Miracle-dz/UniFAR-FTUs huggingface dataset:
Traffic Offloading With Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks

Traffic offloading via device-to-device communications is expected to play a major role to meet the exponential data traffic growth in wireless networks. In this paper, we focus on the problem of user capacity maximization in ultra-dense heterogeneous networks with device-to-device cooperation, where a large number of users in a given geographical area request common data content, such as video on demand streaming, with strict quality of service guarantees. We aim at finding the best strategy for delivering the content either over long range connectivity from the access points or short range connectivity from peer mobile terminals while meeting a target rate per served user. We formulate the multiuser resource management problem as an optimization problem including traffic offloading and channel allocation considering a very high user density reaching up to 1.75 users per square meter. We extend the system model to include mobile terminals acting as content owners by having the content cached locally, in order to further enhance the network capacity and coverage. We then propose an iterative resource management solution, which first solves the optimization subproblem of traffic offloading with orthogonal channels, and then optimally allocates channels to the transmitters with minimized interference due to channel reuse. We also propose efficient suboptimal hierarchical tree-based algorithms that operate in real time with dynamic and fast solutions for ultra-dense networks. For performance evaluation, we consider a realistic scenario consisting of a stadium topology with thousands of mobile terminals active simultaneously. We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity.
Iodine deficiency and its associated factors among primary school children in Anchar district, Eastern Ethiopia

Background Iodine deficiency is a major public health problem in Ethiopia. Most of the studies in Ethiopia were done on clinical goiter without assessing the subclinical iodine deficiency. Therefore, there was a need to study the magnitude and associated factors of iodine deficiency among school-age children in Eastern Ethiopia. Subjects and methods A school-based cross-sectional study design was used to assess the iodine level of 200 primary school children aged 6–12 years who were selected by using the multistage sampling technique. The study used an interview-administered questionnaire and checklists to collect data from the respondents. Data were entered to EpiData version 3.1 and exported to SPSS version 22.0 for analysis. Bivariable and multivariable analyses were conducted, and statistical significance was declared at p value ≤0.05. Results The median urinary iodine concentration of the children was 146 µg/L, and 31% had median urinary iodine concentration below the acceptable level (<100 µg/L). Female sex (adjusted odds ratio [AOR]=3.12, 95% CI: 1.52, 6.39), family size ≥5 (AOR=2.24, 95% CI: 1.06, 4.75), having no awareness of a balanced diet (AOR=3.25, 95% CI: 1.37, 7.71), and cabbage consumption ≥2 times per week (AOR=3.01, 95% CI: 1.31, 6.93) were the significant associated factors. Conclusion and recommendation Ethiopia is implementing the universal iodization of salt. However, urinary iodine deficiency and utilization of inadequately iodized salt were high in the study area. Therefore, the health sectors of the study site should disseminate messages to increase the awareness on iodized salt, iodine-rich foods, and goiterogens.
Measuring the Correlation of Personal Identity Documents in Structured Format

Personal identity documents play a major role in every citizen’s life and the authorities responsible for validating them typically require human intervention to manually crosscheck multiple documents belonging to an individual. The world is rapidly replacing physical documents with digital documents where every piece of data is stored digitally in a machine-readable and structured format. In this paper, we describe a technique to extract identity data from a structured data format and calculate a normalized correlation score for personal identity documents. Experimental results show that the proposed technique effectively calculates the correlation score for personal identity documents.
New Molecular Technologies for Minimal Residual Disease Evaluation in B-Cell Lymphoid Malignancies

The clearance of malignant clonal cells significantly correlates with clinical outcomes in many hematologic malignancies. Accurate and high throughput tools for minimal residual disease (MRD) detection are needed to overcome some drawbacks of standard molecular techniques; such novel tools have allowed for higher sensitivity analyses and more precise stratification of patients, based on molecular response to therapy. In this review, we depict the recently introduced digital PCR and next-generation sequencing technologies, describing their current application for MRD monitoring in lymphoproliferative disorders. Moreover, we illustrate the feasibility of these new technologies to test less invasive and more patient-friendly tissues sources, such as “liquid biopsy”.
Propofol-induced vasodilation of mesenteric arterioles via BKCa channel and gap junction

The present study aimed to investigate the role of propofol in mediating the vasomotor activity of the mesenteric arteriole (MA) of Sprague Dawley (SD) rats, and to elucidate the underlying mechanisms. The pressure myograph technique was used to examine the effect of different concentrations of propofol on the relaxation of blood vessels in the 2–3 mm MA segments freshly separated from the SD rats. The whole-cell patch-clamp technique was applied to observe the outward current of single vascular smooth muscle cells (VSMCs) obtained from the MAs of the SD rats. Furthermore, immunofluorescence was utilized to assess the expression of connexin (Cx) in the MAs of SD rats. The results indicated the following: i) Propofol relaxed the MA of SD rats in a concentration-dependent manner from 1×10−7 to 3×10−4 mol/l; ii) in the acutely dissociated VSMCs, propofol (1×10−7 to 3×10−4 mol/l) enhanced the outward current of VSMCs in a concentration-dependent manner; iii) the enhanced outward currents induced by propofol (1×10−5 mol/l) may be reversed by tetraethylammonium (TEA; 1 mmol/l), a calcium-activated K+ channel inhibitor; iv) the effect of propofol on the relaxation of the vasculature wAS reduced after perfusion with 1 mmol/l TEA; v) Cx40, Cx43 and Cx45 were expressed on the MA; 6) 18β-glycyrrhetintic acid and 2-aminoethoxydiphenyl borate, two types of gap junction blocker, inhibited the propofol-induced relaxation. The present study provides evidence that propofol relaxes the MA, which may be associated with its effect of enhancing the channel current of large-conductance calcium voltage-activated potassium channels, contributing to the K+ outflow and leading to VSMC hyperpolarization; the gap junction may facilitate the hyperpolarization, which may lead to vascular synchronized relaxation and thereby reduce the blood pressure.
Structural basis for cooperative regulation of KIX-mediated transcription pathways by the HTLV-1 HBZ activation domain

Significance The human T cell leukemia virus I basic leucine zipper protein (HBZ) plays a central role in leukemogenesis and proliferation of transformed adult T cell leukemia cells. Through its interactions with the KIX domain of the transcriptional coactivators CBP and p300, HBZ deregulates transcriptional programs involved in hematopoietic differentiation. Here, we describe the crystal structure of the ternary complex formed between KIX and the activation domains of HBZ and the cellular transcription factor c-Myb. By binding to KIX to form the ternary complex, HBZ allosterically stabilizes the interaction between KIX and c-Myb. These studies provide molecular insights into the mechanism by which HBZ interferes with hematopoietic signaling pathways and promotes T cell proliferation. The human T cell leukemia virus I basic leucine zipper protein (HTLV-1 HBZ) maintains chronic viral infection and promotes leukemogenesis through poorly understood mechanisms involving interactions with the KIX domain of the transcriptional coactivator CBP and its paralog p300. The KIX domain binds regulatory proteins at the distinct MLL and c-Myb/pKID sites to form binary or ternary complexes. The intrinsically disordered N-terminal activation domain of HBZ (HBZ AD) deregulates cellular signaling pathways by competing directly with cellular and viral transcription factors for binding to the MLL site and by allosterically perturbing binding of the transactivation domain of the hematopoietic transcription factor c-Myb. Crystal structures of the ternary KIX:c-Myb:HBZ complex show that the HBZ AD recruits two KIX:c-Myb entities through tandem amphipathic motifs (L/V)(V/L)DGLL and folds into a long α-helix upon binding. Isothermal titration calorimetry reveals strong cooperativity in binding of the c-Myb activation domain to the KIX:HBZ complex and in binding of HBZ to the KIX:c-Myb complex. In addition, binding of KIX to the two HBZ (V/L)DGLL motifs is cooperative; the structures suggest that this cooperativity is achieved through propagation of the HBZ α-helix beyond the first binding motif. Our study suggests that the unique structural flexibility and the multiple interaction motifs of the intrinsically disordered HBZ AD are responsible for its potency in hijacking KIX-mediated transcription pathways. The KIX:c-Myb:HBZ complex provides an example of cooperative stabilization in a transcription factor:coactivator network and gives insights into potential mechanisms through which HBZ dysregulates hematopoietic transcriptional programs and promotes T cell proliferation.
A Hybrid Bi-LSTM-CRF model for Knowledge Recognition from eHealth documents

In this work, we describe a Deep Learning architecture for Named Entity Recognition (NER) in biomedical texts. The architecture has two bidirectional Long Short-Term Memory (LSTM) layers and a last layer based on Conditional Random Field (CRF). Our system obtained the first place in the subtask A (identification) of TASS-2018-Task 3 eHealth Knowledge Discovery, with an F1 of 87.2%.
Enhanced Ant Colony Optimization with Local Search

The ant colony optimization (ACO) algorithm frequently gets trapped around local optimum solutions and does not approach the global optimum solution of vehicle routing problem. This work attempts to remedy this drawback by modifying the ant system (AS) algorithm, an instance of ACO. The modification includes a new method of route construction, new weight for improving the pheromone density of each route, and introduction of SA to improve the quality of the solutions from local search. It is called an enhanced ant colony optimization with local search or EACOL. A performance test was performed on EACOL on 10 standard datasets comparing it to those of the ant system algorithm and elitist ant system, and the results show that the proposed algorithm performs better than these two algorithms on these datasets.
Level-wise Segment Parser for Semantic Role Labelling for Myanmar Text

The semantic role labelling plays a key role to extract semantic information from language text for the purpose of information retrieval, text summarization, plagiarism test, etc. This paper presents an improved semantic role labelling approach for Myanmar Text using level-wise segmented parser. It works on parsing the arguments of a sentence from small words into combination of text chucks in the form of suitable arguments to be able to express the semantic meaning of that sentence. In labeling, different forms of segmented text phrases are considered, and it is affordable to categorize different relationship types of segmented Myanmar Text phrases such as core, non-core, etc. The proposed system is trained on roughly 70,000 words with 3000 hand-annotated semantic information for general domain. This system is tested with untrained domains in order to test efficiency of our labelling ability for semantic roles. According to the experiment results, we achieve better results than other semantic role labelers of Myanmar Text.
Telehealth for patients with chronic obstructive pulmonary disease (COPD): a systematic review and meta-analysis protocol

Introduction Chronic obstructive pulmonary disease (COPD) is a highly prevalent chronic disease characterised by persistent respiratory symptoms. A focus of COPD interventional studies is directed towards prevention of exacerbations leading to hospital readmissions. Telehealth as a method of remote patient monitoring and care delivery may be implemented to reduce hospital readmissions and improve self-management of disease. Prior reviews have not systematically assessed the efficacies of various telehealth functionalities in patients with COPD at different stages of disease severity. We aim to evaluate which COPD telehealth interventions, classified by their functionalities, are most effective in improving patient with COPD management measured by both clinical and resource utilisation outcomes. Methods and analysis We will conduct a systematic review which will include randomised controlled trials comparing the efficacy of telehealth interventions versus standard care in patients with COPD with confirmed disease severity based on forced expiratory volume(%) levels. An electronic search strategy will be used to identify trials published since 2000 in MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, CINHAL. Telehealth is described as remote monitoring and delivery of care where patient data/clinical information is routinely or continuously collected and/or processed, presented to the patient and transferred to a clinical care institution for feedback, triage and intervention by a clinical specialist. Two authors will independently screen articles for inclusion, assess risk of bias and extract data. We will merge studies into a meta-analysis if the interventions, technologies, participants and underlying clinical questions are homogeneous enough. We will use a random-effects model, as we expect some heterogeneity between interventions. In cases where a meta-analysis is not possible, we will synthesise findings narratively. We will assess the quality of the evidence for the main outcomes using GRADE. Ethics and Dissemination Research ethics approval is not required. The findings will be disseminated through publication in a peer-reviewed journal. PROSPERO registration number CRD42018083671.
Classification Performances Of Data Mining Clustering Algorithms For Remotely Sensed Multispectral Image Data

This study compares classification algorithm performances of data mining clustering algorithms for remotely sensed multispectral image data using WEKA data mining software. Clustering algorithm selection is very important for data mining classification method based clustering. The class attribute for remotely sensed multispectral image data is obtained from six different clustering algorithms for classification. Classification algorithm performances computed depending on the data labeling of six different clustering algorithms in terms of correctly classified instances and kappa statistics for seven different classification algorithms.A strategy is developed for selecting the best unsupervised clustering algorithm, among different clustering algorithms, giving the highest supervised classification accuracy in terms of correctly classified instances and kappa statistics for semi-supervised classification of remotely-sensed multispectral image data. The performances of seven semi-supervised classification methods assessed depending on six different unsupervised clustering algorithms for supervised classification of remotely sensed multispectral image data. This study determines data free clustering algorithms for classification.
Automated Inter-artefact Traceability Establishment for DevOps Practice

Software traceability is an important aspect in DevOps based software development environments. DevOps practices connect the development level and operational level software artefacts with frequent updates. Consequently, traceability management of the artefacts is essential to avoid the conflicts and inconsistencies during the continuous deployment activities. This paper addresses traceability establishment throughout the entire software development, considering both development and operational level artefacts. In this work, we have extended our previously developed SAT-Analyser traceability tool by establishing traceability between artefacts in source code, unit test scripts and build scrips. The accuracy of the traceability link establishment is evaluated using centrality-based network analysis techniques. The statistical results show an average of 71% accuracy.
“I knew that, I was just testing you”

Research has shown that participants often engage in impression management (IM) to present themselves in a favorable way, out of desire to increase self-esteem or enhance how others perceive them. This tendency has also been shown to affect the validity and reliability of studies. Yet, little is known about how older adults’ IM efforts influence the process of usability studies, even though the literature suggests that individuals perform more IM as they age, possibly to avoid negative stereotypes of ageing. Through a mixed-methods approach, we conducted two exploratory usability studies with older adults (65+). We found that participants performed a range of IM tactics including supplication (i.e., portraying oneself as weak or dependent to obtain help) and exemplification (i.e., doing more than is necessary). We discuss how IM tactics influence the study and define strategies to manage them.
Risk of relapse in clients with alcohol dependence syndrome in a tertiary care hospital

Alcoholism is one of the major health problems seen all over the world. The risk of relapse was estimated among 94 clients with alcohol dependence syndrome (ADS) who attended both in- and out-patient units of a tertiary care hospital. The tools used were the sociodemographic and clinical variables, Clinical Institute of Withdrawal Assessment Alcohol–revised (CIWA–Ar), Alcohol Use Disorder Identification Test (AUDIT), and Advanced Warning of Relapse (AWARE) scale. Out of the 94 clients, 63 (67.7%) were in the low-risk group for getting relapse, 26 (27.7%) were in the moderate-risk group, and 5 (5.3%) were in the high-risk group. Family history of alcohol use was significantly associated with the AWARE score (P < 0.05). Nicotine use was reported by 56 (59.6%) clients. Clients with a positive family history of alcohol use, disturbed sleep pattern, and higher total score (>20) of AUDIT scale were at higher risk of relapse.
Dynamic Modular Modeling of Smart Loads Associated With Electric Springs and Control

Smart loads associated with electric springs (ES) have been used for fast demand-side management for smart grid. While simplified dynamic ES models have been used for power system simulation, these models do not include the dynamics of the power electronic circuits and control of the ES. This paper presents a dynamic and modular ES model that can incorporate the controller design and the dynamics of the power electronic circuits. Based on experimental measurements, the order of this dynamic model has been reduced so that the model suits both circuit and system simulations. The model is demonstrated with the radial-chordal decomposition controller for both voltage and frequency regulation. The modular approach allows the circuit and controller of the ES model and the load module to be combined in the d–q frame. Experimental results based on single and multiple smart loads setup are provided to verify the results obtained from the model simulation. Then, the ES model is incorporated into power system simulations including an IEEE 13 node power system and a three-phase balanced microgrid system.
Validation and Opportunities of Electrocardiographic Imaging: From Technical Achievements to Clinical Applications

Electrocardiographic imaging (ECGI) reconstructs the electrical activity of the heart from a dense array of body-surface electrocardiograms and a patient-specific heart-torso geometry. Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant arrhythmias and other electrophysiological quantities of interest. Importantly, these quantities are directly and non-invasively reconstructed in a digitized model of the patient’s three-dimensional heart, which has led to clinical interest in ECGI’s ability to personalize diagnosis and guide therapy. Despite considerable development over the last decades, validation of ECGI is challenging. Firstly, results depend considerably on implementation choices, which are necessary to deal with ECGI’s ill-posed character. Secondly, it is challenging to obtain (invasive) ground truth data of high quality. In this review, we discuss the current status of ECGI validation as well as the major challenges remaining for complete adoption of ECGI in clinical practice. Specifically, showing clinical benefit is essential for the adoption of ECGI. Such benefit may lie in patient outcome improvement, workflow improvement, or cost reduction. Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. We propose ‘best’ practices for technical validation and highlight collaborative efforts recently organized in this field. Continued interaction between engineers, basic scientists, and physicians remains essential to find a hybrid between technical achievements, pathological mechanisms insights, and clinical benefit, to evolve this powerful technique toward a useful role in clinical practice.
Towards Large-Scale Video Video Object Mining

We propose to leverage a generic object tracker in order to perform object mining in large-scale unlabeled videos, captured in a realistic automotive setting. We present a dataset of more than 360'000 automatically mined object tracks from 10+ hours of video data (560'000 frames) and propose a method for automated novel category discovery and detector learning. In addition, we show preliminary results on using the mined tracks for object detector adaptation.
Low-Complexity Multiuser MIMO Precoder Design Under Per-Antenna Power Constraints

A new precoder design method is proposed for multi-input multioutput (MIMO) systems with per-antenna power constraints (PAPCs). In the proposed scheme, the optimal zero-forcing (ZF) based precoder maximizing the sum rate is evaluated for MIMO systems under the conventional sum power constraint (SPC), after which a new ZF-based precoder conforming to the PAPCs is designed by finding the linear precoder closest to the optimal ZF-based SPC precoder. Using the proposed design procedure, we derive an iterative algorithm based on the modified Newton's method to construct a PAPC precoder for a multiuser MIMO system. The complexity order of the proposed method is compared with those of the existing precoding schemes, and it is shown through numerical simulations that the proposed PAPC precoder achieves near-optimal performance while reducing the power consumption at macrocell base stations.