Graphene oxide nanoparticles as a nonbleaching optical probe for two-photon luminescence imaging and cell therapy

Lasting glow: Under femtosecond laser irradiation, graphene oxide nanoparticles (GONs) give strong two-photon luminescence (TPL; see picture). The presence of GONs also induces microbubbling, which causes cell death at an order of magnitude lower laser power than when cells are not labeled. The results show that GONs can be used for TPL-based imaging and photothermal cancer therapy.

Compression and probing C−H···I hydrogen bonds of iodoform under high pressure by x-ray diffraction and raman scattering

High-pressure methods were applied to investigate the structural stability and hydrogen bonding of polar molecules of iodoform by synchrotron radiation X-ray diffraction and Raman spectra measurements, respectively. Up to a pressure of 40 GPa, no phase transitions were observed. The discontinuous frequency shift of the C−H stretching band is believed to be related to the enhancement of the C−H···I weak hydrogen bonds under high pressures. Ab initio calculations were performed, and the results predict the frequency shift of the C−H stretching vibration as C−H···I interacts via hydrogen bonding. The bulk modulus is 17.3 ± 0.8 GPa, with a pressure derivative of 5.2.

Shrinkage induced stretchable micro-wrinkled reduced graphene oxide composite with recoverable conductivity

A novel thermo-mechanical shrinking method is reported to fabricate a three dimensional (3D) stretchable and highly conductive micro-wrinkled reduced graphene oxide (MWrGO) supported on an elastic polydimethylsiloxane (PDMS) substrates. This 3D rGO architecture not only increases the specific area for more electrons to pass through but also bestows stretchability to the conductive pathway. The structural change of micro-wrinkles has been monitored by an in situ straining microscopy. The electrical conductivity of the samples remained fairly constant and stayed above 25 S/m under low deformation (no more than 30% strain) for up to 500 mechanical stretching-release cycles. Additionally, the MWrGO/PDMS composite can be stretched bi-axially because the shrinking process itself is isotropic. This MWrGO based stretchable composite with stable electrical properties and long life span could form a new platform of stretchable electronics.

Self-assembly of monolayered lipid membranes for surface-coating of a nanoconfined Bombyx mori silk fibroin film

Regenerated Bombyx mori (B. mori) silk fibroin is a type of widely used biomaterial. The β-sheet structure of it after methanol treatment provides water-insolubility and mechanical stability while on the other side leads to a hydrophobic surface which is less preferred by biological systems. In this work we prepare a novel type of nanoconfined silk fibroin film with a thickness below 100 nm. The film has a flat while hydrophobic surface because of its β-sheet structure due to the z-direction confinement during formation. Different types of lipid monolayers, DOPC, DPPC and MO, are assembled on the silk film surface. The lipid coating, especially the DPPC membrane, provides a much smoother and more hydrophilic surface due to the gel phase tails of the lipids, in comparison with the DOPC and MO ones which are in a liquid phase and have a much stronger interfacial association between silk film surface and lipid tails. Such a lipid coating preserves the biocompatibility and cellular affinity of the silk film which promises potential applications as surface coatings for materials for biological use.

KBRE: a framework for knowledge-based requirements engineering

Detecting inconsistencies is a critical part of requirements engineering (RE) and has been a topic of interest for several decades. Domain knowledge and semantics of requirements not only play important roles in elaborating requirements but are also a crucial way to detect conflicts among them. In this paper, we present a novel knowledge-based RE framework (KBRE) in which domain knowledge and semantics of requirements are central to elaboration, structuring, and management of captured requirements. Moreover, we also show how they facilitate the identification of requirements inconsistencies and other-related problems. In our KBRE model, description logic (DL) is used as the fundamental logical system for requirements analysis and reasoning. In addition, the application of DL in the form of Manchester OWL Syntax brings simplicity to the formalization of requirements while preserving sufficient expressive power. A tool has been developed and applied to an industrial use case to validate our approach.

FESTAL: fault-tolerant elastic scheduling algorithm for real-time tasks in virtualized clouds

As clouds have been deployed widely in various fields, the reliability and availability of clouds become the major concern of cloud service providers and users. Thereby, fault tolerance in clouds receives a great deal of attention in both industry and academia, especially for real-time applications due to their safety critical nature. Large amounts of researches have been conducted to realize fault tolerance in distributed systems, among which fault-tolerant scheduling plays a significant role. However, few researches on the fault-tolerant scheduling study the virtualization and the elasticity, two key features of clouds, sufficiently. To address this issue, this paper presents a fault-tolerant mechanism which extends the primary-backup model to incorporate the features of clouds. Meanwhile, for the first time, we propose an elastic resource provisioning mechanism in the fault-tolerant context to improve the resource utilization. On the basis of the fault-tolerant mechanism and the elastic resource provisioning mechanism, we design novel fault-tolerant elastic scheduling algorithms for real-time tasks in clouds named FESTAL, aiming at achieving both fault tolerance and high resource utilization in clouds. Extensive experiments injecting with random synthetic workloads as well as the workload from the latest version of the Google cloud tracelogs are conducted by CloudSim to compare FESTAL with three baseline algorithms, i.e., Non-M igration-FESTAL (NMFESTAL), Non-Overlapping-FESTAL (NOFESTAL), and Elastic First Fit (EFF). The experimental results demonstrate that FESTAL is able to effectively enhance the performance of virtualized clouds.

A Bayesian nonparametric approach to multilevel regression

Regression is at the cornerstone of statistical analysis. Multilevel regression, on the other hand, receives little research attention, though it is prevalent in economics, biostatistics and healthcare to name a few. We present a Bayesian nonparametric framework for multilevel regression where individuals including observations and outcomes are organized into groups. Furthermore, our approach exploits additional group-specific context observations, we use Dirichlet Process with product-space base measure in a nested structure to model group-level context distribution and the regression distribution to accommodate the multilevel structure of the data. The proposed model simultaneously partitions groups into cluster and perform regression. We provide collapsed Gibbs sampler for posterior inference. We perform extensive experiments on econometric panel data and healthcare longitudinal data to demonstrate the effectiveness of the proposed model