Intergranular Corrosion Behavior of 304LN Stainless Steel Heat Treated at 623 K (350 °C)

Low temperature sensitization of 304LN stainless steel from the two pipes, differing slightly in chemical composition, has been investigated; specimens were aged at 623 K (350 °C) for 20,000 hours and evaluated for intergranular corrosion and degree of sensitization. The base and heat-affected zone (HAZ) of the 304LN-1 appear resistant to sensitization, while 304LN-2 revealed a “dual” type microstructure at the transverse section and HAZ. The microstructure at 5.0-mm distance from the fusion line indicates qualitatively less sensitization as compared to that at 2.0 mm. The 304LN-2 base alloy shows overall lower degree of sensitization values as compared to the 304LN-1. A similar trend of degree of sensitization was observed in the HAZ where it was higher in the 304LN-1 as compared to the 304LN-2. The weld zone of both the stainless steels suffered from cracking during ASTM A262 practice E, while the parent metals and HAZs did not show such fissures. A mottled image within the ferrite lamella showed spinodal decomposition. The practice E test and transmission electron microscopy results indicate that the interdendritic regions may suffer from failure due to carbide precipitation and due to the evolution of brittle phase from spinodal decomposition.     

Enzymatic depolymerization of Ricinus communis, a potential lignocellulosic for improved saccharification

Residual lignocellulosics left to decay in fields and forest has a huge potential to serve as a low cost feedstock for production of bioethanol. In Indian subcontinent Ricinus communis is a major lignocellulosics growing in arid conditions containing 42% cellulose and 19.8% lignin. In the present study, Response Surface Methodology (RSM) based on Central Composite Design (CCD) has been used to explore the effects of pH, temperature, solid to liquid ratio (w/v), enzyme concentration and incubation time on enzymatic depolymerization of R. communis. The maximum delignification obtained was 85.69%. In case of lignified R. communis the optimum reducing sugar produced was about 288.83 mg/g dry substrate, whereas, in case of delignified R. communis the optimum reducing sugar produced was about 775.17 mg/g dry delignified substrate. After delignification reducing sugar yield was increased to about 2.68 fold.     

Sonochemical synthesis, characterization, and photocatalytic properties of Bi2−x Sb x WO6 nanorods

We report an efficient route for the sonochemical synthesis of Bi_2?x Sb _x WO₆ (x = 0, 0.01, 0.02, 0.05, 0.1, and 2) nanorods using bismuth nitrate/antimony chloride and sodium tungstate as precursors. The products obtained have been characterized using X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and UV–Vis diffuse reflectance spectroscopy. The photoactivities of all the samples for the Rhodamine-B (RhB) photodegradation were investigated systematically under UV and visible light irradiation. The results of the photocatalytic degradation of RhB in aqueous solution showed that 2–5 % antimony ion doping greatly improved the photocatalytic efficiency of sonochemically synthesized Bi₂WO₆ nanorods under both UV and visible radiation compared to its undoped counterpart. Among all the samples, the Sb₂WO₆ nanorods exhibited the highest photodegradation efficiency since 86 % of RhB could be photodegraded in 90 min under UV radiation. The stability of the photocatalysts was ascertained using FT-IR and Raman spectroscopy.     

Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection

The coronavirus COVID-19 pandemic is today’s major public health crisis, we have faced since the Second World War. The pandemic is spreading around the globe like a wave, and according to the World Health Organization’s recent report, the number of confirmed cases and deaths are rising rapidly. COVID-19 pandemic has created severe social, economic, and political crises, which in turn will leave long-lasting scars. One of the countermeasures against controlling coronavirus outbreak is specific, accurate, reliable, and rapid detection technique to identify infected patients. The availability and affordability of RT-PCR kits remains a major bottleneck in many countries, while handling COVID-19 outbreak effectively. Recent findings indicate that chest radiography anomalies can characterize patients with COVID-19 infection. In this study, Corona-Nidaan, a lightweight deep convolutional neural network (DCNN), is proposed to detect COVID-19, Pneumonia, and Normal cases from chest X-ray image analysis; without any human intervention. We introduce a simple minority class oversampling method for dealing with imbalanced dataset problem. The impact of transfer learning with pre-trained CNNs on chest X-ray based COVID-19 infection detection is also investigated. Experimental analysis shows that Corona-Nidaan model outperforms prior works and other pre-trained CNN based models. The model achieved 95% accuracy for three-class classification with 94% precision and recall for COVID-19 cases. While studying the performance of various pre-trained models, it is also found that VGG19 outperforms other pre-trained CNN models by achieving 93% accuracy with 87% recall and 93% precision for COVID-19 infection detection. The model is evaluated by screening the COVID-19 infected Indian Patient chest X-ray dataset with good accuracy.

     

A dynamic reconfigurable routing framework for wireless sensor networks

Sensornet deployments of the future are expected to deliver a multitude of services, ranging from reliable sensing, real time streams, mission critical support, network reprogramming and so on. Naturally, no one routing protocol can sufficiently cater to the network layer functionalities expected. Severe resource constraints further limit the possibility of multiple routing protocols to be implemented. Further, vertically integrated designs of present protocols hinder synergy and code-reuse among implementations. In this paper, we present an architecture that allows applications to send different types of flows, often with conflicting communication requirements. A flow’s requirements are made visible to our framework by using just 3 bits in the packet header. The core architecture is a collection of highly composable modules that allows rapid protocol development and deployment. We show that our framework can provide: (i) flow based network functionality that ensures each flow gets an application specific network layer which is dynamically knit as per the flow’s needs, (ii) modular organization that promotes code-reuse, run time sharing, synergy and rapid protocol development and (iii) pull processing that allows flows to dictate their traffic rate in the network, and implement flexible scheduling policies. This creates a framework for developing, testing, integrating, and validating protocols that are highly portable from one deployment to another. Using our framework, we show that virtually any communication pattern can be described to the framework. We validate this by gathering requirements for one real world application scenario: predictive maintenance (PdM). The requirements are used to generate a fairly complete and realistic traffic workload to drive our evaluation. Using simulations and 40 node MicaZ testbed experiments, we show that our framework can meet the deployments demands at granularities not seen before in sensornets. We measure the costs of using this framework in terms of code size, memory footprints and forwarding costs on MicaZ motes.     

Designing Auction Mechanisms for Dynamic Spectrum Access

With the increasing demands for radio spectrum, techniques are being explored that would allow dynamic access of spectrum bands that are under-utilized. In this regard, a new paradigm called dynamic spectrum access is being investigated where wireless service providers (WSPs) would dynamically seek more spectrum from the under-utilized licensed bands when and where they need without interfering with the primary users. Currently, there is little understanding on how such a dynamic allocation will operate so as to make the system feasible under economic terms. In this paper, we consider the dynamic spectrum allocation process where multiple WSPs (bidders) compete to acquire necessary spectrum band from a common pool of spectrum. We use auction theory to analyze the allocation process when the demand from WSPs exceeds the available spectrum. We investigate various auction mechanisms under different spectrum allocation constraints to find WSPs’ bidding strategies and revenue generated by spectrum owner. We show that sequential bidding of bands provides better result than the concurrent bidding when WSPs are constrained to at most single unit allocation. On the other hand, when the bidders request for multiple units, (i.e., they are not restricted by allocation constraints) synchronous auction mechanism proves to be beneficial than asynchronous auctions.

Role of Cerium on Transformation Kinetics and Mechanical Properties of Low Carbon Steels

Metallurgical and Materials Transactions A - The present study has focused on the detailed dilatometric and electron microscopic analysis of the formation of austenite and its decomposition in two...     

Real-Time Fluorescence Microscopy on Living E. coli Sheds New Light on the Antibacterial Effects of the King Penguin β-Defensin AvBD103b

(1) Antimicrobial peptides (AMPs) are a promising alternative to conventional antibiotics. Among AMPs, the disulfide-rich β-defensin AvBD103b, whose antibacterial activities are not inhibited by salts contrary to most other β-defensins, is particularly appealing. Information about the mechanisms of action is mandatory for the development and approval of new drugs. However, data for non-membrane-disruptive AMPs such as β-defensins are scarce, thus they still remain poorly understood. (2) We used single-cell fluorescence imaging to monitor the effects of a β-defensin (namely AvBD103b) in real time, on living E. coli, and at the physiological concentration of salts. (3) We obtained key parameters to dissect the mechanism of action. The cascade of events, inferred from our precise timing of membrane permeabilization effects, associated with the timing of bacterial growth arrest, differs significantly from the other antimicrobial compounds that we previously studied in the same physiological conditions. Moreover, the AvBD103b mechanism does not involve significant stereo-selective interaction with any chiral partner, at any step of the process. (4) The results are consistent with the suggestion that after penetrating the outer membrane and the cytoplasmic membrane, AvBD103b interacts non-specifically with a variety of polyanionic targets, leading indirectly to cell death.     

Utility based service differentiation in CDMA data networks

The wireless data services are getting more and more competitive because of the presence of multiple service providers, all of whom offer some relative advantages and flexibilities over the others. As a result, the user churn behavior (i.e., migration from one service provider to another) is causing tremendous revenue loss for the service providers and also failure of existing resource management algorithms to fully capture the impact of churning. Moreover, the quality of service (QoS) offered to users belonging to different classes calls for new resource management schemes that address the issues related to differentiated services. In this paper, we propose a framework to study the impact of user churn behavior on the resource management algorithms to provide class-based differentiated services in CDMA data networks. In particular, our framework incorporates the user churning behavior into the admission control and power management algorithms, so that the service provider’s revenue loss due to churn can be minimized. Since optimal rate/power allocation in multi-rate CDMA systems is in general NP-Complete, we provide heuristics that try to provide solutions to the resource allocation problem in real-time. In our proposed framework, we add another layer of power management called Class-Based Power Allocation/Reduction (CBPAR) function, which works with the rate control algorithm to achieve power allocation. With CBPAR, the number of variables of the optimization problem is significantly reduced helping achieve the results in real-time. Our simulation study shows that the service provider’s revenue can be improved with the help of CBPAR framework. It also reveals the relationship between users’ sensitivity and tolerance to QoS degradation and optimal power allocations. Haitao Lin received his PhD in Computer Science and Engineering from the University of Texas at Arlington in 2004. He received his B.E. degree in Radio Engineering from Southeast University, Nanjing, China, in 1996 and the MS degree in Computer Applications from the Beijing University of Posts and Telecommunications, Beijing, China, in 2000. He is currently with Converged Multimedia Networks (CMN) Systems Engineering at Nortel, Richardson, Texas. His research interests include wireless network performance evaluation and enhancement, wireless link adaptation, wireless network resource management, applied game theory, network overload control performance modeling and analysis. Mainak Chatterjee received his Ph.D. from the department of Computer Science and Engineering at The University of Texas at Arlington in 2002. Prior to that, he completed his B.Sc. with Physics (Hons) from the University of Calcutta in 1994 and M.E. in Electrical Communication Engineering from the Indian Institute of Science, Bangalore, in 1998. He is currently an Assistant Professor in the department of Electrical and Computer Engineering at the University of Central Florida. His research interests include economic issues in wireless networks, applied game theory, resource management and quality-of-service provisioning, ad hoc and sensor networks, CDMA data networking, and link layer protocols. He serves on the executive and technical program committee of several international conferences. Sajal K. Das received the BTech degree in 1983 from Calcutta University, the MS degree in 1984 from the Indian Institute of Science, Bangalore, and the PhD degree in 1988 from the University of Central Florida, Orlando, all in computer science. Prior to 1999, he was a professor of computer science at the University of North Texas, where he twice (in 1991 and 1997) received the Student Associationís Honor Professor Award for best teaching and scholarly research. Currently, he is a professor of computer science and engineering and also the founding director of the Center for Research in Wireless Mobility and Networking (CReWMaN) at the University of Texas at Arlington (UTA). His current research interests include resource and mobility management in wireless and sensor networks, mobile and pervasive computing, wireless multimedia and QoS provisioning, mobile Internet protocols, distributed processing, and grid computing. He has published more than 350 research papers, directed numerous funded projects, and holds five US patents in wireless mobile networks. He received the Best Paper Award in ACM MobiComí99, ICOINí01, ACM MSWIMí00, and ACM/IEEE PADSí97. He was also a recipient of UTAís Outstanding Faculty Research Award in Computer Science in 2001 and 2003, and UTAís College of Engineering Excellence in Research Award in 2003. He is the coauthor of a book Smart Environments: Technology, Protocols and Applications, published in 2004 by John Wiley. Dr. Das is the editor-in-chief of the Pervasive and Mobile Computing journal and serves on the editorial Boards of four international journals, including IEEE Transactions on Mobile Computing and ACM/Kluwer Wireless Networks. He has served as general chair of IEEE WoWMoMí05, IWDCí04, IEEE PerComí04, CITí03, and IEEE MASCOTSí02; general vice chair of IEEE PerComí03, ACM Mobi- Comí00, and HiPCí00-01; program chair of IWDCí02 and WoWMoMí98-99; TPC vice chair of CITí05 and ICPADSí02; and as TPC member of numerous IEEE and ACM conferences. He is the vice chair of IEEE Technical Committees (TCPP and TCCC) and on the Advisory Boards of several cutting-edge companies. He is a member of the IEEE Computer Society.