Miracle-dz/UniFAR-FTUs huggingface dataset:
A Social-Based Approach to Mobile Edge Computing

Mobile Edge Computing (MEC) opens to the opportunity of moving high-volumes of data from the cloud to locations where the information is actually accessed. In turn, the combination of MEC with the Mobile Crowdsensing approach, using a restricted number of devices with respect the number of base stations, matches the performance of the conventional MEC middleware layer ensuring the same spatial coverage. In this work, we envision a MEC architecture composed by mobile and fixed edges. Their goal is to optimize the share of contents among users by exploiting their mobility and sociality. We first present an algorithm to identify a suitable set of mobile edges and we show how such selection increases the performance of a content-sharing scenario. Our experiments are based on the ParticipAct dataset, which captures the mobility of about 170 users for 10 months. The experiments show that the number of requests that can be served mobile edges is similar to that of requests served by fixed edges, and then that mobile edges can be considered a viable (and lowcost) alternative to fixed edges.
The Influence of pH, NaCl, and the Deacidifying Yeasts Debaryomyces hansenii and Kluyveromyces marxianus on the Production of Pigments by the Cheese-Ripening Bacteria Arthrobacter arilaitensis

Arthrobacter arilaitensis is a food-related bacterial species under investigation for its involvement in the coloration of surface-ripened cheeses. Presently, information about this species in association with the development of appropriate cheese coloration is still lacking. This study was performed in order to investigate—with the use of spectrocolorimetry—the influence of pH, NaCl, and deacidifying yeasts on the pigmentation of Arthrobacter arilaitensis biofilms. Three types of cheese-based (curd) solid media were prepared by using different deacidification methods: (i) chemical deacidification by NaOH (CMNaOH); (ii) biological deacidification by the yeast strain Debaryomyces hansenii 304 (CMDh304); and (iii) biological deacidification by the yeast strain Kluyveromyces marxianus 44 (CMKm44). Each medium was prepared with initial pH values of 5.8, 7.0, and 7.5. After pasteurization, agar was incorporated and NaCl was added in varying concentrations (0%, 2%, 4%, and 8% (w/v)). A. arilaitensis Po102 was then inoculated on the so prepared “solid-curd” media, and incubated at 12 °C under light conditions for 28 days. According to the data obtained by spectrocolorimetry in the Compagnie Internationale de l’Eclairage (CIE) L*a*b* color system, all controlled factors appeared to affect the pigments produced by the A. arilaitensis strain. NaCl content in the media showed distinct inhibitory effects on the development of color by this strain when the initial pH was at 5.8. By contrast, when the initial pH of the media was higher (7.0, 7.5), only the highest concentration of NaCl (8%) had this effect, while the coloring capacity of this bacterial species was always higher when D. hansenii 304 was used for deacidification compared to K. marxianus 44.
The Price of Uncertain Priors in Source Coding

We consider the problem of one-way communication when the recipient does not know exactly the distribution that the messages are drawn from, but has a <italic>“prior”</italic> distribution that is known to be close to the source distribution, a problem first considered by Juba <italic>et al.</italic> We consider the question of how much longer the messages need to be in order to cope with the uncertainty about the receiver’s prior and the source distribution, respectively, as compared with the standard source coding problem. We consider two variants of this uncertain priors problem: the original setting of Juba <italic>et al.</italic> in which the receiver is required to correctly recover the message with probability 1, and a setting introduced by Haramaty and Sudan, in which the receiver is permitted to fail with some probability <inline-formula> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>. In both settings, we obtain lower bounds that are tight up to logarithmically smaller terms. In the latter setting, we furthermore present a variant of the coding scheme of Juba <italic>et al.</italic> with an overhead of <inline-formula> <tex-math notation="LaTeX">$\log \alpha +\log 1/\epsilon +1$ </tex-math></inline-formula> bits, thus also establishing the nearly tight upper bound.
Oracles for Testing Software Timeliness with Uncertainty

Uncertainty in timing properties (e.g., detection time of external events) is a common occurrence in embedded software systems, since these systems interact with complex physical environments. Such time uncertainty leads to non-determinism. For example, time-triggered operations may either generate different valid outputs across different executions or experience failures (e.g., results not being generated in the expected time window) that occur only occasionally over many executions. For these reasons, time uncertainty makes the generation of effective test oracles for timing requirements a challenging task. To address the above challenge, we propose Stochastic Testing with Unique Input Output Sequences, an approach for the automated generation of stochastic oracles that verify the capability of a software system to fulfill timing constraints in the presence of time uncertainty. Such stochastic oracles entail the statistical analysis of repeated test case executions based on test output probabilities predicted by means of statistical model checking. Results from two industrial case studies in the automotive domain demonstrate that this approach improves the fault detection effectiveness of tests suites derived from timed automata compared to traditional approaches.
Connectivity of the Human Number Form Area Reveals Development of a Cortical Network for Mathematics

The adult brain contains cortical areas thought to be specialized for the analysis of numbers (the putative number form area, NFA) and letters (the visual word form area, VWFA). Although functional development of the VWFA has been investigated, it is largely unknown when and how the NFA becomes specialized and connected to the rest of the brain. One hypothesis is that NFA and VWFA derive their special functions through differential connectivity, but the development of this differential connectivity has not been shown. Here, we mapped the resting state connectivity of NFA and VWFA to the rest of the brain in a large sample (n = 437) of individuals (age 3.2–21 years). We show that within NFA-math network and within VWFA-reading network the strength of connectivity increases with age. The right NFA is significantly connected to the right intraparietal cortex already at the earliest age tested (age 3), before formal mathematical education has begun. This connection might support or enable an early understanding of magnitude or numerosity In contrast, the functional connectivity from NFA to the left anterior intraparietal cortex and to the right dorsolateral prefrontal cortex is not different from the functional connectivity of VWFA to these regions until around 12–14 years of age. The increase in connectivity to these regions was associated with a gradual increase in mathematical ability in an independent sample. In contrast, VWFA connects significantly to Broca’s region around age 6, and this connectivity is correlated with reading ability. These results show how the differential connectivity of the networks for mathematics and reading slowly emerges through years of training and education.
CNN based Sentence Classification with Semantic Features using Word Clustering

Text classification is one of the natural language processing (NLP) methods that assigns texts to one or more categories. In this paper, we propose a text classification method based on deep neural networks and word clustering. We also provide analysis on the effects of the number of channels, the way of converting the cluster information to a vector, and the update method of the input channel during learning with baseline. To show the effectiveness of our approach, we apply the method to the TREC question dataset and Movie Review dataset. From the results, we confirm that semantic features from word clustering is able to increase the classification accuracy by 1.96%.
Systematic review and meta-analysis of third-line salvage therapy for the treatment of advanced non-small-cell lung cancer: A meta-analysis of randomized controlled trials

Purpose We performed a systematic review and meta-analysis to investigate the efficacy of third-line treatment for advanced non-small-cell lung cancer (NSCLC). Materials and Methods Relevant trials were identified by searching electronic databases and conference meetings. Prospective randomized controlled trials (RCTs) assessing third-line therapy in advanced NSCLC patients were included. Outcomes of interest included overall survival (OS) and progression-free survival (PFS). Results A total of 1,985 advanced NSCLC patients received third-line treatment from 11 RCTs were included for analysis. The use of single targeted agent as third-line therapy for advanced NSCLC did not significantly improved PFS (HR 0.75, 95% CI: 0.28–2.04, p = 0.58) and OS (HR 1.01, 95% CI: 0.86–1.17, p = 0.95) when compared to docetaxel alone. In addition, erlotinib-based doublet combination therapy did not significantly improved PFS (HR 0.94, 95% CI: 0.78–1.13, p = 0.49) and OS (HR 1.08, 95% CI: 0.78–1.51, p = 0.65) in comparison with erlotinib alone. Conclusions The findings of this study show that the efficacy of single novel targeted agent is comparable to that of docetaxel alone in terms of PFS and OS for heavily pretreated NSCLC patients. In addition, no survival benefits are obtained from erlotinib-based doublet therapy, thus single agent erlotinib could be recommended as third-line treatment for unselected advanced NSCLC patients.
Modelling, Design and Optimization of Dependable Softwarized Networks for Industrial Applications

The recent trend of Industry 4.0 promotes the concepts of "industrial internet and digital factory", which requires the transformation of local industrial networks, as well as wide area networks carrying industrial traffic. Softwarized network architectures, i.e., Software Defined Networking (SDN) and Network Function Virtualization (NFV), can aid this transition by providing a fine grained network traffic control and high degree of programmability, with open standards and protocol stack. While first studies and prototypes have demonstrated the feasibility of SDN/NFV based networks, a comprehensive study of dependability of softwarized networks is still missing in state of the art literature. Recent studies on reliability in softwarzed network have focused mainly on the network failures, while the reliability of software functions has been widely overlooked or oversimplified. Our research aims to close this gap, by providing the contribution in three following areas: i) evaluation and forecasting of the reliability of control plane functions, ii) characterization of failure dynamics between control and data plane, and iii) design of robust wide area networks in the presence of software and network failures.
Offline consolidation supersedes prior knowledge benefits in children's (but not adults') word learning.

Prior linguistic knowledge is proposed to support the acquisition and consolidation of new words. Adults typically have larger vocabularies to support word learning than children, but the developing brain shows enhanced neural processes that are associated with offline memory consolidation. This study investigated contributions of prior knowledge to initial word acquisition and consolidation at different points in development, by teaching children and adults novel words (e.g., ballow) that varied in the number of English word-form "neighbours" (e.g., wallow, bellow). Memory for the novel word-forms was tested immediately after training, the next day and 1 week later, to assess the time-course of prior knowledge contributions. Children aged 7-9 years (Experiments 1, 3) and adults (Experiment 2) recalled words with neighbours better than words without neighbours when tested immediately after training. However, a period of offline consolidation improved overall recall and reduced the influence of word-form neighbours on longer term memory. These offline consolidation benefits were larger in children than adults, supporting theories that children have a greater propensity for consolidating phonologically distinctive language information. Local knowledge of just a single word-form neighbour was enough to enhance learning, and this led to the individual differences in word recall that were related to adults' global vocabulary ability. The results support the proposal that the relative contributions of different learning mechanisms change across the lifespan, and highlight the importance of testing theoretical models of word learning in the context of development.
Influence of N-glycosylation on effector functions and thermal stability of glycoengineered IgG1 monoclonal antibody with homogeneous glycoforms

ABSTRACT Glycosylation of the conserved asparagine residue in each heavy chain of IgG in the CH2 domain is known as N-glycosylation. It is one of the most common post-translational modifications and important critical quality attributes of monoclonal antibody (mAb) therapeutics. Various studies have demonstrated the effects of the Fc N-glycosylation on safety, Fc effector functions, and pharmacokinetics, both dependent and independent of neonatal Fc receptor (FcRn) pathway. However, separation of various glycoforms to investigate the biological and functional relevance of glycosylation is a major challenge, and existing studies often discuss the overall impact of N-glycans, without considering the individual contributions of each glycoform when evaluating mAbs with highly heterogeneous distributions. In this study, chemoenzymatic glycoengineering incorporating an endo-β-N-acetylglucosaminidase (ENGase) EndoS2 and its mutant with transglycosylation activity was used to generate mAb glycoforms with highly homogeneous and well-defined N-glycans to better understand and precisely evaluate the effect of each N-glycan structure on Fc effector functions and protein stability. We demonstrated that the core fucosylation, non-reducing terminal galactosylation, sialylation, and mannosylation of IgG1 mAb N-glycans impact not only on FcγRIIIa binding, antibody-dependent cell-mediated cytotoxicity, and C1q binding, but also FcRn binding, thermal stability and propensity for protein aggregation.
Complex sternal and rib reconstruction with allogeneic material

Sternal malunion, or loss, developed after a median sternotomy cannot only be difficult to manage and treat, but also may diminish one’s quality-of-life drastically. The technique presented here represents a multispecialty approach in one stage for the reconstruction of an unstable thoracic cage. The procedure utilized a donated sternum and ribs. The sternum with ribs harvested from a single donor included adipose derived stromal vascular fraction (ADSVF) cells with marrow also from the same donor. Autologous muscle flaps, stabilized with acellular dermal matrix were utilized to provide a robust blood supply to the ADSVF cells and bone grafts. Acellular dermal matrix was used to construct the ribs and stabilize the plugs of stem cells and bone. These procedures, in the hands of multispecialty physicians, have led to several successful reconstructions involving complex chest wall deformities. This surgical intervention was performed in a one stage operation. This represents the first successful complete sternal transplant in a patient with return to normal activities and increased quality-of-life.
A Positioning Accuracy Enhancement Method Based on Inter-Vehicular Communication and Self-Organizing Map

Traditional low-cost GPS installed on vehicles and other equipment has a tolerance of tens of meters. With the help of auxiliary devices and/or methodologies such as Differential GPSs (DGPSs), Assisted GPSs (AG-PSs), Real-Time Kinematic (RTK), computer vision and etc., the positioning accuracy of GPS receivers increased a lot, but a certain amount of cost increased at the same time. In this paper, we propose a new cooperative vehicular localization scheme for improving the accuracy of GPS fixes based on Vehicle-to-vehicle (V2V) communication. The proposed scheme first estimates the distances between neighboring vehicles using WLS-DD scheme [1] and uses a machine learning technique called Constrained Self-Organizing Map (C-SOM) with a set of GPS fixes collected over time to generate the final estimates of GPS locations with much lower errors. We present simulation results that demonstrate the superior performance of the proposed Constrained-SOM.
Pneumonia Detection in Chest Radiographs

In this work, we describe our approach to pneumonia classification and localization in chest radiographs. This method uses only \emph{open-source} deep learning object detection and is based on CoupleNet, a fully convolutional network which incorporates global and local features for object detection. Our approach achieves robustness through critical modifications of the training process and a novel ensembling algorithm which merges bounding boxes from several models. We tested our detection algorithm tested on a dataset of 3000 chest radiographs as part of the 2018 RSNA Pneumonia Challenge; our solution was recognized as a winning entry in a contest which attracted more than 1400 participants worldwide.
Imaging findings of gastric calcifying fibrous tumour

Calcifying fibrous tumours (CFTs) are rare benign lesions that usually affect the soft tissues, the mesentery and the peritoneum. Gastric CFT is particularly rare. Here, we report a CFT found incidentally in a 31-year-old male. The mass was well circumscribed and showed partial calcification on the CT scan, with dark signal intensity seen on T2 weighted MRI. To the best of our knowledge, there is very limited published information concerning imaging findings of CFTs. We discuss the CT scan and MRI findings of this patient, which can be considered typical for gastric CFT, and present a review of the limited literature available.
Instrumented Wireless SmartInsole System for Mobile Gait Analysis: A Validation Pilot Study with Tekscan Strideway

A SmartInsoles Cyber-Physical System (CPS) is designed and implemented for the purpose of measuring gait parameters of multiple users in a restriction-free environment. This CPS comprises a master software installed on a computer and numerous multi-sensory health devices in the form of smart insoles. Each of these insoles contains 12 Force-Sensitive Resistor (FSR) sensors, an Inertial Measurement Unit (IMU), a WiFi-enabled microcontroller and a battery to power all components. A validation pilot study was completed in collaboration with the Interdisciplinary School of Health Sciences at the University of Ottawa by performing 150 trials on 15 healthy subjects. Each subject performed 10 walks on the Tekscan Strideway gait mat system, while simultaneously wearing the designed SmartInsoles CPS. Spatiotemporal data for over 450 unique steps were collected by both systems. These data were analyzed carefully, and a thorough comparison was performed between the results from the two systems. Seven parameters were analyzed in this study: stride time, stance time, swing time, double support time, step time, cadence and gait time. Detailed results in the form of tables, scatterplots, histograms and Bland–Altman graphs were generated. Analysis of the results shows high agreement between the values of the two systems and suggests high accuracy of the implemented CPS as a multi-device, multi-sensory system for gait measurement and analysis.
Omalizumab treatment in a 12 year-old girl with chronic spontaneous urticaria

Abstract Background: Omalizumab is a recombinant humanized IgG monoclonal antibody, which binds the Fc region of free IgE prevent its binding to its high-affinity receptor (FcεR1) on mast cells and basophils. Omalizumab was approved as add-on therapy for moderate-to-severe persistent allergic asthma and for patients with chronic spontaneous urticaria resistant to antihistamine treatment. Patient and results: This article reports effective and safe treatment of a 12 years old girl with add-on omalizumab. On an initial dose of omalizumab of 300 mg once every 4 weeks, the patient experienced resolution of symptoms to a degree that exceeded the effect of previous treatments. Conclusion: Convincing evidence in support of the efficacy and safety of Omalizumab in the treatment of CSU in adolescent has accumulated over the past few years.
A comprehensive overview on osteoporosis and its risk factors

Osteoporosis is a bone disorder with remarkable changes in bone biologic material and consequent bone structural distraction, affecting millions of people around the world from different ethnic groups. Bone fragility is the worse outcome of the disease, which needs long term therapy and medical management, especially in the elderly. Many involved genes including environmental factors have been introduced as the disease risk factors so far, of which genes should be considered as effective early diagnosis biomarkers, especially for the individuals from high-risk families. In this review, a number of important criteria involved in osteoporosis are addressed and discussed.
The Plant Circadian Clock and Chromatin Modifications

The circadian clock is an endogenous timekeeping network that integrates environmental signals with internal cues to coordinate diverse physiological processes. The circadian function depends on the precise regulation of rhythmic gene expression at the core of the oscillators. In addition to the well-characterized transcriptional feedback regulation of several clock components, additional regulatory mechanisms, such as alternative splicing, regulation of protein stability, and chromatin modifications are beginning to emerge. In this review, we discuss recent findings in the regulation of the circadian clock function in Arabidopsis thaliana. The involvement of chromatin modifications in the regulation of the core circadian clock genes is also discussed.
Controlling the Gatekeeper: Therapeutic Targeting of Nuclear Transport

Nuclear transport receptors of the karyopherin superfamily of proteins transport macromolecules from one compartment to the other and are critical for both cell physiology and pathophysiology. The nuclear transport machinery is tightly regulated and essential to a number of key cellular processes since the spatiotemporally expression of many proteins and the nuclear transporters themselves is crucial for cellular activities. Dysregulation of the nuclear transport machinery results in localization shifts of specific cargo proteins and associates with the pathogenesis of disease states such as cancer, inflammation, viral illness and neurodegenerative diseases. Therefore, inhibition of the nuclear transport system has future potential for therapeutic intervention and could contribute to the elucidation of disease mechanisms. In this review, we recapitulate clue findings in the pathophysiological significance of nuclear transport processes and describe the development of nuclear transport inhibitors. Finally, clinical implications and results of the first clinical trials are discussed for the most promising nuclear transport inhibitors.