LLukas22/scidocs huggingface dataset:
Therapeutic Discovery ORAI 1-Mediated Calcium Influx in Lactation and in Breast Cancer

The entry of calcium into the mammary epithelial cell from the maternal plasma (i.e., calcium influx mechanisms) during lactation is poorly understood. As alterations in calcium channels and pumps are a key feature of some cancers, including breast cancer, understanding these calcium influx pathways may have significance beyond mammary biology. We show that the store-operated calcium influx protein, Orai1, is increased during lactation whereas the Orai1 activator Stim1, but not Stim2, is downregulated. Stim2 siRNA reduced basal calcium levels in a lactation model. Our results suggest that calcium influx is remodeled in mammary epithelial cells during lactation, with calcium influx increased through Orai1, activated by Stim2. Breast cancer cell lines had increased levels of ORAI1. ORAI1 siRNA in breast cancer cells reduced storeoperated calcium entry and remodeled the calcium influx associated with invasive stimuli. Analysis of microarray data from 295 breast cancers showed that the transcriptional breast cancer subtype with the poorest prognosis (basal) was associated with an altered relationship between the ORAI1 regulators STIM1 and STIM2, and that women with breast cancers with STIM1/STIM2 tumors had a significantly poorer prognosis. Our studies show that during lactation there is a remodeling in the nature of calcium influx and that alteration in the ORAI1 influx pathway may be a feature of some breast cancers, particularly those with the poorest prognosis. Our studies suggest that this pathway may be a novel therapeutic target for breast cancer treatment in these women. Mol Cancer Ther; 10(3); 448–60. 2011 AACR.
Certain performance values arising from mammographic test set readings correlate well with clinical audit.

INTRODUCTION
Test sets have been increasingly utilised to augment clinical audit in breast screening programmes; however, their relationship has never been satisfactorily understood. This study examined the relationship between mammographic test set performance and clinical audit data.


METHODS
Clinical audit data over a 2-year period was generated for each of 20 radiologists. Sixty mammographic examinations, consisting of 40 normal and 20 cancer cases, formed the test set. Readers located any identifiable cancer, and levels of confidence were scored from 2 to 5, where a score of 3 and above is considered a recall rating. Jackknifing free response operating characteristic (JAFROC) figure-of-merit (FOM), location sensitivity and specificity were calculated for individual readers and then compared with clinical audit values using Spearman's rho.


RESULTS
JAFROC FOM showed significant correlations to: recall rate at a first round of screening (r = 0.51; P = 0.02); rate of small invasive cancers per 10 000 reads (r = 0.5; P = 0.02); percentage of all cancers read that were not recalled (r = -0.51; P = 0.02); and sensitivity (r = 0.51; P = 0.02). Location sensitivity demonstrated significant correlations with: rate of small invasive cancers per 10 000 reads (r = 0.46; P = 0.04); rate of DCIS (ductal carcinoma in situ) per 10 000 reads (r = 0.44; P = 0.05); detection rate of all invasive cancers and DCIS per 10 000 reads (r = 0.54; P = 0.01); percentage of all cancers read that were not recalled (r = -0.57; P = 0.009); and sensitivity (r = 0.57; P = 0.009). No other significant relationships were noted.


CONCLUSION
Performance indicators from test set demonstrate significant correlations with specific aspects of clinical performance, although caution needs to be exercised when generalising test set specificity to the clinical situation.
Discrimination of EEG-Based Motor Imagery Tasks by Means of a Simple Phase Information Method

We propose an off-line analysis method in order to discriminate between motor imagery tasks manipulated in a brain computer interface system. A measure of large-scale synchronization based on phase locking value is established. The results indicate that it can take advantage of the phase synchrony between scalp-recorded EEG activity in the supplementary motor area and in sezorimotor area, computing the differences between the active and the relaxation states. Phase locking value features are more discriminative in β rhythm than in μ rhythm. The proposed method is simple, computationally efficient and proves good results on EEG Motor Movement/Imagery Dataset available from PhysioNet research resource for physiologic signals. Keywords—brain computer interface; motor imagery task; electroencephalogram; phase locking value
Emerging Issues & Challenges in Cloud Computing— A Hybrid Approach

As cloud computing continues to gain more momentum in the IT industry, more issues and challenges are being reported by academics and practitioners. In this paper, we aim to attain an understanding of the types of issues and challenges that have been emerging over the past five years and identify gaps between the focus of the literature and what practitioners deem important. A systematic literature review as well as interviews with experts have been conducted to answer our research questions. Our findings suggest that researchers have been mainly focusing on issues related to security and privacy, infrastructure, and data management. Interoperability across different service providers has also been an active area of research. Despite the significant overlap between the topics being discussed in the literature and the issues raised by the practitioners, our findings show that some issues and challenges that practitioners consider important are understudied such as software related issues, and challenges pertaining to learning fast-evolving technologies.
Effects of Helicobacter pylori eradication on the development of metachronous gastric cancer after endoscopic treatment: analysis of molecular alterations by a randomised controlled trial

Background:Whether Helicobacter pylori eradication actually suppresses the development of metachronous gastric cancer (MGC) after endoscopic resection (ER) remains controversial. The aims of this study were to clarify (1) the molecular markers related to carcinogenesis in intestinal metaplasia (IM) by a cross-sectional study, and (2) the changes of those markers by an open-label, randomised controlled trial (RCT) of H. pylori treatment.Methods:First, we evaluated microsatellite instability (MSI), the methylation status at hMLH1, CDKN2A and APC genes, and immunoreactivity using the monoclonal antibody (mAb) Das-1 in IM in the background mucosa of 131 patients who underwent ER for gastric neoplasia and 22 chronic gastritis cases (control). Next, we performed an RCT to evaluate the changes of MSI between the H. pylori-eradicated (n=19) and non-eradicated patients (n=17) at 1 year among the H. pylori-positive patients.Results:Microsatellite instability and mAb Das-1 reactivity showed significantly higher incidences in both the H. pylori-positive and -negative patients compared with the control group, thus suggesting that MSI and mAb Das-1 reactivity are associated with gastric neoplasia (OR=5.06 for MSI; OR=2.51 for mAb Das-1 reactivity). The RCT showed that H. pylori eradication did not provide significant reversals of any molecular alterations including MSI (the primary end point) and other methylation statuses and mAb Das-1 reactivity (secondary end points).Conclusions:H. pylori eradication did not produce significant changes in the molecular alterations related to carcinogenesis, suggesting that H. pylori treatment may not prevent the development of MGC in background mucosa with IM.
Telemonitoring Systems Interoperability Challenge: An Updated Review of the Applicability of ISO/IEEE 11073 Standards for Interoperability in Telemonitoring

Advances in Information and Communication Technologies, ICT, are bringing new opportunities and use cases in the field of systems and Personal Health Devices used for the telemonitoring of citizens in Home or Mobile scenarios. At a time of such challenges, this review arises from the need to identify robust technical telemonitoring solutions that are both open and interoperable. These systems demand standardized solutions to be cost effective and to take advantage of standardized operation and interoperability. Thus, the fundamental challenge is to design plug-&-play devices that, either as individual elements or as components, can be incorporated in a simple way into different Telecare systems, perhaps configuring a personal user network. Moreover, there is an increasing market pressure from companies not traditionally involved in medical markets, asking for a standard for Personal Health Devices, which foresee a vast demand for telemonitoring, wellness, Ambient Assisted Living (AAL) and e- health applications. However, the newly emerging situations imply very strict requirements for the protocols involved in the communication. The ISO/IEEE 11073 family of standards is adapting and moving in order to face the challenge and might appear the best positioned international standards to reach this goal. This work presents an updated survey of these standards, trying to track the changes that are being fulfilled, and tries to serve as a starting-point for those who want to familiarize themselves with them.
Expressing Interactivity with States and Constraints

......................................................................................................................... iii Acknowledgements ......................................................................................................... iv Table of
Saliency Detection with Recurrent Fully Convolutional Networks

• Employs three kind of low-level contrast features, including color, intensity and orientation, and the center prior knowledge to introduce saliency prior maps. • Train the RFCN with two stage training strategy, pre-training on the segmentation data set and fine-tuning on the saliency data set. The recurrent structure can incorporate the saliency prior maps into the CNNs with an end-to-end training method. • Refine the saliency maps with a postprocessing method which can improve the performance of RFCN. Edge-preserving maps are produced with the computation of color confidence and spatial confidence. 3. Algorithm 4. Results
Comparison of Damage Path Predictions for Composite Laminates by Explicit and Standard Finite Element Analysis Tools

Splitting, ultimate failure load and the damage path in center notched composite specimens subjected to in-plane tension loading are predicted using progressive failure analysis methodology. A 2-D Hashin-Rotem failure criterion is used in determining intra-laminar fiber and matrix failures. This progressive failure methodology has been implemented in the Abaqus/Explicit and Abaqus/Standard finite element codes through user written subroutines “VUMAT” and “USDFLD” respectively. A 2-D finite element model is used for predicting the intra-laminar damages. Analysis results obtained from the Abaqus/Explicit and Abaqus/Standard code show good agreement with experimental results. The importance of modeling delamination in progressive failure analysis methodology is recognized for future studies. The use of an explicit integration dynamics code for simple specimen geometry and static loading establishes a foundation for future analyses where complex loading and nonlinear dynamic interactions of damage and structure will necessitate it.
Conv-RAM: An energy-efficient SRAM with embedded convolution computation for low-power CNN-based machine learning applications

Convolutional neural networks (CNN) provide state-of-the-art results in a wide variety of machine learning (ML) applications, ranging from image classification to speech recognition. However, they are very computationally intensive and require huge amounts of storage. Recent work strived towards reducing the size of the CNNs: [1] proposes a binary-weight-network (BWN), where the filter weights (wi's) are ±1 (with a common scaling factor per filter: α). This leads to a significant reduction in the amount of storage required for the Wi's, making it possible to store them entirely on-chip. However, in a conventional all-digital implementation [2, 3], reading the wjis and the partial sums from the embedded SRAMs require a lot of data movement per computation, which is energy-hungry. To reduce data-movement, and associated energy, we present an SRAM-embedded convolution architecture (Fig. 31.1.1), which does not require reading the wi's explicitly from the memory. Prior work on embedded ML classifiers have focused on 1b outputs [4] or a small number of output classes [5], both of which are not sufficient for CNNs. This work uses 7b inputs/outputs, which is sufficient to maintain good accuracy for most of the popular CNNs [1]. The convolution operation is implemented as voltage averaging (Fig. 31.1.1), since the wj's are binary, while the averaging factor (1/N) implements the weight-coefficient α (with a new scaling factor, M, implemented off-chip).
Merkle Tree Traversal Revisited

We propose a new algorithm for computing authentication paths in the Merkle signature scheme. Compared to the best algorithm for this task, our algorithm reduces the worst case running time considerably.
License Plate Recognition System

Introduction License Plate Recognition is an image-processing technology that is used to identify vehicles by their license plates. A license plate reader works by extracting the characters from an image. This technology is used for many applications such as toll booths, parking decks, border control, and law enforcement. As a solution to the problem of monitoring the tremendous number of vehicles for law enforcement and security, we will design a license plate recognition system to make the task more practical. Our system will provide a way to detect and identify license plates without constant human intervention. This will be both a time and money saving benefit to police departments in the state of Georgia. Our system, based on a Linux platform, will work with both stationary and moving vehicle images and the Georgia license plate. We will consider expanding the project to include license plates from other states once we have a solid system for Georgia plates. A camera will be configured to snap a picture once a motion detector has been tripped, focusing on the rear of the vehicle where license plates are generally stationed. The image will then be processed to determine the characters of the plate, and those characters will be queried into the mySQL database. If the query returns that the license plate belongs to someone with a warrant out for their arrest, or on a stolen vehicle, the authorities will be notified with that information. Figure 1 shows the system setup. The aim of this project is threefold ; first, we will look at optical character recognition techniques and investigate the process of license plate recognition from acquiring an image; second, we will develop a database that contains the user information; and finally, we will develop a graphical user interface for the system. There are multiple license plate recognition systems available; however a majority of the systems are available for foreign plates only.
Ins, outs, and the duration of trade

We employ survival analysis to study the duration of US imports. Our findings indicate that international trade is far more dynamic than previously thought. We find the median duration of exporting a product to the US is very short, on the order of two to four years. There is negative duration dependence—if a country is able to survive in the exporting market for the first few years it will face a very small probability of failure and will likely export the product for a long period of time. The results hold across countries and industries and are robust to aggregation.
Opioid disposition in human sweat after controlled oral codeine administration.

BACKGROUND
Characterization of opioid excretion in sweat is important for accurate interpretation of sweat tests in drug treatment, criminal justice, and workplace drug testing programs.


METHODS
Participants (n=20) received placebo, 3 low (60 mg/70 kg) or 3 high (120 mg/70 kg) codeine sulfate doses (used as a model for opioid excretion) within 1 week. Codeine and metabolites in sweat were collected with PharmChek Sweat Patches; hourly patches were applied for 1 to 15 h (n=775) and weekly patches for 7 days (n=118). Patches were analyzed by solid-phase extraction and gas chromatography-mass spectrometry for codeine, norcodeine, morphine, normorphine, and 6-acetylmorphine. Limits of quantification were 2.5 ng/patch (codeine and morphine) and 5 ng/patch (other analytes).


RESULTS
Codeine was the only analyte identified in 12.6% of hourly patches and 83.3% of weekly sweat patches worn during dosing. Weekly patch concentrations (SD) were 38.6 (59.9) ng/patch [median (range), 15.9 (0-225.1) ng/patch] for low and 34.1 (32.7) ng/patch [24.0 (0-96.2) ng/patch] for high codeine doses. Codeine detected 1 week after dosing was 4.6 (5.3) ng/patch [median (range), 4.0 (0-17.1) ng/patch; n=11] after low and 7.7 (7.1) ng/patch [6.9 (0-20.5) ng/patch; n=10] after high doses. In total, 2.6% of hourly, 38.5% of low-dose, and 45.5% of high-dose weekly patches contained codeine at the proposed Substance Abuse and Mental Health Services Administration cutoff.


CONCLUSIONS
Codeine was the only analyte detected, at highly variable concentrations, up to 2 weeks after dosing. These results are consistent, considering the complex processes of codeine deposition in sweat. Sweat testing is a useful alternative technique for qualitative monitoring of opioid use.
Prostacyclin influences the pressure reactivity in patients with severe traumatic brain injury treated with an ICP-targeted therapy.

BACKGROUND
This prospective consecutive double-blinded randomized study investigated the effect of prostacyclin on pressure reactivity (PR) in severe traumatic brain injured patients. Other aims were to describe PR over time and its relation to outcome.


METHODS
Blunt head trauma patients, Glasgow coma scale ≤8, age 15-70 years were included and randomized to prostacyclin treatment (n = 23) or placebo (n = 25). Outcome was assessed using the extended Glasgow outcome scale (GOSE) at 3 months. PR was calculated as the regression coefficient between the hourly mean values of ICP versus MAP. Pressure active/stable was defined as PR ≤0.


RESULTS
Mean PR over 96 h (PRtot) was 0.077 ± 0.168, in the prostacyclin group 0.030 ± 0.153 and in the placebo group 0.120 ± 0.173 (p < 0.02). There was a larger portion of pressure-active/stable patients in the prostacyclin group than in the placebo group (p < 0.05). Intra-individual changes over time were common. PRtot correlated negatively with GOSE score (p < 0.04). PRtot was 0.117 ± 0.182 in the unfavorable (GOSE 1-4) and 0.029 ± 0.140 in the favorable outcome group (GOSE 5-8). Area under the curve for prediction of death (ROC) was 0.742 and for favorable outcome 0.628.


CONCLUSIONS
Prostacyclin influenced the PR in a direction of increased pressure stability and a lower PRtot was associated with improved outcome. The individual PR varied substantially over time. The predictive value of PRtot for outcome was not solid enough to be used in the clinical situation.
Making graphene visible

Microfabrication of graphene devices used in many experimental studies currently relies on the fact that graphene crystallites can be visualized using optical microscopy if prepared on top of Si wafers with a certain thickness of SiO2. The authors study graphene’s visibility and show that it depends strongly on both thickness of SiO2 and light wavelength. They have found that by using monochromatic illumination, graphene can be isolated for any SiO2 thickness, albeit 300 nm the current standard and, especially, 100 nm are most suitable for its visual detection. By using a Fresnel-law-based model, they quantitatively describe the experimental data. © 2007 American Institute of Physics. DOI: 10.1063/1.2768624
The Complexity of Graph Connectivity

In this paper we survey the major developments in understanding the complexity of the graph connectivity problem in several computational models, and highlight some challenging open problems.
A GP-AHP method for solving group decision-making fuzzy AHP problems

The analytic hierarchy process (AHP) elicits a corresponding priority vector interpreting the preferred information from the decision-maker(s), based on the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale, in practice the decision-maker(s) usually give some or all pair-to-pair comparison values with an uncertainty degree rather than precise ratings. By employing the property of goal programming (GP) to treat a fuzzy AHP problem, this paper incorporates an absolute term linearization technique and a fuzzy rating expression into a GP-AHP model for solving group decision-making fuzzy AHP problems. In contrast to current fuzzy AHP methods, the GP-AHP method developed herein can concurrently tackle the pairwise comparison involving triangular, general concave and concave–convex mixed fuzzy estimates under a group decision-making environment. Scope and purpose Many real world decision problems involve multiple criteria in qualitative domains. As expected, such problems will be increasingly modeled as multiple criteria decision-making problems, which involve scoring on subjective=qualitative domains. This results in a class of signi6cant problems for which an evaluation framework, which handles occurrences of seeming intransitivity and inconsistency will be required. Another interesting issue of group decision-making analysis is how to deal with disagreements between two or more di7erent rankings within an alternative set. These phenomena are likely to appear in qualitative=subjective domains where the decision-making environment is ambiguous and vague. Therefore, this study proposes a GP-AHP model that is su8ciently robust to permit con9ict and imprecision. Numerical examples demonstrate the e7ectiveness and applicability of the proposed models in deriving the most promising priority vector from a fuzzy AHP problem within a group decision-making environment. ? 2002 Elsevier Science Ltd. All rights reserved.
Economic prediction using neural networks: the case of IBM daily stock returns

A report is presented of some results of an ongoing project using neural-network modeling and learning techniques to search for and decode nonlinear regularities in asset price movements. The author focuses on the case of IBM common stock daily returns. Having to deal with the salient features of economic data highlights the role to be played by statistical inference and requires modifications to standard learning techniques which may prove useful in other contexts.<<ETX>>