Miracle-dz/UniFAR-FTUs huggingface dataset:
An electrostatic lower stator axial-gap polysilicon wobble motor. II. Fabrication and performance

For pt. I see ibid., vol. 7, no. 1, p. 79-86 (1998). This paper presents the fabrication and first performance characteristics of electrostatically driven axial-gap polysilicon wobble motors. The fabrication is based on a four mask process using polysilicon surface-micromachining techniques. Three twelve-stator-pole wobble motor designs have been realized with rotor radii of 50 and 100 /spl mu/m. Motors have been operated successfully at driving voltages as low as 6 V at speeds up to 150 rpm. The motor performance is characterized by gear ratio measurements and measuring starting and stopping voltages. Motor lifetimes of several million wobble cycles, comparable to operating times of several hours, have been obtained.
DNA promoter hypermethylation in nipple fluid: a potential tool for early breast cancer detection

Introduction Nipple fluid aspiration provides direct non-invasive sampling of fluid from the mammary ductal system, where the majority of breast cancers originate. DNA promoter hypermethylation (“methylation”) occurs early and at high frequency in breast carcinogenesis, bearing the potential as a biomarker for cancer detection at its earliest stages. We assessed methylation in nipple fluid from breasts of healthy women, of women with sporadic breast cancer and of their contralateral breasts. Our goal was to investigate whether nipple fluid can be used as a reliable methylation biomarker source. Methods Methylation levels of 13 genes were analysed by quantitative multiplex-methylation specific PCR (QM-MSP) in nipple fluid samples from breasts of healthy women, and from the affected and contralateral breasts of breast cancer patients. Results Methylation analysis of the low-volume nipple fluid samples was feasible. Despite the generally low methylation levels, cancerous and healthy breasts nipple fluid could be discriminated with an area under the receiver operating characteristic curve (AUC) of 0.64 (p<0.01) based on a multivariate model including AKR1B1, ALX1, RASSF1A and TM6SF1. Within-patient differences between cancerous and contralateral nipple fluid samples were less prominent. Conclusions Cancerous nipple fluid contains increased levels of methylation of tumor suppressor genes that potentially could serve as a biomarker for early breast cancer detection.
Angiotensin II Induces Angiogenesis in the Hypoxic Adult Mouse Heart In Vitro Through

Angiotensin II is a vasoactive peptide that may affect vascularization of the ischemic heart via angiogenesis. In this study we aimed at studying the mechanisms underlying the angiogenic effects of angiotensin II under hypoxia in the mouse heart in vitro. Endothelial sprout formation from pieces of mouse hearts was assessed under normoxia (21% O2) and hypoxia (1% O2) during a 7-day period of in vitro culture. Only under hypoxia did angiotensin II dose-dependently induce endothelial sprout formation, peaking at 10 7 mol/L of angiotensin II. Angiotensin II type 1 (AT1) receptor blockade by losartan did not affect angiotensin II–induced sprouting in wild-type mice. Conversely, the angiotensin II type 2 (AT2) receptor antagonist PD 123319 blocked this response. In hearts from AT1 / mice, angiotensin II–elicited sprouting was preserved but blocked again by AT2 receptor antagonism. In contrast, no angiotensin II–induced sprouting was found in preparations from hearts of AT2 / mice. Angiotensin II–mediated angiogenesis was also abolished by a specific inhibitor of the B2 kinin receptor in both wild-type and AT1 / mice. Furthermore, angiotensin II failed to induce endothelial sprout formation in hearts from B2 / mice. Finally, NO inhibition completely blunted sprouting in hearts from wild-type mice, whereas NO donors could restore sprouting in AT2 / and B2 / hearts. This in vitro study suggests the obligatory role of hypoxia in the angiogenic effect of angiotensin II in the mouse heart via the AT2 receptor through a mechanism that involves bradykinin, its B2 receptor, and NO as a downstream effector. (Hypertension. 2007;49:1178-1185.)
Noninvasive Visualization of MicroRNA-16 in the Chemoresistance of Gastric Cancer Using a Dual Reporter Gene Imaging System

MicroRNAs (miRNAs) have been implicated to play a central role in the development of drug resistance in a variety of malignancies. However, many studies were conducted at the in vitro level and could not provide the in vivo information on the functions of miRNAs in the anticancer drug resistance. Here, we introduced a dual reporter gene imaging system for noninvasively monitoring the kinetic expression of miRNA-16 during chemoresistance in gastric cancer both in vitro and in vivo. Human sodium iodide symporter (hNIS) and firefly luciferase (Fluc) genes were linked to form hNIS/Fluc double fusion reporter gene and then generate human gastric cancer cell line NF-3xmir16 and its multidrug resistance cell line NF-3xmir16/VCR. Radioiodide uptake and Fluc luminescence signals in vitro correlated well with viable cell numbers. The luciferase activities and radioiodide uptake in NF-3xmir16 cells were remarkably repressed by exogenous or endogenous miRNA-16. The NF-3xmir16/VCR cells showed a significant increase of 131I uptake and luminescence intensity compared to NF-3xmir16 cells. The radioactivity from in vivo 99mTc-pertechnetate imaging and the intensity from bioluminescence imaging were also increased in NF-3xmir16/VCR compared with that in NF-3xmir16 tumor xenografts. Furthermore, using this reporter gene system, we found that etoposide (VP-16) and 5-fluorouracil (5-FU) activated miRNA-16 expression in vitro and in vivo, and the upregulation of miRNA-16 is p38MAPK dependent but NF-κB independent. This dual imaging reporter gene may be served as a novel tool for in vivo imaging of microRNAs in the chemoresistance of cancers, as well as for early detection and diagnosis in clinic.
Flocking control with communication noise based on second-order distributed consensus algorithm

In the paper, we analyze the distributed flocking algorithms with communication noise. Under Boid model, flocking algorithm with communication noise is easy to diverge. In order to improve the convergence performance of flocking algorithms with communication noise and overcome the impact brought by communication noise on flocking algorithm, in the paper, a distributed flocking algorithm based on SODCT distributed consensus algorithm is proposed. The second-order flocking algorithm under Boid model is analyzed, and simulations are done. Results show that the second-order distributed flocking algorithm can reach cohesion, and its convergence performance is better than that of the first-order distributed flocking algorithm, moreover, the impact of communication noise on the second-order flocking algorithm is smaller.
The BRG1 transcriptional coregulator

The packaging of genomic DNA into chromatin, often viewed as an impediment to the transcription process, plays a fundamental role in the regulation of gene expression. Chromatin remodeling proteins have been shown to alter local chromatin structure and facilitate recruitment of essential factors required for transcription. Brahma-related gene-1 (BRG1), the central catalytic subunit of numerous chromatin-modifying enzymatic complexes, uses the energy derived from ATP-hydrolysis to disrupt the chromatin architecture of target promoters. In this review, we examine BRG1 as a major coregulator of transcription. BRG1 has been implicated in the activation and repression of gene expression through the modulation of chromatin in various tissues and physiological conditions. Outstanding examples are studies demonstrating that BRG1 is a necessary component for nuclear receptor-mediated transcriptional activation. The remodeling protein is also associated with transcriptional corepressor complexes which recruit remodeling activity to target promoters for gene silencing. Taken together, BRG1 appears to be a critical modulator of transcriptional regulation in cellular processes including transcriptional regulation, replication, DNA repair and recombination.
BRAF mutation testing with a rapid, fully integrated molecular diagnostics system

Fast and accurate diagnostic systems are needed for further implementation of precision therapy of BRAF-mutant and other cancers. The novel IdyllaTM BRAF Mutation Test has high sensitivity and shorter turnaround times compared to other methods. We used Idylla to detect BRAF V600 mutations in archived formalin-fixed paraffin-embedded (FFPE) tumor samples and compared these results with those obtained using the cobas 4800 BRAF V600 Mutation Test or MiSeq deep sequencing system and with those obtained by a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory employing polymerase chain reaction–based sequencing, mass spectrometric detection, or next-generation sequencing. In one set of 60 FFPE tumor samples (15 with BRAF mutations per Idylla), the Idylla and cobas results had an agreement of 97%. Idylla detected BRAF V600 mutations in two additional samples. The Idylla and MiSeq results had 100% concordance. In a separate set of 100 FFPE tumor samples (64 with BRAF mutation per Idylla), the Idylla and CLIA-certified laboratory results demonstrated an agreement of 96% even though the tests were not performed simultaneously and different FFPE blocks had to be used for 9 cases. The IdyllaTM BRAF Mutation Test produced results quickly (sample to results time was about 90 minutes with about 2 minutes of hands on time) and the closed nature of the cartridge eliminates the risk of PCR contamination. In conclusion, our observations demonstrate that the Idylla test is rapid and has high concordance with other routinely used but more complex BRAF mutation–detecting tests.
Carbon Nanomaterials in Agriculture: A Critical Review

There has been great interest in the use of carbon nano-materials (CNMs) in agriculture. However, the existing literature reveals mixed effects from CNM exposure on plants, ranging from enhanced crop yield to acute cytotoxicity and genetic alteration. These seemingly inconsistent research-outcomes, taken with the current technological limitations for in situ CNM detection, present significant hurdles to the wide scale use of CNMs in agriculture. The objective of this review is to evaluate the current literature, including studies with both positive and negative effects of different CNMs (e.g., carbon nano-tubes, fullerenes, carbon nanoparticles, and carbon nano-horns, among others) on terrestrial plants and associated soil-dwelling microbes. The effects of CNMs on the uptake of various co-contaminants will also be discussed. Last, we highlight critical knowledge gaps, including the need for more soil-based investigations under environmentally relevant conditions. In addition, efforts need to be focused on better understanding of the underlying mechanism of CNM-plant interactions.
Control system design for rotorcraft-based unmanned aerial vehicles using time-domain system identification

This paper introduces the development of flight control system for rotorcraft-based unmanned aerial vehicle (RUAV). In this research, the linear time-invariant model valid for hover is sought. The system response data is acquired in carefully devised experiment procedure and then a linear time-invariant system model is obtained using the time-domain analysis method. The acquired model is used to design feedback controller consisting of inner-loop attitude feedback control, mid-loop velocity feedback control and the outer-loop position control. The proposed controller is implemented on an on-board digital computer and tested in a Berkeley RUAV and shows outstanding hovering performance.
The Proper Treatment of Coordination in Peirce Grammar

Peirce grammar provides a first-order, relational semantics for extensional fragments of natural language. Proposals in the literature to model natural language coordination by boolean operations in Peirce grammar lead to inadaequate results. We propose to equip Peirce grammar with an additional sort of finite trees and to admit recursion on trees for defining the evaluation of expressions. We demonstrate how this leads to a better treatment of coordination and other recursive constructions, such as the inverse linking of quantifiers in nested noun phrases.
Estimating Four Hicksian Welfare Measures for a Public Good: A Contingent Valuation Investigation

Using equivalent loss (the monetary loss equivalent to a proposed amenity reduction, EL) and equivalent gain (the gain equivalent to a proposed amenity increase, EG) alongside traditional welfare measures in a contingent valuation study of traffic disamenity, we report an experiment designed to test theoretical explanations of the well-known disparity between compensating surplus and equivalent surplus measures of welfare. No compelling evidence is found in favor of loss aversion as a cause of the disparity. Meanwhile, as valuation measures, the performance of EL is similar to the traditional willingness to pay for a gain, while EG performs poorly.
Agricultural investment for growth and poverty reduction in Nigeria

This study assesses public investment required for agricultural growth and poverty reduction in Nigeria. Using time series data for public spending and agricultural total factor productivity (TFP) growth, the econometrically estimated results show that one percent of growth in agricultural spending generates 0.24 percent of growth in agricultural TFP. To support 9.5 percent in agricultural annual growth in 2009-17, a growth rate from the economy-wide analysis on options of growth for poverty reduction (Diao et al. 2009), required agricultural investment would have to grow at 23.8 percent annually in the same period. However, if the spending efficiency were improved based on an estimated elasticity for Sub-Saharan Africa as whole, then required agricultural investment would grow at 13.6 percent per year instead. The study also shows that investment outside agriculture benefits the agricultural sector. By taking into account such indirect effect of public investment, required growth in agricultural spending is much lower.
Dynamic Endothelial Cell Rearrangements Drive Developmental Vessel Regression

Patterning of functional blood vessel networks is achieved by pruning of superfluous connections. The cellular and molecular principles of vessel regression are poorly understood. Here we show that regression is mediated by dynamic and polarized migration of endothelial cells, representing anastomosis in reverse. Establishing and analyzing the first axial polarity map of all endothelial cells in a remodeling vascular network, we propose that balanced movement of cells maintains the primitive plexus under low shear conditions in a metastable dynamic state. We predict that flow-induced polarized migration of endothelial cells breaks symmetry and leads to stabilization of high flow/shear segments and regression of adjacent low flow/shear segments.
Identifying reference genes with stable expression from high throughput sequence data

Genes that are constitutively expressed across multiple environmental stimuli are crucial to quantifying differentially expressed genes, particularly when employing quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assays. However, the identification of these potential reference genes in non-model organisms is challenging and is often guided by expression patterns in distantly related organisms. Here, transcriptome datasets from the diatom Thalassiosira pseudonana grown under replete, phosphorus-limited, iron-limited, and phosphorus and iron co-limited nutrient regimes were analyzed through literature-based searches for homologous reference genes, k-means clustering, and analysis of sequence counts (ASC) to identify putative reference genes. A total of 9759 genes were identified and screened for stable expression. Literature-based searches surveyed 18 generally accepted reference genes, revealing 101 homologs in T. pseudonana with variable expression and a wide range of mean tags per million. k-means analysis parsed the whole transcriptome into 15 clusters. The two most stable clusters contained 709 genes, but still had distinct patterns in expression. ASC analyses identified 179 genes that were stably expressed (posterior probability < 0.1 for 1.25 fold change). Genes known to have a stable expression pattern across the test treatments, like actin, were identified in this pool of 179 candidate genes. ASC can be employed on data without biological replicates and was more robust than the k-means approach in isolating genes with stable expression. The intersection of the genes identified through ASC with commonly used reference genes from the literature suggests that actin and ubiquitin ligase may be useful reference genes for T. pseudonana and potentially other diatoms. With the wealth of transcriptome sequence data becoming available, ASC can be easily applied to transcriptome datasets from other phytoplankton to identify reference genes.
Approximate Maximum Likelihood Source Localization from Range Measurements Through Convex Relaxation

This work considers the problem of locating a single source from noisy range measurements to a set of nodes in a wireless sensor network. We propose two new techniques that we designate as Source Localization with Nuclear Norm (SLNN) and Source Localization with l1-norm (SL-l1), which extend to arbitrary real dimensions, including 3D, our prior work on 2D source localization formulated in the complex plane. Broadly, our approach is based on formulating a Maximum-Likelihood (ML) estimation problem for the source position, and then using convex relaxation techniques to obtain a semidefinite program (SDP) that can be globally and efficiently solved. SLNN directly approximates the Gaussian ML solution, and the relaxation is shown to be tighter than in other methods in the same class. We present an analysis of the convexity properties of the constraint set for the 2D complex version of SLNN (SLCP) to justify the observed tightness of the relaxation. In terms of global accuracy of localization, SLNN outperforms state-of-the-art optimization-based methods with either iterative or closed-form formulations. We propose the SL-l1 algorithm to address the Laplacian noise case, which models the presence of outliers in range measurements. We overcome the nondifferentiability of the Laplacian likelihood function by rewriting the ML problem as an exact weighted version of the Gaussian case, and compare two solution strategies. One of them is iterative, based on block coordinate descent, and uses SLNN as a subprocessing block. The other, attaining only slightly worse performance, is noniterative and based on an SDP relaxation of the weighted ML problem.
Low Cost Home Automation Using Offline Speech Recognition

Sound intelligence is added to a home automation based on acoustics for sophistication of physically challenged people as a broad perspective of the thesis. Home automation already in practice is by switching on or off a device via wired networks. But this is inefficient for people with impairment in mobility or spinal cord disability due to ageing factors. The easiest way of controlling a device is through human voice. Existing products are expensive and also speech recognition is available with usage of internet (online). This paper is presented with the concept of speech recognition being implemented using Hidden Markov Model Toolkit (HTK) in an offline manner (without internet). Human voice is converted to text using HTK and it is wirelessly Trans received using GSM modems. According to the received texts appliances can be controlled. The module contains a secured speech recognizer for automatic door opening/closing and a general voice recognizer to control appliances like television, music player, fan, light, etc. All the above are implemented in a low cost Raspberry Pi board. Thus a goal of producing an automation device has been designed at low cost using offline speech recognition [1].
Sequential Error Rate evaluation of SSVEP classification problem with Bayesian sequential learning

An attempt was made to evaluate the Sequential Error Rate (SER) of an SSVEP classification problem with a Bayesian sequential learning algorithm. Sequential Error Rate refers to the average classification error rate windowed over a short trial period. The algorithm was implemented by the Sequential Monte Carlo method. As opposed to the batch learning algorithm, the sequential learning algorithm does not divide the data into training and test datasets; rather, it starts learning with the first single trial data and proceeds with the learning sequentially using the rest of the data. The algorithm was tested against an SSVEP classification problem. The algorithm appeared functional.
Extracellular Molecules Involved in Cancer Cell Invasion

Nowadays it is perfectly clear that understanding and eradicating cancer cell invasion and metastasis represent the crucial, definitive points in cancer therapeutics. During the last two decades there has been a great interest in the understanding of the extracellular molecular mechanisms involved in cancer cell invasion. In this review, we highlight the findings concerning these processes, focusing in particular on extracellular molecules, including extracellular matrix proteins and their receptors, growth factors and their receptors, matrix metalloproteinases and extracellular chaperones. We report the molecular mechanisms underlying the important contribution of this pool of molecules to the complex, multi-step phenomenon of cancer cell invasion.
Drusen volume development over time and its relevance to the course of age-related macular degeneration

Aims To quantify the change in drusen volume over time and identify its prognostic value for individual risk assessment. Methods A prospective observational study over a minimum of 3 years and maximum of 5 years and follow-up examination every 3 months was conducted at the ophthalmology department of the Medical University of Vienna. 109 patients presenting early and intermediate age-related macular degeneration (AMD) were included, of which 30 patients concluded a regular follow-up for at least 3 years. 50 eyes of 30 patients were imaged every 3 months using spectral-domain and polarisation-sensitive optical coherence tomography (OCT). Drusen volume was measured using an automated algorithm. Data of a 6-month follow-up were segmented manually by expert graders. Results Gradings from 24 000 individual B-scans showed solid correlation between manual and automated segmentation with an initial mean drusen volume of 0.17 mm3. The increase in drusen volume was shown to be comparable among all eyes, and a model for long-term drusen volume development could be fitted as a cubic polynomial function and an R2=0.955. Spontaneous drusen regression was observed in 22 of 50 eyes. In this group, four eyes developed choroidal neovascularisation and three geographic atrophy. Conclusions Drusen volume increase over time can be described by a cubic function. Spontaneous regression appears to precede conversion to advanced AMD. OCT might be a promising tool for predicting the individual risk of progression of AMD.
Policies to Promote Fiscal Discipline Richard Hemming Fiscal Affairs Department International Monetary Fund

The first public sector ombudsman office was set up in Sweden in 1890. A second country, Finland, did not follow for more than a hundred years. By 1962, all four Scandinavian countries had an ombudsman office, and by 1983 so did 23 mainly Commonwealth and European countries. However, the number of countries with ombudsman offices has increased from 27 to 110 in the last 20 years. This uneven pattern illustrates the way good ideas often spread, at first slowly, and mainly by following the examples of peers, and then more rapidly, as a response to some challenge. In the case of ombudsman offices, the recent trigger has been the transition to democracy in many parts of the world, and the recognition that having an office to deal with public complaints can contribute significantly to achieving accountability of democratic government.