Computational analysis for morphological evolution in pyrolysis for micro/nano-fabrication

Pyrolysis is recently proposed as an efficient fabrication technique of micro/nanoscale carbon structures. In order to understand the morphological evolution in pyrolysis and design the final shape of carbon structure, this study proposes a comprehensive model that incorporates the essential mechanisms of pyrolysis based on the phase field framework. Computational analysis with the developed model provides information about the effect of interface energy and kinetic rate on the morphological evolution in pyrolysis.open0

Iliac Vein Injury Due to a Damaged Hot Shears™ Tip Cover During Robot Assisted Radical Prostatectomy

We report a rare case of vascular injury secondary to a damaged Hot Shears™ tip cover. Two 1 mm holes in the tip cover resulted in perforations in the obturator and external iliac veins during pelvic node dissection. Bleeding was controlled with bipolar coagulation and a 5 mm metal clip in the obturator and iliac vein, respectively. The rest of the procedure was completed uneventfully. Frequent integrity assessment of this accessory is necessary. Its function is important in order to carry out safe dissection in proximity to delicate structures. When injuries arise from areas not directly involved in the dissection, immediate inspection of the instruments should be mandatory

Pharmacologic Activation of Angiotensin-Converting Enzyme II Alleviates Diabetic Cardiomyopathy in db/db Mice by Reducing Reactive Oxidative Stress

Background Diabetes mellitus is one of the most common chronic diseases worldwide, and cardiovascular disease is the leading cause of morbidity and mortality in diabetic patients. Diabetic cardiomyopathy (DCM) is a phenomenon characterized by a deterioration in cardiac function and structure, independent of vascular complications. Among many possible causes, the renin-angiotensin-aldosterone system and angiotensin II have been proposed as major drivers of DCM development. In the current study, we aimed to investigate the effects of pharmacological activation of angiotensin-converting enzyme 2 (ACE2) on DCM. Methods The ACE2 activator diminazene aceturate (DIZE) was administered intraperitoneally to male db/db mice (8 weeks old) for 8 weeks. Transthoracic echocardiography was used to assess cardiac mass and function in mice. Cardiac structure and fibrotic changes were examined using histology and immunohistochemistry. Gene and protein expression levels were examined using quantitative reverse transcription polymerase chain reaction and Western blotting, respectively. Additionally, RNA sequencing was performed to investigate the underlying mechanisms of the effects of DIZE and identify novel potential therapeutic targets for DCM. Results Echocardiography revealed that in DCM, the administration of DIZE significantly improved cardiac function as well as reduced cardiac hypertrophy and fibrosis. Transcriptome analysis revealed that DIZE treatment suppresses oxidative stress and several pathways related to cardiac hypertrophy. Conclusion DIZE prevented the diabetes mellitus-mediated structural and functional deterioration of mouse hearts. Our findings suggest that the pharmacological activation of ACE2 could be a novel treatment strategy for DCM

A Fusion Approach of RSSI and LQI for Indoor Localization System Using Adaptive Smoothers

Due to the ease of development and inexpensiveness, indoor localization systems are getting a significant attention but, with recent advancement in context and location aware technologies, the solutions for indoor tracking and localization had become more critical. Ranging methods play a basic role in the localization system, in which received signal strength indicator- (RSSI-) based ranging technique gets the most attraction. To predict the position of an unknown node, RSSI measurement is an easy and reliable method for distance estimation. In indoor environments, the accuracy of the RSSI-based localization method is affected by strong variation, specially often containing substantial amounts of metal and other such reflective materials that affect the propagation of radio-frequency signals in nontrivial ways, causing multipath effects, dead spots, noise, and interference. This paper proposes an adaptive smoother based location and tracking algorithm for indoor positioning by making fusion of RSSI and link quality indicator (LQI), which is particularly well suited to support context aware computing. The experimental results showed that the proposed mathematical method can reduce the average error around 25%, and it is always better than the other existing interference avoidance algorithms

Sequential Pattern Mining Approach for Personalized Fraudulent Transaction Detection in Online Banking

Financial institutions face challenges of fraud due to an increased number of online transactions and sophisticated fraud techniques. Although fraud detection systems have been implemented to detect fraudulent transactions in online banking, many systems just use conventional rule-based approaches. Rule-based detection systems have a difficulty in updating and managing their rules and conditions manually. Additionally, generated from the few fraud cases, the rules are general rather than specific to each user. In this paper, we propose a personalized alarm model to detect frauds in online banking transactions using sequence pattern mining on each user’s normal transaction log. We assumed that a personalized fraud detection model is more effective in responding to the rapid increase in online banking users and diversified fraud patterns. Moreover, we focused on the fact that fraudulent transactions are very different from each user’s usual transactions. Our proposed model divides each user’s log into transactions, extracts a set of sequence patterns, and uses it to determine whether a new incoming transaction is fraudulent. The incoming transaction is divided into multiple windows, and if the normal patterns are not found in the consecutive windows, an alarm is sounded. We applied the model to a real-world dataset and showed that our model outperforms the rule-based model and the Markov chain model. Although more experiments on additional datasets are needed, our personalized alarm model can be applied to real-world systems

The Importance of Social Value in the Evaluation of Web Services in the Public Sector

Wireless sensor networks (WSNs) are widely used in many different fields. Even in the public sector, various services using WSN are offered. One of the key issues is how to control and manage heterogeneous devices of WSN devices. Devices Profile for Web Services (DPWS), a standard of Web services, has been adopted to solve the problems of interoperability between WSN devices. In order to evaluate WSN services in the public sector, this paper presents a method to evaluate Web services, a base technology of sensor network services. This paper presents a value analysis methodology assessing tangible and intangible benefits of Web services in the public sector. We classify stakeholders of Web services as a government, citizens, and agents (businesses) and selected the metrics for each stakeholder's benefit. After that, we determine the weight of each metric through AHP. The result shows that social value was the most important benefit in the construction of Web services in the public sector. We expect that the main contribution of this paper is the development of a value assessment framework that reflects the unique characteristics of Web services in the public sector