Miracle-dz/UniFAR-FTUs huggingface dataset:
Sketching for Immersive Analytics with Situated Visualizations

We explored sketching and ideation of situated visualizations at a local food bank with small displays as the hardware target platform. The design of situated and embedded data visualizations poses unique challenges because of the need to account for their situated nature like placement, size and level of detail of visualizations. Based on our observations and experiences at the food bank, we further envision a possible spatial augmented reality sketching tool and design activity for projected, embedded visualizations to provide a higher degree of immersion than with small displays.
Real-world Video Adaptation with Reinforcement Learning

Client-side video players employ adaptive bitrate (ABR) algorithms to optimize user quality of experience (QoE). We evaluate recently proposed RL-based ABR methods in Facebook's web-based video streaming platform. Real-world ABR contains several challenges that requires customized designs beyond off-the-shelf RL algorithms -- we implement a scalable neural network architecture that supports videos with arbitrary bitrate encodings; we design a training method to cope with the variance resulting from the stochasticity in network conditions; and we leverage constrained Bayesian optimization for reward shaping in order to optimize the conflicting QoE objectives. In a week-long worldwide deployment with more than 30 million video streaming sessions, our RL approach outperforms the existing human-engineered ABR algorithms.
Travelling fronts in time-delayed reaction–diffusion systems

We review a series of key travelling front problems in reaction–diffusion systems with a time-delayed feedback, appearing in ecology, nonlinear optics and neurobiology. For each problem, we determine asymptotic approximations for the wave shape and its speed. Particular attention is devoted to their validity and all analytical solutions are compared to solutions obtained numerically. We also extend the work by Erneux et al. (Erneux et al. 2010 Phil. Trans. R. Soc. A 368, 483–493 (doi:10.1098/rsta.2009.0228)) by considering the case of a slowly propagating front subject to a weak delayed feedback. The delay may either speed up the front in the same direction or reverse its direction. This article is part of the theme issue ‘Nonlinear dynamics of delay systems’.
Adaptive Intelligent Manufacturing Control Systems

The article is devoted to development of the concept of the integrated intelligent control system for complex manufacturing process. The base of the system is recurrent decomposition method, which allows reconfiguring systems logical structure in case of the given optimum criteria. A recurrent decomposition model of the general problem of manufacturing process automation and the algorithm of multi-level control for automated facilities with scalable tree structures are suggested. In this paper, the design of processes, as well as the problem of automating the lifecycle of the product are considered within the concept of Industry 4.0. The methods of final product quality control based on the control and testing processes optimization are considered as well as methods of structural and parametric optimization of technological processes. Some application examples of the developed mathematical models for technological systems are given.
The Salmonella Specific, σE-Regulated, STM1250 and AgsA, Function With the sHsps IbpA and IbpB, to Counter Oxidative Stress and Survive Macrophage Killing

The host presents an array of environments which induce bacterial stress including changes in pH, antimicrobial compounds and reactive oxygen species. The bacterial envelope sits at the interface between the intracellular and extracellular environment and its maintenance is essential for Salmonella cell viability under a range of conditions, including during infection. In this study, we aimed to understand the contribution of the σH- and σE-regulated small heat shock proteins IbpA, IbpB, and AgsA and the putative σE-regulated stress response protein STM1250 to the Salmonella envelope stress response. Due to shared sequence identity, regulatory overlap, and the specificity of STM1250 and AgsA to Salmonella sp. , we hypothesized that functional overlap exists between these four stress response proteins, which might afford a selective advantage during Salmonella exposure to stress. We present here new roles for three small heat shock proteins and a putative stress response protein in Salmonella that are not limited to heat shock. We have shown that, compared to WT, a quadruple mutant is significantly more sensitive to hydrogen peroxide, has a lower minimum bactericidal concentration to the cationic antimicrobial peptide polymyxin B, and is attenuated in macrophages.
GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model

It is now widely accepted that glia cells and gamma-aminobutyric acidergic (GABA) interneurons dynamically regulate synaptic transmission and neuronal activity in time and space. This paper presents a biophysical model that captures the interaction between an astrocyte cell, a GABA interneuron and pre/postsynaptic neurons. Specifically, GABA released from a GABA interneuron triggers in astrocytes the release of calcium (Ca2+) from the endoplasmic reticulum via the inositol 1, 4, 5-trisphosphate (IP3) pathway. This results in gliotransmission which elevates the presynaptic transmission probability rate (PR) causing weight potentiation and a gradual increase in postsynaptic neuronal firing, that eventually stabilizes. However, by capturing the complex interactions between IP3, generated from both GABA and the 2-arachidonyl glycerol (2-AG) pathway, and PR, this paper shows that this interaction not only gives rise to an initial weight potentiation phase but also this phase is followed by postsynaptic bursting behavior. Moreover, the model will show that there is a presynaptic frequency range over which burst firing can occur. The proposed model offers a novel cellular level mechanism that may underpin both seizure-like activity and neuronal synchrony across different brain regions.
Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality

We present Bento Box, a virtual reality data visualization technique and bimanual 3D user interface for exploratory analysis of 4D data ensembles. Bento Box helps scientists and engineers make detailed comparative judgments about multiple time-varying data instances that make up a data ensemble (e.g., a group of 10 parameterized simulation runs). The approach is to present an organized set of complementary volume visualizations juxtaposed in a grid arrangement, where each column visualizes a single data instance and each row provides a new view of the volume from a different perspective and/or scale. A novel bimanual interface enables users to select a sub-volume of interest to create a new row on-the-fly, scrub through time, and quickly navigate through the resulting virtual “bento box. ” The technique is evaluated through a real-world case study, supporting a team of medical device engineers and computational scientists using in-silico testing (supercomputer simulations) to redesign cardiac leads. The engineers confirmed hypotheses and developed new insights using a Bento Box visualization. An evaluation of the technical performance demonstrates that the proposed combination of data sampling strategies and clipped volume rendering is successful in displaying a juxtaposed visualization of fluid-structure-interaction simulation data (39 GB of raw data) at interactive VR frame rates.
Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks

Gene regulatory networks (GRNs) are often inferred based on Gaussian graphical models that could identify the conditional dependence among genes by estimating the corresponding precision matrix. Classical Gaussian graphical models are usually designed for single network estimation and ignore existing knowledge such as pathway information. Therefore, they can neither make use of the common information shared by multiple networks, nor can they utilize useful prior information to guide the estimation. In this paper, we propose a new weighted fused pathway graphical lasso (WFPGL) to jointly estimate multiple networks by incorporating prior knowledge derived from known pathways and gene interactions. Based on the assumption that two genes are less likely to be connected if they do not participate together in any pathways, a pathway-based constraint is considered in our model. Moreover, we introduce a weighted fused lasso penalty in our model to take into account prior gene interaction data and common information shared by multiple networks. Our model is optimized based on the alternating direction method of multipliers (ADMM). Experiments on synthetic data demonstrate that our method outperforms other five state-of-the-art graphical models. We then apply our model to two real datasets. Hub genes in our identified state-specific networks show some shared and specific patterns, which indicates the efficiency of our model in revealing the underlying mechanisms of complex diseases.
Nodulation of Retama monosperma by Ensifer aridi in an Abandonned Lead Mine Soils in Eastern Morocco

Millions tons of lead and zinc wastes from the abandoned Touissit mine are stored in the open air as dikes in the vicinity of the villages in Eastern Morocco and pose a real danger to both the environment and local populations. To prevent the movement of minerals to the nearby villages and limit the damages to the environment and health, we proposed the nitrogen-fixing leguminous shrub Retama monosperma, as a model plant to use for phytostabilization experimentations. This plant species is known by its ability to grow in hard climatic conditions and in heavy metals contaminated soils. The isolation of bacterial strains nodulating R. monosperma in the abandoned mine soils will permit the selection of rhizobia to inoculate young plant seedlings before their use for the phytostabilization of the mine tailings. In this work, 44 bacteria were isolated from the root nodules of R. Monosperma grown in the Touissit abandoned mine. Twenty-four isolates were considered as true rhizobia as they possess a copy of the nodC symbiotic gene and were able to renodulate their original host. The phenotypic characterization showed that all the strains are tolerant in vitro to different concentrations of heavy metals. The analysis of the 16S rRNA sequences of two selected representative strains showed they were related to different strains of Ensifer aridi isolated from different legumes in three continents deserts. The glnII, recA, and gyrB housekeeping genes analysis confirmed the affiliation of the strains to E. aridi. Moreover, the phylogenic analysis of nodA, nodC, and nifH symbiotic genes showed that the strains are more related to E. aridi JNVUTP6 species isolated from Tephrosia purpurea root nodules in the Thar Desert in India. To our knowledge, this is the first report about the isolation of E. aridi from R. monosperma root nodules.
Arrhythmic Burden and Outcomes in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) is a devastating, life-limiting disease driven by small vessel vascular remodeling leading to a rise in pulmonary vascular resistance (PVR). Patients present with a range of symptoms including shortness of breath, exercise intolerance, palpitations or syncope. Symptoms may be related to vascular disease progression or arrhythmia secondary to the adaptation of the right heart to pressure overload. Arrhythmic burden is high in patients with left heart disease and guideline-based treatment of arrhythmias improves quality of life and prognosis. In PAH the incidence and prevalence of arrhythmias is less well-defined and there are no PAH-specific guidelines for arrhythmia management. We undertook a literature search identifying 13 relevant papers; detection of arrhythmias was acquired from 12-lead electrocardiogram (ECG) or Holter monitors. In all forms of pulmonary hypertension (PH) the prevalence of supraventricular arrhythmias (SVA) was 26–31%, ventricular arrhythmias (VA) 24% and a 5-year incidence of SVA ~13.2–25.1%. Prevalence and incidence of arrhythmias in PAH is less clear due to limited study numbers and the heterogenous nature of the patient population studied. For arrhythmia treatment, only single-arm studies of therapeutic strategies were reported using antiarrhythmic drugs (AAD), direct current cardioversion (DCCV) and ablation. Periods between ECG or Holter have not been investigated, highlighting the possibility that significant arrhythmias may be undetected. Advances in monitoring allow long-term surveillance via implanted/non-invasive monitors. Use of such technologies may provide an accurate estimate of incidence and prevalence of arrhythmias in patients with PAH, further defining relationships to adverse outcomes, and therapeutic options.
MRD in AML: The Role of New Techniques

In the context of precision medicine, assessment of minimal residual disease (MRD) has been used in acute myeloid leukemia (AML) to direct individual treatment programs, including allogeneic stem cell transplantation in patients at high-risk of relapse. One of the limits of this approach has been in the past the paucity of AML markers suitable for MRD assessment. Recently, the number of biomarkers has increased, due to the identification of highly specific leukemia-associated immunophenotypes by multicolor flow-cytometry, and of rare mutated gene sequences by digital droplet PCR, or next-generation sequencing (NGS). In addition, NGS allowed unraveling of clonal heterogeneity, present in AML at initial diagnosis or developing during treatment, which influences reliability of specific biomarkers, that may be unstable during the disease course. The technological advances have increased the application of MRD-based strategies to a significantly higher number of AML patients, and the information deriving from MRD assessment has been used to design individual post-remission protocols and pre-emptive treatments in patients with sub-clinical relapse. This led to the definition of MRD-negative complete remission as outcome definition in the recently published European Leukemianet MRD guidelines. In this review, we summarized the principles of modern technologies and their clinical applications for MRD detection in AML patients, according to the specific leukemic markers.
Maintenance of Fluorescence During Paraffin Embedding of Fluorescent Protein-Labeled Specimens

Paraffin embedding is widely used in microscopic imaging for preparing biological specimens. However, owing to significant fluorescence quenching during the embedding process, it is not compatible with fluorescent-labeling techniques, such as transgenic and viral labeling using green fluorescent protein (GFP). Here, we investigate the quenching mechanism and optimize the embedding process to improve the preservation of fluorescence intensity. The results show that dehydration is the main reason for fluorescence quenching during paraffin embedding, caused by the full denaturation of GFP molecules in ethyl alcohol. To evaluate fluorescent and morphological preservation, we modified the embedding process using tertiary butanol (TBA) instead of ethyl alcohol. Fluorescence intensity following TBA dehydration increased 12.08-fold of that observed in the traditional method. We obtained uniform fluorescence maintenance throughout the whole mouse brain, while the continuous apical dendrites, spines, and axon terminals were shown evenly within the cortex, hippocampus, and the amygdala. Moreover, we embedded a whole rat brain labeled with AAV in the prelimbic cortex (Prl). With the axon terminals in different areas, such as the caudate putamen, thalamus, and pyramidal tract, the results showed a continuous tract of Prl neurons throughout the whole brain. This method was also suitable for tdTomota labeled samples. These findings indicate that this modified embedding method could be compatible with GFP and provides a potential turning point for applications in the fluorescent labeling of samples.
Accelerated Monte Carlo simulations with restricted Boltzmann machines

Despite their exceptional flexibility and popularity, the Monte Carlo methods often suffer from slow mixing times for challenging statistical physics problems. We present a general strategy to overcome this difficulty by adopting ideas and techniques from the machine learning community. We fit the unnormalized probability of the physical model to a feedforward neural network and reinterpret the architecture as a restricted Boltzmann machine. Then, exploiting its feature detection ability, we utilize the restricted Boltzmann machine for efficient Monte Carlo updates and to speed up the simulation of the original physical system. We implement these ideas for the Falicov-Kimball model and demonstrate improved acceptance ratio and autocorrelation time near the phase transition point.
Isolation, Culture and Functional Characterization of Glia and Endothelial Cells From Adult Pig Brain

Primary cultures of glial and endothelial cells are important tools for basic and translational neuroscience research. Primary cell cultures are usually generated from rodent brain although considerable differences exist between human and rodent glia and endothelial cells. Because many translational research projects aim to identify mechanisms that eventually lead to diagnostic and therapeutic approaches to target human diseases, glia, and endothelial cultures are needed that better reflect the human central nervous system (CNS). Pig brain is easily accessible and, in many aspects, close to the human brain. We established an easy and cost-effective method to isolate and culture different primary glial and endothelial cells from adult pig brain. Oligodendrocyte, microglia, astrocyte, and endothelial primary cell cultures were generated from the same brain tissue and grown for up to 8 weeks. Primary cells showed lineage-specific morphology and expressed specific markers with a purity ranging from 60 to 95%. Cultured oligodendrocytes myelinated neurons and microglia secreted tumor necrosis factor alpha when induced with lipopolysaccharide. Endothelial cells showed typical tube formation when grown on Matrigel. Astrocytes enhanced survival of co-cultured neurons and were killed by Aquaporin-4 antibody positive sera from patients with Neuromyelitis optica. In summary, we established a new method for primary oligodendrocyte, microglia, endothelial and astrocyte cell cultures from pig brain that provide a tool for translational research on human CNS diseases.
Evolving Clinical Applications of Tissue Transcriptomics in Kidney Disease

Nephrotic syndrome is classically categorized by the histopathology with examples including focal segmental glomerulosclerosis (FSGS) and minimal change disease. Pediatric patients are also classified by whether their nephrotic syndrome is sensitive to, dependent on, or resistant to steroids. However, this traditional classification system overlooks the frequent clinical conundrum when, for example, one patient with FSGS responds briskly to steroids, and another quickly progresses to end stage kidney disease despite therapy. Two patients may have similar histopathologic appearances on kidney biopsy but entirely different clinical characteristics, rates of progression, and treatment responses. Transcriptional regulation of gene activation and posttranscriptional processing of mRNA may drive the unique and heterogeneous phenotypes which are incompletely understood in kidney disease and are a recent focus of research. Gene expression profiles provide insight on active transcriptional programs in tissues, are being used to understand biologic mechanisms of progressive chronic kidney disease, and may help to identify patients with shared mechanisms of kidney damage. This mini-review discusses clinically relevant techniques of bulk tissue and single cell transcriptomics, as well as strengths and limitations of each methodology. Further, we summarize recent examples in kidney research achieved through transcriptomics. This review offers an outlook on the role of transcriptomics in an integrative systems biology model with the goal of defining unique disease subgroups, finding targets for drug development, and aligning the right drug with the right patient.
Asynchronous Branch-Parallel Simulation of Detailed Neuron Models

Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topological representations of the neurons. Acceleration of such simulation is possible in the weak scaling limit by modeling neurons as indivisible computation units and increasing the computing power. Strong scaling and simulations close to biological time are difficult, yet required, for the study of synaptic plasticity and other use cases requiring simulation of neurons for long periods of time. Current methods rely on parallel Gaussian Elimination, computing triangulation and substitution of many branches simultaneously. Existing limitations are: (a) high heterogeneity of compute time per neuron leads to high computational load imbalance; and (b) difficulty in providing a computation model that fully utilizes the computing resources on distributed multi-core architectures with Single Instruction Multiple Data (SIMD) capabilities. To address these issues, we present a strategy that extracts flow-dependencies between parameters of the ODEs and the algebraic solver of individual neurons. Based on the resulting map of dependencies, we provide three techniques for memory, communication, and computation reorganization that yield a load-balanced distributed asynchronous execution. The new computation model distributes datasets and balances computational workload across a distributed memory space, exposing a tree-based parallelism of neuron topological structure, an embarrassingly parallel execution model of neuron subtrees, and a SIMD acceleration of subtree state updates. The capabilities of our methods are demonstrated on a prototype implementation developed on the core compute kernel of the NEURON scientific application, built on the HPX runtime system for the ParalleX execution model. Our implementation yields an asynchronous distributed and parallel simulation that accelerates single neuron to medium-sized neural networks. Benchmark results display better strong scaling properties, finer-grained parallelism, and lower time to solution compared to the state of the art, on a wide range of distributed multi-core compute architectures.