TITAN Wireless Camera Control System

The Titan Camera Control System is an eletromechanical device that allows the user to wirelessly control a camera’s digital operations as well as physical orientation through the use of a mobile device application. The Titan system accepts input in the form of virtual user commands on the mobile app and performs system output in the form of sending photos/video from the camera back to the app as well as changing the orientation of the camera in accordance with the user’s commands

Studies of Molecular Clouds associated with H II Regions: S175

We are studying the impact of HII regions on star formation in their associated molecular clouds. In this paper we present JCMT RxA molecular line observations of S175 and environs. This is the first within a sample of ten HII regions and their surrounding molecular clouds selected for our study. We first make 7'x 7' maps in $^{12}$CO(2-1), which are used to investigate the structure of the cloud and to identify individual clumps. Single point observations were made in $^{13}$CO(2-1) and CS(5-4) at the peak of the $^{12}$CO(2-1) emission within each clump in order to measure the physical properties of the gas. Densities, temperatures, clump masses, peak velocities, and line widths were measured and calculated using these observations. We have identified two condensations (S175A and S175B) in the molecular cloud associated with this HII region. S175A is adjacent to the ionization front and is expected to be affected by the HII region while S175B is too distant to be disturbed. We compare the structure and gas properties of these two regions to investigate how the molecular gas has been affected by the HII region. S175A has been heated by the HII region and partially compressed by the ionized gas front, but contrary to our expectation it is a quiescent region while S175B is very turbulent and dynamically active. Our investigation for the source of turbulence in S175B resulted in the detection of an outflow within this region.Comment: 33 pages, 11 figures, 6 tables, accepted for publication in Astronomical Journa

When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms

Most works on the fairness of machine learning systems focus on the blind optimization of common fairness metrics, such as Demographic Parity and Equalized Odds. In this paper, we conduct a comparative study of several bias mitigation approaches to investigate their behaviors at a fine grain, the prediction level. Our objective is to characterize the differences between fair models obtained with different approaches. With comparable performances in fairness and accuracy, are the different bias mitigation approaches impacting a similar number of individuals? Do they mitigate bias in a similar way? Do they affect the same individuals when debiasing a model? Our findings show that bias mitigation approaches differ a lot in their strategies, both in the number of impacted individuals and the populations targeted. More surprisingly, we show these results even apply for several runs of the same mitigation approach. These findings raise questions about the limitations of the current group fairness metrics, as well as the arbitrariness, hence unfairness, of the whole debiasing process

A Survey on Facilities for Experimental Internet of Things Research

International audienceThe initial vision of the Internet of Things (IoT) was of a world in which all physical objects are tagged and uniquelly identified by RFID transponders. However, the concept has grown into multiple dimensions, encompassing sensor networks able to provide real-world intelligence and goal-oriented collaboration of distributed smart objects via local networks or global interconnections such as the Internet. Despite significant technological advances, difficulties associated with the evaluation of IoT solutions under realistic conditions, in real world experimental deployments still hamper their maturation and significant roll out. In this article we identify requirements for the next generation of the IoT experimental facilities. While providing a taxonomy, we also survey currently available research testbeds, identify existing gaps and suggest new directions based on experience from recent efforts in this field

Tissue microarrays: one size does not fit all

<p>Abstract</p> <p>Background</p> <p>Although tissue microarrays (TMAs) are commonly employed in clinical and basic-science research, there are no guidelines for evaluating the appropriateness of a TMA for a given biomarker and tumor type. Furthermore, TMA performance across multiple biomarkers has not been systematically explored.</p> <p>Methods</p> <p>A simulated TMA with between 1 and 10 cores was designed to study tumor expression of 6 biomarkers with varied expression patterns (B7-H1, B7-H3, survivin, Ki-67, CAIX, and IMP3) using 100 patients with clear cell renal cell carcinoma (RCC). We evaluated agreement between whole tissue section and TMA immunohistochemical biomarker quantification to assess how many TMA cores are necessary to adequately represent RCC whole tissue section expression. Additionally, we evaluated associations of whole tissue section and TMA expression with RCC-specific death.</p> <p>Results</p> <p>The number of simulated TMA cores necessary to adequately represent whole tissue section quantification is biomarker specific. Although 2-3 cores appeared adequate for B7-H3, Ki-67, CAIX, and IMP3, even as many as 10 cores resulted in poor agreement for B7-H1 and survivin compared to RCC whole tissue sections. While whole tissue section B7-H1 was significantly associated with RCC-specific death, no significant associations were detected using as many as 10 TMA cores, suggesting that TMAs can result in false-negative findings if the TMA is not optimally designed.</p> <p>Conclusions</p> <p>Prior to TMA analysis, the number of TMA cores necessary to accurately represent biomarker expression on whole tissue sections should be established as there is not a one-size-fits-all TMA. We illustrate the use of a simulated TMA as a cost-effective tool for this purpose.</p

Crater Morphology in the Phoenix Landing Ellipse: Insights Into Net Erosion and Ice Table Depth

Icebreaker [1] is a Discovery class mission being developed for future flight opportunities. Under this mission concept, the Icebreaker payload is carried on a stationary lander, and lands in the same landing ellipse as Phoenix. Samples are acquired from the subsurface using a drilling system that penetrates into materials which may include loose or cemented soil, icy soil, pure ice, rocks, or mixtures of these. To avoid the complexity of mating additional strings, the drill is single-string, limiting it to a total length of 1 m