293 research outputs found
Diffusion-based clock synchronization for molecular communication under inverse Gaussian distribution
Nanonetworks are expected to expand the capabilities of individual nanomachines by allowing them to cooperate and share information by molecular communication. The information molecules are released by the transmitter nanomachine and diffuse across the aqueous channel as a Brownian motion holding the feature of a strong random movement with a large propagation delay. In order to ensure an effective real-time cooperation, it is necessary to keep the clock synchronized among the nanomachines in the nanonetwork. This paper proposes a model on a two-way message exchange mechanism with the molecular propagation delay based on the inverse Gaussian distribution. The clock offset and clock skew are estimated by the maximum likelihood estimation (MLE). Simulation results by MATLAB show that the mean square errors (MSE) of the estimated clock offsets and clock skews can be reduced and converge with a number of rounds of message exchanges. The comparison of the proposed scheme with a clock synchronization method based on symmetrical propagation delay demonstrates that our proposed scheme can achieve a better performance in terms of accuracy
Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection
Weakly supervised object detection (WSOD) is a challenging task that requires
simultaneously learn object classifiers and estimate object locations under the
supervision of image category labels. A major line of WSOD methods roots in
multiple instance learning which regards images as bags of instances and
selects positive instances from each bag to learn the detector. However, a
grand challenge emerges when the detector inclines to converge to
discriminative parts of objects rather than the whole objects. In this paper,
under the hypothesis that optimal solutions are included in local minima, we
propose a discovery-and-selection approach fused with multiple instance
learning (DS-MIL), which finds rich local minima and select optimal solution
from multiple local minima. To implement DS-MIL, an attention module is
proposed so that more context information can be captured by feature maps and
more valuable proposals can be collected during training. With proposal
candidates, a selection module is proposed to select informative instances for
object detector. Experimental results on commonly used benchmarks show that our
proposed DS-MIL approach can consistently improve the baselines, reporting
state-of-the-art performance
An Artificial Liposome Compartment with Size Exclusion Molecular Transport
The cellular compartment plays an essential role in organizing the complex and diverse biochemical reactions within the cell. By mimicking the function of such cellular compartments, the challenge of constructing artificial compartments has been taken up to develop new biochemical tools for efficient material production and diagnostics. The important features required for the artificial compartment are that it isolates the interior from the external environment and is further functionalized to control the transport of target chemicals to regulate the interior concentration of both substrate and reaction products. In this study, an artificial compartment with size-selective molecular transport function was constructed by using a DNA origami-guided liposome prepared by modifying the method reported by Perrault et al. This completely isolates the liposome interior, including the DNA origami skeleton, from the external environment and allows the assembly of a defined number of molecules of interest inside and/or outside the compartment. By incorporating a bacterial membrane protein, OmpF, into the liposome, the resulting artificial compartment was shown to transport only the molecule of interest with a molecular weight below 600 Da from the external environment into the interior of the compartment
The crystal facet-dependent electrochemical performance of TiO2 nanocrystals for heavy metal detection: Theoretical prediction and experimental proof
Tailored design/fabrication of electroanalytical materials with highly-active exposed crystal planes is of great importance for the development of electrochemical sensing. In this work, combining experimental and theoretical efforts, we reported a facile strategy to fabricate TiO2 nanocrystals with tunable electrochemical performance for heavy metal detection. Density functional theory (DFT) calculations indicated that TiO2 (001) facet showed relative larger adsorption energy and lower diffusion energy barrier toward heavy metal ions, which is favorable for obtaining better electrochemical stripping behaviors. Based on this prediction, a series of TiO2 nanocrystals with different ratios of exposed (001) and (101) facets were synthesized. Electrochemical stripping experiments further demonstrated that with the increase of the percentage of exposed (001) facet, the sensitivity toward Pb(II) and Cd(II) was increased accordingly. When the percentage of exposed (001) facet was increased from 7% to 80%, the sensitivity increased by 190% and 93% for Pb(II) and Cd(II), respectively. Our work provides an effective route to construct advanced electroanalytical materials for sensing
Effects of Surface Modification of Nanotube Arrays on the Performance of CdS Quantum-Dot-Sensitized Solar Cells
CdS-sensitized TiO2 nanotube arrays have been fabricated using the method of successive ionic layer adsorption and reaction and used as a photoanode for quantum-dot-sensitized solar cells. Before being coated with CdS, the surface of TiO2 nanotube arrays was treated with TiCl4, nitric acid (HNO3), potassium hydroxide (KOH), and methyltrimethoxysilane (MTMS), respectively, for the purpose of reducing the interface transfer resistance of quantum-dot-sensitized solar cells. The surfaces of the modified samples represented the characteristics of superhydrophilic and hydrophobic which directly affect the power conversion efficiency of the solar cells. The results showed that surface modification resulted in the reduction of the surface tension, which played a significant role in the connectivity of CdS and TiO2 nanotube arrays. In addition, the solar cells based on CdS/TiO2 electrode treated by HNO3 achieved a maximum power conversion efficiency of 0.17%, which was 42% higher than the reference sample without any modification
Effects of Peer Support on Body Composition and Circumference in Chinese University Students
This study aimed to understand the effects of adopting peer support in physical education (PE) class on university students’ body composition and circumference. Two university PE classes were recruited and assigned randomly to class with peer support (CWP; n=41; 8 underweight, 23 normal weight, 5 overweight, and 5 obesity; mean age=19.6±1.3yrs; height=169.5±8.0 cm) or class without peer support (CWOP; n=41; 9 underweight, 23 normal weight, 4 overweight, 5 obesity; mean age=19.3±1.1yrs; height=169.1±6.7 cm). Both classes adopted 16 weeks the same bodyweight management program for fitness promotion for 90 min/session/week (15 min warm-up, 60 min main training, 15 min cool-down). Students in CWP were asked to group with 2-3 students and required to train in the same group throughout the program, while students in CWOP were asked to train individually. The two classes were coached by the same teacher and held in the same semester. Body composition (InBody320, South Korea) and circumference metrics (waist and hip circumferences, waist-to-hip ratio [WHR], body adiposity index [BAI]) were obtained before and after the program and statistically analyzed using repeated measures ANOVA. Weekly training frequency and duration after class were obtained using questionnaire and compared using t-tests. Results showed that the proportion of students in abnormal weight is significantly reduced only in CWP (χ2=10.7, P=0.013). Body mass (F=5.96, P=0.017) and body mass index (F=4.40, P=0.039) significantly reduced in both classes, and changes in muscle mass and body fat percentage were greater in CWP (45.1±8.9kg vs. 46.0±9.1kg, P \u3c 0.001, Cohen’s d=0.10; 19.8%±8.0% vs. 18.4%±8.3%, P=0.002, Cohen’s d=0.18) than CWOP (45.8±7.8kg vs. 45.6±8.0kg, P=0.42; 19.9%±7.3% vs. 19.6%±7.3%, P=0.23). Further, waist circumference, WHR, and BAI were significantly reduced in both groups, and BAI changes were greater in CWP (25.01±3.44 vs. 24.06±3.08, P \u3c 0.001, Cohen’s d=0.29) than CWOP (24.29±3.53 vs. 24.08±3.34, P=0.42). Finally, CWP group trained longer (3.2±0.9hrs vs. 1.6±0.8hrs, P=0.003, Cohen’s d=1.88) and more frequently (2.6±1.3 vs. 1.3±2.1, P \u3c 0.001, Cohen’s d=0.74) than their counterparts. University students benefited from the 16-week PE class with reduced body composition and circumference. However, CWP group showed greater changes. Accordingly, social support from a peer can enhance motivation, such as elders with a partner would more likely be active. Meanwhile, students with a peer would have longer training duration and higher training frequency. Thus, peer support affects training habits and benefits students in body composition and circumference. PE teachers are encouraged to adopt peer support in their classes for fitness promotion
Early Stage of Oxidation on Titanium Surface by Reactive Molecular Dynamics Simulation
Understanding of metal oxidation is very critical to corrosion control, catalysis synthesis, and advanced materials engineering. Metal oxidation is a very complex phenomenon, with many different processes which are coupled and involved from the onset of reaction. In this work, the initial stage of oxidation on titanium surface was investigated in atomic scale by molecular dynamics (MD) simulations using a reactive force field (ReaxFF). We show that oxygen transport is the dominant process during the initial oxidation. Our simulation also demonstrate that a compressive stress was generated in the oxide layer which blocked the oxygen transport perpendicular to the Titanium (0001) surface and further prevented oxidation in the deeper layers. The mechanism of initial oxidation observed in this work can be also applicable to other self-limiting oxidation
Interference Mitigation Methods for Unmanned Aerial Vehicles Served by Cellular Networks
A main challenge in providing connectivity to the low altitude unmanned
aerial vehicles (UAVs) through existing cellular network arises due to the
increased interference in the network. The increased altitude and favourable
propagation condition cause UAVs to generate more interference to the
neighbouring cells, and at the same time experience more interference from the
downlink transmissions of the neighbouring base stations. The uplink
interference problem may result in terrestrial UEs having degraded performance,
whereas the downlink interference problem may make it challenging for a UAV to
maintain connection with the network. In this paper, we propose several uplink
and downlink interference mitigation techniques to address these issues. The
results indicate that the proposed solutions can reduce the uplink throughput
degradation of terrestrial UEs and ensure UAVs to remain in LTE coverage under
the worst case scenarios when all the base stations transmit at full power.Comment: Submitted to IEEE 5G Word Forum 201
Tetrakis(1-ethyl-3-methylimidazolium) β-hexacosaoxidooctamolybdate
The title compound, (C6H11N2)4[Mo8O26] or (emim)4[β-Mo8O26] (emim is 1-ethyl-3-methylimidazolium), was obtained from the ionic liquid [emim]BF4. The asymmetric unit contains two [emim]+ cations and one-half of the [β-Mo8O26]4− tetraanion, which occupies a special position on an inversion centre. The β-[Mo8O26]4− tetraanion features eight distorted MoO6 coordination octahedra linked together through bridging O atoms
- …