Miracle-dz/UniFAR-FTUs huggingface dataset:
Blockchain Support for Flexible Queries with Granular Access Control to Electronic Medical Records (EMR)

In this paper, we propose an architecture for Blockchain-based Electronic Medical Records (EMRs) called GAA-FQ (Granular Access Authorisation supporting Flexible Queries) that comprises an access model and an access authorisation scheme. Unlike existing Blockchain schemes, our access model can authorise different levels of granularity of authorisation, whilst maintaining compatibility with the underlying Blockchain data structure. Furthermore, the authorisation, encryption, and decryption algorithms proposed in the GAA-FQ scheme dispense with the need to use a public key infrastructure (PKI) and hence improve the computation performance needed to support more granular and distributed, yet authorised, EMR data queries. We validated the computation performance and transmission efficiency for GAA-FQ using a simulation of GAA-FQ against an access control scheme for EMRs called ESPAC as our baseline that was not designed using a Blockchain. To the best of our knowledge, GAA- FQ is the first Blockchain-oriented access authorisation scheme with granular access control, supporting flexible data queries, that has been proposed for secure EMR information management.
HDL impairs osteoclastogenesis and induces osteoclast apoptosis via upregulation of ABCG1 expression

Cholesterol is one of the major components of biological membranes and has an important function in osteoclast formation and survival. It has been reported that high-density lipoprotein (HDL) promotes cholesterol efflux from osteoclasts and induces their apoptosis, but the underlying mechanisms are unclear. In this study, we investigated how HDL promotes osteoclast cholesterol efflux and explored its effect on osteoclast formation and survival. Our results showed that the maximum diameter and fusion index of osteoclasts were decreased, while the ratios of osteoclasts with pyknotic nuclei were increased when cells were treated with HDL (600 ng/ml), as revealed by tartrate-resistant acid phosphatase-positive staining and microscopy assay. HDL enhanced cellular cholesterol efflux from osteoclasts in both concentration- and time-dependent manners. The ability of HDL3 to stimulate cholesterol efflux was stronger than preβ-HDL, HDL2, and ApoAI. Knockdown of ABCG1 expression reduced HDL-mediated cholesterol efflux and restored the HDL-induced reduction in osteoclast formation. Finally, HDL3 promoted sphingomyelin efflux from osteoclasts and reduced the expression of caveolin-1. Together, the findings demonstrate that HDL3 upregulates ABCG1 expression and promotes cholesterol efflux from osteoclast, impairs cholesterol homeostasis in osteoclasts, and consequently enhances osteoclast apoptosis.
Species-Specific Changes in a Primate Transcription Factor Network Provide Insights into the Molecular Evolution of the Primate Prefrontal Cortex

Abstract The human prefrontal cortex (PFC) differs from that of other primates with respect to size, histology, and functional abilities. Here, we analyzed genome-wide expression data of humans, chimpanzees, and rhesus macaques to discover evolutionary changes in transcription factor (TF) networks that may underlie these phenotypic differences. We determined the co-expression networks of all TFs with species-specific expression including their potential target genes and interaction partners in the PFC of all three species. Integrating these networks allowed us inferring an ancestral network for all three species. This ancestral network as well as the networks for each species is enriched for genes involved in forebrain development, axonogenesis, and synaptic transmission. Our analysis allows us to directly compare the networks of each species to determine which links have been gained or lost during evolution. Interestingly, we detected that most links were gained on the human lineage, indicating increase TF cooperativity in humans. By comparing network changes between different tissues, we discovered that in brain tissues, but not in the other tissues, the human networks always had the highest connectivity. To pinpoint molecular changes underlying species-specific phenotypes, we analyzed the sub-networks of TFs derived only from genes with species-specific expression changes in the PFC. These sub-networks differed significantly in structure and function between the human and chimpanzee. For example, the human-specific sub-network is enriched for TFs implicated in cognitive disorders and for genes involved in synaptic plasticity and cognitive functions. Our results suggest evolutionary changes in TF networks that might have shaped morphological and functional differences between primate brains, in particular in the human PFC.
Security, privacy'); drop table users; - and forced trust in the information age?: when trusting an information system is not optional and why it matters

In this study, we discuss forced trust in the context of information systems, information society and surveillance. Trust definitions and concepts pertinent to the discussion are examined and portrayed with case examples of forced trust in different situations that are central to the information society. As forced trust appears mostly in governmental information systems, we reflect the concept from security and privacy point-of-view, concepts that are important for users of such systems in the current age of information. We portray the trust landscape of critical governmental information systems and discuss forced trust also in the context of Internet infrastructure and mass surveillance. We provide a glimpse of an information society that combines security, trust, and privacy, while also providing discussion on what kind of trust dynamics such a utopia would require.
Comparing the validity of different ICD coding abstraction strategies for sepsis case identification in German claims data

Introduction Administrative data are used to generate estimates of sepsis epidemiology and can serve as source for quality indicators. Aim was to compare estimates on sepsis incidence and mortality based on different ICD-code abstraction strategies and to assess their validity for sepsis case identification based on a patient sample not pre-selected for presence of sepsis codes. Materials and methods We used the national DRG-statistics for assessment of population-level sepsis incidence and mortality. Cases were identified by three previously published International Statistical Classification of Diseases (ICD) coding strategies for sepsis based on primary and secondary discharge diagnoses (clinical sepsis codes (R-codes), explicit coding (all sepsis codes) and implicit coding (combined infection and organ dysfunction codes)). For the validation study, a stratified sample of 1120 adult patients admitted to a German academic medical center between 2007–2013 was selected. Administrative diagnoses were compared to a gold standard of clinical sepsis diagnoses based on manual chart review. Results In the validation study, 151/937 patients had sepsis. Explicit coding strategies performed better regarding sensitivity compared to R-codes, but had lower PPV. The implicit approach was the most sensitive for severe sepsis; however, it yielded a considerable number of false positives. R-codes and explicit strategies underestimate sepsis incidence by up to 3.5-fold. Between 2007–2013, national sepsis incidence ranged between 231-1006/100,000 person-years depending on the coding strategy. Conclusions In the sample of a large tertiary care hospital, ICD-coding strategies for sepsis differ in their accuracy. Estimates using R-codes are likely to underestimate the true sepsis incidence, whereas implicit coding overestimates sepsis cases. Further multi-center evaluation is needed to gain better understanding on the validity of sepsis coding in Germany.
Checking Weak Observable Liveness on Unfoldings Through Asynchronous Games

We define an asynchronous two-player game, played on the unfolding of a Petri net. The set of transitions of the net is partitioned among the two players, and a play is a run of the unfolding. The role of the two players is different: we assume that one of them (the User) has the right to block transitions under its control, while the other player (the System) must ensure progress of its transitions. We then define a notion of strategy for the User. In this framework, one can set different aims for the two players. Here, we consider the problem of weak observable liveness, in which the User tries to enforce liveness of a given transition. We show that a transition is weakly observably live if and only if the User has a winning strategy in the game.
GSK3-β promotes calpain-1–mediated desmin filament depolymerization and myofibril loss in atrophy

Myofibril breakdown is a fundamental cause of muscle wasting and inevitable sequel of aging and disease. We demonstrated that myofibril loss requires depolymerization of the desmin cytoskeleton, which is activated by phosphorylation. Here, we developed a mass spectrometry–based kinase-trap assay and identified glycogen synthase kinase 3-&bgr; (GSK3-&bgr;) as responsible for desmin phosphorylation. GSK3-&bgr; inhibition in mice prevented desmin phosphorylation and depolymerization and blocked atrophy upon fasting or denervation. Desmin was phosphorylated by GSK3-&bgr; 3 d after denervation, but depolymerized only 4 d later when cytosolic Ca2+ levels rose. Mass spectrometry analysis identified GSK3-&bgr; and the Ca2+-specific protease, calpain-1, bound to desmin and catalyzing its disassembly. Consistently, calpain-1 down-regulation prevented loss of phosphorylated desmin and blocked atrophy. Thus, phosphorylation of desmin filaments by GSK3-&bgr; is a key molecular event required for calpain-1–mediated depolymerization, and the subsequent myofibril destruction. Consequently, GSK3-&bgr; represents a novel drug target to prevent myofibril breakdown and atrophy.
Market-Based Incentive Mechanism Design for Crowdsourcing

Participants coverage is an important role in the crowdsourcing-based applications. However most of the existing incentive mechanisms for the crowdsourcing has focused on how to allocate tasks to the participants to maximize the social welfare, and none of them consider the problem of participant coverage hole created by the uneven distribution of participants. In this paper, we propose a market-based incentive mechanism for crowdsourcing, where the platform motivates the participants to move to the coverage hole and complete the sensing tasks there from a market-based perspective. The market-based incentive mechanism is built on a novel reverse auction framework with reserve price, where the reserve price of a sensing task is the maximum payment for a participant to complete this task. The platform systematically reduces the reserve price of tasks in popular areas and participants are stimulated to complete the tasks in unpopular areas. Each round of reverse auction consists of a winning participant selection problem and a payment determination problem. Since the task allocation problem is NP-hard, we propose a greedy algorithm to solve it. We also design a critical payment policy to guarantee that participants declare their cost truthfully. Evaluation results show that the proposed mechanism outperforms existing solutions under various conditions.
Dynamics of Feature-based Attentional Selection during Color–Shape Conjunction Search

Feature-based attentional selection is accomplished by increasing the gain of sensory neurons encoding target-relevant features while decreasing that of other features. But how do these mechanisms work when targets and distractors share features? We investigated this in a simplified color–shape conjunction search task using ERP components (N2pc, PD, and SPCN) that index lateralized attentional processing. In Experiment 1, we manipulated the presence and frequency of color distractors while holding shape distractors constant. We tested the hypothesis that the color distractor would capture attention, requiring active suppression such that processing of the target can continue. Consistent with this hypothesis, we found that color distractors consistently captured attention, as indexed by a significant N2pc, but were reactively suppressed (indexed by PD). Interestingly, when the color distractor was present, target processing was sustained (indexed by SPCN), suggesting that the dynamics of attentional competition involved distractor suppression interlinked with sustained target processing. In Experiment 2, we examined the contribution of shape to the dynamics of attentional competition under similar conditions. In contrast to color distractors, shape distractors did not reliably capture attention, even when the color distractor was very frequent and attending to target shape would be beneficial. Together, these results suggest that target-colored objects are prioritized during color–shape conjunction search, and the ability to select the target is delayed while target-colored distractors are actively suppressed.
A View-Dependent Metric for Patch-Based LOD Generation 8 Selection

With hardware tessellation, highly detailed geometric models are decomposed into patches whose tessellation factor can be specified dynamically and independently at render time to control polygon resolution. Yet, to achieve maximum efficiency, an appropriate factor needs to be selected for each patch according to its content (geometry and appearance) and the current viewpoint distance and orientation. We propose a novel patch-based error metric that addresses this problem. It summarizes both the geometrical error and the texture parametrization deviation of a simplified patch compared to the corresponding detailed surface. This metric is compact and can be efficiently evaluated on the GPU along any view direction. Furthermore, based on this metric, we devise an easy-to-implement refitting optimization that further reduces the simplification error of any decimation algorithm, and propose a new placement strategy and cost function for edge-collapses to reach the best quality/performances trade-off.
Safebot: A Safe Collaborative Chatbot

Chatbots have been a core measure of AI since Turing has presented his test for intelligence, and are also widely used for entertainment purposes. In this paper we present a platform that enables users to collaboratively teach a chatbot responses, using natural language. We present a method of collectively detecting malicious users and using the commands taught by the malicious users to further mitigate activity of future malicious users. We ran an experiment with several subjects, playing different roles, showing the effectiveness of our chatbot.
A Non-structural Representation Scheme for Articulated Shapes

Articulated shapes are successfully represented by structural representations which are organized in the form of graphs of shape components. We present an alternative representation scheme which is equally powerful but does not require explicit modeling or discovery of structural relations. The key element in our scheme is a novel multi scale pixel-based distinctness measure which implicitly quantifies how rare a particular pixel is in terms of its geometry with respect to all pixels of the shape. The spatial distribution of the distinctness yields a partitioning of the shape into a set of regions. The proposed representation is a collection of size normalized probability distribution of the distinctness over regions over shape dependent scales. We test the proposed representation on a clustering task.
Digital Epigraphic Heritage Made Simple: an Android App for Exploring 3D Roman Inscriptions

Spain keeps an exceptional epigraphic heritage, dated from the Roman civilization, that integrates thousands of Latin inscriptions nowadays disseminated along the Iberian peninsula. For many purposes such as education, innovation, cataloging, study and dissemination of this type of historical documentation, a clear demand of placing all this epigraphic heritage into modern 3D graphics, internet and mobile devices is increasing. We present the novel 'Epigraphia 3D' for handheld devices, a native Android app for exploring a total of 60 Roman inscriptions from the National Museum of Roman Art (Merida, Badajoz). The work emphasizes the 3D nature feature for navigating through the inscriptions, by using Glob3 Mobile, an open source GIS framework for visualizing the 3D inscriptions. Besides, an error analysis of the simplified models is tackled.
Stochastic models of compliant spine arrays for rough surface grasping

This paper presents models of arrays of compliantly supported spines that attach to rough surfaces. The applications include climbing and perching robots. Surfaces are characterized in terms of asperity distributions, which lead to stochastic models of spine force capabilities over a range of loading directions. Models cover unidirectional spine arrays and pairs of opposed arrays that withstand normal forces pulling away from a surface. Experiments on a variety of surfaces confirm the predicted behavior. For opposed spine arrays, the overall load capability also depends on the preloading strategy for applying internal forces. Insights from the analysis guide the design of spine array mechanisms to allow, for example, a small aerial platform to attach to walls and ceilings.
RIFNOM: 3D Rotation-Invariant Features on Normal Maps

This paper presents 3D rotation-invariant features on normal maps: RIFNOM. We assign a local coordinate system (CS) to each pixel by using neighbor normals to extract the 3D rotation-invariant features. These features can be used to perform interest point matching between normal maps. We can estimate 3D rotations between corresponding interest points by comparing local CSs. Experiments with normal maps of a rigid object showed the performance of the proposed method in estimating 3D rotations. We also applied the proposed method to a non-rigid object. By estimating 3D rotations between corresponding interest points, we successfully detected deformation of the object
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity

We investigate the quality of task specific word embeddings created with relatively small, targeted corpora. We present a comprehensive evaluation framework including both intrinsic and extrinsic evaluation that can be expanded to named entities beyond drug name. Intrinsic evaluation results tell that drug name embeddings created with a domain specific document corpus outperformed the previously published versions that derived from a very large general text corpus. Extrinsic evaluation uses word embedding for the task of drug name recognition with Bi-LSTM model and the results demonstrate the advantage of using domain-specific word embeddings as the only input feature for drug name recognition with F1-score achieving 0.91. This work suggests that it may be advantageous to derive domain specific embeddings for certain tasks even when the domain specific corpus is of limited size.
Evolution of Nanoporous Surface Layers on Gas-Atomized Ti60Cu39Au1 Powders during Dealloying

Nanoporous golf ball-shaped powders with a surface porous layer consisting of fcc Cu and Cu3Au phases have been fabricated by selectively dissolving gas-atomized Ti60Cu39Au1 powders in 0.13 M HF solution. The distribution profiles of the Ti2Cu and TiCu intermetallic phases and powder size play an important role of the propagation of the selective corrosion frontiers. The final nanoporous structure has a bimodal characteristic with a finer nanoporous structure at the ridges, and rougher structure at the shallow pits. The powders with a size of 18–75 m dealloy faster due to their high crystallinity and larger powder size, and these with a powder size of smaller than 18 m tend to deepen uniformly. The formation of the Cu3Au intermetallic phases and the finer nanoporous structure at the ridges proves that minor Au addition inhibits the fast diffusion of Cu adatoms and decreases surface diffusion by more than two orders. The evolution of the surface nanoporous structure with negative tree-like structures is considered to be controlled by a percolation dissolution mechanism.
OFDMA Uplink Scheduling in IEEE 802.11ax Networks

In the modern world, a high-speed wireless Internet connection is a necessity rather than a luxury. To improve the efficiency of Wi-Fi networks in dense deployment, a novel amendment to the Wi-Fi standard, namely IEEE 802.11ax introduces Orthogonal frequency-division multiple access (OFDMA). In contrast to legacy Wi-Fi, where performance of a station to a considerable degree depends on rate control, aggregation and other decision-making algorithms implemented at the station, in 11ax networks it is the access point that schedules channel time and specifies transmission parameters for both uplink and downlink. Although OFDMA scheduling in 11ax has much in common with that in cellular networks, e.g. LTE, 11ax has some peculiarities, especially for uplink transmission. Focusing on such peculiarities, in this paper, we investigate the scheduling problem in 11ax, propose a set of schedulers for 11ax, compare their performance and determine the gain achievable by the usage of OFDMA.
PS-Sim: A Framework for Scalable Simulation of Participatory Sensing Data

Emergence of smartphone and the participatory sensing (PS) paradigm have paved the way for a new variant of pervasive computing. In PS, human user performs sensing tasks and generates notifications, typically in lieu of incentives. These notifications are real-time, large-volume, and multi-modal, which are eventually fused by the PS platform to generate a summary. One major limitation with PS is the sparsity of notifications owing to lack of active participation, thus inhibiting large scale real-life experiments for the research community. On the flip side, research community always needs ground truth to validate the efficacy of the proposed models and algorithms. Most of the PS applications involve human mobility and report generation following sensing of any event of interest in the adjacent environment. This work is an attempt to study and empirically model human participation behavior and event occurrence distributions through development of a location-sensitive data simulation framework, called PS-Sim. From extensive experiments it has been observed that the synthetic data generated by PS-Sim replicates real participation and event occurrence behaviors in PS applications, which may be considered for validation purpose in absence of the groundtruth. As a proof-of-concept, we have used real-life dataset from a vehicular traffic management application to train the models in PS-Sim and cross-validated the simulated data with other parts of the same dataset.
Dirichlet Forms and Finite Element Methods for the SABR Model

We propose a deterministic numerical method for pricing vanilla options under the SABR stochastic volatility model, based on a finite element discretization of the Kolmogorov pricing equations via non-symmetric Dirichlet forms. Our pricing method is valid under mild assumptions on parameter configurations of the process both in moderate interest rate environments and in near-zero interest rate regimes such as the currently prevalent ones. The parabolic Kolmogorov pricing equations for the SABR model are degenerate at the origin, yielding non-standard partial differential equations, for which conventional pricing methods ---designed for non-degenerate parabolic equations--- potentially break down. We derive here the appropriate analytic setup to handle the degeneracy of the model at the origin. That is, we construct an evolution triple of suitably chosen Sobolev spaces with singular weights, consisting of the domain of the SABR-Dirichlet form, its dual space, and the pivotal Hilbert space. In particular, we show well-posedness of the variational formulation of the SABR-pricing equations for vanilla and barrier options on this triple. Furthermore, we present a finite element discretization scheme based on a (weighted) multiresolution wavelet approximation in space and a $\theta$-scheme in time and provide an error analysis for this discretization.