Miracle-dz/UniFAR-FTUs huggingface dataset:
A K-Factor CPU Scheduling Algorithm

In a multi-tasking environment, it is crucial to optimize the CPU scheduling process. Several algorithms have been proposed and are in use to schedule processes on CPU. This paper aims to evaluate shortest job first (SJF) algorithm and propose an algorithm to overcome the shortcomings of SJF. The simulation results yield useful data for comparison and evaluation. The performance metrics include average turnaround time and average waiting time. The numbers of processes have been varied in the range 10 to 100000, which provides actual scenarios inside a system. For evaluation, simulations have been run many times, between 10 to 100 runs. The results indicate that the starvation created by SJF for longer processes is not present in the proposed algorithm, making it a suitable choice for implementation.
Micromagnetics of FePt-L10 Media With Thermally Insulating Magnetic Grain Boundaries

The Curie temperature distribution induced from grain size variation in heat-assisted magnetic recording (HAMR) can be alleviated by including the thermally insulating magnetic grain boundaries. In this paper, we present a systematic micromagnetic study on this new type of HAMR media, focusing on the impact to the recording behaviors from the exchange coupled magnetic boundary (shell). It is found that the soft magnetic shell of higher Curie temperature is capable of assisting the switching of FePt grain in both magnetization and transition process. The important implication of the proposed media for practical HAMR recording is that optimal performance now can be accomplished with relaxed recording conditions in both head field intensity and the heating source, eventually enhancing area density capability and the overall HAMR system stability.
Modeling and Verification of Automotive Multi-Gig Ethernet Communication up to 2.5 Gbps and the Corresponding EMC Analysis

Implementation of 5G mobile technology, fully autonomous driving, HD video transmission and much more are currently pursued by most of the automotive manufacturers worldwide. The bandwidth requirements for the realization of the mentioned objectives pose new challenges for the vehicle industry. Pulse amplitude modulation (PAM) is an effective approach for limiting the bandwidth. The increase in data rate and the use of higher modulation formats, e.g. PAM-5 to PAM-16, is associated with higher electrical interference sensitivity. The possible consequences are the reduction of signal-to-noise ratio (SNR), the increase of crosstalk, etc. Therefore, a tradeoff between bandwidth and the SNR is required. Pulse amplitude modulation with three signal levels (PAM-3) is implemented in 100BASE-T1 and 1000BASE-T1. There is no fixed definition of PAM level for 2.5 Gbps data transmission. As an example, for 2.5 Gbps with PAM-3 signaling, the required bandwidth is approx. 900 MHz – 1 GHz in the frequency domain. At such high-frequency ranges, the investigation of electromagnetic compatibility (EMC) of the Ethernet bus system plays an important role in designing the automotive Multi-Gig chips. The functionality of each physical component of the transmission system including the EMC issues should be modeled and verified. To the author's knowledge, this is the first time that SPICE model of the whole analog front end of automotive Multi-Gig Ethernet communication (up to 2.5 Gbps) is presented and verified by measurements.
Classification of the PolSAR Data Using Dual Classifiers

Classification of the polarimetric synthetic aperture radar (PolSAR) data is an important facet of synthetic aperture radar (SAR) image interpretation. In general, many polarimetric features can be extracted from PolSAR data. However, not all features are benefit for classification and too many polarimetric features result in the low classification efficiency. We introduce a method to deal with many polarimetric features and obtain both high classification accuracy and high classification efficiency. We first preprocess the PolSAR data to obtain objects, i.e., homogeneous regions. Next, we apply polarimetric feature processing to compute various polarimetric features of the PolSAR data. Based on the classification of the sample information, we then select the prominent polarimetric features using the data mining attributes of decision tree algorithm (DTA). Finally, we obtain classification results through the selected polarimetric features by DTA, the sample data and support vector machine (SVM). We verified the proposed method using the AirSAR L-Band PolSAR data. Our experiments indicate that the classification accuracy of the proposed method is equivalent to that of SVM and the computational efficiency is comparable to that of DTA. Thus, the proposed method integrates the advantages of both DTA and SVM.
De-noising and Feature Enhancement of fMRI Data Based on Naive Bayesian Link Prediction

The traditional functional connectivity network (FCN) is greatly affected by external factors such as head movements, resulting in inaccurate classification results. This paper proposes a link prediction algorithm based on Naive Bayes to reconstruct the FCN. The proposed Naive Bayes-based link prediction algorithm can de-noise and enhance the features of the original FCN. Specifically, the FCN is obtained by matching the AAL template with pre-processing and sliding time windows. Then the Bayesian algorithm is used to change the weight of each node and then expressed by Common Neighbors (CN), Adamic-Adar (AA) and Resource Allocation (RA) coefficients to obtain reconstructed functional connection network. We call the coefficients as Local Naive Bayes Common Neighbors (LNB-CN), Local Naive Bayes Adamic-Adar (LNB-AA) and Local Naive Bayes Resource Allocation (LNB-RA). Finally, the classifier is used to classify the reconstructed network to verify the effectiveness of the proposed algorithm. The use of schizophrenia data provided by the Olin Neuropsychiatry Research Center of Hartford in United States was used to validate the effect of the reconstructed FCN by link prediction. In the experiment, we compared the changes of network characteristics before and after FCN reconstruction, and the classification performance was evaluated using three indicators-accuracy, sensitivity and specificity. The experimental results show that compared with the original FCN, the reconstructed FCN can achieve better results. To some extent, it has helped the diagnosis of brain diseases.
Review on QoS Provisioning Approaches for Supporting Video Traffic in IEEE802.11e: Challenges and Issues

Recently, the demand for multimedia applications is dramatically increased, which in turn increases the portion of video traffic on the Internet. The video streams, which require stringent quality of service (QoS), are expected to occupy more than two-thirds of Web traffic by 2019. IEEE802.11e has introduced HCF-controlled channel access (HCCA) to provide QoS for delay-sensitive applications, including highly compressed video streams. However, IEEE802.11e performance is hindered by the dynamic nature of variable bit rate (VBR) video streams in which packet size and interval time are rapidly fluctuating during the traffic lifetime. In order to make IEEE802.11e able to accommodate with the irregularity of VBR video traffic, many approaches have been used in the literature. In this paper, we highlight and discuss the QoS challenges in IEEE802.11e. Then, we classify the existing QoS approaches in IEEE802.11e and also discuss the selection of recent promising and interesting enhancements of HCCA. Eventually, a set of open research issues and potential future directions is presented.
Losses Modeling Based on Domain Wall Processes and Validation Considering Rotational Excitation of Electrical Steel Sheets

The domain wall processes are investigated and modeled at low-to-medium frequencies in electrical steel sheets based on the damping principle of vibration. Due to the energy dissipation chiefly descends from a micro-vortex current caused by domain wall motion, the coupled Landau–Lifshitz–Gilbert and Maxwell electromagnetic diffusion equations are thus considered to describe the high-frequency characteristics. The overall core losses are eventually deduced in terms of separate contributions by domain wall processes and classical eddy current. Moreover, the calculation model can be extended to rotational excitation pattern. Hence, taking typical electrical steel sheets as example, the novel core loss calculation model is analyzed and compared with the total alternating core losses supplied by electrical steel sheet manufacturers and the 3-D rotating experimental core losses of testing sheets which are carried out by using a 3-D magnetic properties’ testing system, and also achieve some beneficial conclusions.
Treatment Efficacy for Veterans With Posttraumatic Stress Disorder: Latent Class Trajectories of Treatment Response and Their Predictors

Abstract Evidence suggests that veterans with posttraumatic stress disorder (PTSD) have a poorer treatment response than nonveterans. In this study, we explored heterogeneity in treatment response for 960 veterans in the United Kingdom with PTSD who had been offered a residential intervention consisting of a mixture of group sessions and individual trauma‐focused cognitive behavioral therapy (TF–CBT). The primary outcome was PTSD score on the Impact of Event Scale–Revised (IES–R). Covariates included depression, anxiety, anger, alcohol misuse, functional impairment, and sociodemographic characteristics. Follow‐up occurred posttreatment at set time points for 12 months. We present predictors of PTSD severity at posttreatment and follow‐up obtained using a latent class growth analysis to identify different treatment trajectories. Multinomial logistic regression models were used to identify covariates predicting class membership, and five classes were identified. Of participants, 71.3% belonged to three classes showing positive treatment responses, and 1.2% showed initial improvement but later relapsed. Additionally, 27.5% of participants were identified within a treatment‐resistant class that showed little change in severity of presentation. Depression, anxiety, and having had a combat role during military service increased the likelihood of membership in the treatment‐resistant class, odds ratios (ORs) = 1.12–1.53, 1.16–1.32, and 2.89, respectively. Additionally, participants in the treatment‐resistant class had higher pretreatment PTSD scores for reexperiencing, avoidance, and hyperarousal symptoms, ORs = 5.24, 2.62, and 3.86, respectively. Findings suggest the importance of triaging individuals and offering interventions tailored to severity of presentation.
Statistical Analysis of Prosumer Behaviour in a Real Distribution Network Over Two Years

This paper presents a statistical analysis about domestic PV prosumers in Terni (Italy). Data of energy produced by domestic photovoltaic systems (PVs) and of energy injected into the grid are collected for years 2015 and 2016. Statistical distributions of self-consumption and self-sufficiency rates per prosumer are reported. The analyses show low values of both self-consumption and self-sufficiency rates with respect to expected ones, as well as a reduction of such indexes from 2015 to 2016, prompting the need to increase such values (by means of storage systems and/or demand side management) in order to attain a higher penetration of PVs in low voltage distribution networks.
SoMAS Based Cooperative Control for Cyber Physical Energy Systems

This paper discuss new consumers termed as “Prosumers” visualized as Cyber Physical Energy Systems (CPES). These CPES require being agile smart autonomous energy entities possessing capability to be interconnected at Local Power Distribution (LPD) level to share renewable energy. This build concept of Internet of Energy (IoE), forming bottom up decentralized model for energy network. In order to coordinate these CPES to share energy at LPD level, distributed smart cooperative control mechanism based on Service Oriented Architecture (SOA) and Multi Agent System (MAS) termed SoMAS is proposed in this paper. This mechanism include smart energy sharing scheme for cooperation and coordination to manage energy sharing among interconnected CPES. Simulation setup for proposed mechanism is also presented in paper.
Development of Power Assist Wheelchair Control with Driving Assistance using Fish-eye Vision

This paper presents a power assisting control system with driving assistance using monocular fish-eye vision for electric wheelchair. In our past researches, several approaches to vision-based power assist control have been studied in order to achieve driving assistance. In order to obtain wide angle view in front of wheelchair, the fish-eye vision system is employed, and the optical flow vectors are only used for simplified calculation process of driving assistance without complicated 3D reconstruction in our approach. Also, the noise influence of the optical flow vectors calculated by block matching algorithm is reduced for improving the practical performance. The validity of our system is evaluated by several experimental results.
Analytical Method for Overhang Effect of Surface-Mounted Permanent-Magnet Motor Using Conformal Mapping

In this paper, an analytical method for predicting the rotor overhang (OH) effect is presented using two types of conformal mappings (CMs), which are the <inline-formula> <tex-math notation="LaTeX">${r}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${\theta }$ </tex-math></inline-formula> and <italic>zr</italic> plane CMs. First, the no-load air-gap flux density (AFD) of a slotted air gap without OH is determined using the <inline-formula> <tex-math notation="LaTeX">${r} {\theta }$ </tex-math></inline-formula> plane CM. Second, the complex relative air-gap permeance (CRAP) in the <italic>zr</italic> plane is obtained by the <italic>zr</italic> plane CM. This helps in taking the OH effect into account. Finally, the no-load AFD of the slotted and OH air gaps in cylindrical coordinates is derived from the no-load AFD in the <inline-formula> <tex-math notation="LaTeX">${r} {\theta }$ </tex-math></inline-formula> plane with CRAP along the <inline-formula> <tex-math notation="LaTeX">${z}$ </tex-math></inline-formula>-axis. The accuracy of the presented method is verified by comparing the results of no-load analysis with those of 3-D finite-element analysis.
Pathomon: A Social Augmented Reality Serious Game

The release of Pokémon GO attracted a huge player base ranging from children to adults, thereby establishing augmented reality (AR) on the mass market. In this paper, we present Pathomon, a social AR serious game which combines the location-based game mechanics of Pokémon GO with the benefits of using AR in a serious context. We describe the concept of the game which is based on cooperatively scanning QR codes, enabling the players to work together towards their common goal of eradicating viruses in their environment, while at the same time acquiring knowledge about these viruses. Furthermore, we present a first user study suggesting favorable results with respect to game experience, yet indicating room for improvement concerning the social game aspects. Finally, we outline the opportunity of the game to serve as a starting point for the development of a more versatile social AR platform capable of including arbitrary contents beyond the context of virus infections.
Fault Detection, Isolation and Restoration Test Platform Based on Smart Grid Architecture Model Using Intenet-of-Things Approaches

To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform.
Angioedema: a rare and sometimes delayed side effect of angiotensin-converting enzyme inhibitors

Abstract The effects of angiotensin converting enzyme (ACE) inhibitors result from the inhibition of the ACE (kininase II) to ultimately influence both the renin–angiotensin system and the degradation of the bradykinin (BK) metabolism. ACE inhibitors block the degradation of BK and substance P by ACE. In addition, an active metabolite of BK (Des-Arg9-BK) is catalysed by kininase I and its degradation is controlled in part by the conversion enzyme. These molecules have been associated with increased plasma extravasation associated with ACE inhibitors. ACE inhibitors are the leading cause of drug-induced Angioedema (AE). Symptoms of AE mainly occur after the first month of treatment by ACE. However, very late onset cases, sometimes after several years of stable therapy, are also described in the literature. It has been observed that patients previously stable under ACE inhibitor will most likely develop AE soon after the addition of another medication, including the combination of aspirin or non-steroid anti-inflammatory drugs with ACE inhibitor which has proved to be the most common cause, accounting for close to 50% of all AE cases related to ACE inhibitors. This side effect of ACE inhibitors, sometimes very late and rare, deserves to be recalled
EBF1 gene promotes the proliferation and inhibits the apoptosis of bone marrow CD34+ cells in patients with myelodysplastic syndrome through negative regulation of mitogen‐activated protein kinase axis

The transcription factor, early B cell factor 1 (EBF1), plays a vital role in the lineage specification involving early B cell development and the onset of myelodysplastic syndrome (MDS). Therefore, to investigate whether or not EBF1 affects MDS as well as the transcription factor's underlying mechanism, we used CD34+ hematopoietic stem cells in bone marrow from patients with MDS. The extracted cells were then transfected with a series of EBF1, short hairpin RNA against EBF1 (shEBF1), and SB203580 (a specific mitogen‐activated protein kinase [MAPK] axis inhibitor). The effects EBF1 gene and MAPK axis had on cell proliferation, apoptosis, and migration were determined by in vitro cell culturing. We made observations that involved EBF1 inhibiting the messenger RNA (mRNA) level of p38 MAPK, increasing the mRNA levels of extracellular‐signal–regulated kinase (ERK), c‐Jun N‐terminal kinase (JNK), extracellular‐signal–regulated kinase 5 (ERK5), decreasing the protein expression of Bcl‐2–associated X protein (Bax), and finally elevating the protein levels of B cell lymphoma/leukemia‐2 (Bcl‐2), stem cell factor (SCF), erythropoietin receptor (EpoR), p‐ERK, p‐JNK, p‐ERK5, cyclin D, cyclin E, cyclin‐dependent kinase 2 (CDK2), and CDK6, implying that EBF1 may very well have an inhibitory role in the MAPK axis. Another discovery found that EBF1 had a positive effect on the promotion of bone marrow CD34+ cell proliferation as well as its migration, but inhibited the apoptosis of cells. The results we obtained from this study indicated that the EBF1 gene suppresses the activation of the MAPK axis, thereby promoting both the proliferation and migration of bone marrow CD34+ cells as well as inhibiting the associating apoptosis. The effects of the EBF1 gene are likely to present a new therapeutic target in preventing the progression of MDS.
Codebook Optimization for the Superposition Transmission of Uplink SCMA Systems

For an uplink sparse code multiple access (SCMA) system, a codebook-domain superposition transmission can be applied to increase the multiplexing gain by efficient utilization of the codebooks as multiple access resources. However, the destructive collision of superposed codewords can restrict the performance improvement of the system because of the increasing interlayer interferences. In this paper, we analyze the effects of the interlayer interferences on the bit error rates, and optimize the SCMA codebooks that can mitigate the interlayer interferences. Simulation results show that the optimized codebooks can provide a noticeable gain to improve the performance of uplink SCMA systems applied with superposition transmission.
Recommendations on the Use of Anti‐CGRP Monoclonal Antibodies in Children and Adolescents

Migraine is common in children and adolescents and can have long-term consequences on educational performance, self-esteem, and cognitive well-being1,2. However, effective, well-tolerated, evidence-based therapies for migraine prevention in children and adolescents remain limited3. In adults, monoclonal antibodies (mAbs) to calcitonin gene-related peptide (CGRP), or its receptor, have been shown to be efficacious for migraine prevention 4–11, and in episodic cluster headache 12. Although CGRP is expressed in multiple body systems13, trials to date have demonstrated minimal adverse events. The most commonly seen adverse events in adult trials included: injection site reactions, upper respiratory symptoms and constipation. These treatments avoid the need for daily pill taking, and thus may improve adherence, which is known to be low with oral migraine preventives14. Pediatric and adolescent migraine prevention trials will follow; however, outcome data from these will likely not be available for several years. In the interim, the decision regarding whether to treat pediatric patients with anti-CGRP mAbs will require providers to balance the potential for unknown risks against the potential benefits of the therapy. To bridge the gap until empiric data become available, this manuscript, written by members of the Pediatric & Adolescent Headache special interest group of the American Headache Society, is meant to serve as expert opinion, i.e. class IV evidence, on the use of these antibodies in children and adolescents. This topic was discussed at the Pediatric & Adolescent Headache special interest group (SIG) meeting at the 2018 Annual Scientific Meeting of the American Headache Society, and via email communication to SIG members. Interested members volunteered to collaborate as co-authors on this document. Authors divided into subgroups to draft the various sections of the manuscript. Recommendations were reached by consensus first within the subgroups and then all co-authors had the opportunity to read the entire manuscript so that final recommendations could be reached by consensus. The opinions expressed in this manuscript represent those of the co-authors and do not represent the opinion of the American Headache Society.