Mazandaran rivers and Gyilan coasts provinces respectively. After propagation and larvae rearing, 11500 (10-15 g.) and 50000 (less than 10 g.) juveniles were released in Gyilan and Mazandaran rivers respectively

Growth performance and age composition of Salmo trutta caspius in Iranian part of Caspian Sea

The aim of this project is to study the growth and age structure in the Caspian trout, comparison with other coldwater species and check the trend of these parameters in recent years. This study was conducted during 2013 till 2015. Totally, 43 specimens for back calculation and 101 specimens for biometrical study of the Caspian trout have been caught in two month period. Biometric parameters such as length, weight and age of the fish were recorded. Base on Back calculation method in 1393, the average length of fish at ages 1, 2 and 3 years old were 18.98 ± 3.5, 30.5 ± 7.24 and 41.7 ± 9.1 cm. So these age groups are under the adult age and don’t approaching to near the beach and rivers for spawning behavior. Therefore, these length groups cannot be observed in catch composition. The result showed, the mean of gonad weight in this fish was about 11 percent of total weight and number of eggs per gram of gonad calculated about 10.8 numbers. Minimum age and maximum age of this species determined 4 years and 7 years (mean = 5.6) and the most frequency allocated to 5 age group and the frequency of 6 and 7 years has been remarkable. The average length of salmon was 69.2 ± 6.2 cm (minimum 57 and maximum 81 cm) and the average weight was measured 3323 ± 677 g (2400 to 5600 g) in the catch composition. Growth parameters such as k, L_∞ and ø’ was measured 0.18, 104 cm and 3.289 respectively. The amount of b for relation length and weight was 2.9 which imply negative allometry. L_∞ and growth coefficient (K) on the Caspian trout were acceptable range, that it shows good growth the fish in the sea water. Most of the fishes were catched from Cheshmehkileh River. As at present Shilat uses just the broods of the Tonekaboon region for restocking of this species, we recommend using the broods of the western region separately for rehabilitation of the stocks of this region