Ultrasound‐Propelled Nanoporous Gold Wire for Efficient Drug Loading and Release

Ultrasound (US)‐powered nanowire motors based on nanoporous gold segment are developed for increasing the drug loading capacity. The new highly porous nanomotors are characterized with a tunable pore size, high surface area, and high capacity for the drug payload. These nanowire motors are prepared by template membrane deposition of a silver‐gold alloy segment followed by dealloying the silver component. The drug doxorubicin (DOX) is loaded within the nanopores via electrostatic interactions with an anionic polymeric coating. The nanoporous gold structure also facilitates the near‐infrared (NIR) light controlled release of the drug through photothermal effects. Ultrasound‐driven transport of the loaded drug toward cancer cells followed by NIR‐light triggered release is illustrated. The incorporation of the nanoporous gold segment leads to a nearly 20‐fold increase in the active surface area compared to common gold nanowire motors. It is envisioned that such US‐powered nanomotors could provide a new approach to rapidly and efficiently deliver large therapeutic payloads in a target‐specific manner.     

Model-based testing of digital TVs: an industry-as-laboratory approach

Model-based testing is a promising approach for increasing the efficiency of the testing process and for improving software quality. It has been employed in the industry for more than a decade. Nevertheless, there are still challenges regarding its application in different domains. Some of these challenges are general, while some others are domain-specific. In this paper, we explain our experiences in enhancing model-based testing for its adoption in the consumer electronics domain, in particular for Digital TV systems. We applied the so-called industry-as-laboratory approach to define/refine research problems and evaluate our research results. We summarize these results and provide an evaluation of relevant research problems for our context. We observed that the industry-as-laboratory approach is highly effective for industry-academia collaboration and technology transfer in the scope of model-based software testing.     

Part-set cuing effect with word-fragment cuing: Evidence against the strategy disruption and increased-list-length explanations.

A series of five experiments provide evidence against a strategy disruption explanation (e.g., Basden, Basden, & Galloway, 1977) of the part-set cuing effect. Word-fragment cuing tests were used to gauge memory performance; subjects tried to discover each word with the help of the given letters. With the words thus probed for recall individually and in an experimenter-imposed order, the strategies in the cue and control conditions were kept constant. Yet performance was impaired when the critical fragments were preceded by relevant cues, for both studied and nonstudied words and in the case of studied words, with both intralist and extralist cues. In addition, Experiment 6 provides evidence against the increased-list-length explanation (Watkins, 1975). Presenting cues in the beginning of the test list impaired recall performance, whereas presenting the same cues in the same way at the end of the study list did not. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Rock Salt Ni/Co Oxides with Unusual Nanoscale‐Stabilized Composition as Water Splitting Electrocatalysts

The influence of nanoscale on the formation of metastable phases is an important aspect of nanostructuring that can lead to the discovery of unusual material compositions. Here, the synthesis, structural characterization, and electrochemical performance of Ni/Co mixed oxide nanocrystals in the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is reported and the influence of nanoscaling on their composition and solubility range is investigated. Using a solvothermal synthesis in tert ‐butanol ultrasmall crystalline and highly dispersible Ni _x Co_{1? x} O nanoparticles with rock salt type structure are obtained. The mixed oxides feature non‐equilibrium phases with unusual miscibility in the whole composition range, which is attributed to a stabilizing effect of the nanoscale combined with kinetic control of particle formation. Substitutional incorporation of Co and Ni atoms into the rock salt lattice has a remarkable effect on the formal potentials of NiO oxidation that shift continuously to lower values with increasing Co content. This can be related to a monotonic reduction of the work function of (001) and (111)‐oriented surfaces with an increase in Co content, as obtained from density functional theory (DFT+U) calculations. Furthermore, the electrocatalytic performance of the Ni _x Co_{1? x} O nanoparticles in water splitting changes significantly. OER activity continuously increases with increasing Ni contents, while HER activity shows an opposite trend, increasing for higher Co contents. The high electrocatalytic activity and tunable performance of the nonequilibrium Ni _x Co_{1? x} O nanoparticles in HER and OER demonstrate great potential in the design of electrocatalysts for overall water splitting.     

Tuning algorithms for fractional order internal model controllers for time delay processes

This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.     

3D‐Printed Microrobotic Transporters with Recapitulated Stem Cell Niche for Programmable and Active Cell Delivery

Poor retention rate, low targeting accuracy, and spontaneous transformation of stem cells present major clinical barriers to the success of therapies based on stem cell transplantation. To improve the clinical outcome, efforts should focus on the active delivery of stem cells to the target tissue site within a controlled environment, increasing survival, and fate for effective tissue regeneration. Here, a remotely steerable microrobotic cell transporter is presented with a biophysically and biochemically recapitulated stem cell niche for directing stem cells towards a pre‐destined cell lineage. The magnetically actuated double‐helical cell microtransporters of 76 µm length and 20 µm inner cavity diameter are 3D printed where biological and mechanical information regarding the stem cell niche are encoded at the single‐cell level. Cell‐loaded microtransporters are mobilized inside confined microchannels along computer‐controlled trajectories under rotating magnetic fields. The mesenchymal stem cells are shown retaining their differentiation capacities to commit to the osteogenic lineage when stimulated inside the microswimmers in vitro. Such a microrobotic approach has the potential to enable the development of active microcarriers with embedded functionalities for controlled and precisely localized therapeutic cell delivery.     

基于深度迁移学习的饮食图像识别研究

卷积神经网络(CNN)应用于图像识别具有很大优势,但是需要足够深的网络和大量标签完善的数据集才能发挥其优越性.实际应用中,往往需要应对的是质量差和大小不一的数据集,且受硬件设备限制.为了提高图像识别效率和精度,提出一种基于深度卷积神经网络和迁移学习的识别算法.该算法首先对图像预处理和数据增强,后迁移大样本提取出的特征信息用于CNN特征提取,再接入微调网络对数据集再训练.实验结果显示,本文算法对饮食识别的精度和时间性能均有显著的提高,精确度最高可达98％以上,精度提升最高可达10％以上,时间性能提升幅度最高可达110％.     

Preparation and characterization of aluminum pillared K10 and KSF for adsorption of trimethoprim

Montmorillonite KSF and K10 were used as precursor materials for synthesis of aluminum pillared K10 and KSF (Al-K10 and Al-KSF) which characterized by TGA, XRD, SEM and FT-IR spectroscopic analysis. The sorption of trimethoprim (TMP) which is commonly employed as an antibiotic onto Al-K10 and Al-KSF was also investigated as a function of adsorbent dosage, solution pH, contact time and temperature. The adsorption kinetics was interpreted using pseudo-first-order, pseudo-second-order kinetic models and intraparticle diffusion model. The pseudo-second-order model provided the best correlation. Adsorption isotherm parameters were obtained from Freundlich, Langmuir and Dubinin–Radushkevich (DR) isotherm models. Adsorption of TMP onto Al-K10 and Al-KSF was physical in nature and ion-exchange mechanism for DR equation, respectively. Al-K10 exhibits higher removal capacity at lower adsorbent dosages in comparison with Al-KSF. The removal capacity was increased by increasing pH. ΔH⁰, ΔS⁰ and ΔG⁰ showed that adsorption of trimethoprim was endothermic, increasing randomness and not spontaneous in nature.