Repair of cracks in simply supported beams using epoxy injection technique

The research reported in this paper is a contribution in understanding the epoxy injection retrofitting technique to strengthen the existing RC cracked members. This technique consists of injecting epoxy resin adhesive in a cracked beam to increase the stiffness and the strength. A total of six full scale RC beams were constructed with the same material using the same mix and water-cement ratio. The beams were tested until the width of cracks reached a limiting value of 1 mm. The beams were then repaired with the epoxy injection technique. After 3 days of water curing, the beams were tested again and loaded till the failure occurred. A considerable enhancement in the load carrying capacity was observed in the beams after the retrofitting. A reduction in deflection was also observed due to the injection of epoxy. These results clearly demonstrate the effectiveness of the proposed technique in repairing the RC members for strengthening the existing structures.     

Microscopic and mechanical properties of semi‐crystalline and amorphous polymeric parts produced by laser cutting

Microscopic and mechanical properties of polymeric parts are effective factors on their durability. Laser cutting is one of the most common methods for production of 2D polymeric parts. Experimental study of the mentioned properties of semi‐crystalline and amorphous polymeric parts after laser cutting is conducted in this research. Low density polyethylene (LDPE) and polystyrene (PS) are considered as semi‐crystalline and amorphous polymers, respectively. Laser power and cutting velocity were selected as input parameters of cutting process. According to microscopic observations, the microcracks, re‐solidified spots of molten material, and sink marks just appear in heat affected zone (HAZ) on amorphous polymer. Results also showed that the HAZ width and surface roughness values are smaller for semi‐crystalline polymer. For both polymers, decreasing of power and increasing of cutting velocity reduce the HAZ and surface roughness. In the case of mechanical properties, tensile strength of semi‐crystalline and amorphous polymers reduces after laser cutting. Results of experiments revealed that the extension of HAZ and deterioration of surface finish decrease tensile strength of parts. Therefore, lower power and higher cutting velocity condition is preferable for reaching the better mechanical properties. Furthermore, two separate mathematical models for each polymer are presented for prediction of tensile strength after laser cutting process. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44179.     

Threshold based locking routing strategy for delay tolerant network

Delay tolerance network probabilistic routing protocols forward message to a node by observing its predictability value to meet the message destination. However, it is vital to predict the ability of node to carry the transmitted message. For instance, the traffic confluence on the high probable nodes can produce congestion that results in the drop of previously stored messages. These drops diminish the delivery ratio because the dropped message lost its opportunity to be delivered. Since, there exist multiple copies of each message; therefore, the same node invariably receives the dropped messages from other parts of the network and causes the highest number of transmissions. Additionally, the replication from source node continues on the high probable peers even the previous copies were transmitted on the better predictable neighbors than the current. In this paper, we have proposed a novel routing method called as the adaptive threshold based locking method that maintains the contemporary status of the node based on its activity in the network. We have used the adaptive status measuring metrics such as transmit factor, drop factor and hop away count. Moreover, a threshold based locking method has been introduced to control the diffusion of messages. We have performed the comparison of existing and proposed routing methods with real time mobility traces. The proposed strategy has bolstered the delivery ratio and minimizes hop count, end-to-end delay and number of transmission.     

Serum paraoxonase after myocardial infarction

A new concept in reproductive endocrinology is that the status of the ovary as a glucocorticoid target organ alters with follicular development. Evidence for a physiological role of glucocorticoids in the regulation of ovarian folliculogenesis has been strengthened by the discovery that 11beta-hydroxysteroid dehydrogenase (11betaHSD) mRNA expression in human granulosa cells is developmentally regulated. In this study, we quantified the pattern of expression and investigated the cellular location of 11betaHSD type 1 (11betaHSD1), 11betaHSD type 2 (11betaHSD2), glucocorticoid receptor (GR), and mineralocorticoid receptor (MR) mRNAs during follicular maturation in rat ovary. Immature female rats received treatment with eCG to induce preovulatory follicular development or eCG followed by hCG to induce luteinization. 11betaHSD1, 11betaHSD2, GR, and MR mRNAs were all detectable by ribonuclease protection assay in ovarian total RNA. Treatment with eCG alone caused an approximately 8-fold increase in the ovarian level of 11betaHSD1 mRNA, which rose to approximately 30-fold after additional treatment with hCG. Equine CG alone did not measurably affect the ovarian 11betaHSD2 mRNA level, but additional treatment with hCG reduced it to 34% of the control level. Expression of GR mRNA was unchanged by any gonadotropin treatment, while MR mRNA was down-regulated. A similar pattern of 11betaHSD1, 11betaHSD2, GR, and MR mRNA expression was observed in isolated granulosa cells. These results provide direct experimental evidence that 11betaHSD genes are gonadotropically regulated in the rat ovary, including granulosa cells, and are consistent with a shift in glucocorticoid metabolism from inactivation (due to oxidation by 11betaHSD2) to activation (reduction by 11betaHSD1) during hCG-induced granulosa cell luteinization.     

Biological activity of Boswellia serrata Roxb. oleo gum resin essential oil: effects of extraction by supercritical carbon dioxide and traditional methods

The findings of this study suggests that chemical composition, essential oil yield, antioxidant and antimicrobial activity of Boswellia serrata oleo gum resin essential oils extracted by hydro distillation, steam distillation and supercritical fluid carbon dioxide methods vary greatly from each other. The optimum essential oil yield was obtained using hydro distillation method (8.18 ± 0.15 %). The essential oils isolated through different extraction methods contained remarkable amounts of total phenolics and total flavonoids. Essential oil isolated through supercritical fluid carbon dioxide extraction exhibited better antioxidant activity with highest free radical scavenging potential (96.16 ± 1.57 %), inhibition of linoleic acid oxidation (94.18 ± 1.47 %) and hydrogen peroxide free radical scavenging potential (68.25 ± 1.02 %). Moreover, the antimicrobial activity of essential oils was performed through well diffusion, resazurin microtiter plate and micro dilution broth assay assays. The essential oil isolated through steam distillation method revealed highest antimicrobial activity with maximum inhibition zone (24.21 ± 0.34 to12.08 ± 0.30 mm) and least MIC values (35.18 ± 0.77 to 281.46 ± 7.03 µg/mL). The comparison of chemical composition of essential oils isolated at different extraction methods have shown that the concentration of α-thujene, camphene, β-pinene, myrcene, limonene, m-cymene and cis-verbenol was higher in steam distilled essential oil as compared to hydro and supercritical fluid carbon dioxide extracted essential oils. These compounds may be responsible for the higher antimicrobial activity of Boswellia serrata oleo gum resin steam distilled essential oil.     

CUPSEED - A combined use of prediction syntax elements to embed data in SHVC video

Multimedia Tools and Applications - With the rapid advancement in digital technologies, video rises to become one of the most effective communication tools that continues to gain popularity and...     

Current and future prospects of enhanced heat transfer in ammonia systems

In the last decade a moderate headway has been made in the application of enhanced surface heat exchangers in ammonia refrigeration systems. This has been a result of the persistent issue of ozone and global warming which has resulted in keen interest in natural refrigerants such as ammonia that has played a prominent role in the refrigeration industry for years, particularly in the field of food, beverage and marine. The only drawback with ammonia is the toxicity; hence, if smaller heat exchangers could be introduced in order to reduce ammonia charge, this negative aspect about ammonia can be addressed to a great extent. In order to achieve this goal, novel and compact heat exchangers with enhanced surfaces have to be introduced. This paper presents an over view of the status of ammonia as a refrigerant and discusses the present and the future trends in the development of compact heat exchangers for use in ammonia refrigeration.     

Histogram modification based enhancement along with contrast-changed image quality assessment

Contrast is the difference in visual characteristics which make an object more recognizable. Despite the significance of contrast enhancement (CE) in image processing applications, few attempts have been made on assessment of the contrast change. In this paper, a visual information fidelity-based contrast change metric (VIF-CCM) is presented which includes visual information fidelity (VIF), local entropy, correlation coefficient, and mean intensity measures. The validation results of the presented VIF-CCM show its efficiency and superiority over the state-of–the-arts image quality assessment metrics. A histogram modification based contrast enhancement (HMCE) method is also proposed in this paper. The proposed HMCE comprises of four steps: segmentation of the input image, employing a set of weighting constraints, applying the combination of adaptive gamma correction and equalization on modified histogram, and optimization the value of the constraint weights by PSO algorithm. Experimental results demonstrate that the proposed HMCE outperforms other existing CE methods subjectively and objectively.

     

Machine Learning Enabled Early Detection of Breast Cancer by Structural Analysis of Mammograms

Clinical image processing plays a significant role in healthcare systems and is currently a widely used methodology. In carcinogenic diseases, time is crucial; thus, an image’s accurate analysis can help treat disease at an early stage. Ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS) are common types of malignancies that affect both women and men. The number of cases of DCIS and LCIS has increased every year since 2002, while it still takes a considerable amount of time to recommend a controlling technique. Image processing is a powerful technique to analyze preprocessed images to retrieve useful information by using some remarkable processing operations. In this paper, we used a dataset from the Mammographic Image Analysis Society and MATLAB 2019b software from MathWorks to simulate and extract our results. In this proposed study, mammograms are primarily used to diagnose, more precisely, the breast’s tumor component. The detection of DCIS and LCIS on breast mammograms is done by preprocessing the images using contrast-limited adaptive histogram equalization. The resulting images’ tumor portions are then isolated by a segmentation process, such as threshold detection. Furthermore, morphological operations, such as erosion and dilation, are applied to the images, then a gray-level co-occurrence matrix texture features, Harlick texture features, and shape features are extracted from the regions of interest. For classification purposes, a support vector machine (SVM) classifier is used to categorize normal and abnormal patterns. Finally, the adaptive neuro-fuzzy inference system is deployed for the amputation of fuzziness due to overlapping features of patterns within the images, and the exact categorization of prior patterns is gained through the SVM. Early detection of DCIS and LCIS can save lives and help physicians and surgeons todiagnose and treat these diseases. Substantial results are obtained through cubic support vector machine (CSVM), respectively, showing 98.95% and 98.01% accuracies for normal and abnormal mammograms. Through ANFIS, promising results of mean square error (MSE) 0.01866, 0.18397, and 0.19640 for DCIS and LCIS differentiation during the training, testing, and checking phases.