Micro Sensor Node for Air Pollutant Monitoring: Hardware and Software Issues

Wireless sensor networks equipped with various gas sensors have been actively used for air quality monitoring. Previous studies have typically explored system issues that include middleware or networking performance, but most research has barely considered the details of the hardware and software of the sensor node itself. In this paper, we focus on the design and implementation of a sensor board for air pollutant monitoring applications. Several hardware and software issues are discussed to explore the possibilities of a practical WSN-based air pollution monitoring system. Through extensive experiments and evaluation, we have determined the various characteristics of the gas sensors and their practical implications for air pollutant monitoring systems

Effects of Haptic Feedback on the Wrist during Virtual Manipulation

As an alternative to thimble devices for the fingertips, we investigate haptic systems that apply stimulus to the user's forearm. Our aim is to provide effective interaction with virtual objects, despite the lack of co-location of virtual and real-world contacts, while taking advantage of relatively large skin area and ease of mounting on the forearm. We developed prototype wearable haptic devices that provide skin deformation in the normal and shear directions, and performed a user study to determine the effects of haptic feedback in different directions and at different locations near the wrist during virtual manipulation. Participants performed significantly better while discriminating stiffness values of virtual objects with normal forces compared to shear forces. We found no differences in performance or participant preferences with regard to stimulus on the dorsal, ventral, or both sides of the forearm.Comment: 7 pages, submitted conference paper for IEEE Haptics Symposium 202

Assessment of glomerular filtration rate with dynamic computed tomography in normal Beagle dogs

The objective of our study was to determine individual and global glomerular filtration rates (GFRs) using dynamic renal computed tomography (CT) in Beagle dogs. Twenty-four healthy Beagle dogs were included in the experiment. Anesthesia was induced in all dogs by using propofol and isoflurane prior to CT examination. A single slice of the kidney was sequentially scanned after a bolus intravenous injection of contrast material (iohexol, 1 mL/kg, 300 mgI/mL). Time attenuation curves were created and contrast clearance per unit volume was calculated using a Patlak plot analysis. The CT-GFR was then determined based on the conversion of contrast clearance per unit volume to contrast clearance per body weight. At the renal hilum, CT-GFR values per unit renal volume (mL/min/mL) of the right and left kidneys were 0.69 ± 0.04 and 0.57 ± 0.05, respectively. No significant differences were found between the weight-adjusted CT-GFRs in either kidney at the same renal hilum (p = 0.747). The average global GFR was 4.21 ± 0.25 mL/min/kg and the whole kidney GFR was 33.43 ± 9.20 mL/min. CT-GFR techniques could be a practical way to separately measure GFR in each kidney for clinical and research purposes

Synthesis and CO2 Capture of Porous Hydrogel Particles Consisting of Hyperbranched Poly(amidoamine)s

We successfully synthesized new macroporous hydrogel particles consisting of hyperbranched poly(amidoamine)s (HPAMAM) using the Oil-in-Water-in-Oil (O/W/O) suspension polymerization method at both the 50 mL flask scale and the 5 L reactor scale. The pore sizes and particle sizes were easily tuned by controlling the agitation speeds during the polymerization reaction. Since O/W/O suspension polymerization gives porous architecture to the microparticles, synthesized hydrogel particles having abundant amine groups inside polymers exhibited a high CO2 absorption capacity (104 mg/g) and a fast absorption rate in a packed-column test

Poly (Amidehydrazide) Hydrogel Particles for Removal of Cu2+ and Cd2+ Ions from Water

Poly(amidoamine)s (PAMAM) are very effective in the removal of heavy metal ions from water due to their abundant amine and amide functional groups, which have a high binding ability to heavy metal ions. We synthesized a new class of hyperbranched poly(amidehydrazide) (PAMH) hydrogel particles from dihydrazides and N,N′-methylenebisacrylamide (MBA) monomer by using the A2 + B4 polycondensation reaction in an inverse suspension polymerization process. In Cd2+ and Cu2+ ion sorption tests, the synthesized dihydrazide-based PAMH hydrogel particles exhibited sorption capacities of 85 mg/g for copper and 47 mg/g for cadmium. Interestingly, the PAMH showed only a 10% decrease in sorption ability in an acidic condition (pH = 4) compared to the diamine-based hyperbranched PAMAM, which showed a ~90% decrease in sorption ability at pH of 4. In addition, PAMH hydrogel particles remove trace amounts of copper (0.67 ppm) and cadmium (0.5 ppm) in water, below the detection limit

Application-Centric Networking Framework for Wireless Sensor Nodes

Wireless sensor network technology has found diverse applications in numerous fields. As the networking technology is refined in many ways, the need for system modulation with effective performance becomes essential. A multitude of architectures, which includes system abstraction and layering, has been proposed to solve the need at the operating system level. However, previous efforts do not qualify for networking architecture required by sensor networking, since they are aimed at hardware abstraction or protocol-based layering. In this paper, we classify developers into kernel, network and application developers and propose a network architecture that enables those developers to program independently. Network stack is separated into three different layers; MLL, NSL, DNL. This three-layered architecture provides an effective programming environment to sensor network developers by minimizing modification of other layers and maximizing reusability of the networking module. To validate the proposed mechanism, we implemented and assessed the performance with a few network algorithms and applications, based on the RETOS, which supports a dynamic loadable kernel module. 1

Development of Tissue-Specific Age Predictors Using DNA Methylation Data

DNA methylation patterns have been shown to change throughout the normal aging process. Several studies have found epigenetic aging markers using age predictors, but these studies only focused on blood-specific or tissue-common methylation patterns. Here, we constructed nine tissue-specific age prediction models using methylation array data from normal samples. The constructed models predict the chronological age with good performance (mean absolute error of 5.11 years on average) and show better performance in the independent test than previous multi-tissue age predictors. We also compared tissue-common and tissue-specific aging markers and found that they had different characteristics. Firstly, the tissue-common group tended to contain more positive aging markers with methylation values that increased during the aging process, whereas the tissue-specific group tended to contain more negative aging markers. Secondly, many of the tissue-common markers were located in Cytosine-phosphate-Guanine (CpG) island regions, whereas the tissue-specific markers were located in CpG shore regions. Lastly, the tissue-common CpG markers tended to be located in more evolutionarily conserved regions. In conclusion, our prediction models identified CpG markers that capture both tissue-common and tissue-specific characteristics during the aging process

Fast and Scalable Distributed Consensus Over Wireless Large-Scale Internet of Things Network

Due to the rapid paradigm shift in Internet of Things networks from wired and centralized to flexible wireless and decentralized networks, building effective and reliable distributed consensus mechanisms over wireless is becoming essential. Especially, since the performance of consensus over communication endpoints in a large-scale wireless network is limited by their communication capability, it requires a careful co-design of communication and consensus to attain a fast and scalable distributed wireless consensus mechanism with high resiliency against faulty nodes. Within this context, this article addresses such problem by designing two wireless consensus mechanisms that well-suit in large-scale wireless networks. On the one hand, as a reinterpretation of the conventional referendum consensus (RC) in a large-scale wireless network, gossip-broadcasting-based RC (GB-RC) is proposed. On the other hand, to overcome the scalability issue of the GB-RC, cooperative-broadcast-based electoral-college consensus (CB-EC) is proposed. By mathematically analyzing the performance of both of the consensus mechanisms, in terms of consensus latency and resiliency against the faulty nodes, we show that the GB-RC outperforms the conventional RC, while the CB-EC significantly reduces the consensus latency compromising the stochastic resiliency. We further evaluate their performance numerically to show their effectiveness and feasibility under realistic large-scale wireless environments.N