Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptional responses of brain endothelium to Plasmodium falciparum patient-derived isolates in vitro

A hallmark of cerebral malaria (CM) is sequestration of Plasmodium falciparum infected erythrocytes (IE) within the brain microvasculature. Binding of IE to endothelium reduces microvascular flow and combined with an inflammatory response perturbs endothelial barrier function, resulting in breakdown of the blood- brain barrier (BBB). Cytoadherence leads to activation of the endothelium and alters a range of cell processes affecting signalling pathways, receptor expression, coagulation, and disruption of BBB integrity. Here, we investigated whether CM derived parasites elicit differential effects on human brain microvascular endothelial cells (HBMECs), as compared to uncomplicated malaria (UM) derived parasites. Patient-derived IE from UM and CM clinical cases, as well as non-binding skeleton-binding protein 1 knockout parasites, were overlaid onto TNF-activated HBMECs. Gene expression analysis of endothelial responses was performed using probe-based assays of a panel of genes involved in inflammation, apoptosis, endothelial barrier function, and prostacyclin synthesis pathway. We observed a significant effect on endothelial transcriptional responses in the presence of IE, yet there was no significant correlation between HBMEC responses and type of clinical syndrome (UM or CM). Further, there was no correlation between HBMEC gene expression and both binding itself and level of IE binding to HBMEC, as we detected the same change in endothelial responses when employing both binding and non-binding parasites. Our results suggest that interaction of IE with endothelial cells in this co-culture model induce some endothelial responses that are independent of clinical origin and independent of the expression of the major variant antigen PfEMP1 on the IE surface.
Red blood cell dynamics during malaria infection violate the assumptions of mathematical models of infection dynamics

For decades, mathematical models have been used to understand the course and outcome of malaria infections (i.e., infection dynamics) and the evolutionary dynamics of the parasites that cause them. A key conclusion of these models is that red blood cell (RBC) availability is a fundamental driver of infection dynamics and parasite trait evolution. The extent to which this conclusion holds will in part depend on model assumptions about the host-mediated processes that regulate RBC availability i.e., removal of uninfected RBCs and supply of RBCs. Diverse mathematical functions have been used to describe host-mediated RBC supply and clearance, but it remains unclear whether they adequately capture the dynamics of RBC supply and clearance during infection. Here, we use a unique dataset, comprising time-series measurements of erythrocyte (i.e., mature RBC) and reticulocyte (i.e., newly supplied RBC) densities during Plasmodium chabaudi malaria infection, and a quantitative data-transformation scheme to elucidate whether RBC dynamics conform to common model assumptions. We found that RBC clearance and supply are not well described by mathematical functions commonly used to model these processes. Furthermore, the temporal dynamics of both processes vary with parasite growth rate in a manner again not captured by existing models. Together, these finding suggest that new model formulations are required if we are to explain and ultimately predict the within-host population dynamics and evolution of malaria parasites.
Exploring unique sequence repeat patterns and secondary structures in rDNA internal transcribed spacers ITS1 and ITS2 for characterization of catfish species

The genetic variabilities in internal transcribed spacers ITS1 and ITS2 of rDNA are explored to a limited extent in vertebrates including fish species. This study explores unique molecular signature in these spacers from multiple fish species from the order siluriformes. Supporting the concerted evolution, both ITS1 and ITS2 were found prevalent with microsatellite and random repeats, with diverse distribution in each species in term of nucleotide composition, position and length, giving a species-specific impression in repeats. Their secondary structures too have shown distinct structural homology with variations in helix length, loops, and non-canonical bps, where ITS2 4-helix carries additional nine conserved motifs while that of ITS1 was found highly branched with multiple sub-branching unique to each species and a long tail helix common in all. This combination of secondary structures and repeats have formed unique molecular signatures distinguishing each species. Since the evolutionary and maturation biology of rDNA is similar in vertebrates, these molecular signatures in internal spacers could effectively contribute in the molecular characterization of other species too.
Torque Ripple Suppression of Rounded Square Permanent Magnet DC Motor by the Harmonic Injection method

The previous study of PM motor torque ripple is generally considered that the current distortion is the root cause of torque ripple of PMDC motor, and it is AC motor or brushless motor, not considered the effect of EMF and PMDC motor. To solve the problem, using the voltage harmonic injection method to suppress the PMDC motor torque ripple, considered the effect of EMF and PMDC motor. Base on the theory model of round square PMDC torque ripple suppression method, apply the FEM method to analyze the current and torque ripple, the improvement target is the minimum of torque and current ripple, compare the injection voltage harmonic with different optimization targets, The study provide theoretical and simulation basis to make round square torque ripple suppression sample and achieve the torque ripple suppression target.
Implementation Strategies for STEM Learning Using A Computer-Based Simulation

Educational Computer-based simulations (CBSs) can be applied to provide students with experiences they would not otherwise be able to have, given that realistic scenarios may not be possible due to expense, danger associated, or rare occurrence of the scenario (Smetana & Bell, 2012). Principles of Experiential Learning Theory (ExL) as identified by the National Society of Experiential Learning (NSEE, 1998) include intention, preparedness and planning, authenticity, reflection, orientation and training, monitoring and continuous improvement, assessment and evaluation, and acknowledgment. These principles served as a framework to develop an intervention designed to help teachers effectively implement CBSs. Using a qualitative approach, findings from a pre, post, and post-post survey and participant interviews indicate a shift in teachers' description and perception of effective implementation before and after a professional development and classroom implementation experience. The study also identified instructional strategies for implementing computer-based simulation in the classroom and goes on to describe professional development experiences to support the implementation of simulations.
- A Python Toolbox for FAIR Data Management around HDF5

Sustainable data management is fundamental to efficient and successful scientific research. The FAIR principles (Findable, Accessible, Interoperable and Reusable) have been proven to be successful guidelines to enable comprehensible analysis, discovery and re-use. Although the topic has recently gained increasing awareness in both academia and industry, the engineering sciences in particular are lagging behind in managing the valuable asset of data. While large collaborations and research facilities have already implemented metadata strategies, smaller research groups and institutes are often missing a common strategy due to heterogeneous and rapidly changing environments as well as missing capacity or expertise. This paper presents an open-source package, called h5RDMtoolbox , written in Python helping to quickly implement and maintain FAIR research data management along the entire data lifecycle using HDF5 as the core file format. One of the key features of the toolbox is the flexible, high-level implementation of metadata standards, adaptable to the changing requirements of projects, collaborations and environments, such as experimental or computational setups. Implementation of existing schemas such as EngMeta or the cf-conventions are possible and intended use-cases. Other benefits of the toolbox include a simplified interface to the data and database solutions to query metadata stored in HDF5 files.
Poor man's TBR: a simple model reduction scheme

This work presents a model reduction algorithm motivated by a connection between frequency-domain projection methods and approximation of truncated balanced realizations. The method is computationally simple to implement, has near-optimal error properties, and possesses simple error estimation and order-control procedures. Usage of the method also enables straightforward exploitation of information about the particular application and setting, as well as circuit functional information, such as frequency weighting information and correlations between network port waveforms. When such specific information is available, standard truncated balanced realization algorithms generate models far from optimal according to statistical decision criteria. Examples are shown to demonstrate that the method can outperform the standard order reduction techniques by providing similar accuracy with lower order models or superior accuracy for the same size model.
Influence of canopy cover on vegetation in P. roxburghii sarg (chir-pine) dominated forests in Uttarakhand Himalaya, India.

Increasing anthropogenic pressure and dependence on plant products have led to widespread exploitation of natural forests in the Uttaranchal Himalaya. The present study was carried out to study the influence of canopy cover on tree, shrub and herb vegetation. For this three different canopy types, open canopy ( 60%, cover) were identified in Pinus roxburghii (chir-pine) dominated forests. The study area is located between 29 0 20’and 29 0 30’ N latitude and 79 0 23’ and 79 0 42’ E longitude between 1350-2000m elevations in Uttarakhand a newly created hill state. Total tree density was high in close canopy sites basal area was greater in open canopy sites. Total shrub density varied from 26107 to 28560 shrub/ha. It was maximum for open canopy sites and minimum for moderate canopy sites. Total shrubs cover varied from 45.8 to 50.6%. Shrubs cover was maximum for moderate canopy sites and minimum for open canopy sites. Herbs density was greater in open canopy and total herbs cover was greater in close canopy. Tree and shrub diversity was high in close canopy sites and herbs diversity in open canopy sites.
Consistent variations in personality traits and their potential for genetic improvement in biocontrol agents: Trichogramma evanescens as a case study

Improvements in the biological control of agricultural pests require improvements in the phenotyping methods used by practitioners to select efficient biological control agent (BCA) populations in industrial rearing or field conditions. Consistent inter‐individual variations in behaviour (i.e. animal personality) probably affect BCA efficiency, but have never been taken into account in the development of phenotyping methods, despite having characteristics useful for phenotyping: repeatable (by definition), often heritable, etc. We developed a video‐tracking method targeting animal personality traits and evaluated the feasibility of its use for genetic improvement in the BCA Trichogramma evanescens, by phenotyping 1,049 individuals from 24 isogenic lines. We found consistent individual variations in boldness, activity and exploration. Personality differences between the 24 isogenic lines suggested a genetic origin of the variations in activity and exploration (broad‐sense heritability estimates of 0.06 to 0.11) and revealed a trade‐off between exploration and fecundity.
Privacy and the internet of things

1. The salience of privacy The sensors and other devices that constitute the Internet of Things (IoT) will provide an unprecedently rich picture of anything in their purview. As the IoT is projected to include devices embedded in the home, on people's bodies (via instrumenting the body and also wearable computing devices), in communities, on goods and services, and in the environment (Anderson & Rainie 2014, 2), very many previously-hidden activities will be exposed to potential view. The point does not need belabouring – indeed, Sir Mark Walport's opening remark in this event alluded to the privacy issue. Martin Winterkorn, the CEO of Volkswagen, whose company places many digital devices in the cars it builds, recently warned of the dangers of creating a " data monster " (Bacon 2014). Meanwhile security is a genuine worry. Security firm Proofpoint recently uncovered the first known large-scale IoT cyberattack (Proofpoint 2014). The attack that Proofpoint observed and profiled occurred between December 23, 2013 and January 6, 2014, and featured waves of malicious email, typically sent in bursts of 100,000, three times per day, targeting Enterprises and individuals worldwide. More than 25 percent of the volume was sent by things that were not conventional laptops, desktop computers or mobile devices; instead, the emails were sent by everyday consumer gadgets such as compromised home-networking routers, connected multi-media centers, televisions and at least one refrigerator. No more than 10 emails were initiated from any single IP address, making the attack difficult to block based on location – and in many cases, the devices had not been subject to a sophisticated compromise; instead, misconfiguration and the use of default passwords left the devices completely exposed on public networks, available for takeover and use. 2. How should we understand privacy? It is tempting to understand privacy as a type of control – one prevents data or information about oneself reaching other people. One sets rules and then enforces them. Yet this badly misrepresents the ways in which we talk about our privacy, or in which privacy concerns us. I would contend that privacy is better understood as a constant effort to negotiate the boundaries of our selves and our personal space (literally and metaphorically) with our peers. We perceive benefits from being visible to our networks, and to other entities such as our governments or our employers, and at the same time wish to restrict that visibility in …
Challenges in publishing research data – a Fraunhofer Case Study

Sharing of research data is becoming more and more established as part of the scientific process, triggered by corresponding requirements of research funders. A large number of subject-specific and institutional research data repositories were created as publication agents for the research data. Nevertheless, the publication processes are not yet established and need to find a way to best practice. The aim of this paper is to work out what challenges currently exist in the publication of research data and how these can be overcome. Answers to the research question are provided by a case study of research data publication with the participation of industrial partners in the institutional research data repository of the Fraunhofer-Gesellschaft ”Fordatis”. The publication process is described from the perspective of the researcher, the data curator and the repository operator. In summary, the challenges can be overcome primarily by the division of labor and communication.
Partial differential equations / Functional analysis Electromagnetic wave propagation in media consisting of dispersive metamaterials

Article history: Received 24 October 2017 Accepted after revision 22 May 2018 Available online 31 May 2018 Presented by Jean-Michel Coron We establish the well-posedness, the finite speed propagation, and a regularity result for Maxwell’s equations in media consisting of dispersive (frequency dependent) metamaterials. Two typical examples for such metamaterials are materials obeying Drude’s and Lorentz’ models. The causality and the passivity are the two main assumptions and play a crucial role in the analysis. It is worth noting that by contrast the well-posedness in the frequency domain is not ensured in general. We also provide some numerical experiments using the Drude’s model to illustrate its dispersive behaviour. © 2018 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved. r é s u m é Nous montrons que les équations de Maxwell dans un milieu constitué de métamatériaux dispersifs (dépendant de la fréquence) forment un problème bien posé, à vitesse de propagation finie et satisfaisant un résultat de régularité. Deux exemples typiques de tels métamatériaux sont les matériaux régis par les modèles de Drude et de Lorentz. La causalité et la passivité sont les deux hypothèses principales ; elles jouent un rôle essentiel dans l’analyse. Il vaut la peine de remarquer qu’en revanche, rien n’assure, en général, le caractère bien posé dans le domaine des fréquences. Nous présentons également quelques résultats numériques utilisant le modèle de Drude, afin d’illustrer le comportement dispersif. © 2018 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved. E-mail addresses: hoai-minh.nguyen@epfl.ch (H.-M. Nguyen), valentin.vinoles@epfl.ch (V. Vinoles). https://doi.org/10.1016/j.crma. 2018.05. 012 1631-073X/© 2018 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved. 758 H. -M. Nguyen, V. Vinoles / C. R. Acad. Sci. Paris, Ser. I 356 (2018) 757–775
Frequency evaluation of UTC(NPL) by NPL-Sr1 for the period MJD 58659 to MJD 58679

secondary frequency standard NPL-Sr1 and an optical frequency comb were used to evaluate the frequency of UTC(NPL) over a period of 20 days from MJD 58659 to MJD 58679 (25 th June 2019 – 15 th July 2019). The Sr optical lattice clock operation covers 71.1% of the total measurement period. The result of the evaluation is reported in table 1 and is made using the CCTF 2021 recommended frequency value for the 5s 2 1 S 0 – 5s5p 3 P 0 unperturbed optical transition in 87 Sr: 429 228 004 229 872 . 99 Hz with a relative standard uncertainty of u Srep = 1 . 9 × 10 − 16 [1].
Acceleration and automation of genomic data analysis to meet corporate compliance standards using advanced cloud components.

Recent advancements in High-throughput next-generation sequencing (NGS) technologies grew exponentially in genomic research revolutionizing biological data analysis, and enhancing the study of complex biological systems at an unprecedented scale. The technological limitations of the NGS system are the deluge of genomic data produced. It’s difficult for a single workstation to execute sequential methods and produce results quickly. Efficacy decreases significantly with human interference and to mitigate them, we developed an in-house pipeline, with the help of AWS services and tools like snakemake, kallisto, etc., for automating RNA-seq data analysis. It’s efficient, scalable, reproducible, version-controlled, transparent, and cost-effective for large volumes of data. In this study, we have reviewed the RNA-sequencing technique using AWS to analyze gene expression at the transcriptional level. The systematic approach allows CROs to transfer raw data using an SFTP server, followed by an automated transfer to Simple Storage Service (S3) and preceded by data quality validation. Helper scripts then transfer data from S3 to Elastic File System (EFS), launch the Fastq processing pipeline, clone a GitHub repo of the corresponding project, and leverages AWS Batch to spin up a dynamic Elastic Compute Cloud (EC2) instance as desired. After successful execution, outputs are available in EFS, and actual data analysis is performed using RStudio Workbench ending with automated results archival in S3.
PSYCHOSOCIAL RISKS IN THE HEALTH AND SOCIAL CARE SECTOR

overall rates per year and injury costs) for their unit in comparison to the entire hospital. Based on these data, supervisors were asked to develop an action plan for reducing workplace violence, using a checklist of possible risk factors and evidence-based strategies for violence reduction. The intervention was evaluated in a randomised-controlled trial with 21 intervention units and 20 control units across seven hospitals. Six months after the intervention, incident rate ratios of violent events in intervention units were significantly lower in comparison to control units. Two years after the intervention, the risk for violence-related injury in intervention units was significantly lower in comparison to control units. The results of the study suggest that the intervention was effective in decreasing the risk of workplace violence in hospital settings
Exploiting General Coe(cid:14)cient Representation for the Optimal Sharing of Partial Products in MCMs

| We propose a new algorithm that maximizes the sharing of partial terms in Multiple Constant Multiplication (MCM) operations under a general number representation for the coe(cid:14)cients. MCM operations are required by many algorithms in digital signal processing and have been the subject of extensive research. By making no assumptions as to the number representation, the algorithm described in this paper is able to perform a better search for the optimal sharing of partial terms than previous meth-ods based on MSD or CSD representations. We have applied our algorithm for the hardware minimization of FIR (cid:12)lters. The results show that we can obtain solutions that require between 20% to 50% less hardware when compared against the solutions using the MSD representation.
Evaluating Extremal Dependence in Stock Markets Using Extreme Evaluating Extremal Dependence in Stock Markets Using Extreme Value Theory Value Theory

: Estimation of tail dependence between ﬁnancial assets plays a vital role in various aspects of ﬁnancial risk modelling including portfolio theory and hedging amongst others. Extreme Value Theory (EVT) that provides well established methods for univariate and multivariate tail distributions which are useful for forecasting ﬁnancial risk or modelling the tail dependence of risky assets. This paper uses nonparametric measures based on bivariate EVT to investigate asymptotic dependence and estimate the degree of tail dependence of the ASX-All Ordinaries daily returns with four other international markets, viz., the S&P-500, Nikkei-225, DAX-30 and Heng-Seng for both right and left tails of the return distribution in extreme quantiles. It is investigated whether the asymptotic dependence between these markets is related to the heteroskedasticity present in the logarithmic return series using GARCH ﬁlters. The empirical evidence from bivariate EVT methods show that the asymptotic dependence between the extreme tails of the stock markets does not necessarily exist and rather can be associated with the heteroskedasticity present in the ﬁnancial time series of the various stock markets.
Using Hex Maps to Classify & Cluster Dribble Hand-off Variants in the NBA

In recent years, the strategies of NBA teams have evolved with the skillsets of players and the emergence of advanced analytics. One of the most effective actions in dynamic offensive strategies in basketball is the dribble hand-off (DHO). This work proposes an architecture for a classification and pattern mining pipeline for detecting DHOs and their variants in an accurate and automated manner. This pipeline consists of a combination of player tracking data and event labels, a rule set to identify candidate actions, player trajectories embedded into hexbin cell paths, and passing the completed training set of generated features to the classification and clustering models. This work then evaluates the extracted and engineered features, provides a comprehensive accuracy evaluation of the classification models to compare various machine learning algorithms, and finally, analyzes the resulting DHO variant clusters and their ability to provide deeper context to players’ actions and abilities.