Cryogenic Characterization of 180 nm CMOS Technology at 100 mK

Conventional CMOS technology operated at cryogenic conditions has recently attracted interest for its uses in low-noise electronics. We present one of the first characterizations of 180 nm CMOS technology at a temperature of 100 mK, extracting I/V characteristics, threshold voltages, and transconductance values, as well as observing their temperature dependence. We find that CMOS devices remain fully operational down to these temperatures, although we observe hysteresis effects in some devices. The measurements described in this paper can be used to inform the future design of CMOS devices intended to be operated in this deep cryogenic regime

Distribution of user-perceived usefulness of four presentation styles of opinion summarization

In this study, four opinion summarization styles were compared under an experimental environment. Thirty four participants sorted thirty two cards into five usefulness categories. Every eight cards belong to one presentation style. It was found that the users spent the shortest time on cards in “not at all useful” category. The time of viewing “extremely useful” cards was also shorter than that of “somewhat useful”, “useful”, and “very useful” cards. This result can be explained with the components of the usefulness categories. Tag clouds and Aspect oriented sentiments needed less time to view. They are the major styles in “not at all useful” and “extremely useful”. Paragraph summaries and Group samples requested more time and they took at least 50% in “somewhat useful”, “useful”, and “very useful”. The findings are consistent with our previous results

Numerical Approximations to the Cumulative Chi-Square Distribution, the Cumulative t-Distribution and the Cumulative F-Distribution for Digital Computers

There are good tables of the frequently used cumulative frequency distributions. These tables have some limitations with respect to the number of percentage points that are available. The main drawback in computer usage of these tables is that large amounts of storage and elaborate search and interpolation techniques are necessary for their use. It is the purpose of this study to present associated numerical methods for digital computer which are satisfactorily accurate and which are reasonably economical in both time and machine memory capacity. To carry out this objective the following procedures were used: 1. A review of literature on numerical approximations-both texts and articles from statistical journals and computer science publications. 2. .Writing test programs in Fortran for all the associated methods which can be obtained. 3. Checking the answers obtained by numerical approximation with the known answers in the table in order to determine usefulness of the numerical method. 4. Writing Fortran subprograms to evaluate those integrals by using the most accurate methods according to the experimental results

Temporally and Spatially Distinct Thirst Satiation Signals

For thirsty animals, fluid intake provides both satiation and pleasure of drinking. How the brain processes these factors is currently unknown. Here, we identified neural circuits underlying thirst satiation and examined their contribution to reward signals. We show that thirst-driving neurons receive temporally distinct satiation signals by liquid-gulping-induced oropharyngeal stimuli and gut osmolality sensing. We demonstrate that individual thirst satiation signals are mediated by anatomically distinct inhibitory neural circuits in the lamina terminalis. Moreover, we used an ultrafast dopamine (DA) sensor to examine whether thirst satiation itself stimulates the reward-related circuits. Interestingly, spontaneous drinking behavior but not thirst drive reduction triggered DA release. Importantly, chemogenetic stimulation of thirst satiation neurons did not activate DA neurons under water-restricted conditions. Together, this study dissected the thirst satiation circuit, the activity of which is functionally separable from reward-related brain activity

MR-Medicine: Improving Telemedicine Video Consultation with Mixed Reality and User Experience Design

MR-Medicine is a research project exploring how Mixed Reality and User Experience Design can be used to improve patient experience in Telemedicine. It focuses on three main problems identified in the existing telemedicine platforms: 1) unintegrated electronic medical record system, 2) lack of strong presence, and 3) the hierarchical physician-patient relationship. It uses dermatology as a case study to explore possible design solutions for remote healthcare consultation. MR-Medicine was developed with the Research Through Design methodology and examined with the Descriptive Design Evaluation methods. By creating and evaluating three types of prototypes for Virtual Reality (VR), Augmented Reality (AR), and desktop applications as proofs of concept, the research study suggests findings that may contribute to telemedicine consultation applications' development and how patients and physicians may better interact in the future

Deep Learning CT Image Restoration using System Blur and Noise Models

The restoration of images affected by blur and noise has been widely studied and has broad potential for applications including in medical imaging modalities like computed tomography (CT). Although the blur and noise in CT images can be attributed to a variety of system factors, these image properties can often be modeled and predicted accurately and used in classical restoration approaches for deconvolution and denoising. In classical approaches, simultaneous deconvolution and denoising can be challenging and often represent competing goals. Recently, deep learning approaches have demonstrated the potential to enhance image quality beyond classic limits; however, most deep learning models attempt a blind restoration problem and base their restoration on image inputs alone without direct knowledge of the image noise and blur properties. In this work, we present a method that leverages both degraded image inputs and a characterization of the system blur and noise to combine modeling and deep learning approaches. Different methods to integrate these auxiliary inputs are presented. Namely, an input-variant and a weight-variant approach wherein the auxiliary inputs are incorporated as a parameter vector before and after the convolutional block, respectively, allowing easy integration into any CNN architecture. The proposed model shows superior performance compared to baseline models lacking auxiliary inputs. Evaluations are based on the average Peak Signal-to-Noise Ratio (PSNR), selected examples of good and poor performance for varying approaches, and an input space analysis to assess the effect of different noise and blur on performance. Results demonstrate the efficacy of providing a deep learning model with auxiliary inputs, representing system blur and noise characteristics, to enhance the performance of the model in image restoration tasks

Decorin-mediated inhibition of colorectal cancer growth and migration is associated with E-cadherin in vitro and in mice.

Previous studies have shown that decorin expression is significantly reduced in colorectal cancer tissues and cancer cells, and genetic deletion of the decorin gene is sufficient to cause intestinal tumor formation in mice, resulting from a downregulation of p21, p27(kip1) and E-cadherin and an upregulation of β-catenin signaling [Bi,X. et al. (2008) Genetic deficiency of decorin causes intestinal tumor formation through disruption of intestinal cell maturation. Carcinogenesis, 29, 1435-1440]. However, the regulation of E-cadherin by decorin and its implication in cancer formation and metastasis is largely unknown. Using a decorin knockout mouse model (Dcn(-/-) mice) and manipulated expression of decorin in human colorectal cancer cells, we found that E-cadherin, a protein that regulates cell-cell adhesion, epithelial-mesenchymal transition and metastasis, was almost completely lost in Dcn(-/-) mouse intestine, and loss of decorin and E-cadherin accelerated colon cancer cell growth and invasion in Dcn(-/-) mice. However, increasing decorin expression in colorectal cancer cells attenuated cancer cell malignancy, including inhibition of cancer cell proliferation, promotion of apoptosis and importantly, attenuation of cancer cell migration. All these changes were linked to the regulation of E-cadherin by decorin. Moreover, overexpression of decorin upregulated E-cadherin through increasing of E-cadherin protein stability as E-cadherin messenger RNA and promoter activity were not affected. Co-immunoprecipitation assay showed a physical binding between decorin and E-cadherin proteins. Taken together, our results provide direct evidence that decorin-mediated inhibition of colorectal cancer growth and migration are through the interaction with and stabilization of E-cadherin