Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic properties of composite cores made of nanocrystalline material for high frequency inductors and transformers

By choosing parameters of production process of magnetic powder core (MPC), it is possible to develop magnetic properties of cores and match them to specific application. This paper shows how the size of granular material can impact the magnetic characteristics of powder cores. Particular attention is paid to high frequency inductance elements, made of nanocrystalline powder, like inductors, chokes and transformers. Advantages of this components are: stable relative permeability pr, low specific power loss P, and possibility to develop a wide range of other magnetic parameters.
Linear Lepidopteran ambidensovirus 1 sequences drive random integration of a reporter gene in transfected Spodoptera frugiperda cells

Background The Lepidopteran ambidensovirus 1 isolated from Junonia coenia (hereafter JcDV) is an invertebrate parvovirus considered as a viral transduction vector as well as a potential tool for the biological control of insect pests. Previous works showed that JcDV-based circular plasmids experimentally integrate into insect cells genomic DNA. Methods In order to approach the natural conditions of infection and possible integration, we generated linear JcDV-gfp based molecules which were transfected into non permissive Spodoptera frugiperda (Sf9) cultured cells. Cells were monitored for the expression of green fluorescent protein (GFP) and DNA was analyzed for integration of transduced viral sequences. Non-structural protein modulation of the VP-gene cassette promoter activity was additionally assayed. Results We show that linear JcDV-derived molecules are capable of long term genomic integration and sustained transgene expression in Sf9 cells. As expected, only the deletion of both inverted terminal repeats (ITR) or the polyadenylation signals of NS and VP genes dramatically impairs the global transduction/expression efficiency. However, all the integrated viral sequences we characterized appear “scrambled” whatever the viral content of the transfected vector. Despite a strong GFP expression, we were unable to recover any full sequence of the original constructs and found rearranged viral and non-viral sequences as well. Cellular flanking sequences were identified as non-coding ones. On the other hand, the kinetics of GFP expression over time led us to investigate the apparent down-regulation by non-structural proteins of the VP-gene cassette promoter. Conclusion Altogether, our results show that JcDV-derived sequences included in linear DNA molecules are able to drive efficiently the integration and expression of a foreign gene into the genome of insect cells, whatever their composition, provided that at least one ITR is present. However, the transfected sequences were extensively rearranged with cellular DNA during or after random integration in the host cell genome. Lastly, the non-structural proteins seem to participate in the regulation of p9 promoter activity rather than to the integration of viral sequences.
Robust adaptive control for robotic systems with input time-varying delay using Hamiltonian method

This paper addresses the problem of robust adaptive control for robotic systems with model uncertainty and input time-varying delay. The Hamiltonian method is applied to develop the stabilization results of the robotic systems. Firstly, with the idea of shaping potential energy and the pre-feedback skill, the n degree-of-freedom ( DOF ) uncertain robotic systems are realized as an augmented dissipative Hamiltonian formulation with delay. Secondly, based on the obtained Hamiltonian system formulation and by using of the Lyapunov-Krasovskii ( L-K ) functional method, an adaptive controller is designed to show that the robotic systems can be asymptotically stabilized depending on the input delay. Meanwhile, some sufficient conditions are spelt out to guarantee the rationality and validity of the proposed control law. Finally, study of an illustrative example with simulations shows that the controller obtained in this paper works very well in handling uncertainties and input delay in the robotic systems.
Advantages of eye-gaze over head-gaze-based selection in virtual and augmented reality under varying field of views

The current best practice for hands-free selection using Virtual and Augmented Reality (VR/AR) head-mounted displays is to use head-gaze for aiming and dwell-time or clicking for triggering the selection. There is an observable trend for new VR and AR devices to come with integrated eye-tracking units to improve rendering, to provide means for attention analysis or for social interactions. Eye-gaze has been successfully used for human-computer interaction in other domains, primarily on desktop computers. In VR/AR systems, aiming via eye-gaze could be significantly faster and less exhausting than via head-gaze. To evaluate benefits of eye-gaze-based interaction methods in VR and AR, we compared aiming via head-gaze and aiming via eye-gaze. We show that eye-gaze outperforms head-gaze in terms of speed, task load, required head movement and user preference. We furthermore show that the advantages of eye-gaze further increase with larger FOV sizes.
RTSense: Providing Reliable Trust-Based Crowdsensing Services in CVCC

CVCC has garnered significant attention in recent years as a special cloud computing platform capable of broadening network service provisioning in mobile computing. Vehicular crowdsensing is a prime candidate for CVCC applications as connected vehicles can provide tremendous sensing, computing, and storage resources. Truthfulness of sensing data is very important, as malicious vehicles may create inaccuracy in sensing results. In this work, we propose RTSense, which enables trust-based crowdsensing services in CVCC. The architecture divides the system into control and data planes, where the trust authority and service providers sit in the control plane, and vehicles and fogs exist in the data plane. We provide solutions for anonymous vehicle authentication, interactive filtering truth discovery, and trust management for reliable crowdsensing. The experimental analysis shows that RTSense can effectively segregate malicious and trustworthy vehicles. We also identify interesting future directions along with possible solutions.
Energy-Harvesting Wireless Sensor Networks (EH-WSNs)

Wireless Sensor Networks (WSNs) are crucial in supporting continuous environmental monitoring, where sensor nodes are deployed and must remain operational to collect and transfer data from the environment to a base-station. However, sensor nodes have limited energy in their primary power storage unit, and this energy may be quickly drained if the sensor node remains operational over long periods of time. Therefore, the idea of harvesting ambient energy from the immediate surroundings of the deployed sensors, to recharge the batteries and to directly power the sensor nodes, has recently been proposed. The deployment of energy harvesting in environmental field systems eliminates the dependency of sensor nodes on battery power, drastically reducing the maintenance costs required to replace batteries. In this article, we review the state-of-the-art in energy-harvesting WSNs for environmental monitoring applications, including Animal Tracking, Air Quality Monitoring, Water Quality Monitoring, and Disaster Monitoring to improve the ecosystem and human life. In addition to presenting the technologies for harvesting energy from ambient sources and the protocols that can take advantage of the harvested energy, we present challenges that must be addressed to further advance energy-harvesting-based WSNs, along with some future work directions to address these challenges.
Transcriptomics of the Vaccine Immune Response: Priming With Adjuvant Modulates Recall Innate Responses After Boosting

Transcriptomic profiling of the immune response induced by vaccine adjuvants is of critical importance for the rational design of vaccination strategies. In this study, transcriptomics was employed to profile the effect of the vaccine adjuvant used for priming on the immune response following re-exposure to the vaccine antigen alone. Mice were primed with the chimeric vaccine antigen H56 of Mycobacterium tuberculosis administered alone or with the CAF01 adjuvant and boosted with the antigen alone. mRNA sequencing was performed on blood samples collected 1, 2, and 7 days after priming and after boosting. Gene expression analysis at day 2 after priming showed that the CAF01 adjuvanted vaccine induced a stronger upregulation of the innate immunity modules compared with the unadjuvanted formulation. The immunostimulant effect of the CAF01 adjuvant, used in the primary immunization, was clearly seen after a booster immunization with a low dose of antigen alone. One day after boost, we observed a strong upregulation of multiple genes in blood of mice primed with H56 + CAF01 compared with mice primed with the H56 alone. In particular, blood transcription modules related to innate immune response, such as monocyte and neutrophil recruitment, activation of antigen-presenting cells, and interferon response were activated. Seven days after boost, differential expression of innate response genes faded while a moderate differential expression of T cell activation modules was appreciable. Indeed, immunological analysis showed a higher frequency of H56-specific CD4+ T cells and germinal center B cells in draining lymph nodes, a strong H56-specific humoral response and a higher frequency of antibody-secreting cells in spleen of mice primed with H56 + CAF01. Taken together, these data indicate that the adjuvant used for priming strongly reprograms the immune response that, upon boosting, results in a stronger recall innate response essential for shaping the downstream adaptive response.
Multiscale scanpath visualization and filtering

The analysis of eye-tracking data can be very useful when evaluating controlled user studies. To support the analysis in a fast and easy fashion, we have developed a web-based framework for a visual inspection of eye-tracking data and a comparison of scanpaths based on filtering of fixations and similarity measures. Concerning the first part, we introduce a multiscale aggregation of fixations and saccades based on a spatial partitioning that reduces visual clutter of overlaid scanpaths without changing the overall impression of large-scale eye movements. The multiscale technique abstracts the individual scanpaths and allows an analyst to visually identify clusters or patterns inherent to the gaze data without the need for lengthy precomputations. For the second part, we introduce an approach where analysts can remove fixations from a pair of scanpaths in order to increase the similarity between them. This can be useful to discover and understand reasons for dissimilarity between scanpaths, data cleansing, and outlier detection. Our implementation uses the MultiMatch algorithm to predict similarities after the removal of individual fixations. Finally, we demonstrate the usefulness of our techniques in a use case with scanpaths that were recorded in a study with metro maps.
DeCoST: A New Approach in Drug Repurposing From Control System Theory

In this paper, we propose DeCoST (Drug Repurposing from Control System Theory) framework to apply control system paradigm for drug repurposing purpose. Drug repurposing has become one of the most active areas in pharmacology since the last decade. Compared to traditional drug development, drug repurposing may provide more systematic and significantly less expensive approaches in discovering new treatments for complex diseases. Although drug repurposing techniques rapidly evolve from “one: disease-gene-drug” to “multi: gene, dru” and from “lazy guilt-by-association” to “systematic model-based pattern matching,” mathematical system and control paradigm has not been widely applied to model the system biology connectivity among drugs, genes, and diseases. In this paradigm, our DeCoST framework, which is among the earliest approaches in drug repurposing with control theory paradigm, applies biological and pharmaceutical knowledge to quantify rich connective data sources among drugs, genes, and diseases to construct disease-specific mathematical model. We use linear–quadratic regulator control technique to assess the therapeutic effect of a drug in disease-specific treatment. DeCoST framework could classify between FDA-approved drugs and rejected/withdrawn drug, which is the foundation to apply DeCoST in recommending potentially new treatment. Applying DeCoST in Breast Cancer and Bladder Cancer, we reprofiled 8 promising candidate drugs for Breast Cancer ER+ (Erbitux, Flutamide, etc.), 2 drugs for Breast Cancer ER- (Daunorubicin and Donepezil) and 10 drugs for Bladder Cancer repurposing (Zafirlukast, Tenofovir, etc.).
How to perform aggregometry and lumi-aggregometry in mouse platelets

Abstract Light transmission aggregometry and lumi-aggregometry are the gold standard platelet assays both clinically and for basic research. The availability of different strains of genetically modified mice and mouse models of human disease means that often laboratories need to use mouse platelets in these assays. Overall, performing aggregometry and lumi-aggregometry with mouse platelets is similar to with human platelets, although methods need be adapted to accommodate their small size, reduced blood volume, and different protein levels. This review aims to highlight these key considerations when planning aggregometry experiments with mouse platelets. These include the method of taking blood, including the use of anticoagulants, as well as the method of platelet preparation, and how to maximize yields. This review also covers how to maximize the number of aggregations that can be performed, both by understanding the minimum requirements of your aggregometer, or by considering new approaches. These include employing high throughput plate-based aggregometry (Optimul), or the use of TPO-mimetics to stimulate platelet production in mice to boost their platelet counts. Finally, phenotypic differences between mouse and human platelets, such as protein expression or sensitivity to agonists are discussed as an important consideration when planning experiments.
Remarkable Progress with Small-Molecule Modulation of TRPC1/4/5 Channels: Implications for Understanding the Channels in Health and Disease

Proteins of the TRPC family can form many homo- and heterotetrameric cation channels permeable to Na+, K+ and Ca2+. In this review, we focus on channels formed by the isoforms TRPC1, TRPC4 and TRPC5. We review evidence for the formation of different TRPC1/4/5 tetramers, give an overview of recently developed small-molecule TRPC1/4/5 activators and inhibitors, highlight examples of biological roles of TRPC1/4/5 channels in different tissues and pathologies, and discuss how high-quality chemical probes of TRPC1/4/5 modulators can be used to understand the involvement of TRPC1/4/5 channels in physiological and pathophysiological processes.
Spatial coefficient of variation in pseudo-continuous arterial spin labeling cerebral blood flow images as a hemodynamic measure for cerebrovascular steno-occlusive disease: A comparative 15O positron emission tomography study

Pseudo-continuous arterial spin labeling (pCASL) is a completely non-invasive method of cerebral perfusion measurement. However, cerebral blood flow (CBF) quantification is hampered by arterial transit artifacts characterized by bright vascular signals surrounded by decreased signals in tissue regions, which commonly appear in patients with reduced cerebral perfusion pressure. The spatial coefficient of variation (CoV) of pCASL CBF images has been proposed as an alternative region-of-interest (ROI)-based hemodynamic measure to predict prolonged arterial transit time (ATT). This retrospective study investigates the utility of spatial CoV by comparison with 15O positron emission tomography (PET). For patients with cerebrovascular steno-occlusive disease (n = 17), spatial CoV was positively correlated with ATT independently measured by pulsed arterial spin labeling (r = 0.597, p < 0.001), confirming its role as an ATT-like hemodynamic measure. Comparisons with 15O PET demonstrated that spatial CoV was positively correlated with vascular mean transit time (r = 0.587, p < 0.001) and negatively correlated with both resting CBF (r = −0.541, p = 0.001) and CBF response to hypercapnia (r = −0.373, p = 0.030). ROI-based spatial CoV calculated from single time-point pCASL can potentially detect subtle perfusion abnormalities in clinical settings.
The Hypoxic Tumor Microenvironment Promotes Invadopodia Formation and Metastasis through LPA1 Receptor and EGFR Cooperation

Hypoxia, a common feature of solid tumors, has been critically involved in cell invasion and metastasis, but the underlying mechanisms remain poorly understood. Previously, it has been observed that the lysophosphatidic acid receptor 4 (LPA4) signaling axis mediates production of the degradative subcellular structures invadopodia, which are known to be required for metastasis. Here, it is demonstrated that LPA1 (LPAR1) is a common and major receptor used for hypoxia-induced invadopodia production in various cancer cell lines. The widespread use of LPA1 was not due to increased LPA1 expression but rather relied on Src-mediated cross-talk with EGFR. LPA1-mediated phosphorylation of Y845-EGFR under hypoxia led to PI3K/Akt activation, an event that increases the ability of cells to produce invadopodia. Moreover, phospho-Y845-EGFR was upregulated in hypoxic zones of tumors and a combination of EGFR and LPA1 inhibition synergistically suppressed metastasis in vivo. Implications: This study uncovers an LPA1–EGFR signaling axis that is used for cell invasion in hypoxia and suggests a potential target to impede cancer metastasis. Mol Cancer Res; 16(10); 1601–13. ©2018 AACR.
Elastic Response and Failure Studies of Multi-Wall Carbon Nanotube Twisted Yarns

Experimental data on the stress-strain behavior of a polymer multiwall carbon nanotube (MWCNT) yarn composite are used to motivate an initial study in multi-scale modeling of strength and stiffness. Atomistic and continuum length scale modeling methods are outlined to illustrate the range of parameters required to accurately model behavior. The carbon nanotubes yarns are four-ply, twisted, and combined with an elastomer to form a single-layer, unidirectional composite. Due to this textile structure, the yarn is a complicated system of unique geometric relationships subjected to combined loads. Experimental data illustrate the local failure modes induced by static, tensile tests. Key structure-property relationships are highlighted at each length scale indicating opportunities for parametric studies to assist the selection of advantageous material development and manufacturing methods.
Towards implementing lean construction in the Moroccan construction industry: Survey study

Traditional construction management techniques are criticized by its inability to deliver construction projects on time, with the quality requested by the customer, and without cost overrun. It has become crucial for Moroccan construction practitioners to seek creative approach and to look for new ways of thinking in order to resist to the increasing competition and to survive with market constraints, especially when compared to the significant improvements achieved in the Moroccan manufacturing industry. Lean Construction (LC) is a very effective approach to design production systems for the purpose of reducing waste of time, of materials, and effort as well as generating the maximum possible amount of value. Lean construction has been introduced into the Moroccan construction industry; however, it is still in its infancy. Based on a structured questionnaire survey, this article aims to evaluate the perceptions of the Moroccan construction professionals on the Lean Construction implementation in the Moroccan construction industry. To achieve this objective, a total of 330 responses were collected and then analyzed using Statistical Package for Social Sciences (SPSS V20.0 for Windows). The following conclusions were made, more than half of the respondents (172 professional; 52.1%) think that Lean Construction approach is adapted to any size of Moroccan companies; the respondents agreed that Lean Construction implementation would add positive impacts to the Moroccan construction projects (with an overall mean value of 3.84); LC is a high priority for the Moroccan construction projects (with an overall mean value of 3.84).
A Survey of Emerging Concepts and Challenges for QoE Management of Multimedia Services

Quality of Experience (QoE) has received much attention over the past years and has become a prominent issue for delivering services and applications. A significant amount of research has been devoted to understanding, measuring, and modelling QoE for a variety of media services. The next logical step is to actively exploit that accumulated knowledge to improve and manage the quality of multimedia services, while at the same time ensuring efficient and cost-effective network operations. Moreover, with many different players involved in the end-to-end service delivery chain, identifying the root causes of QoE impairments and finding effective solutions for meeting the end users’ requirements and expectations in terms of service quality is a challenging and complex problem. In this article, we survey state-of-the-art findings and present emerging concepts and challenges related to managing QoE for networked multimedia services. Going beyond a number of previously published survey articles addressing the topic of QoE management, we address QoE management in the context of ongoing developments, such as the move to softwarized networks, the exploitation of big data analytics and machine learning, and the steady rise of new and immersive services (e.g., augmented and virtual reality). We address the implications of such paradigm shifts in terms of new approaches in QoE modeling and the need for novel QoE monitoring and management infrastructures.
Predicting Cancer Drug Response Using a Recommender System

Motivation As we move towards an era of precision medicine, the ability to predict patient-specific drug responses in cancer based on molecular information such as gene expression data represents both an opportunity and a challenge. In particular, methods are needed that can accommodate the high-dimensionality of data to learn interpretable models capturing drug response mechanisms, as well as providing robust predictions across datasets. Results We propose a method based on ideas from “recommender systems” (CaDRReS) that predicts cancer drug responses for unseen cell-lines/patients based on learning projections for drugs and cell-lines into a latent “pharmacogenomic” space. Comparisons with other proposed approaches for this problem based on large public datasets (CCLE, GDSC) shows that CaDRReS provides consistently good models and robust predictions even across unseen patient-derived cell-line datasets. Analysis of the pharmacogenomic spaces inferred by CaDRReS also suggests that they can be used to understand drug mechanisms, identify cellular subtypes, and further characterize drug-pathway associations. Availability Source code and datasets are available at https://github.com/CSB5/CaDRReS Contact nagarajann@gis.a-star.edu. sg Supplementary information Supplementary data are available online.