Rheological behavior of neat and carbon fiber-reinforced poly(ether ketone ketone) for extrusion deposition additive manufacturing

To develop new materials for extrusion additive manufacturing (AM) systems, a fundamental understanding of rheological properties is essential to correlate the effect of processing on material structure and its properties. In this work, the rheological properties of five different grades of neat and carbon fiber (CF)-reinforced poly(ether ketone ketone) are reported. Rheological properties are essential to understand the effect of reinforcing fibers and AM process parameters such as time, temperature, environment, and shear rate on flow behavior during processing. Small-amplitude oscillatory shear tests and steady shear tests indicated neat grades to exhibit less increase in viscosity over time when processed in air than the CF-filled grades. The filled grades showed greater shear thinning and lower sensitivity to temperature. Overall, this rheological analysis provides a broad framework for determining appropriate processing conditions for extrusion deposition AM of such high-temperature polymer systems.     

Effects of a single dose of N-Acetyl-5-methoxytryptamine (Melatonin) and resistance exercise on the growth hormone/IGF-1 axis in young males and females

Melatonin and resistance exercise alone have been shown to increase the levels of growth hormone (GH). The purpose of this study was to determine the effects of ingestion of a single dose of melatonin and heavy resistance exercise on serum GH, somatostatin (SST), and other hormones of the GH/insulin-like growth factor 1 (IGF-1) axis. Physically active males (n = 30) and females (n = 30) were randomly assigned to ingest either a melatonin supplement at 0.5 mg or 5.0 mg, or 1.0 mg of dextrose placebo. After a baseline blood sample, participants ingested the supplement and underwent blood sampling every 15 min for 60 min, at which point they underwent a single bout of resistance exercise with the leg press for 7 sets of 7 reps at 85% 1-RM. After exercise, participants provided additional blood samples every 15 min for a total of 120 min. Serum free GH, SST, IGF-1, IGFBP-1, and IGFBP-3 were determined with ELISA. Data were evaluated as the peak pre- and post-exercise values subtracted from baseline and the delta values analyzed with separate three-way ANOVA (p < 0.05). In males, when compared to placebo, 5.0 mg melatonin caused GH to increase (p = 0.017) and SST to decrease prior to exercise (p = 0.031), whereas both 0.5 and 5.0 mg melatonin were greater than placebo after exercise (p = 0.045) and less than placebo for SST. No significant differences occurred for IGF-1; however, males were shown to have higher levels of IGFBP-1 independent of supplementation (p = 0.004). The 5.0 mg melatonin dose resulted in higher IGFBP-3 in males (p = 0.017). In conclusion, for males 5.0 mg melatonin appears to increase serum GH while concomitantly lowering SST levels; however, when combined with resistance exercise both melatonin doses positively impacts GH levels in a manner not entirely dependent on SST.     

Mass spectrometric immunoassay and MRM as targeted MS-based quantitative approaches in biomarker development: Potential applications to cardiovascular disease and diabetes

Type 2 diabetes mellitus (T2DM) is an important risk factor for cardiovascular disease (CVD)—the leading cause of death in the United States. Yet not all subjects with T2DM are at equal risk for CVD complications; the challenge lies in identifying those at greatest risk. Therapies directed toward treating conventional risk factors have failed to significantly reduce this residual risk in T2DM patients. Thus newer targets and markers are needed for the development and testing of novel therapies. Herein we review two complementary MS-based approaches—mass spectrometric immunoassay (MSIA) and MS/MS as MRM—for the analysis of plasma proteins and PTMs of relevance to T2DM and CVD. Together, these complementary approaches allow for high-throughput monitoring of many PTMs and the absolute quantification of proteins near the low picomolar range. In this review article, we discuss the clinical relevance of the high density lipoprotein (HDL) proteome and Apolipoprotein A-I PTMs to T2DM and CVD as well as provide illustrative MSIA and MRM data on HDL proteins from T2DM patients to provide examples of how these MS approaches can be applied to gain new insight regarding cardiovascular risk factors. Also discussed are the reproducibility, interpretation, and limitations of each technique with an emphasis on their capacities to facilitate the translation of new biomarkers into clinical practice.     

A Review of “Technology and Literacy: 21st Century Library Programming for Children and Teens”

ABSTRACT

Given the endless volume of information available today, searchers are forced to satisfice when searching. The first satisfactory alternative is chosen over the best. Digital library search services, however, do not support satisficing users. There is no single, simple, comprehensive search service available to end-users to meet their need to gather information on alternatives from all information repositories accessible through a digital library. Federated search services bridge the gap between satisficing searchers and today's digital libraries.     

Glassy phases in organic semiconductors

Organic semiconductors may be processed from fluids using graphical arts printing and patterning techniques to create complex circuitry. Because organic semiconductors are weak van der Waals solids, the creation of glassy phases during processing is quite common. Because structural disorder leads to electronic disorder, it is necessary to understand these phases to optimize and control the electronic properties of these materials. Here we review the significance of glassy phases in organic semiconductors. We examine challenges in the measurement of the glass transition temperature and the accurate classification of phases in these relatively rigid materials. Device implications of glassy phases are discussed. Processing schemes that are grounded in the principles of glass physics and sound glass transition temperature measurement will more quickly achieve desired structure and electronic characteristics, accelerating the exciting progress of organic semiconductor technology development.     

A hybrid capacitive pressure and temperature sensor fabricated by adhesive bonding technique for harsh environment of kraft pulp digesters

We have developed a compensated capacitive pressure and temperature sensor for kraft pulp digesters (pH 13.5, temperatures 25–175°C reaching a local maximum of 180°C and pressures up to 2 MPa). The gauge capacitive pressure sensor was fabricated by bonding silicon and Pyrex chips using a high temperature, low viscosity UV (ultraviolent) adhesive as the gap-controlling layer and heat curing adhesive as the bonding agent. A simple chip bonding technique, involving insertion of the adhesive into the gap between two chips was developed. A platinum thin-film wire was patterned on top of a silicon chip to form a resistance temperature detector (RTD) with a nominal resistance of 1,500 Ω. A silicon dioxide layer and a thin layer of Parylene were deposited to passivate the pressure sensor diaphragm and the sensors were embedded into epoxy for protection against the caustic environment in kraft digesters. The sensors were tested up to 2 MPa and 170°C in an environment chamber. The maximum thermal error of ±1% (absolute value of ±20 kPa) full scale output (FSO) and an average sensitivity of 0.554 fF/kPa were measured. Parylene-coated silicon chips were tested for a full kraft pulping cycle with no signs of corrosion.     

A multi-level cache model for run-time optimization of remote visualization

Remote visualization is an enabling technology aiming to resolve the barrier of physical distance. While many researchers have developed innovative algorithms for remote visualization, previous work has focused little on systematically investigating optimal configurations of remote visualization architectures. In this paper, we study caching and prefetching, an important aspect of such architecture design, in order to optimize the fetch time in a remote visualization system. Unlike a processor cache or web cache, caching for remote visualization is unique and complex. Through actual experimentation and numerical simulation, we have discovered ways to systematically evaluate and search for optimal configurations of remote visualization caches under various scenarios, such as different network speeds, sizes of data for user requests, prefetch schemes, cache depletion schemes, etc. We have also designed a practical infrastructure software to adaptively optimize the caching architecture of general remote visualization systems, when a different application is started or the network condition varies. The lower bound of achievable latency discovered with our approach can aid the design of remote visualization algorithms and the selection of suitable network layouts for a remote visualization system.     

A longitudinal study of emoticon use in text messaging from smartphones

Our goal in the present study was to understand how emoticons are used in text messaging and, in particular, how genders differed in the frequency and variety of emoticons used via this medium. Previous research has found small and sundry differences in emotive expression online suggesting that technology has closed the gender gap. However, the data collected in these studies were public. In this study, we collected real portions of private communications data from individuals’ smartphones over a 6-month period. SMS messages, in general, were not used very much overall, with only 4% of all messages containing at least one emoticon. Still, differences between genders manifested in the amount and variety of emoticons used. Females sent more messages with emoticons; however, surprisingly, males used a more diverse range of emoticons.     

Interval Set Clustering of Web Users with Rough K-Means

Data collection and analysis in web mining faces certain unique challenges. Due to a variety of reasons inherent in web browsing and web logging, the likelihood of bad or incomplete data is higher than conventional applications. The analytical techniques in web mining need to accommodate such data. Fuzzy and rough sets provide the ability to deal with incomplete and approximate information. Fuzzy set theory has been shown to be useful in three important aspects of web and data mining, namely clustering, association, and sequential analysis. There is increasing interest in research on clustering based on rough set theory. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users. Researchers have pointed out some important differences between clustering in conventional applications and clustering in web mining. For example, the clusters and associations in web mining do not necessarily have crisp boundaries. As a result, researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have used genetic algorithms based on rough set theory for clustering. However, the genetic algorithms based clustering may not be able to handle the large amount of data typical in a web mining application. This paper proposes a variation of the K-means clustering algorithm based on properties of rough sets. The proposed algorithm represents clusters as interval or rough sets. The paper also describes the design of an experiment including data collection and the clustering process. The experiment is used to create interval set representations of clusters of web visitors.