Preliminary Evidence on the Diagnostic and Molecular Role of Circulating Soluble EGFR in Non-Small Cell Lung Cancer

Assessment of biological diagnostic factors providing clinically-relevant information to guide physician decision-making are still needed for diseases with poor outcomes, such as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) is a promising molecule in the clinical management of NSCLC. While the EGFR transmembrane form has been extensively investigated in large clinical trials, the soluble, circulating EGFR isoform (sEGFR), which may have a potential clinical use, has rarely been considered. This study investigates the use of sEGFR as a potential diagnostic biomarker for NSCLC and also characterizes the biological function of sEGFR to clarify the molecular mechanisms involved in the course of action of this protein. Plasma sEGFR levels from a heterogeneous cohort of 37 non-advanced NSCLC patients and 54 healthy subjects were analyzed by using an enzyme-linked immunosorbent assay. The biological function of sEGFR was analyzed in vitro using NSCLC cell lines, investigating effects on cell proliferation and migration. We found that plasma sEGFR was significantly decreased in the NSCLC patient group as compared to the control group (median value: 48.6 vs. 55.6 ng/mL respectively; p = 0.0002). Moreover, we demonstrated that sEGFR inhibits growth and migration of NSCLC cells in vitro through molecular mechanisms that included perturbation of EGF/EGFR cell signaling and holoreceptor internalization. These data show that sEGFR is a potential circulating biomarker with a physiological protective role, providing a first approach to the functional role of the soluble isoform of EGFR. However, the impact of these data on daily clinical practice needs to be further investigated in larger prospective studies.     

Ozonation of CI Reactive Black 5 using rotating packed bed and stirred tank reactor

This study investigates the ozonation of CI Reactive Black 5 (RB5) by using the rotating packed bed (RPB) and completely stirred tank reactor (CSTR) as ozone contactors. The RPB, which provides high gravitational force by adjusting the rotational speed, was employed as a novel ozone contactor. The same ozone dosage was separately introduced into either the RPB or the CSTR for the investigation, while the experimental solution was continuously circulated within the apparatus consisting of the RPB and CSTR. The decolorization and mineralization efficiencies of RB5 in the course of ozonation are compared for these two methods. Moreover, the dissolved and off‐gas ozone concentrations were simultaneously monitored for the further analysis. As a result, the ozone mass transfer rate per unit volume of the RPB was significantly higher because of its higher mass transfer coefficient and gas–liquid concentration driving force. Furthermore, ozonation kinetics was found to be independent of the gravitational magnitude of an ozone gas–liquid contactor. Therefore, the results suggest employing RPBs as ozone‐contacting devices with the advantage of volume reduction. The experimental results, which can be used for further modeling of the ozonation process in the RPB, also show the requirement of correct design for the RPB. Consequently, the present study is useful for the understanding of practical application of RPBs. Copyright © 2004 Society of Chemical Industry     

封装与测试——解决功率电子器件的热问题

纽约州立大学Buffalo分校电子封装实验室正在为美国海军开发新型的功率电子封装，在一些极端苛刻的工作条件下（比如在军舰和战机上）．它们能够解决大电流密度、高温和大的温度梯度所引起的种种问题。这类功率电子封装还有可能很快进入民用产品。     

TTI hydraulics and erosion control laboratory research field performance of erosion-control blankets

Storm water management issues facing the Texas Department of Transportation in the late 1980s led to the development of a coordinated research program with the Texas Transportation Institute. Researchers developed methodologies for evaluating the field performance of various erosion control technologies of the most widely used products within the Department's construction and maintenance operations. From these methodologies, the Hydraulics and Erosion Control Laboratory was designed and constructed. Currently, participants include private industry (manufacturers of erosion control products), transportation researchers (TTI), and the public sector (TxDOT).The results reported in this paper reflect 2 years of erosion-control blanket research. The study objectives were to determine the effectiveness of erosion-control blankets on the growth of warm-season perennial grasses and their ability to prevent sediment loss in a sloped condition.The laboratory simulates the highway environment with the sloped plots (6 m in width) located on an earthen embankment that is 300 m in length and 6.75 m in height (94 ft. by 22 ft., vertically). A randomized experimental design was replicated on two soil types (sand and clay) for each slope condition (3:1 or 2:1) with a control.In general, the results indicate better combined results relating to sediment retention and vegetation establishment performance for erosion-control blankets on sandy soils (noncohesive) regardless of slope condition (3:1 or 2:1) or material type. A minimum of 50% more sediment was retained on the sandy treatment plots and a 45% more vegetation coverage was achieved compared with the control plots. When analyzed by material type related to performance, excelsior, synthetic blends, and straw/coconut blends performed the best. For clay soils (cohesive), regardless of slope condition (3:1 or 2:1), the combined results indicate a minimum of 75% more sediment was retained and a minimum of 5% more vegetation establishment was achieved compared with the control plots. When analyzed by material type related to performance, excelsior, straw, and straw/coconut blends performed the best.     

Clustering semantically heterogeneous distributed aggregate databases

Databases developed independently in a common open distributed environment may be heterogeneous with respect to both data schema and the embedded semantics. Managing schema and semantic heterogeneities brings considerable challenges to learning from distributed data and to support applications involving cooperation between different organisations. In this paper, we are concerned mainly with heterogeneous databases that hold aggregates on a set of attributes, which are often the result of materialised views of native large-scale distributed databases. A model-based clustering algorithm is proposed to construct a mixture model where each component corresponds to a cluster which is used to capture the contextual heterogeneity among databases from different populations. Schema heterogeneity, which can be recast as incomplete information, is handled within the clustering process using Expectation-Maximisation estimation and integration is carried out within a clustering iteration. Our proposed algorithm resolves the schema heterogeneity as part of the clustering process, thus avoiding transformation of the data into a unified schema. Results of algorithm evaluation on classification, scalability and reliability, using both real and synthetic data, demonstrate that our algorithm can achieve good performance by incorporating all of the information from available heterogeneous data. Our clustering approach has great potential for scalable knowledge discovery from semantically heterogeneous databases and for applications in an open distributed environment, such as the Semantic Web.     

Tributary confluences are dynamic thermal refuges for a juvenile salmonid in a warming river network

As rivers warm, cold‐water fish species may alleviate thermal stress by moving into localized thermal refuges such as cold‐water plumes created by cool tributary inflows. We quantified use of two tributary confluence plumes by juvenile steelhead, Oncorhynchus mykiss, throughout the summer, including how trout positioned themselves in relation to temperature within confluence plumes. At two confluences, Cedar and Elder creeks, along the South Fork Eel River, California, USA, we monitored temperatures using in situ logger grids throughout summer 2016. Fish were counted within confluences via snorkel surveys five times a day on 5 days at each site. We found diel and seasonal dependence on confluence use by steelhead, especially at the Cedar Creek confluence, where mainstem temperatures exceeded 28°C. At this site, fish moved into the confluence on the warmest days and warmest times of the day. Fish observed within the Cedar Creek confluence plume were most common in locations between 20–22°C, rather than the coldest locations (14.5°C). At Elder Creek, where mainstem temperatures remained below 24°C, there was little relationship between mainstem temperature and steelhead presence in the confluence plume. At both sites, steelhead distribution within plumes was influenced by spatial variation of temperature and mean temperature in surveyed grid cells. Our results show that cool tributaries flowing into warmer mainstem reaches (over 24°C) likely create important thermal refuges for juvenile steelhead. As mainstem rivers warm with climate change, cool‐water tributary inputs may become more important for sustaining cold‐water salmonids near the southern end of their range.     

Adapting Memory Hierarchies for Emerging Datacenter Interconnects

E?cient resource utilization requires that emerging datacenter interconnects support both high performance communication and e?cient remote resource sharing. These goals require that the network be mor...     

PAC Learning of One-Dimensional Patterns

Developing the ability to recognize a landmark from a visual image of a robot's current location is a fundamental problem in robotics. We consider the problem of PAC-learning the concept class of geometric patterns where the target geometric pattern is a configuration ofk points on the real line. Each instance is a configuration ofn points on the real line, where it is labeled according to whether or not it visually resembles the target pattern. To capture the notion of visual resemblance we use the Hausdorff metric. Informally, two geometric patternsP andQ resemble each other under the Hausdorff metric if every point on one pattern is close to some point on the other pattern. We relate the concept class of geometric patterns to the landmark matching problem and then present a polynomial-time algorithm that PAC-learns the class of one-dimensional geometric patterns. We also present some experimental results on how our algorithm performs.