Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Diffusion on Synthesis of High-Strength Titanium Alloys from Elemental Powder Blends

High strength near-beta titanium alloys are being increasingly used in industry due to their excellent combination of properties. Blended elemental powder metallurgy (BEPM) allows to produce the above alloys and parts from them in a cost-effective manner. However, the alloy synthesis is complicated by a big amount (up to 18 wt.%) of alloying elements which diffusional redistribution between alloying particles and titanium matrix has a strong impact on microstructure evolution. In this paper synthesis of the high-strength alloys from the powder blends based on hydrogenated titanium was studied. It was found that hydrogen strongly affects diffusion controlled processes upon synthesis, such as chemical homogenization, densification and grain growth through its influence on phase composition and defect structure of the blends. Optimization of the processing parameters allowed to produce uniform, nearly-dense alloys with reduced grain size, which mechanical properties met the requirements of corresponding specifications.
An Efficient Approach for Requirement Volatility Identification

Development is a dynamic activity. Requirements of the stakeholders keep on changing throughout the lifecycle of a project development. These Volatile requirements are considered as a major risk factor during system development in the software industry. Requirement Volatility is found to be having a significant impact on schedule & cost overrun in software projects. This paper discusses an approach for identifying volatile requirement and proposes an algorithm to automate the identification of volatile requirements in a requirement document at an early stage so that preventive measures can be taken. Also, we are proposing an approach to analyze the dependencies among various requirements which can be very lucrative in requirement management especially in the presence of volatile requirements.
Distributed databases and peer-to-peer databases: past and present

The need for large-scale data sharing between autonomous and possibly heterogeneous decentralized systems on the Web gave rise to the concept of P2P database systems. Decentralized databases are, however, not new. Whereas a definition for a P2P database system can be readily provided, a comparison with the more established decentralized models, commonly referred to as distributed, federated and multi-databases, is more likely to provide a better insight to this new P2P data management technology. Thus, in the paper, by distinguishing between db-centric and P2P-centric features, we examine features common to these database systems as well as other ad-hoc features that solely characterize P2P databases. We also provide a non-exhaustive taxonomy of the most prominent research efforts toward the realization of full-fledged P2P databases.
Integrated simulation framework for crash back operation

We present a comparison of performance of an all-electric-ship (AES) simulator using two different approaches to control the induction machine in forward as well as in cash astern operations. The first approach uses a constant-slip control while the second uses direct-torque control. We also investigate the use of proper breaking resistors required for minimal power dissipation during the crash astern operation. The AES simulator describes a medium voltage DC system (MVDC) for the USS DDG-51 Arleigh Burke-Class destroyer.
Combined vertical-velocity observations with Doppler lidar, cloud radar and wind profiler

Abstract. Case studies of combined vertical-velocity measurements of Doppler lidar, cloud radar and wind profiler are presented. The measurements were taken at the Meteorological Observatory, Lindenberg, Germany. Synergistic products are presented that are derived from the vertical-velocity measurements of the three instruments: a comprehensive classification mask of vertically moving atmospheric targets and the terminal fall velocity of water droplets and ice crystals corrected for vertical air motion. It is shown that this combination of instruments can up-value the measurement values of each single instrument and may allow the simultaneous sensing of atmospheric targets and the motion of clear air.
Effect of Donepezil on Sleep and Activity in Alzheimer's Disease: Actigraphic and Polysomnographic Assessment

Aim: To examine the effect of donepezil on sleep and daily activity in patients with Alzheimer-type dementia (ATD) using polysomnography and actigraphy. Methods: Ten patients with mild to moderate ATD (mean age: 76 ± 6.2 years) were studied. The Alzheimer’s disease Assessment Scale-cognitive component-Japanese version (ADAS-Jcog),polysomnography, and 7-day recording of actigraphy data were performed. Following this baseline assessment, donepezil (5 mg daily) was administered every morning for 6 weeks, after which the ADAS-Jcog, polysomnography, and actigraphy were repeated. Results: After 6 weeks of treatment with donepezil, daily activity was significantly increased (276.2 ± 89.2 vs. 326.1 ± 98.6; p < 0.05). Similarly, rapid eye movement (REM) sleep (11.3 ± 4.1 vs. 17.1 ± 4.4; p<0.01) and sleep efficiency (76.2 ± 16.3 vs. 82.8 ± 10.6; p<0.05) were significantly increased compared with baseline. Although the ADAS-Jcog score did not decrease significantly (18.5 ± 6.8 vs. 15.9 ± 7.3; P= 0.054), there was a significant positive correlation between the decrease of this score and the increase of daily activity (r= 0.2137, p= 0.4809). Conclusions: An increase of daily activity and cognition were induced by donepezil treatment in patients with ATD, possibly based on improvement of the sleep structure. Trial Registration: Controlled-trials. Com Identifier: UMIN000005018
Mechanical Properties of Individual Composite Poly(methyl-methacrylate) -Multiwalled Carbon Nanotubes Nanofibers

Multiwalled carbon nanotubes with their superb mechanical properties are an unique filler material for polymer composites. Here, we present an investigation of mechanical properties of electrospun Poly-(methyl-methacrylate) multiwalled carbon nanotubes composite nanofibers. The method of electrospinning was used to fabricate suspended individual Poly-(methyl-methacrylate) multiwalled carbon nanotubes nanofibers. In order to reinforce the nanofibers, different high concentration of multiwalled carbon nanotubes were used. Transmission electron microscopy measurements reveal a successful filling of the nanofibers. The different types of nanofibers were deposited at SiO2 substrates. Which were previously etched, to create trenches for bend tests. Followed by fixing the nanofiber with a focus ion beam platinum deposition at the trench edges. An atomic force microscopy was used to perform the mechanical nanofiber bending tests over trenches. The results were compared with pristine Poly-(methyl- methacrylate) nanofibers to nanofibers with 15 weight% and 20 weight% multiwalled carbon nanotubes composite fibers. We observed that pristine nanofibers have Young's modulus of 136 MPa, while for composite nanofibers with 15 weight% have 2.65 GPa and with 20 weight% have 6.06 GPa (at room temperature and air ambiance). This corresponds to an increase of Young's modulus of 19 fold between the pristine nanofibers and the 15 weight% of mutliwalled carbon nanotubes filled nanofibers. Therefore the increase of the Young's modulus compared between the pristine and the 20 weight% MWCNT filled nanofibers corresponds to 45 fold.
A Vascular Endothelial Growth Factor Receptor-2 Kinase Inhibitor Potentiates the Activity of the Conventional Chemotherapeutic Agents Paclitaxel and Doxorubicin in Tumor Xenograft Models

Inhibition of angiogenesis may have wide use in the treatment of cancer; however, this approach alone will not cause tumor regression but may only slow the growth of solid tumors. The clinical potential of antiangiogenic agents may be increased by combining them with conventional chemotherapeutics. 4-[4-(1-Amino-1-methylethyl)phenyl]-2-[4-(2-morpholin-4-yl-ethyl)phenylamino]pyrimidine-5-carbonitrile (JNJ-17029259) represents a novel structural class of 5-cyanopyrimidines that are orally available, selective, nanomolar inhibitors of the vascular endothelial growth factor receptor-2 (VEGF-R2) and other tyrosine kinases involved in angiogenesis, such as platelet-derived growth factor receptor, fibroblast growth factor receptor, VEGF-R1, and VEGF-R3, but have little activity on other kinase families. At nanomolar levels, JNJ-17029259 blocks VEGF-stimulated mitogen-activated protein kinase signaling, proliferation/migration, and VEGF-R2 phosphorylation in human endothelial cells; inhibits the formation of vascular sprouting in the rat aortic ring model of angiogenesis; and interferes with the development of new veins and arteries in the chorioallantoic membrane assay. At higher concentrations of 1 to 3 μM, this compound shows antiproliferative activity on cells that may contribute to its antitumor effects. JNJ-17029259 delays the growth of a wide range of human tumor xenografts in nude mice when administered orally as single-agent therapy. Histological examination revealed that the tumors have evidence of reduced vascularity after treatment. In addition, JNJ-17029259 enhances the effects of the conventional chemotherapeutic drugs doxorubicin and paclitaxel in xenograft models when administered orally in combination therapy. An orally available angiogenesis inhibitor that can be used in conjunction with standard chemotherapeutic agents to augment their activity may have therapeutic benefit in stopping the progression of cancer and preventing metastasis.
A SURVEY OF UPPER ONTOLOGIES FOR SITUATION AWARENESS

Situation awareness enables an intelligent agent to determine the meaning of perceived information in highly dynamic environments and to share the thereby discovered knowledge. Recently, ontology-based approaches to situation awareness have been proposed; some of them facilitate upper ontologies in order to provide a common vocabulary for collaborating agents and information sources. This paper proposes an evaluation framework for such upper ontologies to elaborate missing features and to develop a better understanding of the diverse concepts involved. To demonstrate the applicability of the evaluation framework, four upper ontologies providing concepts for situation awareness are compared. The findings from this comparison indicate common as well as mutual weaknesses of the examined approaches.
Frontiers in Synaptic Neuroscience Synaptic Neuroscience

However, these models usually represent only a statistical average of synaptic responses, as the relevant experiments exhibit a large spread in experimental data This statistical spread may be explained by the fact that relevant local plasticity variables are only unreliably influenced by action potentials (Lisman and Spruston, 2005). Consequently, some experiments seem to indicate that LTP and LTD can be more reliably induced qualitatively as well as quantitatively (i.e., with less variability in the direction and amount of weight change) if local variables are directly influenced, e.g., by evoking dendritic spikes (Holthoff et al., 2006) or by setting the membrane potential artificially (Artola et al., 1990; Ngezahayo et al., 2000; Sjöström et al., 2001). Thus, we hypothesize that the governing variables of plasticity are based on the local environment of the synapse such as the local depolarization or Ca 2+ levels (Aihara et al., 2007). Motivated by these findings, several models have tried to incorporate a dependence of plasticity on the Ca 2+ concentration or the membrane potential. However, most of the Ca 2+ based models, while able to reproduce BCM-type plasticity, result in unrealistic In addition, the reproduction of higher-order spike interaction effects such as spike triplets (Froemke and Dan, 2002) are either not attempted by the authors or produce results only partially consistent with experimental data (Shah et al., 2006). As well, due to their biophysical motivation, these models tend to be very complex and thus computationally expensive and difficult to analyze mathematically. Models incorporating the membrane potential have mostly been influenced by computational aspects (Saudargiene et al.
Supercritical Fluid Spray Application Process for Adhesives and Primers

Abstract : In this project, we reformulated various solvent borne, high volatile organic compound (VOC) adhesives and adhesive primers, as cited in SERDP's Statement of Need, for application by a supercritical carbon dioxide spray process. Over the last several years, a new spray application process has been developed for polymeric based paints and other coatings that can reduce solvent VOC emissions up to 80%. This process was conceived by the principal investigator of this project and has been commercialized by the Dow Chemical Company. This unique process (known as the UNICARB (trademark) process) is based on the use of supercritical carbon dioxide as a replacement for organic solvents in multi-component spray coating formulations. By adapting this process to adhesives and adhesive primer applications, stringent compliance standards can be achieved respective to environmental, toxicological, materials compatibility, and, physical property performance characteristics as outlined in the original proposal and Statement of Need. Furthermore, by employing this process to apply adhesives that are presently used in the military, the costs incurred for developing and testing new (different) low/no-VOC, non-structural adhesives will be negated.
Segmentation of Pulmonary Nodules in Thoracic CT Scans: A Region Growing Approach

This paper presents an efficient algorithm for segmenting different types of pulmonary nodules including high and low contrast nodules, nodules with vasculature attachment, and nodules in the close vicinity of the lung wall or diaphragm. The algorithm performs an adaptive sphericity oriented contrast region growing on the fuzzy connectivity map of the object of interest. This region growing is operated within a volumetric mask which is created by first applying a local adaptive segmentation algorithm that identifies foreground and background regions within a certain window size. The foreground objects are then filled to remove any holes, and a spatial connectivity map is generated to create a 3-D mask. The mask is then enlarged to contain the background while excluding unwanted foreground regions. Apart from generating a confined search volume, the mask is also used to estimate the parameters for the subsequent region growing, as well as for repositioning the seed point in order to ensure reproducibility. The method was run on 815 pulmonary nodules. By using randomly placed seed points, the approach was shown to be fully reproducible. As for acceptability, the segmentation results were visually inspected by a qualified radiologist to search for any gross misssegmentation. 84% of the first results of the segmentation were accepted by the radiologist while for the remaining 16% nodules, alternative segmentation solutions that were provided by the method were selected.
Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist

The purpose of this study is to determine the correlation between texture features of Diffraction Enhanced Imaging (DEI) images and trabecular properties of human wrist bone in the assessment of osteoporosis. Osteoporosis is a metabolic bone disorder that is characterized by reduced bone mass and a deterioration of bone structure which results in an increased fracture risk. Since the disease is preventable, diagnostic techniques are of major importance. Bone micro-architecture and Bone mineral density (BMD) are two main factors related to osteoporotic fractures. Trabecular properties like bone volume (BV), trabecular number (Tb.N), trabecular thickness (Tb.Th), bone surface (BS), and other properties of bone, characterizes the bone architecture. Currently, however, BMD is the only measurement carried out to assess osteoporosis. Researchers suggest that bone micro-architecture and texture analysis of bone images along with BMD can provide more accuracy in the assessment. We have applied texture analysis on DEI images and extracted texture features. In our study, we used fractal analysis, gray level co-occurrence matrix (GLCM), texture feature coding method (TFCM), and local binary patterns (LBP) as texture analysis methods to extract texture features. 3D Micro-CT trabecular properties were extracted using SkyScanTM CTAN software. Then, we determined the correlation between texture features and trabecular properties. GLCM energy feature of DEI images explained more than 39% of variance in bone surface by volume ratio (BS/BV), 38% of variance in percent bone volume (BV/TV), and 37% of variance in trabecular number (Tb.N). TFCM homogeneity feature of DEI images explained more than 42% of variance in bone surface (BS) parameter. LBP operator LBP 11 of DEI images explained more than 34% of variance in bone surface (BS) and 30% of variance in bone surface density (BS/TV). Fractal dimension parameter of DEI images explained more than 47% of variance in bone surface (BS) and 32% of variance in bone volume (BV). This study will facilitate in the quantification of osteoporosis beyond conventional BMD.
Small Business Management Information System Design and Implementation

Abstract. This paper presents a model of C/S based database application system --enterprise information Management system. System uses a modular design, user information, customer information, product information, Inventory information detailed records, and convenient, fast query of the required information, to provide a strong guarantee for the enterprise production and sales, improve work efficiency and enterprise benefit.
Brokerage Commissions and Pre-disclosure Information Environment

for helpful comments and suggestions. Some aspects of the ideas developed in this paper were also explored in my dissertation at the University of California at Berkeley where I benefited from discussions with Brett Trueman and David Romer. All errors are my own. Abstract This paper contrasts information production and subsequent trading on an individual basis with trading on information produced and distributed by a full-service broker. Focusing on differential incentives, rather than differential costs, in investigating endogenous information production it is assumed that a broker's objective is to maximize volume-based commissions. It is found that the quality of the broker's signal is increasing in the number of traders the broker informs, whereas the quality of own-produced private information by investors is declining in their number. Price reaction at the announcement date will be lower for broker-produced forecast than for own-produced signals only if the number of traders in the marketplace is sufficiently large and the broker's forecast is sufficiently more accurate. In addition, it is found that trading volume may be an inappropriate measure of pre-disclosure information environment. The paper also examines implications for investor profits and demonstrates that switching from self gathering to a broker-provided signal could be beneficial even when the broker's signal is of lower quality.
Development of a NIR microspectrometer based on a MOEMS scanning grating

In the last few years the importance of Micro Opto Electro Mechanical Systems (MOEMS) increased significantly in technical applications. This is caused by the possibility of combining micro optical elements with micromachining technology that makes it feasible to develop new systems with high volumes and low prices. In this article, we report on the realization of a NIR (near infrared) spectrometer in the range of 900 - 2000 nm using MOEMS technology. It is based on a scanning mirror chip, which mirror plate is structured with a diffractive aluminium layer on top. This offers the possibility to fabricate a spectrometer, which needs only one single InGaAs detector photo diode. In contrast to common CCD arrays, the obtained resolution is only limited by the performance of the spectrometer (entrance slit, exit slit, focus length, diffractive element). The scanning grating chip operates at a frequency of 500 Hz, at an optical scan range of ± 4°. The whole spectrometer has a size of 90 x 60 x 50 mm. For first investigations of the performance, IR LEDs (light emitting diode) with 1300, 1450 and 1550 nm wavelength have been measured.
Automatic classification of cardioembolic and arteriosclerotic ischemic strokes from apparent diffusion coefficient datasets using texture analysis and deep learning

Stroke is a leading cause of death and disability in the western hemisphere. Acute ischemic strokes can be broadly classified based on the underlying cause into atherosclerotic strokes, cardioembolic strokes, small vessels disease, and stroke with other causes. The ability to determine the exact origin of an acute ischemic stroke is highly relevant for optimal treatment decision and preventing recurrent events. However, the differentiation of atherosclerotic and cardioembolic phenotypes can be especially challenging due to similar appearance and symptoms. The aim of this study was to develop and evaluate the feasibility of an image-based machine learning approach for discriminating between arteriosclerotic and cardioembolic acute ischemic strokes using 56 apparent diffusion coefficient (ADC) datasets from acute stroke patients. For this purpose, acute infarct lesions were semi-atomically segmented and 30,981 geometric and texture image features were extracted for each stroke volume. To improve the performance and accuracy, categorical Pearson’s χ2 test was used to select the most informative features while removing redundant attributes. As a result, only 289 features were finally included for training of a deep multilayer feed-forward neural network without bootstrapping. The proposed method was evaluated using a leave-one-out cross validation scheme. The proposed classification method achieved an average area under receiver operator characteristic curve value of 0.93 and a classification accuracy of 94.64%. These first results suggest that the proposed image-based classification framework can support neurologists in clinical routine differentiating between atherosclerotic and cardioembolic phenotypes.
Long-memory processes in global ozone and temperature variations

Global column ozone and tropospheric temperature observations made by groundbased (1964–2004) and satellite-borne (1978–2004) instrumentation are analyzed. Ozone and temperature fluctuations in small time-intervals are found to be positively correlated to those in larger time-intervals in a power-law fashion. For temperature, the 5 exponent of this dependence is larger in the mid-latitudes than in the tropics at long time scales, while for ozone, the exponent is larger in tropics than in the mid-latitudes. The ability of the models to reproduce this scaling could be a good test for improved predictions of future variations in ozone layer and global warming.