Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Multiple Access Technique for 5G: Power Domain Sparse Code Multiple Access (PSMA)

In this paper, a new approach for multiple access in the fifth generation (5G) of cellular networks called power domain sparse code multiple access (PSMA) is proposed. In PSMA, we adopt both the power domain and the code domain to transmit multiple users’ signals over a subcarrier simultaneously. In such a model, the same sparse code multiple-access (SCMA) codebook can be used by multiple users, where, for these users, the power domain non-orthogonal multiple access (PD-NOMA) technique is used to send signals non-orthogonally. Although the signal of different SCMA codebooks can be detected orthogonally, the same codebook used by multiple users produces interference over these users. With PSMA, a codebook can be reused in the coverage area of each base station more than one time, which can improve the spectral efficiency. We investigate the signal model as well as the receiver and transmitter of the PSMA method. In the receiver side, we propose a message passing algorithm-based successive interference cancellation detector to detect the signal of each user. To evaluate the performance of PSMA, we consider a heterogeneous cellular network. In this case, our design objective is to maximize the system sum rate of the network subject to some system level and QoS constraints such as transmit power constraints. We formulate the proposed resource allocation problem as an optimization problem and solve it by successive convex approximation techniques. Moreover, we compare PSMA with SCMA and PD-NOMA from the performance and computational complexity perspective. Finally, the effectiveness of the proposed approach is investigated using numerical results. We show that by a reasonable increase in complexity, PSMA can improve the spectral efficiency about 50% compared with SCMA and PD-NOMA.
SPHK1‐S1PR1‐RANKL Axis Regulates the Interactions Between Macrophages and BMSCs in Inflammatory Bone Loss

Accumulating evidence indicates that the immune and skeletal systems interact with each other through various regulators during the osteoclastogenic process. Among these regulators, the bioactive lipid sphingosine‐1‐phosphate (S1P), which is synthesized by sphingosine kinase 1/2 (SPHK1/2), has recently been recognized to play a role in immunity and bone remodeling through its receptor sphingosine‐1‐phosphate receptor 1 (S1PR1). However, little is known regarding the potential role of S1PR1 signaling in inflammatory bone loss. We observed that SPHK1 and S1PR1 were upregulated in human apical periodontitis, accompanied by macrophage infiltration and enhanced expression of receptor activator of NF‐κB ligand (RANKL, an indispensable factor in osteoclastogenesis and bone resorption) and increased numbers of S1PR1‐RANKL double‐positive cells in lesion tissues. Using an in vitro co‐culture model of macrophages and bone marrow stromal cells (BMSCs), it was revealed that in the presence of lipopolysaccharide (LPS) stimulation, macrophages could significantly induce SPHK1 activity, which resulted in activated S1PR1 in BMSCs. The activated S1P‐S1PR1 signaling was responsible for the increased RANKL production in BMSCs, as S1PR1‐blockage abolished this effect. Applying a potent S1P‐S1PR1 signaling modulator, Fingolimod (FTY720), in a Wistar rat apical periodontitis model effectively prevented bone lesions in vivo via downregulation of RANKL production, osteoclastogenesis, and bone resorption. Our data unveiled the regulatory role of SPHK1‐S1PR1‐RANKL axis in inflammatory bone lesions and proposed a potential therapeutic intervention by targeting this cell‐signaling pathway to prevent bone loss. © 2018 American Society for Bone and Mineral Research.
Surface compression with geometric bandelets

This paper describes the construction of second generation bandelet bases and their application to 3D geometry compression. This new coding scheme is orthogonal and the corresponding basis functions are regular. In our method, surfaces are decomposed in a bandelet basis with a fast bandeletization algorithm that removes the geometric redundancy of orthogonal wavelet coefficients. The resulting transform coding scheme has an error decay that is asymptotically optimal for geometrically regular surfaces. We then use these bandelet bases to perform geometry image and normal map compression. Numerical tests show that for complex surfaces bandelets bring an improvement of 1.5dB to 2dB over state of the art compression schemes.
Accelerated virtual switching support of 5G NFV-based mobile networks

5G should be operational with high penetration beyond the year 2020 with data traffic rates increasing exponentially and the number of connected devices expected to surpass tens of billions. Requirements for 5G mobile networks include higher flexibility, scalability, cost effectiveness and energy efficiency. Towards these goals, Software Defined Networking (SDN) and Network Functions Virtualisation have been adopted in recent proposals for future mobile networks architectures because they are considered critical technologies for 5G. In this paper, we make a case for using virtual switching acceleration of EPC Virtual Network Function interconnection with the goal of meeting 5G network requirements. In our implementation, we use DPDK user space virtual switching as well as XDP kernel space forwarding instead of native OVS switching found an many standard network virtualisation environments. Using these tools we measure improved network service quality performance for EPC connections.
Joint solution of low, intermediate, and high-level vision tasks by evolutionary optimization: Application to computer vision at low SNR

Methods for conducting model-based computer vision from low-SNR (=/<1 dB) image data are presented. Conventional algorithms break down in this regime due to a cascading of noise artifacts, and inconsistencies arising from the lack of optimal interaction between high- and low-level processing. These problems are addressed by solving low-level problems such as intensity estimation, segmentation, and boundary estimation jointly (synergistically) with intermediate-level problems such as the estimation of position, magnification, and orientation, and high-level problems such as object identification and scene interpretation. This is achieved by formulating a single objective function that incorporates all the data and object models, and a hierarchy of constraints in a Bayesian framework. All image-processing operations, including those that exploit the low and high-level variables to satisfy multi-level pattern constraints, result directly from a parallel multi-trajectory global optimization algorithm. Experiments with simulated low-count (7-9 photons/pixel) 2-D Poisson images demonstrate that compared to non-joint methods, a joint solution not only results in more reliable scene interpretation, but also a superior estimation of low-level imaging variables. Typically, most object parameters are estimated to within a 5% accuracy even with overlap and partial occlusion.
When Simpler Data Does Not Imply Less Information

The exponential growth in smartphone adoption is contributing to the availability of vast amounts of human behavioral data. This data enables the development of increasingly accurate data-driven user models that facilitate the delivery of personalized services that are often free in exchange for the use of its customers’ data. Although such usage conventions have raised many privacy concerns, the increasing value of personal data is motivating diverse entities to aggressively collect and exploit the data. In this article, we unfold profiling scenarios around mobile HTTP(S) traffic, focusing on those that have limited but meaningful segments of the data. The capability of the scenarios to profile personal information is examined with real user data, collected in the wild from 61 mobile phone users for a minimum of 30 days. Our study attempts to model heterogeneous user traits and interests, including personality, boredom proneness, demographics, and shopping interests. Based on our modeling results, we discuss various implications to personalization, privacy, and personal data rights.
How to Co-Develop Services, Work, and Information Systems in Healthcare: The Daisy Approach

Information systems in healthcare need to be designed and developed in a collaborative way. However, existing collaborative methodologies for the parallel development of healthcare work and information systems are vague and fragmented. Furthermore, they neither address people-centred healthcare nor limited-resource contexts. In this paper we introduce an emerging holistic approach, based on a unifying theoretical basis, for co-developing the services, work and information systems in healthcare. The approach intends to (a) be collaborative in nature; (b) address the domains of both healthcare professionals and ordinary people / communities; (c) span the main analysis and design tasks of socio-technical information systems development from needs assessment through requirements setting to functional-architectural solutions; (d) be contextually sensitive; and (e) be practicable in "real life" beyond research settings.
UKSM: Swift Memory Deduplication via Hierarchical and Adaptive Memory Region Distilling

In cloud computing, deduplication can reduce memory footprint by eliminating redundant pages. The responsiveness of a deduplication process to newly generated memory pages is critical. State-of-the-art Content Based Page Sharing (CBPS) approaches lack responsiveness as they equally scan every page while finding redundancies. We propose a new deduplication system UKSM, which prioritizes different memory regions to accelerate the deduplication process and minimize application penalty. With UKSM, memory regions are organized as a distilling hierarchy, where a region in a higher level receives more CPU cycles. UKSM adaptively promotes/demotes a region among levels according to the region’s estimated deduplication benefit and penalty. UKSM further introduces an adaptive partial-page hashing scheme which adjusts a global page hashing strength parameter according to the global degree of page similarity. Experiments demonstrate that, with the same amount of CPU cycles in the same time envelop, UKSM can achieve up to 12.6× and 5× more memory saving than CBPS approaches on static and dynamic workloads, respectively.
Mechanisms regulating expansion of CD8+ T cells during HIV‐1 infection

Abnormal immune activation and expansion of CD8+ T cells, especially of memory and effector phenotypes, take place during HIV‐1 infection, and these abnormal features persist during administration of antiretroviral therapy (ART) to infected patients. The molecular mechanisms for CD8+ T‐cell expansion remain poorly characterized. In this article, we review the literature addressing features of CD8+ T‐cell immune pathology and present an integrated view on the mechanisms leading to abnormal CD8+ T‐cell expansion during HIV‐1 infection. The expression of molecules important for directing the homing of CD8+ T cells between the circulation and lymphoid tissues, in particular CCR5 and CXCR3, is increased in CD8+ T cells in circulation and in inflamed tissues during HIV‐1 infection; these disturbances in the homing capacity of CD8+ T cells have been linked to increased CD8+ T‐cell proliferation. The production of IL‐15, a cytokine responsible for physiological proliferation of CD8+ T cells, is increased in lymphoid tissues during HIV‐1 infection as result of microbial translocation and severe inflammation. IL‐15, and additional inflammatory cytokines, may lead to deregulated proliferation of CD8+ T cells and explain the accumulation of CD8+ T cells in circulation. The decreased capacity of CD8+ T cells to localize to gut‐associated lymphoid tissue also contributes to the accumulation of these cells in blood. Control of inflammation, through ART administration during primary HIV‐1 infection or therapies aimed at controlling inflammation during HIV‐1 infection, is pivotal to prevent abnormal expansion of CD8+ T cells during HIV‐1 infection.
Dynamic State Estimation for Multi-Machine Power System by Unscented Kalman Filter With Enhanced Numerical Stability

In this paper, in order to enhance the numerical stability of the unscented Kalman filter (UKF) used for power system dynamic state estimation, a new UKF with guaranteed positive semidifinite estimation error covariance (UKF-GPS) is proposed and compared with five existing approaches, including UKF-schol, UKF-<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\kappa }$ </tex-math></inline-formula>, UKF-modified, UKF-<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\Delta Q}$ </tex-math></inline-formula>, and the square-root UKF (SR-UKF). These methods and the extended Kalman filter (EKF) are tested by performing dynamic state estimation on WSCC 3-machine 9-bus system and NPCC 48-machine 140-bus system. For WSCC system, all methods obtain good estimates. However, for NPCC system, both EKF and the classic UKF fail. It is found that UKF-schol, UKF-<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\kappa }$ </tex-math></inline-formula>, and UKF-<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\Delta Q}$ </tex-math></inline-formula> do not work well in some estimations while UKF-GPS works well in most cases. UKF-modified and SR-UKF can always work well, indicating their better scalability mainly due to the enhanced numerical stability.
Primary Frequency Control Scheme for a Fixed-Speed Dish-Stirling Solar–Thermal Power Plant

The ability of an induction generator-based dish-Stirling (DS) solar–thermal power plant in providing primary frequency control is examined. A dynamic model of the power plant is developed, in which the receiver/absorber temperature of the Stirling engine is allowed to vary. Primary frequency control is achieved through the adaptive regulation of the receiver temperature set-point and the droop setting of the output power–temperature characteristics of the DS system. However, the penetration level of the solar–thermal generation into the grid system has to be constrained to avoid the onset of instability due to the nonminimum phase characteristics of the DS system. The transient droop compensation technique is then proposed to alleviate the instability issue and results in an increase in the allowable DS penetration level.
Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes

In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM) based on pathway interaction network (PIN) which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA) was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs), and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed pathway and classification accuracy. To evaluate whether the PIN method was feasible or not, we compared the introduced method with standard network centrality measures. The pathway of RNA polymerase II pretranscription events was selected as the seed pathway. Taking this seed pathway as start, one pathway set (9 dysregulated pathways) with AUC score of 1.00 was identified. Among the 5 hub pathways obtained using standard network centrality measures, 4 pathways were the common ones between the two methods. RNA polymerase II transcription and DNA replication owned a higher number of pathway genes and DEGs. These dysregulated pathways work together to influence the progression of LM infection, and they will be available as biomarkers to diagnose LM infection.
Cervical Cancer Screening Among Arab Women in the United States: An Integrative Review.

PROBLEM IDENTIFICATION Arab American women are an ethnic minority and immigrant population in the United States with unique and nuanced sociocultural factors that influence preventive health behaviors. The aims of this article are to evaluate and synthesize the existing evidence on cervical cancer screening behaviors, as well as determine factors that influence these behaviors, among Arab American women. LITERATURE SEARCH Extensive literature searches were performed using PubMed, CINAHL®, Scopus, Embase, and Cochrane databases; articles published through October 2015 were sought. DATA EVALUATION Of 17 articles, 14 explicitly identified Arab and/or Muslim women and cervical cancer screening in either the title or the abstract; the remaining three focused on cancer attitudes and behaviors in Arab Americans in general but measured cervical cancer screening. Eleven articles reported different aspects of one intervention. Because of methodologic heterogeneity, the current authors synthesized results narratively. SYNTHESIS Key factors influencing cervical cancer screening were identified as the following. CONCLUSIONS Cervical cancer screening rates among Arab American women are comparable to other ethnic minorities and lower than non-Hispanic White women. Findings are inconsistent regarding factors influencing cervical cancer screening behaviors in this underrepresented group. IMPLICATIONS FOR RESEARCH Significant need exists for more research to better understand cervical cancer prevention behaviors in this group to inform culturally relevant interventions. Healthcare providers play a crucial role in increasing cervical cancer screening awareness and recommendations for Arab American women.
Visualization of similar news articles with network analysis and text mining

This paper proposes the method to classify news articles by combining tf-idf and n-gram. This method extracts characteristic words from each news article and classify news based on these words. Numerical experiment results show the relationship among the news articles and visualize the similar articles with networks. Additionally, the authors compare proposal method with only tf-idf in order to verify the effectiveness of this method.
A negotiation approach to support interoperability in a collaborative manufacturing environment

Maintaining the interoperability in a dynamic competitive manufacturing environment in which different business enterprises collaborate is difficult to achieve. Our approach highlights negotiation as the best solution to solve interoperability problems by reaching the common decision suitable for all managers of various enterprises in the most optimized amount of time. In this context, this paper proposes a multi-agent negotiation model, able to coordinate several negotiations taking place in parallel among multiple participants. It is described the negotiation strategy for evaluating and generating offers and the protocol for sending the offers to the other agents. This model can be used in the H2020 C2NET project for supporting manufacturing.
Localization and Expression of Nuclear Factor of Activated T-Cells 5 in Myoblasts Exposed to Pro-inflammatory Cytokines or Hyperosmolar Stress and in Biopsies from Myositis Patients

Aims: Regeneration in skeletal muscle relies on regulated myoblast migration and differentiation, in which the transcription factor nuclear factor of activated T-cells 5 (NFAT5) participates. Impaired muscle regeneration and chronic inflammation are prevalent in myositis. Little is known about the impact of inflammation on NFAT5 localization and expression in this group of diseases. The goal of this study was to investigate NFAT5 physiology in unaffected myoblasts exposed to cytokine or hyperosmolar stress and in myositis. Methods: NFAT5 intracellular localization and expression were studied in vitro using a cell culture model of myositis. Myoblasts were exposed to DMEM solutions enriched with pro-inflammatory cytokines IFN-γ with IL-1β or hyperosmolar DMEM obtained by NaCl supplementation. NFAT5 localization was visualized using immunohistochemistry (IHC) and Western blotting (WB) in fractionated cell lysates. NFAT5 expression was assessed by WB and RT-qPCR. In vivo localization and expression of NFAT5 were studied in muscle biopsies of patients diagnosed with polymyositis (n = 6), dermatomyositis (n = 10), inclusion body myositis (n = 11) and were compared to NFAT5 localization and expression in non-myopathic controls (n = 13). Muscle biopsies were studied by means of quantitative IHC and WB of total protein extracts. Results: In unaffected myoblasts, hyperosmolar stress ensues in NFAT5 nuclear translocation and increased NFAT5 mRNA and protein expression. In contrast, pro-inflammatory cytokines did not lead to NFAT5 nuclear translocation nor increased expression. Cytokines IL-1β with IFN-γ induced colocalization of NFAT5 with histone deacetylase 6 (HDAC6), involved in cell motility. In muscle biopsies from dermatomyositis and polymyositis patients, NFAT5 colocalized with HDAC6, while in IBM, this was often absent. Conclusions: Our data suggest impaired NFAT5 localization and expression in unaffected myoblasts in response to inflammation. This disturbed myogenic NFAT5 physiology could possibly explain deleterious effects on muscle regeneration in myositis.
The HELICOPTER project: Wireless sensor network for multi-user behavioral monitoring

Continuous monitoring of daily life activities within the home environment is among most appealing and challenging goals of technologies supporting the Active and Assisted Living paradigm. The HELICOPTER (AAL-JP) project aims at merging conventional telemedicine and home monitoring into a unique, holistic framework. To this purpose, a network of heterogeneous sensors is deployed into the user's home: raw data coming from sensors should then be gathered and analyzed to extract meaningful information, possibly related to user's health and wellness. Besides the inherent complexity of designing and deploying a suitable infrastructure, intrusiveness, usability and acceptability concern come into play. In this paper, we introduce the overall project vision, focusing mostly on the infrastructure implementation and discussing the extension of the monitoring approach to a multi-user environment. In fact, if two or more persons live in the same environment, data coming from home sensors need disambiguation, i.e., the activity detected by a given sensor need to be ascribed to a specific user, in order to contribute to the appropriate behavioral profile. We propose a simple approach, based on fusion of data coming from wearable and home devices. We discuss lab tests, showing good accuracy in “action tagging”, and illustrate practical results coming from actual pilots, involving older end-users in different European countries.
An unusual case of reversible mild cognitive impairment

ABSTRACT Mild cognitive impairment (MCI) is cognitive dysfunction greater than expected for age and education in either a single cognitive domain or in multiple domains without impairment of activities of daily living. The present case report describes the case of an elderly male patient of 71 years who presented with MCI and was Venereal Disease Research Laboratory test reactive in serum. This was confirmed by Treponema pallidum Hemagglutination Assay. After a complete course of antibiotic therapy, his memory complaints disappeared completely. Though syphilis is termed as reversible dementia; to the best of our knowledge, this is the first case of MCI with reactive syphilis serology who responded to antimicrobial therapy.