Microwave assisted synthesis and antimicrobial activity of Fe3O4-doped ZrO2 nanoparticles

Composites play important role in dental filling by controlling shrinkage along with correction in teeth's shape and position. Rehabilitation of severely worn dentition can be achieved using mechanically strong composites. This study aims to synthesize zirconia-based composites to be used as dental fillers. Effect of microwave powers (100–900?W) along with Fe₃O₄ doping are studied on the structural, mechanical and magnetic properties of stabilized zirconia. SEM and TEM reveal formation of spherical nanoparticles with diameter of ～30?nm. XRD results shows phase pure tetragonal zirconia (t-ZrO₂) at microwave power of 500?W without any post heat treatment. Crystallite size calculated from XRD data (～23?nm) matches well with the previously reported value for stabilization of t-ZrO₂. Microwave energy dissipation results in stresses causing volume shrinkage leading to monoclinic to tetragonal phase transformation with higher X-ray density and hardness of ～1347HV. VSM results show ferromagnetic response with low coercivity (600Oe) value and saturation magnetization (～2emu/g). It is worth mentioning here that this is one of its kind study reporting synthesis of room temperature stabilized Fe₃O₄ doped zirconia composites at microwave power of 500?W. Antibacterial studies reveal inhibition zone of ～32?mm against bacillus bacteria suggesting their potential use as dental filler.     

Sign Language to Sentence Formation: A Real Time Solution for Deaf People

Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular words such as I, eat, drink, home are unalike the plural words as school, cars, players. A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately. Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration. The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment. Hence, there is still a demand for specific environment to automate such a communication solution to interact with such type of special people. This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words. Finally, these are converted into the respective words/sentences within a reasonable time. This provide a real time solution for the deaf people to communicate and interact with the society.     

Erratum to: Conductivity Sensors Based System Development and Application to Investigate the Interfacial Behaviour between Supersonic Steam Jet and Water

Instruments and Experimental Techniques - An Erratum to this paper has been published: https://doi.org/10.1134/S0020441221050249     

Throughput and delay limits of chirp spread spectrum‐based IEEE 802.15.4a

The IEEE 802.15.4 standard is designed to provide a low‐power, low data rate protocol offering a high reliability. As an amendment to this standard, IEEE 802.15.4a introduces new options for physical layer to enable precision ranging. In this work, we analyzed the theoretical throughput and delay bounds of the unslotted version of chirp spread spectrum PHY‐based 802.15.4a. The formulae for transmission between one sender and one receiver for an ideal channel with no transmission errors are given. The throughput and delay bounds are derived for different frequency bands and data rates. Additionally, to measure spectral utilization, we measured the bandwidth efficiency for both the standards. We also compared our results with IEEE 802.15.4. The comparative analysis concludes that the performance of 802.15.4a exceeds 802.15.4 in terms of throughput and delay. The analytical results of throughput are verified by computer simulations. Copyright © 2011 John Wiley & Sons, Ltd.     

How does plant leaf senescence of grassland species influence decomposition kinetics and litter compounds dynamics?

The influence of litter quality on plant litter decomposition rates is a crucial aspect of the soils C cycle. In grassland ecosystems, leaf litter, which is not removed either by herbivores or by mowing, returns to soil after the senescence process (brown litter). In grassland managed by mowing, another significant proportion of litter returns to the soil before senescence through harvesting losses (green litter). We hypothesized that changes in leaf tissue quality due to the senescence process would lead to contrasting decomposition dynamics of brown litter compared to green litter. Our conceptual approach included the monitoring of decomposition of green (fresh leaves) and brown litter (dead leaves, still attached to the plant) of three different grassland species (Lolium perenne, Festuca arundinacea and Dactylis glomerata) during a 1 year field incubation. After 0, 2, 4, 20 and 44 weeks, we retrieved the litterbags and analysed the remaining material for carbon and nitrogen content and stable isotope composition. Additionally, we determined the lignin content and composition by CuO oxidation and the non-cellulosic neutral carbohydrate content and composition after TFA hydrolysis. As expected, green litter, being higher in N and soluble compounds, while showing a lower C:N ratio and lower lignin contents compared to brown litter, was degraded at a higher rate. Carbon decomposition kinetics suggests that both leaf litter types consist of two pools with contrasting turnover times. The size of the active pool was related to the initial content of soluble plant litter compounds and the size of the recalcitrant pool was related to the lignin to N ratio of initial plant material. More lignin was lost from green litter compared to brown litter. P-coumaryl-type lignin units were decomposed at a higher rate than vanillyl and syringyl units. Total non cellulosic polysaccharide content showed little changes for both litter types. In contrast, the ratios of hexoses/pentoses (C6/C5) and desoxy sugars/pentoses (desoxy/C5) increased during decomposition of green litter only. This is an indication for an increasing contribution of microbial derived compounds being consistant with the higher decomposition rate of this material. Our results showed that grassland management (grazing versus mowing) could influence soil carbon sequestration through different proportions of green and brown litter returned to soil.     

Framed slotted aloha based MAC protocol for low energy critical infrastructure monitoring networks

Recently, the IEEE TG4k has been formed to amend the IEEE 802.15 family to address the low energy critical infrastructure monitoring networks. The purpose is to facilitate point to multi‐thousands of point communication to collect the scheduled and event data from a large number of nonmains powered endpoints that are widely dispersed. It should support low energy operation, which is necessary for multiyear battery life. Other major features are application data rate up to 40 Kb/s, thousands of endpoints per mains powered infrastructure, asymmetric application data flow, small and infrequent messages, tolerant to data latency, etc. In this paper, we present a discussion on low energy critical infrastructure monitoring networks. We propose a medium access control protocol based on framed slotted aloha for these networks. We investigated probable packet sizes, energy consumptions, battery lifetime and the success rate for our protocol. The proposed protocol is simple to implement. Simulation results show that it is efficient in terms of packet success rate, energy consumption, and battery lifetime.Copyright © 2012 John Wiley & Sons, Ltd.     

Dynamic Similarity of Six Bar Ball Tensegrity Structure in Compression and Expansion Processes

Tensegrity structures have identical members in an orientation that have correlated dynamics under external force. To study this interdependent dynamics in different members in compression and expansion processes, it is vital to analyze the dynamics of the whole structure. In this study, six bar tensegrity structure was studied under compression and expansion, and interdependent movement of different members of the structure in both processes was obtained. First, the relationship between external force and members force densities was analytically developed based on the assumption that each bar moves with the same distance when an external force is applied on the six bar tensegrity ball structure along one plane that either compresses or expands the structure. Then, two individual simulations were carried out to analyze the movement of each bar in compression and expansion under the effect of external force, and elongation in all strings was studied in both processes. Finally, comparative dynamic study of different members in compression and expansion of the structure with the effect of external force was performed, which were categorized according to dynamic symmetry.     

Effect of different storage conditions on coagulating properties and cheese quality of Withania coagulans extract

The effects of different storage conditions on the coagulating properties of extracts of Withania coagulans berries were investigated in terms of coagulation time, pH and quality attributes of cheese prepared from buffalo milk. The extracts were stored under different conditions, viz. room temperature (27 ± 3 °C), refrigerated storage (4 °C), frozen storage (?20 °C) and lyophilisation. The milk‐coagulating activity of the plant extracts was measured on a fortnightly basis for a period of 5 months. There was a nonsignificant change in pH and the milk coagulating properties of the lyophilised extract. Physiochemical analysis revealed that cheese prepared with lyophilised extract retained the highest content of ash (2.3%), fat (23.8%), total solids (48.7%) and crude protein (22.7%), and resulted in the highest cheese yield (17.6%) compared to other tested treatments. Thus, it is concluded that lyophilisation has good potential for storage of vegetable extract coagulants.     

Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning

Cancer is the second deadliest human disease worldwide with high mortality rate. Rehabilitation and treatment of this disease requires precise and automatic assessment of effective drug response and control system. Prediction of treated and untreated cancerous cell line is one of the most challenging problems for precise and targeted drug delivery and response. A novel approach is proposed for prediction of drug treated and untreated cancer cell line automatically by employing modified Deep neural networks. Human hepatocellular carcinoma (HepG2) cells are exposed to anticancer drug functionalized CFO@BTO nanoparticles developed by our lab. Prediction models are developed by modifying ResNet101 and exploiting the transfer learning concept. Last three layers of ResNet101 are re-trained for the identification of drug treated cancer cells. Transfer learning approach in an appropriate choice especially when there is limited amount of annotated data. The proposed technique is validated on acquired 203 fluorescent microscopy images of human HepG2 cells treated with drug functionalized cobalt ferrite@barium titanate (CFO@BTO) magnetoelectric nanoparticles in vitro. The developed approach achieved high prediction with accuracy of 97.5% and sensitivity of 100% and outperformed other approaches. The high performance reveals the effectiveness of the approach. It is scalable and fully automatic prediction approach which can be extended for other similar cell diseases such as lung, brain tumor and breast cancer.