Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Optimal Task Graph Scheduling by Means of an Optimized Parallel A*-Algorithm

The development of high speed local networks and cheap, but also powerful PCs, lead to an extensive use of PCs as building blocks in modern parallel computer systems. In order to exploit the available resources at the best, any program has to be split into parallel executable tasks, which have to be scheduled to the available processing elements. The need for data communication between these tasks leads to dependencies, which strongly effect the schedule. In this paper, we consider task graphs that take computation and communication costs into account. For a completely meshed homogeneous computing system with a fixed number of processing elements, we compute schedules with minimum schedule length. Our contribution consists of parallelizing an informed search algorithm for calculating optimal schedules based on the IDA∗algorithm, a memory-saving derivative of the well known A∗-algorithm. Due to the resulting memory requirements, the application of the A∗algorithm is restricted to task graph scheduling problems with a quite small number of tasks. In contrast, the IDA∗-algorithm can compute optimal schedules for more complex task graphs.
Entity sentiment extraction using text ranking

Entity extraction and sentiment classification are among the most common types of information derived from documents, but the problem of directly associating entities and sentiment has received less attention. We use TextRank on a graph linking entities and sentiment-laden words and phrases. We extract from the resulting eigenvector the final sentiment weights of the entities. We then explore the algorithm's performance and accuracy, compared to a baseline.
Data sets and data quality in software engineering

OBJECTIVE - to assess the extent and types of techniques used to manage quality within software engineering data sets. We consider this a particularly interesting question in the context of initiatives to promote sharing and secondary analysis of data sets. METHOD - we perform a systematic review of available empirical software engineering studies. RESULTS - only 23 out of the many hundreds of studies assessed, explicitly considered data quality. CONCLUSIONS - first, the community needs to consider the quality and appropriateness of the data set being utilised; not all data sets are equal. Second, we need more research into means of identifying, and ideally repairing, noisy cases. Third, it should become routine to use sensitivity analysis to assess conclusion stability with respect to the assumptions that must be made concerning noise levels.
A mathematical model of the Skype VoIP congestion control algorithm

The Internet is changing from being only an efficient platform for data delivery to become also a platform for audio/video applications. The stability of the traditional Internet is due to the TCP congestion control algorithm. However, the TCP congestion control is not optimal for VoIP applications because of its retransmission mechanism and additive increase multiplicative decrease sliding window control. As a consequence, VoIP applications often employ proprietary and hidden congestion control algorithms executed over the UDP protocol. In this paper we focus on Skype audio, which is the most known and used VoIP application, in order to derive a mathematical model of its congestion control algorithm and evaluate properties such as efficiency in network utilization while avoiding congestion, which is particularly detrimental for VoIP traffic. To the purpose, the controller input/output variables are first identified and then their dynamic relation is described in the form of a hybrid automaton. Main findings are: (1) Skype does not implement a delay based control; (2) the loss ratio is the main input that affects the sending rate; (3) the sending rate matches the available bandwidth with a finite error.
Transfusion Reactions and Fatalities due to Circulatory Overloading*

Much research has recently been devoted to the identification of abnormal agglutinogens and iso-agglutinins. Noteworthy has been the discovery of the Rh factor by Landsteiner and Wiener (1940). Attention, too, has been focused on the grave danger of transfusion of incompatible blood. It is well known that death may follow transfusion of an incompatible agglutinogen-e.g., B cells into an A recipient, etc. Yet recovery may follow such a mishap. Kilduffe and DeBakey (1942) give the mortality rate as about 50%. The total incidence of haemolytic reactions due to transfusion of incompatible cells over a large series of cases is very low. Thus Kilduffe and DeBakey in a collectea series of 40,000 transfusions found 80 (0.18%) haemolytic shock reactions, of which 32 (0.07%) were fatal. The total number of deaths was 45. I have personally seen only two such cases in 10 years; both were fatal, and both were due to faulty blood grouping by the slide technique. However, as Wiener (1939) remarks, " it is fortunate that the transfusion of incompatible blood is not always fatal; indeed, in a number of instances the reactions were so mild or insidious that they passed unnoticed or were attributed to other causes. " Serious reactions have followed transfusion of as small a quantity as 10 c.cm. of incompatible blood. In some cases death has been almost instantaneous.
Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

Background Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control.
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System

In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user’s ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user’s high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a good set of algorithm parameters that were suggested based on empirical analyses. The results showed that the system could capture ECG reliably and extract highly accurate ECG-derived features with a reasonable rate of data drop during the user’s daily smartphone use.
Projection Multilevel Methods for Quasilinear Elliptic Partial Differential Equations: Numerical Results

The goal of this paper is to introduce a new multilevel solver for two-dimensional elliptic systems of nonlinear partial differential equations (PDEs), where the nonlinearity is of the type \(u \partial v\). The incompressible Navier--Stokes equations are an important representative of this class and are the target of this study. Using a first-order system least-squares (FOSLS) approach and introducing a new variable for $\partial v$, for this class of PDEs we obtain a formulation in which the nonlinearity appears as a product of two different dependent variables. The result is a system that is linear within each variable but nonlinear in the cross terms. In this paper, we introduce a new multilevel method that treats the nonlinearities directly. This approach is based on a projection multilevel (PML) method [S. F. McCormick, Multilevel Projection Methods for Partial Differential Equations, SIAM, Philadelphia, 1992] applied to the FOSLS functional. The implementation of the discretization process, relaxation, coarse-grid correction, and cycling strategies is discussed, and optimal performance is established numerically. A companion paper [T. A. Manteuffel, S. F. McCormick, and O. Rohrle, SIAM J. Numer. Anal. , 44 (2006), pp. 139-152] establishes a two-level convergence proof for this new multilevel method.
A Mathematical Model for the Validation of Gene Selection Methods

Gene selection methods aim at determining biologically relevant subsets of genes in DNA microarray experiments. However, their assessment and validation represent a major difficulty since the subset of biologically relevant genes is usually unknown. To solve this problem a novel procedure for generating biologically plausible synthetic gene expression data is proposed. It is based on a proper mathematical model representing gene expression signatures and expression profiles through Boolean threshold functions. The results show that the proposed procedure can be successfully adopted to analyze the quality of statistical and machine learning-based gene selection algorithms.
Facing the Inevitable ? The Dynamics of Impasse in Collective Contexts

This contribution aims at showing some of the advantages of taking a novel, broad and systemic view on constitutive rules based on a failure oriented analysis, relying on the notion of impasse. Basically, impasses can descend by two main kinds of causes: either a mismatch between rules (how things should be done) and facts (how things are actually done), or an internal contradiction among rules. Given the definitional character of constitutive rules, one could say that they set a new “logical space” for action, and that impasses (both mismatches and internal contradictions) push the action out of such space, thus threatening the identity of the regulated interaction and coordination. It is fairly clear that constitutive impasses may endanger the life of an institution, on the other hand, in a lot of other situations similar issues can arise in systems of constitutive rules that are not fatal to them. The main claim here is that, in order to understand such situations, an analysis of the dynamic evolution of impasses from definitional to institutional, in social settings is necessary. What the proposed analysis will show is a stepwise process towards the “institutionalization” of the impasse. Both definitional and institutional impasses can be said to be ontological, though each in a different sense. What makes definitional impasse ontological are the rules of the institution, while what
Characterisation of optical flow anomalies in pedestrian traffic

This paper applies a video modelling technique to a surveillance scenario where pedestrians are monitored to detect unusual events. The aim is to investigate the components of an automatic vision system capable of detecting normal and abnormal behaviour. Such a system has application in surveillance scenarios like town centre plazas, stadiums, train stations and shopping malls. Surveillance usually relies on tracking, but in crowded scenarios tracking is not reliable. Thus our framework for representation and analysis is based on optical flow to avoid tracking of individuals. We demonstrate that patterns derived from optical flow and encoded by a Hidden Markov Model are able to capture the dynamic evolution of normal behaviour allowing the classification of abnormal events.
Stem rot affects the structure of rhizosphere microbiome in Berseem Clover (Trifolium alexandrinum)

Rhizosphere microbiome plays an essential role in maintaining plant health and productivity. Fungal and bacterial diseases may affect the rhizosphere-associated microbial communities and overall structure of plant microbiome. Here, we studied the effect of stem rot of berseem clover on the bacterial and fungal communities associated with the rhizosphere. We analyzed the rhizosphere-associated bacterial and fungal microbiome from healthy and infected berseem clover collected from three sampling sites by using 16S rRNA and ITS based Illumina sequencing metabarcoding approach. Microbiome analysis showed that healthy plants had higher bacterial and fungal diversity as compared to stem rot infected plants. At the genus level, bacterial genera Rhizobium and Comamonas were more abundant in healthy plants while Pantoea was more abundant in infected plants and fungal genera Sclerotinia, Fusarium and Cladorrhinum were more abundant in infected plants while Microdochium and Cladosporium were distinctively abundant in healthy Berseem. Functional characterization of bacterial and fungal microbiomes revealed that bacterial communities from infected plants showed more abundance of bacteria with functions replication and repair, enzyme families and biosynthesis of other secondary metabolites as compared to healthy plant microbiome and decreased in fungal groups including arbuscular mycorrhiza and soil saprotrophs and an increase in plant saprotrophs and fungal parasite-plant pathogens. This study provides comprehensive information about the structure and composition of bacterial and fungal communities associated with the berseem clover rhizosphere that could be utilized for future research on the control of stem rot of berseem clover.
Short paper: a look at smartphone permission models

Many smartphone operating systems implement strong sandboxing for 3rd party application software. As part of this sandboxing, they feature a permission system, which conveys to users what sensitive resources an application will access and allows users to grant or deny permission to access those resources. In this paper we survey the permission systems of several popular smartphone operating systems and taxonomize them by the amount of control they give users, the amount of information they convey to users and the level of interactivity they require from users. We discuss the problem of permission overdeclaration and devise a set of goals that security researchers should aim for, as well as propose directions through which we hope the research community can attain those goals.
The extracellular heparan sulfatase SULF2 limits myeloid IFNβ signaling and Th17 responses in inflammatory arthritis

Heparan sulfate (HS) proteoglycans are important regulators of cellular responses to soluble mediators such as chemokines, cytokines and growth factors. We profiled changes in expression of genes encoding HS core proteins, biosynthesis enzymes and modifiers during macrophage polarisation, and found that the most highly regulated gene was Sulf2, an extracellular HS 6-O-sulfatase that was markedly downregulated in response to pro-inflammatory stimuli. We then generated Sulf2+/- bone marrow chimeric mice and examined inflammatory responses in antigen-induced arthritis, as a model of rheumatoid arthritis. Resolution of inflammation was impaired in myeloid Sulf2+/- chimeras, with elevated joint swelling and increased abundance of pro-arthritic Th17 cells in synovial tissue. Transcriptomic and in vitro analyses indicated that Sulf2 deficiency increased type I interferon signaling in bone marrow-derived macrophages, leading to elevated expression of the Th17-inducing cytokine IL-6. This establishes that dynamic remodeling of HS by Sulf2 limits type I interferon signaling in macrophages, and so protects against Th17-driven pathology.
Role of non-coding RNA hsa_circ_0001495 in 16HBE cellular inflammation induced by PM2.5 and O3 combined exposure

Background PM2.5 and O3 are the main air pollutants in China, and inflammation of the respiratory system is one of their main toxic effects. Cyclic RNAs are involved in many pathophysiological processes, but their relationship to the combined exposure to PM2.5 and O3 has not yet been investigated. Objective To elucidate the biological function played by hsa_circ_0001495 in the induction of 16HBE cellular inflammation by combined exposure to PM2.5 and O3. Method Detection of cell survival after 24h exposure of 16HBE cells to a combination of PM2.5 and O3 by CCK8. RT-qPCR and ELISA were used to detect inflammatory factors in 16HBE cells after co-exposing to PM2.5 and O3. CircRNA was screened using high throughput sequencing and bioinformatics analysis approaches. RNaseR experiments were carried out to verify the circular RNA properties of the circRNAs. Cytoplasmic-nuclear subcellular localisation assays and fish assays were used to verify the distribution of circRNAs in the nucleus versus the cytoplasm of the cell. To validate functions related with circRNA,RT-qPCR and ELISA were employed. Result Combined exposure to PM2.5 and O3 resulted in decreased cell viability.Combined exposure to PM2.5 and O3 resulted in 16HBE inflammation. High throughput sequencing and RT-qPCR results showed that the expression of hsa_circ_0001495 was significantly downregulated in 16HBE exposed to PM2.5 and O3 in combination. Hsa_circ_0001495 is not easily digested by RNaseR enzymes and has the properties of a circular RNA. Hsa_circ_0001495 is expressed in the cytoplasm as well as in the nucleus, but its distribution is predominantly in the cytoplasm. Conclusion In 16HBE cells, combined exposure to PM2.5 and O3 can induce an inflammatory response. hsa_circ_0001495 plays an inhibitory role in the inflammatory response of 16HBE cells that can be induced by combined exposure to PM2.5 and O3.
Sustainable management of wastewater systems: presentation of an adaptative model based on local dialogue and quality of service assessment

Water resources management is a worldwide challenge for the 21 st century. Water resources management in urbanized cities raises the question of cohabitation between the collective wastewater services and the individualized systems. Thus, an objective measure of efficiency is required: this can be done by evaluating the lev el of provided service instead of evaluating the means available themselves. For several decades , the emergence of new alternative technologies has been raising the question of servi ces efficiency offered by traditional technologies used in drainage management. This question is emphasized by the need for a global management of wastewater systems and the evolution of legislation, from discharges standards ("emission based") to standards in enviro nment acceptance capacities ("immision based"). Integrating these impacts becomes a neces sary step in order to plan sustainable drainage decisions. In this context, a methodology, named E DASR 1 , is proposed to support wastewater management strategies. This methodology is applied on the SIVOM (Intermunicipal Union with multiple vocations) of t he Mulhousian agglomeration (Alsace, France). This study is conducted with a close colla boration of local authorities, of the “Lyonnaise Des Eaux” (Mulhousian manager) and of local stakeholders (associations, Water Agency, etc.).
Type I interferon induces TCR-dependent and -independent antimicrobial responses in γδ intraepithelial lymphocytes

Intraepithelial lymphocytes (IEL) expressing the γδ T cell receptor (TCR) survey the intestinal epithelium to limit the invasion of microbial pathogens. The production of type I interferon (IFN) is a central component of an antiviral immune response, yet how these pro-inflammatory cytokines contribute to γδ IEL effector function remains unclear. Based on the unique activation status of IELs, and their ability to bridge innate and adaptive immunity, we investigated the extent to which type I IFN signaling modulates γδ IEL function. Using an ex vivo culture model, we find that type I IFN alone is unable to drive IFNγ production, yet low level TCR activation synergizes with type I IFN to induce IFNγ production in murine γδ IELs. Further investigation into the underlying molecular mechanisms of co-stimulation revealed that TCRγδ-mediated activation of NFAT and JNK is required for type I IFN to promote IFNγ expression in a STAT4- dependent manner. Whereas type I IFN rapidly upregulates antiviral gene expression independent of a basal TCRγδ signal, neither tonic TCR triggering nor the presence of a TCR agonist was sufficient to elicit type I IFN-induced IFNγ production in vivo. However, bypassing proximal TCR signaling events synergized with IFNAR/STAT4 activation to induce γδ IEL IFNγ production. These findings indicate that γδ IELs contribute to host defense in response to type I IFN by mounting a rapid antimicrobial response independent of TCRγδ signaling, and under permissive conditions, produce IFNγ in a TCR-dependent manner.
Towards an Eye-Brain-Computer Interface: Combining Gaze with the Stimulus-Preceding Negativity for Target Selections in XR

Gaze-assisted interaction techniques enable intuitive selections without requiring manual pointing but can result in unintended selections, known as Midas touch. A confirmation trigger eliminates this issue but requires additional physical and conscious user effort. Brain-computer interfaces (BCIs), particularly passive BCIs harnessing anticipatory potentials such as the Stimulus-Preceding Negativity (SPN) - evoked when users anticipate a forthcoming stimulus - present an effortless implicit solution for selection confirmation. Within a VR context, our research uniquely demonstrates that SPN has the potential to decode intent towards the visually focused target. We reinforce the scientific understanding of its mechanism by addressing a confounding factor - we demonstrate that the SPN is driven by the user’s intent to select the target, not by the stimulus feedback itself. Furthermore, we examine the effect of familiarly placed targets, finding that SPN may be evoked quicker as users acclimatize to target locations; a key insight for everyday BCIs. CCS CONCEPTS Human-centered computing → Virtual reality; Mixed / augmented reality; Accessibility technologies; Interaction techniques. ACM Reference Format G. S. Rajshekar Reddy, Michael J. Proulx, Leanne Hirshfield, and Anthony J. Ries. 2024. Towards an Eye-Brain-Computer Interface: Combining Gaze with the Stimulus-Preceding Negativity for Target Selections in XR. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ‘24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 17 pages. https://doi.org/10.1145/3613904.3641925
Subspace based DOA estimation in the presence of correlated signals and model errors

High-resolution subspace based direction-of-arrival (DOA) estimation requires a number of assumptions about the signal and antenna. In our application automotive radar, among many practical problems, signals are often correlated and the antenna is not calibrated. This difficult combination has been seldom addressed in the literature. In this paper, we study their simultaneous impact on DOA estimation, describe a so called “coherent model error interference” phenomenon, propose a prewhitening scheme for algebraic subspace based DOA estimation, and show some simulation results.