Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconstruction of MRI Images based on Compressive Sensing

Magnetic Resonance Imaging (MRI) is a medical imaging technique for diagnosing patients suffering from torn ligaments to cancerous tumors. MRI is also very useful for examining the brain and spinal cord related issues. The size of the image decides how many times the Radio Frequency pulse needs to be applied, hence making the MRI scan a time consuming process. There is a growing requirement for reducing the diagnosing time in MRI necessitating investigation to accelerate this non linear optimization problem. Compressed Sensing (CS) aims to reconstruct images from considerably smaller measurements than were thought before. Applying CS to MRI offers potentially significant scan time reductions. A method to MRI reconstruction from under sampled measurements is proposed in this paper. Discrete Wavelet Transform is used to sparsely characterize MRI. CS reconstruction is performed using l1 norm by applying Basis pursuit primal-dual interior point method. Experimental results reveal that the proposed method reconstructs images with good quality.
An end-user pipeline for scrapping and visualizing semi-structured data over the Web

The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to diﬀerent kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets.
A Review on Multi-Model Medical Image Fusion

Nowadays, Image fusion seems to be the most promising area in image processing. It plays a pivotal role in different applications, namely medical diagnosis, object detection and recognition, navigation, military, civilian surveillance, robotics, satellite imaging for remote sensing. The process of image fusion aims to integrate two or more images into a single image, which consists of more useful information when compared with each of the source images without introducing any artefacts. In this review paper, three aspects are considered: image fusion methods on spatial domain and transform domain methods, Image fusion rules on transform domain method and image fusion metrics. This review includes different applications, including medical image fusion methodologies.
SDNMS: A software defined network measurement system for NFV networks

As a promising technology to completely transform how we architect, deploy, operate and manage various networks, software-based Network Function Virtualization (NFV) enables hardware-independent, flexible, fast and efficient network service provision. With the increasing popularity of NFV paradigm, the Internet has also transformed to be a hybrid environment where NFV-based network entities coexist with traditional network devices. To facilitate our understanding, design, evaluate and manage of such novel network environment, there is a great need for a new NFV-compatible network measurement system which is still in absent so far. To bridge this gap, a system, named Software Defined Network Measurement System (SDNMS), is presented in this paper. Firstly, the architecture of SDNMS is proposed. In this architecture, a formal method to describe the working mode of the network measurement is defined. This method can also be utilized to generate a network measurement middle box (NMMB) in a specific location of the NFV network according to the customized description file, and to flexibly deploy the network measurement function. Secondly, the technology of virtual network measurement function (VNMF) combined with LXC is studied to form NMMB function. Thirdly, a control method is presented to control the start, stop, and update NMMB to form a specific network measurement system function. Finally, a prototype of SDNMS with network monitoring function to monitor network performance anomalies and locate faults is introduced. Experimental results have shown that SDNMS architecture and related technologies are feasible and effective to deploy and control network measurement functions in NFV networks. We hope SDNMS could provide a new method for practitioners to conduct network management and research at the age of NFV.
ScienceDirect The 6 th International Conference on Ambient Systems , Networks and Technologies ( ANT 2015 ) Computations on the Edge in the Internet of Things

In the Internet of Things (IoT), many applications focus on gathering data which can then be processed and visualized. However, such computations are usually spread generically based on parameters such as CPU and/or network load. This may mean that a significant amount of data needs to be transported over the network (either directly, or transparently using a network file system) in order for the data to be available to the node that is responsible for processing them. This paper proposes a method for deploying computations that can take factors such as data proximity into consideration. Thus, processing can be moved from central highpowered processing nodes to smaller devices on the edge of the network. By doing this, costs for gathering, processing and actuation can be minimized. In order to capture data dependencies among computations, but also to deploy and handle individual processing tasks in an easy way, the actor-model programming paradigm is used. To minimize the overall cost and to handle extra factors that weigh in on the distribution of tasks, a constraint programming approach is used. The combination of these two techniques results in an efficient distribution of tasks to processing resources in IoT. Taking into consideration the NP-hard nature of this problem, we present empirical results that illustrate how this technique performs in relation to the amount of devices/actors. c © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Conference Program Chairs.
Non-Magnetic CMOS Switched-Transmission-Line Circulators With High Power Handling and Antenna Balancing: Theory and Implementation

Recently, CMOS non-magnetic circulators have been demonstrated based on switch-based spatio-temporal conductivity modulation, but these initial demonstrations remain limited in transmitter power handling, linearity, and ability to combat antenna variations. This paper describes a non-magnetic circulator architecture that uses no external components, and employs a variety of linearity enhancement techniques, such as device stacking, optimal switch biasing, and localized electrostatic discharge (ESD) design to achieve watt-class power handling and high IIP3. A new antenna balancing approach is described that uses no inductors or lossy resistors and yet allows high isolation in the face of strong antenna reflections. The concepts are validated through a 1-GHz 180-nm SOI CMOS prototype that achieves >1-W TX–ANT <inline-formula> <tex-math notation="LaTeX">$\text{P}_{1~{\mathrm{ dB}}}$ </tex-math></inline-formula>, >+50-dBm TX–ANT IIP3, and high isolation for as high as 1.85 ANT VSWR and beyond. The circulator also exhibits low insertion losses of 2.1/2.9 dB in the TX–ANT and ANT–RX paths, and ANT–RX noise figure (NF) of 3.1 dB. These results represent a 10–100<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> enhancement in linearity/power handling over prior non-magnetic circulators and are shown to lower the power consumption of a communication link when compared with the state-of-the-art electrical balance duplexers in scenarios, where dynamic range is limited by <inline-formula> <tex-math notation="LaTeX">$\text{P}_{1~{\mathrm{ dB}}}$ </tex-math></inline-formula> and NF.
Specializing in Generality: Firm Strategies When Intermediate Markets Work

This paper studies the relationship between two decisions shaping the organizational configuration of a firm: whether to make the upstream resources more general and deployable to more markets (vs. keeping them tailored to a few markets), and whether to trade with downstream firms as an upstream supplier of intermediate products and services (vs. directly entering downstream markets). While the literature has looked at these two decisions separately, we argue that they depend on each other. This has the important implication that they can generate organizational complementarities, inducing firms to implement them simultaneously. We are motivated in particular by the observation that an increasing number of firms invest in general upstream resources and exploit them as upstream suppliers of intermediate services or products-an organizational configuration resulting from a strategy that we refer to as specialization in generality. Interestingly, the literature following the seminal work by Penrose (1959) and Nelson (1959) has mainly highlighted the use of general upstream resources to enter new downstream markets. We identify the supply and demand conditions under which specialization in generality is instead more likely to emerge: lack of prior downstream assets, on the supply side, and a roughly equal distribution of buyers across intermediate markets (a "broad" demand), on the demand side. We test our predictions using a sample of firms in the U.S. laser industry between 1993 and 2001. A regulatory shock that increases the value of trading relative to downstream entry provides the setting for a quasi-natural experiment, which corroborates our theoretical predictions.
Ultrasound-guided serratus plane block enhances pain relief and quality of recovery after breast cancer surgery: A randomised controlled trial

BACKGROUND Multimodal analgesia can improve postoperative pain and possibly accelerate functional recovery after surgery. Serratus plane block (SPB) is a novel, ultrasound-guided regional anaesthetic technique for complete analgesia of the anterolateral chest wall. But, the effect of SPB on the quality of recovery after breast cancer surgery has not been established. OBJECTIVE To test the hypothesis that pre-operative SPB would enhance the quality of recovery following breast cancer surgery. DESIGN A randomised, double-blind, parallel-group, placebo-controlled trial. SETTING Single university teaching hospital, from March 2016 to June 2017. PATIENTS Seventy-two women scheduled for breast cancer surgery. INTERVENTION Participants were randomised in a 1 : 1 ratio to receive SPB with 25 ml of ropivacaine 0.5% or physiological saline. MAIN OUTCOME MEASURES The primary endpoint was the 40-item Quality of Recovery questionnaire score 24 hours postoperatively hours. Secondary endpoints were postoperative pain intensity, cumulative opioid consumption, postoperative nausea and vomiting, dizziness, post anaesthesia care unit discharge time and patient satisfaction. RESULTS The global median [IQR] 40-item Quality of Recovery questionnaire score at 24 postoperative hours was significantly higher in the SPB group (158 [153.8 to 159.3]) than the control group (141 [139 to 145.3]) with a median difference of 15 (95% confidence interval: 13 to 17, P < 0.001). Compared with the control group, postoperative pain scores at rest were significantly lower up to 24 h in the SPB group. Pre-operative SPB reduced postoperative cumulative opioid consumption, the incidence of postoperative nausea and vomiting and the post anaesthesia care unit discharge time. In addition, patient satisfaction scores were higher in the SPB group. CONCLUSION Pre-operative administration of SPB with ropivacaine improved the quality of recovery, postoperative analgesia and patient satisfaction following breast cancer surgery. TRIAL REGISTRATION ClinicalTrials.gov (identifier: NCT02691195).
Low Complexity Polar Decoder for 5G Embb Control Channel

Polar codes have become the channel coding scheme for control channel of enhanced mobile broadband in the fifth generation (5G) communication systems. Belief propagation (BP) decoding of polar codes has the advantage of low decoding latency and high parallelism but suffers from high complexity. In this paper, a low complexity BP decoder is proposed for polar codes. We reduce the computational complexity by two steps. First, the cyclic redundancy check is concatenated to the decoder in order to decrease the number iterations of the BP algorithm. Then, a threshold is proposed based on Gaussian approximation to save the computational complexity of BP nodes. If the log-likelihood ratio of a node in the tanner graph is larger than the threshold, this node is no longer updated during the rest of the decoding process. The simulation results show that the proposed scheme has a similar block error rate performance with the original BP decoder, while the computational complexity is reduced significantly.
Comprehensive Assessment of Security Attack Detection Algorithms in Internet of Things

The Internet of Things (IoT) is becoming an important part of every business domain including health, education, industrial manufacturing, agriculture and domestic products. These applications of IoT raise concerns over security of IoT system. Several security attacks on IoT systems have been demonstrated in the state of the art. Further multiple attackers attacking IoT system collaboratively is more hazardous and stealthy. This paper reviews and evaluates the state of the art for security attack detection mechanisms on IoT protocol stack. Evaluation of the effectiveness of attack detection mechanism through an extensive simulation study is presented in the paper. Results of simulation study highlight the failure of attack detection mechanisms presented in the state of the art in case of multiple attackers attacking IoT system collaboratively. Simulation study also shows considerable deviations in network parameters in IoT system under attack of multiple collaborative attackers from normal operation. These deviations in parameters can be used for early and effective detection of security attacks on IoT system. This paper highlights need for the design of an early detection algorithm for security attacks on IoT system.
Construction et exploration de configurations spatiales : comparaison experts-novices

This paper presents two experiments which the aim is to examine the effects of using Information New Technology (INT) on individual's cognitive processing. The first experiment's results show that level expertise didn't affect processing capacities of working memory, neither visuo-spatial imagery abilities (for short-range forecasts). In return, data collected in the second experiment emphasize differences between expert and novice in the way of using INT, specially Internet web site. Indeed, experts implement systematic exploration strategies, which are regulated by semantical information processing.
Development and pilot of a multicriteria decision analysis (MCDA) tool for health services administrators

Introduction Health administration is complex and serves many masters. Value, quality, infrastructure and reimbursement are just a sample of the competing interests influencing executive decision-making. This creates a need for decision processes that are rational and holistic. Methods We created a multicriteria decision analysis tool to evaluate six fields of healthcare provision: return on investment, capacity, outcomes, safety, training and risk. The tool was designed for prospective use, at the beginning of each funding round for competing projects. Administrators were asked to rank their criteria in order of preference. Each field was assigned a representative weight determined from the rankings. Project data were then entered into the tool for each of the six fields. The score for each field was scaled as a proportion of the highest scoring project, then weighted by preference. We then plotted findings on a cost-effectiveness plane. The project was piloted and developed over successive uses by the hospital’s executive board. Results Twelve projects competing for funding at the Royal Brisbane and Women’s Hospital were scored by the tool. It created a priority ranking for each initiative based on the weights assigned to each field by the executive board. Projects were plotted on a cost-effectiveness plane with score as the x-axis and cost of implementation as the y-axis. Projects to the bottom right were considered dominant over projects above and to the left, indicating that they provided greater benefit at a lower cost. Projects below the x-axis were cost-saving and recommended provided they did not harm patients. All remaining projects above the x-axis were then recommended in order of lowest to highest cost-per-point scored. Conclusion This tool provides a transparent, objective method of decision analysis using accessible software. It would serve health services delivery organisations that seek to achieve value in healthcare.
Simultaneous representation and separation for multiple interference allied with approximation message passing in WB-IoT

∗Reliable communication is a competitive task for wideband Internet of Things (WB-IoT) system due to the fact that multiform interference has been introduced to the existing broadband transmission, which promotes the development of cognitive IoT communication systems. To facilitate the improvement of the anti-jamming performance for the coexistence of diverse interference and signals in wireless heterogeneous networks, separating and eliminating various interference to cognitive communication systems is of importance. This paper formulated a novel sparse learning method-based cognitive transformation framework of interference separation for precise interference recovery, which can be efficiently resolved by iteratively learning the prior probability distribution of the sparse interference support. Moreover, through different sparsity states of spectrum analysis, the proposed novel interference separation algorithm was applied to simultaneous separation based on state evolving of approximation message passing, which iteratively learned the belief propagation posteriors and shrank by iterative shrinkage threshold. Simulation results demonstrate that the proposed methods were effective in separating and recovering sparse diversities of interference to communication systems, thereby significantly outperformed the state-of-the-art methods.
The cyclical hit model: how paligenosis might establish the mutational landscape in Barrett's esophagus and esophageal adenocarcinoma.

PURPOSE OF REVIEW In this review, we explore a paligenosis-based model to explain Barrett's esophagus development and progression: 'the cyclical hit model. ' RECENT FINDINGS Genomic analyses have highlighted the high mutational burden of esophageal adenocarcinoma, Barrett's esophagus, and even normal esophageal epithelium. Somatic mutations in key genes including TP53 occur early in the neoplastic progression sequence of Barrett's esophagus, whereas chromosomal amplification resulting in oncogene activation occurs as a critical late event. Paligenosis is a shared injury response mechanism characterized by activation of autophagy, expression of progenitor markers, and increased mTORC signaling-induced cell-cycle reentry. In the setting of chronic injury/inflammation, cycles of paligenosis may allow accumulation of mutations until eventually the mutational burden, in concert perhaps with mutations in key driver oncogenes, finally alters the cell's ability to redifferentiate, leading to the emergence of a potential neoplastic clone. SUMMARY Under conditions of chronic gastroesophageal refluxate exposure, the normal esophageal squamous epithelium might undergo multiple cycles of paligenosis, allowing initially silent mutations to accumulate until key events impart mutant clones with an oncogenic survival advantage.
Resource-Aware Session Types for Digital Contracts

Digital contracts are protocols that describe and enforce execution of a contract, oen among mutually distrusting parties. Programming digital contracts comes with its unique challenges, which include describing and enforcing protocols of interaction, analyzing resource usage and tracking linear assets and accounting for fault tolerance. is thesis designs programming languages and techniques for implementation and analysis of digital contracts. e core of the language is based on resource-aware session types. e thesis rst introduces resource-aware session types aer providing a brief background on session types and resource analysis. It also formalizes sequential and parallel complexity analysis of concurrent programs using resourceaware session types. Second, the thesis describes how these techniques can be applied to the design of Nomos, a domain-specic language for implementation of digital contracts. Nomos uses shared session types to ensure clients interact with contracts in mutual exclusion, tracks assets using a linear type system and derives bounds on resource usage. As proposed work, I plan to design an ecient implementation of Nomos to evaluate its usability. Furthermore, I would like to add support for fault tolerance such that Nomos contracts can interact with clients implemented in a dierent language, thus providing safety guarantees in the presence of potentially malicious clients.
The protein kinase activity of fructokinase A specifies the antioxidant responses of tumor cells by phosphorylating p62

KHK-A, a metabolic enzyme in fructose metabolism, acts as a protein kinase to phosphorylate p62 for tumor antioxidant responses. Cancer cells often encounter oxidative stress. However, it is unclear whether normal and cancer cells differentially respond to oxidative stress. Here, we demonstrated that under oxidative stress, hepatocellular carcinoma (HCC) cells exhibit increased antioxidative response and survival rates compared to normal hepatocytes. Oxidative stimulation induces HCC-specifically expressed fructokinase A (KHK-A) phosphorylation at S80 by 5′-adenosine monophosphate-activated protein kinase. KHK-A in turn acts as a protein kinase to phosphorylate p62 at S28, thereby blocking p62 ubiquitination and enhancing p62’s aggregation with Keap1 and Nrf2 activation. Activated Nrf2 promotes expression of genes involved in reactive oxygen species reduction, cell survival, and HCC development in mice. In addition, phosphorylation of KHK-A S80 and p62 S28 and nuclear accumulation of Nrf2 are positively correlated in human HCC specimens and with poor prognosis of patients with HCC. These findings underscore the role of the protein kinase activity of KHK-A in antioxidative stress and HCC development.