Adaptive Q control for tapping-mode nanoscanning using a piezoactuated bimorph probe

A new approach, called adaptive Q control, for tapping-mode atomic force microscopy (AFM) is introduced and implemented on a homemade AFM setup utilizing a laser Doppler vibrometer and a piezoactuated bimorph probe. In standard Q control, the effective Q factor of the scanning probe is adjusted prior to the scanning depending on the application. However, there is a trade-off in setting the effective Q factor of an AFM probe. The Q factor is either increased to reduce the tapping forces or decreased to increase the maximum achievable scan speed. Realizing these two benefits simultaneously using standard Q control is not possible. In adaptive Q control, the Q factor of the probe is set to an initial value as in standard Q control, but then modified on the fly during scanning when necessary to achieve this goal. In this article, we present the basic theory behind adaptive Q control, the electronics enabling the online modification of the probe's effective Q factor, and the results of the experiments comparing three different methods: scanning (a) without Q control, (b) with standard Q control, and (c) with adaptive Q control. The results show that the performance of adaptive Q control is superior to the other two methods.     

Micro-RNA and Proteomic Profiles of Plasma-Derived Exosomes from Irradiated Mice Reveal Molecular Changes Preventing Apoptosis in Neonatal Cerebellum

Cell communication via exosomes is capable of influencing cell fate in stress situations such as exposure to ionizing radiation. In vitro and in vivo studies have shown that exosomes might play a role in out-of-target radiation effects by carrying molecular signaling mediators of radiation damage, as well as opposite protective functions resulting in resistance to radiotherapy. However, a global understanding of exosomes and their radiation-induced regulation, especially within the context of an intact mammalian organism, has been lacking. In this in vivo study, we demonstrate that, compared to sham-irradiated (SI) mice, a distinct pattern of proteins and miRNAs is found packaged into circulating plasma exosomes after whole-body and partial-body irradiation (WBI and PBI) with 2 Gy X-rays. A high number of deregulated proteins (59% of WBI and 67% of PBI) was found in the exosomes of irradiated mice. In total, 57 and 13 miRNAs were deregulated in WBI and PBI groups, respectively, suggesting that the miRNA cargo is influenced by the tissue volume exposed to radiation. In addition, five miRNAs (miR-99b-3p, miR-200a-3p, miR-200a, miR-182-5p, miR-182) were commonly overexpressed in the exosomes from the WBI and PBI groups. In this study, particular emphasis was also given to the determination of the in vivo effect of exosome transfer by intracranial injection in the highly radiosensitive neonatal cerebellum at postnatal day 3. In accordance with a major overall anti-apoptotic function of the commonly deregulated miRNAs, here, we report that exosomes from the plasma of irradiated mice, especially in the case of WBI, prevent radiation-induced apoptosis, thus holding promise for exosome-based future therapeutic applications against radiation injury.     

Micro Piezoelectric Ultrasonic Motors

This paper reviews recent developments of micro ultrasonic rotary motors using piezoelectric resonant vibrations. Following the historical background, four ultrasonic motors recently developed at Penn State University are introduced; windmill, PZT tube, metal tube, and shear-type motors. Driving principles and motor characteristics are described in comparison with the conventional ultrasonic motors. Motors with 1.5 mm in diameter and 0.8 mNm in torque have been actually developed.     

Biocompatibility and Mechanical Stability of Nanopatterned Titanium Films on Stainless Steel Vascular Stents

Nanoporous ceramic coatings such as titania are promoted to produce drug-free cardiovascular stents with a low risk of in-stent restenosis (ISR) because of their selectivity towards vascular cell proliferation. The brittle coatings applied on stents are prone to cracking because they are subjected to plastic deformation during implantation. This study aims to overcome this problem by using a unique process without refraining from biocompatibility. Accordingly, a titanium film with 1 µm thickness was deposited on 316 LVM stainless-steel sheets using magnetron sputtering. Then, the samples were anodized to produce nanoporous oxide. The nanoporous oxide was removed by ultrasonication, leaving an approximately 500 nm metallic titanium layer with a nanopatterned surface. XPS studies revealed the presence of a 5 nm-thick TiO₂ surface layer with a trace amount of fluorinated titanium on nanopatterned surfaces. Oxygen plasma treatment of the nanopatterned surface produced an additional 5 nm-thick fluoride-free oxide layer. The samples did not exhibit any cracking or spallation during plastic deformation. Cell viability studies showed that nanopatterned surfaces stimulate endothelial cell proliferation while reducing the proliferation of smooth muscle cells. Plasma treatment further accelerated the proliferation of endothelial cells. Activation of blood platelets did not occur on oxygen plasma-treated, fluoride-free nanopatterned surfaces. The presented surface treatment method can also be applied to other stent materials such as CoCr, nitinol, and orthopedic implants.     

Polypropylene microfibers via solution electrospinning under ambient conditions

Uniform beadless fibers of chlorinated polypropylene (PP-Cl) are prepared by electrospinning of PP-Cl solutions in tetrahydrofuran at different concentrations, feed rates, applied voltages, and tip-to-collector distances (TCDs) under ambient conditions for the first time. Average fiber diameter and morphology of the electrospun PP-Cl fibers are determined by scanning electron microscopy. On the other hand, the wettability of the fibers is examined by water contact angle (WCA) measurements. Furthermore, thermal behavior of fibers is investigated by differential scanning calorimetry and thermogravimetric analyses, respectively. Obtained results show that the higher concentrations and feed rates of polymer solutions not only enhance the average diameter of the electrospun fibers ranging from 2.2 ± 0.5 to 2.8 ± 0.3 μm but improve the hydrophobicity of the fiber surfaces from 128° ± 1.1 to 141° ± 1.0 as well. On the other hand, when applied voltage is increased or TCD is decreased, diameters of achieved fibers are enhanced. It is suggested that PP-Cl is an useful material for solution electrospinning process at under ambient conditions, exhibiting great scientific merit and good industrial expectation in the potential PP applications. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48199.     

The Role of Interleukin-1-Receptor-Antagonist in Bladder Cancer Cell Migration and Invasion

Background: The interleukin-1-receptor antagonist IL1RA (encoded by the IL1RN gene) is a potent competitive antagonist to interleukin-1 (IL1) and thereby is mainly involved in the regulation of inflammation. Previous data indicated a role of IL1RA in muscle-invasive urothelial carcinoma of the bladder (UCB) as well as an IL1-dependent decrease in tissue barrier function, potentially contributing to cancer cell invasion. Objective: Based on these observations, here we investigated the potential roles of IL1RA, IL1A, and IL1B in bladder cancer cell invasion in vitro. Methods: Cell culture, real-time impedance sensing, invasion assays (Boyden chamber, pig bladder model), qPCR, Western blot, ELISA, gene overexpression. Results: We observed a loss of IL1RA expression in invasive, high-grade bladder cancer cell lines T24, UMUC-3, and HT1197 while IL1RA expression was readily detectable in the immortalized UROtsa cells, the non-invasive bladder cancer cell line RT4, and in benign patient urothelium. Thus, we modified the invasive human bladder cancer cell line T24 to ectopically express IL1RA, and measured changes in cell migration/invasion using the xCELLigence Real-Time-Cell-Analysis (RTCA) system and the Boyden chamber assay. The real-time observation data showed a significant decrease of cell migration and invasion in T24 cells overexpressing IL1RA (T24-IL1RA), compared to cells harboring an empty vector (T24-EV). Concurrently, tumor cytokines, e.g., IL1B, attenuated the vascular endothelial barrier, which resulted in a reduction of the Cell Index (CI), an impedance-based dimensionless unit. This reduction could be reverted by the simultaneous incubation with IL1RA. Moreover, we used an ex vivo porcine organ culture system to evaluate cell invasion capacity and showed that T24-IL1RA cells showed significantly less invasive capacity compared to parental T24 cells or T24-EV. Conclusions: Taken together, our results indicate an inverse correlation between IL1RA expression and tumor cell invasive capacity and migration, suggesting that IL1RA plays a role in bladder carcinogenesis, while the exact mechanisms by which IL1RA influences tumor cells migration/invasion remain to be clarified in future studies. Furthermore, we confirmed that real-time impedance sensing and the porcine ex vivo organ culture methods are powerful tools to discover differences in cancer cell migration and invasion.     

Flux Dynamics and Time Dependent Effects in Superconducting MgB2

We have investigated the time dependent flux motion in a polycrystalline superconducting MgB₂ sample by means of current-voltage (I?CV curves) and transport relaxation (V?Ct curves) measurements. The transport measurements were carried out as functions of temperature (T), transport current (I), and applied magnetic field (H). The time effects in the I?CV curves were investigated with the help of the sweep rate of transport current (dI/dt). The I?CV curves exhibit nearly reversible behavior for both slow and high current sweep rates (dI/dt) upon cycling the transport current. It was observed that the evolution of the I?CV curves is nearly independent of dI/dt. The small instabilities, voltage jump, and drops appearing at low dissipation levels were interpreted as a kind of plastic flow of the vortices evolving in the form of stripe or cluster in different sizes and local fluctuations in the superconducting order parameter. It was shown that the experimental I?CV curves are in good agreement with a power law behavior, V(I)??I ⁿ . The pinning potential U ₀ extracted from the fitting procedure is found to be approximately independent of dI/dt. In addition to the standard procedure, a reverse procedure was employed to study how the transport current (or associated vortices) penetrates from the surface into the sample. It was found that there is no marked difference between the I?CV curves obtained in the standard and reverse procedures. These results suggest that, in polycrystalline MgB₂, the weak links between grains (standard procedure) and surface weak links (reverse procedure) do not have a considerable effect on the evolution of the I?CV curves and also on the other transport measurements. In order to understand better the flux dynamics, the experimental results for polycrystalline MgB₂ sample were compared to previous similar studies on superconducting Y₁Ba₂Cu₃O_7?x (YBCO) and Bi_1.7Pb_0.3Sr₂Ca₂Cu₃O _x (BSCCO) polycrystalline samples.     

A systematic review of software fault prediction studies

This paper provides a systematic review of previous software fault prediction studies with a specific focus on metrics, methods, and datasets. The review uses 74 software fault prediction papers in 11 journals and several conference proceedings. According to the review results, the usage percentage of public datasets increased significantly and the usage percentage of machine learning algorithms increased slightly since 2005. In addition, method-level metrics are still the most dominant metrics in fault prediction research area and machine learning algorithms are still the most popular methods for fault prediction. Researchers working on software fault prediction area should continue to use public datasets and machine learning algorithms to build better fault predictors. The usage percentage of class-level is beyond acceptable levels and they should be used much more than they are now in order to predict the faults earlier in design phase of software life cycle.     

Investigating the effect of dataset size, metrics sets, and feature selection techniques on software fault prediction problem

Software quality engineering comprises of several quality assurance activities such as testing, formal verification, inspection, fault tolerance, and software fault prediction. Until now, many researchers developed and validated several fault prediction models by using machine learning and statistical techniques. There have been used different kinds of software metrics and diverse feature reduction techniques in order to improve the models’ performance. However, these studies did not investigate the effect of dataset size, metrics set, and feature selection techniques for software fault prediction. This study is focused on the high-performance fault predictors based on machine learning such as Random Forests and the algorithms based on a new computational intelligence approach called Artificial Immune Systems. We used public NASA datasets from the PROMISE repository to make our predictive models repeatable, refutable, and verifiable. The research questions were based on the effects of dataset size, metrics set, and feature selection techniques. In order to answer these questions, there were defined seven test groups. Additionally, nine classifiers were examined for each of the five public NASA datasets. According to this study, Random Forests provides the best prediction performance for large datasets and Naive Bayes is the best prediction algorithm for small datasets in terms of the Area Under Receiver Operating Characteristics Curve (AUC) evaluation parameter. The parallel implementation of Artificial Immune Recognition Systems (AIRS2Parallel) algorithm is the best Artificial Immune Systems paradigm-based algorithm when the method-level metrics are used.     

An information theoretic approach to camera control for crowded scenes

Navigation and monitoring of large and crowded virtual environments is a challenging task and requires intuitive camera control techniques to assist users. In this paper, we present a novel automatic camera control technique providing a scene analysis framework based on information theory. The developed framework contains a probabilistic model of the scene to build entropy and expectancy maps. These maps are utilized to find interest points which represent either characteristic behaviors of the crowd or novel events occurring in the scene. After an interest point is chosen, the camera is updated accordingly to display this point. We tested our model in a crowd simulation environment and it performed successfully. Our method can be integrated into existent camera control modules in computer games, crowd simulations and movie pre-visualization applications.